owed in both talks some impacts on current stratification. Thank you for the introduction deal. Can you comment on how those changes scale to natural variability either like within season or even week to week or year to year. Are these of the same order smaller larger. That can be in the same order, while at least for the productivity but clearly the seasonal variability in the North sea for example the super large. So, since we have a very clear seasonal cycle in productivity so that's much larger than this attack but for the inter annual variability I think these like 10% that can be in the range of what you would expect. So it's less about natural variability. However, what I, what I forgot to say is actually when you integrate over the whole area. The net change and prime production for example was very small was almost not there. So it's less about a net change and prime production and more about a redistribution in both space and time and I think that's important to consider. Yeah, thank you for the presentation. I had a question about the explicit integration of the foundations into the hydrodynamic model. If I saw correctly your grid resolution ranges between four meters and 1000 meters in those simulations. And with the foundation sizes of let's say 810 meters. Of course the resolution of the grid is nowhere near fine enough to capture all the local processes around the foundation foundation so I was wondering how you model the foundations and what the value of that explicit relatively course integration is in that model. Yeah, that's actually that's a very long story. And just can certainly say even more on this because the parameterization is kept from his model. This is explicit integration. We actually had a couple of more problems. That's why we chose for the final simulation the direct parameterization. Since the schism model is has a uses a hydrostatic assumption, and that doesn't work on these very fine scales. So, in the paper from me that just came out, like, two or three weeks ago, and Jeff and myself a course or so. He makes an assessment on this implementation of this of these foundations and clearly explained why it's very probably not so appropriate using that in a hydrostatic model. But yeah, that's a very long story so I recommend to look into the paper and maybe talk to Jeff as well. I think you Christina you've had a, or do you want to respond for do it later. Okay. I wasn't sure if you had your hand up to make a comment that questions. Okay. Yeah. Maybe Christina you had a question in the chat did you want to ask that and then we'll come back to your question. The question is in the chat to, and I'm concerned about several of the figures that you showed the numerical simulations had an incredible amount of numerical noise that can potentially mask the real results. I emphasize them exaggerate them when I see a figure full of blue and red dots everywhere so far away from the location where the perturbations actually occurred. I'm very, very concerned and I'm very aware of the numerical noise, chaos seeding issues that some models have. So I'm wondering if you've taken care of this problem in any way. And yeah, I'm, I'm just very suspicious of these results. Lots of American noise came actually also from the atmospheric foresee, but I actually checked the signal to this noise signal and the surrounding and the signals from the simulation was significantly stronger than from the noise. Okay, thank you. Jeff, did you had questions. Yeah. Hi, it's Jeff here I'm in the United States actually. So I had a question if you've looked at for the windway parameterizations have you have you looked at different types of parameterizations and any effects that that would have on the results. No, I haven't further simulations we had we just had this kind of one simulation, which took months to do in the atmosphere. So, but now it is currently working also and, well, not on different types of parameterization but on different types of parameter settings for the, I mean, I'm not sure what you mean parameterization or the parameter settings for the for the clusters. So I think he's very testing these different types like how high changes on how high can changes in density of piles to see how that affects the results but we haven't made simulations with that yet. And then maybe one quick other question was on the primary productivity results. So this dipoles they show, you know, positive and negative anomalies, and then you see very little net change in an NPP. And is that just because these dipoles kind of have a canceling nature to themselves. Yes, but also because they are not very consistent. I mean, you have constantly changing wind directions. So what I showed we're actually very basically just analyze the situations with certain directions. But in reality, there's also constantly changing. So I think that's one of the reasons and then the effects I think also cancel each other out. We're going to hear about hydrodynamic models, methods, assumptions and conclusions and how these translate to the Nantucket-Scholes region and we have three presentations. The first of these will be by Chang Xin Chen, who is a professor at the School for Marine Science and Technology at the University of Massachusetts Dartmouth. And I think it's fair to say that he is the person behind the development of the finite volume community ocean model that we've already heard referenced in presentations this morning. And so he's going to talk to us today about some of the about the model and some of the applications of the model for looking at offshore wind farms. Is everyone can see that? Okay, I put it like a presentation mode. So, okay. So, when I talk today, you know, we talk about the potential impact of renewable energy for environment issues in the Northeast region. So we've, this project was first funded by Bong, the 2014, later we get a NOAA. So we get a lot of people involved in the project, you know, we get a fisheries people like Kevin Stalbury, like Pingo. We also had a fish oceanography, like a Bob Beasley in the Wusha and also had a, you know, had a right away person that's got a garage. Okay. This project is working by, you know, UMass and the Wusha together. Okay. So, okay, okay, why not able to move. Okay, so look about the structure here, you know, look at the wind farm. So, we see interesting, so we get a whole region, you look at the Northeast region, you get Massachusetts and the Northern water. So they have a larger area in the region, they're all Northeast region. So this look about, you know, Glenn talked about a lot of fiscal oceanography already, I probably don't need to go so many anymore, but we look at the circulation pattern here. So that's the whole offshore wind farm area. So you get a circulation for Cape Corp region also come from Georgia Bank and the short big front circulation come down.  They will be deployed no wind turbine into system. The only show that before, when we get a 2014 they said they put a 136 wind turbine into system. But now only one company come from, you know, like a, like wind farm. So they will be put here smaller yellow region here was half region put a hundred. That means you get a lot of wind farm, you know, there.  So what do you do, you had to think about without a system here, then look about what a structure here. This picture shows the scallop distribution for future data. So you see the most regions are very interesting. You get a, you know, you get a middle and divide a larger population scholar there. I think Alan will do a lot of work about this. Right. So they also had a Georgia Bank region had a one here. You look at the Nantucki saw region. This region here you don't, you don't have a lot of scallop major over here, but that's the point of wind farm there. The question is how they affect that. So, so you look about a picture here. I want to see most scallop we find over there. They're swarming on the Georgia Bank, a great size of China. When it's swarming the Georgia Bank region is swarming there. So then the lobby were moving down by the current, then 40 days later they settled down in the bottom. So the red one, the surface, not a modest simulation. So we do a 40 year simulation for a scholar. So then the blue one is all settled down here. Okay, most of it, but in a lot of a lobby will settle down in the, in the, in the southern New England shop on the Nantucki saw region. But then the question, the problem, you know, then you, then you look about it.  I put individual wind turbine into system. So they get a, you know, what tax week. All right, okay, I'm going to wait as a week over there. That's the model simulation. You can see a lot of way can generate there. So the question here, you know, does this is really true on Nantucki saw region. What can be happened like this. So we, let me, we was doing. Okay. So we were the question here. Then you look at circulation pattern, I'll probably skip this one because the ground talk a really nice talk and shop or whole things here. So that's the red ones, the surface circulation, the blue, you know, know why the one is like a steeper circulation, you can see the circulation. One, two secretion. Why is the comfort government region go down, keep courage. Another one's come from Georgia back secretion home here. This region is a flu system. It's not like you look about North Sea, they have a basin like a semi-employed basin, but in our region everything's open. Okay, they just go through a system there. So that's why you full, they also had a one, you know, no God string, the one chlorine that can have some mention about it. There was a lot of intrusion in the shopping region. So then we want to see that for long term, you know, God string is really important. I will see what the condom for for short term, they can stronger tie the current over there. So what's happened. So I want to show you some kind of work we done before. And I think it's Anthony and the was all in the government department. So he had answered proposal funding for quarter measurement. So we get up obviously under Steve Lance, I'm working together. I do the modeling Anthony to observation. That's the region never said region they do a quarter measurement. So that's the data coverage. You see that you look about the, you know, signal. So semi-dialyte is a very dominant energy in the region. You know, the data has a very important semi M2 tests are very dominant. So we compare with the mother and the quarter data tied the simulation really match each other. Had a simulation, but even you have a lot of data uncertainty, but you still get a very much of a tie. But then look, then a question here that you, you can do this one here. So you look at the ties in our region. This is the whole Georgia Bank government region stronger tie. Over here, Nantaki saw some region that Nantaka solution, they get a lot of for tight generation 80 along the, along the island. So this equation can be stronger force back over there to all time. All time region. That's why you know region is very different for we saw in other region. Okay. So like, you know, we mentioned here today, the grand mention that wind driving circulation is one or the smaller than time.  So most strongly daily variation is tied. So then a question here, then we also had a noise stone, because a lot of stone coming. So stone come here, they can, they carry the big way. No, they carry no way stronger wind. No, they get a lot stronger way also ways very important. We don't come here, you can serve as a way in Nantaki saw region. And the one stone come here way high can be 10 meter. 10 meter high the way and the song come here. So when you have a hurricane, for example, we only had one hero can really cross our region in the hurricane Bob 1991. So that's how I was student in the woods. So we, we all, you actually start everything down over there. So you can see the window stone, you know, here we can come. It writes out a big way. Come here along the region. So that's the way come here, you got a wind turbine how to interact with it.  No long term, you get a downstream meandering or other thing. You know, that's a lot of physical process over there. So we have developed a model called North, North East or coastal ocean forecast system called NECOP. A time it was the deal man near course of finding us. That's the, it's the atmosphere ocean couple model system. So we next in the global model and original model. And also mass cost model. That's the model mass cost model is 10 meter resolution in cool region here. The Nantucket region is about a hundred meter resolution. So ocean, we use this model to use for ocean rescue. The rest of ocean rescue doing fully couple via the four in addition model. I don't want to talk about it anymore about it. We talk about Nantucket South region. But uses the model system we run for 40 years. We had a 40 year audit data build up data simulation to whole region. So then uses a fair.  Okay, that's the movie show you about low pass filter. See how they change it with the monthly red wine is the mother in the blue wine. So call that it no red wine. So call that data.  You see that it really match where we're going to switch in high. So then we do a trip to study. Let's have a trip to study. No, this is a trip to study is kind of observation and the modeling is really match, you know, showing the color a dissimulation of this here. So based on the study, we saw that can be do the offshore wind wind farm. So the question, you know, like we took it to the day. If you do the wind farm, you have to resolve the wind turbine. How you do the wind turbine. So we walking with the company, you know, we know when we get a desire. They have a two layoff. The one left here. There's a layoff one layoff two. I have a question here is the first thing you can you model resolve the wind turbine. You will resolve wind turbine how to look at that. The second question how they affect the fall. No ecosystem. We do the scope of population model see how population will move. So I go quickly the model resolution one meter. Included by this next thing with the global regional and the local model. Included a new you have this region we can put a wind turbine into a system. So that's a whole nesting. You get a really true environment in the region. So we also run for me knowledge model it I show you. The three me knowledge of the couple together see how the wind changes. Okay, so that's what we do the publishing one about it is quite more about this. So that in 2014. We want to see how the cure can, how to know is stone can affect that. So we do this one here. We finally know really dependent on how your stone come from. For no is a stone the case a hundred years long. You see the big change in the way surface way change a lot. You will talk about a circulation talk about the way way, but then you can see the way change a lot. If a hurricane come here. They know the effect if you put a wind turbine here, we put 135 wind turbine. You find a hole here in the in the coast region can be really change the big way. You can cause a lot more signal in the nation future if a hurricane come from south. If you know is stone come from North East. You see whole region the wind we can be changing in the region too. So then look at the bottom. You can see the bottom hepatitis. This is H point is the wind turbine. You can see how the wind turbine change the bottom circulation. You can cause a lot of, you know, residual circulation near the bottom. The sentiment can be changes. So that's the first study we do for bomb. We only put a 130 by wind turbine. But now they change everything changes story changes. Okay, so, so then we do a 40 year.  You see the percentage in the list of mean distribution. A lot of a lot of you stay here in the region. But then, okay, no variability. Much variability is a new English shelf region. But it's a really larger variability. Okay. George make a very stable. That's a variability. So we do this one here. When you run for basic model without a wind farm. You see, that's the settle down the lobby. You run for the full year. Recruit a model. You find that's the observation show you that's that's the observation the model. No many lobby can survive. Into New England shelf region. They all because of hepatitis or all things there. So most high pubs region is stayed under still like observation, like a great South China or Georgia bank. But in the region most of the time. We run for 40 years simulation. We find all the problem. I talk about the scalpel. Sanctuary Tommy said a basic issue. This is a hepatitis issue causal problem or temperature. Also cause a problem. But then we want to see how the effect. Now we do a really window simulation. So that's the model we do for 100 years. The hundred winter might be put into like a new engine into design. So this is a movie show you how to change the circulation look like. Each one is the winter turbine. Okay. So we don't put a transition in there, which is wrong. The simulation. So you look about it when you're zoning. You want to see individual term to mine. You see the red lines of part of what he see the blue lines and negative what he see. So you did not see. Like a vortex awake. Okay. So you don't have all the time over here. But you do see the change of your time. The tight cycle red one. You see individual right one is the part of what he see. The blue one is negative what he see. They change with the tight cycle. The one two time per day. Because same with Diana. So they tend to shop. They don't have a steady circulation. Over there. That's why you don't. You do see the way shocking shortly. Participation really quickly. Okay. So that's what I said. Individual circulation. Over there. That's really resolved for the winter. My mother. You know, you're doing this one. So that's why our North East region. It's very different from the European region. No, because we get so open. Why we got so stronger time. So that's the circulation can become a different. So then I look about, you know, look about here. You look at a whole type of cycle. You see over here. This is an active artistic. So you did what he did change with time. With the side cycle. So the influence region. Okay. They do have a shooting. But it is shooting to the page very quickly. Like a random walk. But then they all just because. The water also. The region is really stratified. Also our region is completely different from other region. Because we so stronger time. Tight circulation. You know, circulation. That's what you'll find. You know, you look about a surface, the bottom, red ones, the bottom, the blue, the black ones, the surface. Because the water stratified. That's what surface occurring at the bottom current, not to go to the same direction. So you see the mostly side of surface over here. The bottom is that direction. When they change with a tight cycle, they change with a tight cycle. They change with a long time. If you do the averaging. I do the three months of averaging. You see, that's the bottom. You know, that's the, that's the bottom stress. The bottom stress is a change here and here, but scarce, not very big. No, Jeff. Ranger ask a question. See how large your effect is. It's only about a 50, 50 meter. Significant change and the 50 meter in the local domain. But then you look about. That's the maximum for three months. That's the maximum you can find. But you look at what the column. The mixing with the column. The most everywhere. Okay, the bottom stress. Look at very north, east, north, south, and teaching. But what the column mixing. It was causing around the whole region. Also, maximum, you can see the edgy shooting. Some region you can see, but not like a steady, like we find it so that's what happened. So then what really happened is, you know, you look about this one here. This is the wind turbine. We put a hundred wind turbine here. You look at the bottom stress. This top months without wind turbine, the bottom line with turbine. You find the most about the stress intensified by the larger, not in the wind turbine region. What's in the shallow region and then talk is all. Because this is shallow. That's the shallow region. Because it's a little bit deeper than 40 and 50 meter. But here is like a 30 and 40 meter. That's the bottom stress. It can be changed a lot. So then you do the transect. You want to try a second. You want to see what happened. You want to have a transect over here. You find that this top ones without a wind turbine. That's the great South China or the water here. You see that that's a cold water. No, in the deep China. The wind turbine was using here.  And they put the outwelling. The outwelling is strongly from the Great South China Club onto the Nantaki Salt region. That means you can bring a lot of nutrient into the system. So then they are fed here. You can have a cold water intruding from the surrounding Great South China region to here. For the wind turbine. That's why the reason because the bottom stress and the shore region becomes so strongly. The circulation reaching the changes. So that's the model for the next model. So then we look at the larvae distribution. The fish larvae, not like a scarper larvae distribution. You look at one here. We also consider about the semi-dianada, the behavior of the phytoplankton larvae. But this one is without wind turbine is in cold turbine. What happened? Everything moving offshore. Everything moving offshore. This morning I talked to one person. He was European he was talking there. He finally you know, if a wind turbine the circulation is drifting. So we find a similar thing you see here. This one without the wind turbine. This one without a turbine. Everything moving offshore.  He feels very happy because a close region boxes. That's a closing area. That's a closing area for fishing. Okay, that's why they say all larvae stay there. They probably get a more scar. You know, because they're not allowed to catch you over there. Okay, but then you look publishing the same way. We do the many simulation. Many year simulation. All same pattern. All same pattern. So then we do the static analysis to assemble include all the swimming behavior. Okay, we finally know this is without a wind turbine up level is below as a wind turbine. So you can see they're all moving now offshore. That's the reason you get a transport moving offshore. That's the reason you get a intrusion water you can offshore transport over there. Then you get intrusion water come from the bottom. That's really affected regionally. So that's what happened. We finally here. So now you look about how the wind can be changers. So you look about we put a hundred wind termizes here. So we run a war for whole year. One kilometer resolution. So we win the turbine. We look about how the energy we use to turn my height one hundred twenty one meter use in touch with design. So we know how the lottery the diameter the one hundred eighty meter. So we know what a parameter for the model we run a wall. That's I do the whole scene. Every you see over here that spring time. All the wind effect in this side. Not every place. Summer time you see this side because the window mark come from southeast. You see this side that can be changed by inside is not changing much. But then you see the autumn the fall. You see the wind the most a lot of ability to win. You see the region still was in the lee side over there. If that's the hundred wind term I hold the wind changers. So then the winter time you see the most whole area can be changers. The wind time in the winter come from in the northeast region. So that's why you can see the way to be strong in the wind. So the wind changer. So then you want to see how the circulation can change. So I didn't show the movie show you how to change it. So this one you know this one show you you know without the wind you know you have affected by the you know the wind not changes. This one had to consider wind changes by turbine. You see they still show the same pattern. You still show the offshore cities go there. But however they're more concentrated over there. You see this one is a little bit spare. This one is pushing to be larger. This one is smaller. So that means you know even you don't consider wind changers you know you put a wind turbine into the system you really can call offshore transport enhancement transport. You can do the circulation can be much complicated. So that's the basic we found. So then what reason you know when we do the study I think Bob said let's do the dispersion study see how this happened. So we said okay let's put only particle not like a larvae put a particle there. So this one without a wind turbine we found in the wind turbine dispersion becomes smaller because you have a larger dispersion wind turbine dispersion is very small. You see here it's very narrow. Okay you put everything here in the wind turbine you see here it changes a lot. Then you look at this one here this wind turbine dispersion is really bigger. Everything is spare out. In cool turbine you see here it was a dispersion yellow. Dispersion is smaller. That's why when you include wind turbine system the dispersion changes. That's the circulation can be changes. That's all basically we found. So then another question about industry design because regular D1 designing I can put the wind turbine this way. I can put the eastern north this way. Even separation scale is the same but location is different orientation is different. How this designing can affect the circulation. So we find they do affect it but not like current it do affect it. That's the layer of one layer of two. You see they are very similar but change is very smaller not very bigger but they do change it but not like we think of the current like a tide. So that's what happened. So now the question come up and the climate change climate change here Glamour mentioned this warming system here. This 2010 they got a big warming here. So we do the simulation for 40 years simulation region model. We found bottom temperature change a lot. So you can see the georgia much stratified. The gradient can be much stronger warming. So before you get all chance to go south but now the chance for larger variability you know the annual variability thousand chance here change a lot. So then you also see you have a you can put the water in here lot of one core AD can be affected region. That's why we finally know how to do the climate change. So to address the question we do a couple thing for since we do a couple model we already couple with our wind resolving termite model with the atomized model wall. Before I just run the wind termite change the wind adjust with the ocean. But now we do the whole couple. You know, instantly your SIT changes the factor work model see how they changes. So that's the model we develop. Okay. Last couple years my student published paper 2022 in the Parker oceanography. So then the four things we've added the model. We also make a new designing for the four nesting model the one two three four. So that's for the model the couple model system. Each one we have a nesting model wrong for couple model. You result wind termite you're going to see what happens. Okay. That's a whole domain. We got a one common resolution in our model. So we get one meter resolution wind termite model. Okay. So then then the simulation we do the testing for who can send it. We finally the AC coupling change a lot. Okay. If without AC coupling that's the hurricane pack with a coupling get this way get a very close. The pressure simulation. I don't want to talk too much about this. We find as a AC the energy flux is very important. But now we make a tooth ready. We can wrongly this one to simulate how the wind termite is. Last one I want to show this kind of climate change model. We also look like a people talking about the awesome model. So we're working them together. We already couple awesome into the new cop. We have a fully couple awesome model with the new cop region simulation origin. So we already run for many years. That's the data we compare region here. We rather couple region we compare the old model. This model is good. They go to the PCO to PhD. They have low traffic for the web model. So I just quickly go through. That's the comparison come out. We can simulation the new train, simulation phytoplankton, zooplankton simulation whole region. We do the many years simulation. Come on is the coverage model is pretty good for region. So then last things I want to talk about downscaling. So we have you know me knowledge downscaling. We run for global regional technology model, downscaling model. So we can reach in the wolf model climate change model, three common resolution. We run for we prediction for 2050. So we run a climate change model all we found. We found for 2050 stratification change a lot. The springtime you get a stratification intensified significantly. But in the fall summer we found a storm. We don't know how can we change the model correct or not. At least we found a stone number in the 2050 had a much more than before. You get a more stone. So you find in our region in the spring or summertime water because it's very stratified in the fall you can enhance the mixing. That's why the question come out if you include a wind farm what's really happened. So we have a lot of fiscal about we try to do the simulation use this way to see what happened. So the basically you know that's what I talk. So we have been we find you know you really need to resolve the wind turbine. If you really want to do simulation. So that's the reason we have a wind turbine resolving the model. So we get a fiscal by large amount of region we do assessment. But really question we do only in our night company we're put all the wind turbine there. So what accumulation effect we don't know right you to a hundred year already significantly changing if we're not solid what happened. So we finally here today probably not a true anymore. If you put a more that's why I saw this really you know important things understand accumulation effect. Okay that's what I basically what I talk today. I go to fast but I put a pop up here. So you know if everyone interesting can look my pop up. Yeah wow lots of interesting simulations and things to think about maybe we'll take one question and then we'll move on to the next presentation. If there is a question. Yes Richard. Title mixing sorry. Title mixing was really important in your research. How widespread would that be in the larger area though. Okay. Yeah you know larger no type of this government region this whole government you have a couple of type of mixing zone. Nantaki saw is the one technique is on if you look at type very interesting feature there. I the system in the region there are two types of system. Why is the title come from down another New England gone down. Nantaki saw region is a converging wrong. It's a title converging wrong. That's reaching title mixing very strongly. So like a most like a where text mixing and on the close to the great south China side by another side is no new English region that's the mixed region. But a whole region below what a bit no shorter than 40 meter kind of very important. No 40 to 50 meter very stronger type mixing. So I made this to be sure understand that full region of all not no, you know Nova Scotia had one region. So sorry Georgia bank and then Nantaki saw. I just I'm we're really concerned about the area that's subsumed by those nine projects south of the vineyard and Nantucket. So my question is really focused on that one area. So is that full area one where title mixing whether it's a dino or semi dino tide is important to be considering in the modeling. I should see this important but however stratification also important. You know because reason you know because region is very stratified. So in Nantaki saw region like summertime and spring time really stratified. So there's really no stratification you don't have a cold pool there. Okay region there. That's why I the mix is strongly but stratification was important you know so you compatible together not every mix every regions mix it is still stratified so you put a wind turbine in there you enhance the mixing but however the mixing is locally locally the locally about a 15 meter around the wind turbine but this is very intensified but however they change the whole transport surface current as Graham mentioned today they can show big they can intrusion water we found you know we found this region here if you wind turbine this region here you can surface current to go offshore the bottom current is going so you probably can the future can in enhance the intrusion water for short break region okay yeah no one another things one other things I want to forget to mention we do a chemistry study for mixed layer when the warming get mixed in the shallow wind turbine in cooler push water offshore but in cooler stratification the shallow mix layer they put the water you flow in that's why two things will complete each other you don't know what's really happened okay yeah Christina and Jeff I love your setup with the variable resolution domain and the high resolution around the wind turbine so there's no parameterization you resolve it what I just can't understand is how it's possible that you show as results where the effects of the of the foundation are limited within 30 to 50 meters of the turbines they are absolutely gone from the domain in 100 meters and yet you see regional impacts 500 kilometers away what does that how can it be physically what can possibly do that okay you mean no wind we put like a wind turbine like a you know like a small region 100 meters right but then the question they got a lot of mass scarcity no circulation changes so then they push the water surface offshore there's nothing left you know there's nothing to push if they had a current to go out so then what happened so then the surrounding water compensation of water in that's the reason the water if you look at the tide you see nothing because it's moving like this way but then you feel the tide out you do see low frame circulation changes you know from Great South China flowing up compensation of water loss was in the region so that's why we find the most significant changes in the shallow nearby region not in the wind turbine region a long region had a very shallow you look at the possibility here's the deep here's the shallow the strongest effect cannot possibly be away from the location where it's caused there's nothing that it's like there's some kind of a convergence of small effects that converge somewhere else and become stronger that is not natural oh no I I believe you live individual termite there that's why we do we do analysis right now we had a big box model in region so we want to see how much net transfer changes bring the wind turbine region so then we want to see how the water in because we get a week I want to calculate your water mass balance see how the balance will come in so then we'll see how the water why the water can intrude in the deep region come down come out so you look about circulation there you want to see that so you know so you look about because if you only want to put one or two is not affectable much but you will put a hundred hundred there that's why the whole region you know you look at you know particle tracking dispersion dispersion change you see the whole water just moving out okay that's what they do but you know probably I'm not able to address your question well aware okay but that's why you know the simulation to see this one because we do the region is nesting this model is a region the model nesting model there region is really far away the model region so that's why you don't affect it but you know the reason we run the model for you know you when you go to boundary you can be affected by but we have to not reach the boundary we find all the side of circulation not much change but just transport change yes okay sounds like but we can talk further discussion Jeff and then Douglas yeah I seems to me like there's two different ways of including the turbine effects in the ocean you know there's the sort of bulk parameterization where you say this patch is wind farm and I'm going to extract a certain amount of momentum from that patch that's provided by the drag formulas or some other law and then there's the method that you chose which is to actually resolve or try to resolve the individual wakes with a really high resolution around the structures themselves and I guess you know you chose a very challenging approach but I wonder how well do you think that that model is representing these small scale wake effects you know it should have a parameterization that's I think capable of dealing with those types of flows and the effects that you would expect in those very small scale rapidly changing flows so how well do you how confident are you in what the model is doing there that's a very good question you know I should honestly you know because we use the term as a closure model we validate the closed closure model for tidal mixing before okay my you know like Georgia Bank region we validate but we finally know we use the model you know term as a closure scheme this model this scheme is a really good simulation tidal mixing but not for wind mixing okay wind mixing sometimes are fair okay but tidal mixing they can result way too well so we compare with the observation data term as a measurement comes pretty good but then you when you want to go to a small scale the questions of my address you know I run a simulation with a hydrostatic approximation but when you go to one meter resolution you have to turn on a non hydrostatic you have to consider convection so I didn't mention here no RC couple more we do non hydrostatic the hurricane simulation we did is non hydrostatic so when we do the hurricane simulation so we finally though when you turn on non hydrostatic convection can cause really important impact but then I can bring Tommy said turn when we test the hurricane we do the resolution is about one kilometer 500 meters in the sharp region the cancelling not result of non hydrostatic be true we compare with the model hydrostatic if resolution not horizontal resolution not enough you didn't result but in deep ocean the weather where when the sharp region not but when turn my model running now we have to turn on the non hydrostatic so we want to see how convection because we find the convection probably more important than the diffusion when the small scale coming so I don't get the answer yet but the system we have right now we have a non hydrostatic so when you turn on a really RC couple model you have to turn on the non hydrostatic for the small scale like a one meter okay go ahead thanks Eileen well I'm first of all I need some time to digest all this of course and not just not just chins but one thing does occur to me and I know we can't do it because we don't have the turbines aren't in the water yet but are there some examples either chin with yours or some of our European colleagues that presented earlier use of some data source remotely sense data or otherwise to actually test against the model predictions and I look at things like the productivity predictions from the models in the North Sea yes and I understand that they're different systems but are we using any available data to ground truth and verify some of the model predictions you know let me do a regional model this model is wrong we use our Hank's model wrong this includes all data assimilation include a temperature, humidity current assimilation for whole region so we compare with the SCT data comparison region they're pretty good but the problem is when you go to downscaling like a winter my results is the one meter resolution there so we don't have a data compare that's why we don't know the temperature assimilation we get the clarification correctly or something that's only the model result so recently we're working on an all-star company all-star company so they have been making like a three region measurement they got a control area when they put a winter measurement temperature, humidity so they already give us data but the problem this data is before we put a winter my in you know this is like regional scale so compare come out pretty good but the question come out to us after they put a winter my into system how they change it so we have no data so I saw the Woosaw group Anthony's group they get DOE funding they will put like a moring into the system so they will be measured temperature over there but we really want to wait see what's happened after they put a winter my we don't have a data yet we don't compare yet that's a very good question that's why you don't know what a model correct so now we just make a technology develop but that's ground true or not we don't know one last question okay comment one comment is that regarding ground tools we have a unique moment now if we do measurements now before the turbines are in we can do it after and then let me give us a very good basis for that I think that's up to maybe the developers and bone to focus that Jen you mentioned that you use data simulation in your modeling how do you do that when you know now make changes you have data simulation you simulate the situation as it is now historically and then you put in turbines and what happens then with the data simulation when you turn my model we don't do data simulation anymore that's the next model wrong we run a region the model and the whole domain you go to God's chain you put everything there so that's how the data simulation so once you have a similar when you do the winter my we use the next in boundary we get a next in boundary I just put a next in boundary there to drive it one way next thing we didn't do the two way next thing yet the one way next thing that's why the no boundary change with time because that's an unsurgical model so you can you don't need to have an interpretation just I know you have a mic it's an unsurgical model so you don't need that out of the pool you put it there you can run but then importantly you want to make sure your running period is not too long you don't want to have water cut to the boundary that's why everything changes because small scary things because if you have a small larger one way next thing most important internal time internal way so when the internal way propagation touch your boundary so they can your boundary can be changes so then you can get energy accumulation over there because scary different when you resolution high your result internal way why we're assuming causing probably not resolved that's why we run the model we have to make sure you know initial condition make sure the time we running so you want to chapel check that it really affect your boundary now if a fact boundary stop you have to restart again because that's why yeah that's good interesting discussion but I think we're going to need to move on and we can come back to this if we have some time at the end okay so we're going to hear about a different modeling structure or framework might D.H.I. and it'll be from Olli Peterson is the chief engineer the ports and ports and offshore technology the Danish hydraulic institute and Tom Johnson chief operating officer at the Danish hydraulic institute. Thank you for inviting us here being here this morning I'm not sure I dare say much we heard now Dr. Chin here he's a hard man to follow here and then we all heard about all these details Glenn you have presented amazing amount of details of how complicated this system is so we come here with the models and it is even if it's very very complicated and very advanced we think I don't think it matches anything in reality so it is a simplification so that's I want to say that up front here so let's see why are we here the very specific reason is that we have been doing two studies one historic study for bone looking at accumulated impact of the Massachusetts Rhode Island area that's completed and reported and we have an ongoing study right now looking at the whole U.S. east coast that's very specific reason and we will try and develop discuss here today what we have learned from these two studies and try and put that forward another reason is that we think this discussion about accumulative impacts is very important for the industry and for the society and it is a discussion that often falls between jazz developers they don't require they have to their own projects to look for and really cares about these accumulative impacts but I think it is important and it will be an issue in the future that may affect how we develop offshore wind in the future so that's why we chose to come here and I think it's a very very good initiative that you're taking just a few words about who is we are a little bit new in the street here in U.S. so I can hear all of you you know each other very well the entire we are in based in Denmark we have about 1000 people working with water we are like a private research institution that also do commercial you have similar institutions here in the U.S. we have offices around the world also here in the U.S. in Denmark in Portland Tom here is chief officer in the U.S. we have been around for about 50 years and we have worked with waters and we work do studies we don't do design we don't do but it's natural water is the key and another key factor for us that is numerical modeling that has been kind of our legacy we do projects and we ought to do about 25% of our activities research and another 25% is our software we settle this commercial mic software that we're using here so let's see well we have been in the offshore wind business in many years that was the first offshore wind park in the world we were part of that in 1991 about 5 megawatts and that was a revolution at that time so we supported that one and was part of the research project behind and today we are now up to we have supported 25 gigawatt of realized projects and we are still supporting 130 gigawatt of coming projects we are involved in we say 80% of all commissioned offshore projects in the world and we are also doing a lot of say research projects related to offshore wind let's see if this can come up and what are we doing for offshore wind made ocean conditions waves hydrodynamics as we are discussing today we are looking supporting scour, cabling all this kind of water things sediment transport is part of it and we also do ecology biodynamics EIAs and some special things is noise noise for EIA and also bird detection we have some bird detection systems that can basically stop wind turbines when something comes flying past as I said modeling has been key it's part of nearly all our projects one way or the other and we have this mic suite that we are using here which is a well recognized standard in the coastal and ocean engineering and today we will use two of these models that's a wave model that looks at waves and another one is our flow model it's called mic tree 3D so they are the key tools that we will employ here and have employed in the projects this we have talked about all day just for someone has listened that the accumulate impact that we look at these things this is mostly the wind wave effects and how that affects waves how that affects the currents we look at drag from the foundations and from the towers and from the scour protection and how that affects the flows around we will not look at cables or new habitats but we have the continuation in the bone study we have done it goes the wave further down and look at the migrating of larvae or scallops and how they change as a consequence of say impact from the offshore wind turbines so today we will not go into that in much detail this is the same again the impacts and say what we learned from the study the first bone study was that initially we thought that it was the towers that were an important part the mixing and the drag on these foundations directly in the water that must be a big impact but it seems it's not it is really the wind the wind break and the wind energy reduction by the offshore farms that is a big factor and that affects the waves they will not grow as fast or they will decay faster it affects the currents because they drag the currents so that is really a big one I'll show you why later and then of course we have the drag and mixing induced from the foundations directly whether it's monopiles or it's jacket structures they are the ones there is a paper by Corina longer list of more impacts on temperature and heat exchange on other things and we have not looked at these things if we take the one of the effects on the foundations as Jen discussed the flow around these structures is very complicated the boundary layer is about 2-3 cm thick so I think even with a 1 meter resolution there is still a lot of things going on there that is important so it's very difficult to resolve actually these flows and if we do it in a 2-course mess we overestimate the forces we have done that many times we can easily get 10 times the drag if we don't resolve properly so what we do here is that we make an empirical model drag on a cylinder structure that is kind of a standard engineering exercise also turbulence induced by a structure it's well known so we have this input as a parameterization such that we assure that the drag induced by that structure is correct as we can get it and it also includes the mixing we have done some experiments they are referenced here earlier where we looked at mixing induced by stratified flow by these structures so we can put that into a formula that can calculate the effect on the flow by these structures the same for the waves I can't remember if I said no the same goes for the waves wave interaction with a cylinder structure in the ocean that is something you can write many PhDs about without knowing everything but we try to do a simplification where we look at basically what they call the dynamic model of the waves and then we could boil that down to some empirical relations that tells us how much of the wave is transmitted through the structure how much is reflected and that gives us this reduction in wave height due to the presence of structures inside the water that's also built into the models and I say that would be sub grid so our grids are not one meter they may be larger but we try to make such that we have one structure within each grid cells that gives us a good control of how these things they work next is the effect of the wind waves the first study we did we took a simplified approach and we said okay the effect of the wind wave is inside the footprint of the wind farm that has been discussed and we have now taken that out and improved it so what we do now is that we use a system called PiWake that's the one they use for resource assessment of wind farm so that is accurate I'll tell you because that's money but we use the same the same feature basically it takes each turbine it calculates say what is the incoming wind what is the wind production and then it calculates the wave and empirical relations for the wave and then we take all the other turbines how that wave come in and maybe reduce the incoming wind to that turbine which is downstream so that last turbine will get much less wind than the first one and it will also calculate downstream the wind farm how are all these waves combining and going downstream that's up in hop height that's now today in 125 meter above the sea bed so that has not really much to do with what's going on at the sea surface so what we do is that we use this called Francis model which basically takes and we can transform the reduced wind speed in hop height down to the sea surface because that transformation is not straightforward it depends on the weather it depends on the stability of the atmosphere and that makes this thing very site specific on US west coast whether it's stable normally so that has one impact on how much of the reduced wind stress will come down to the surface in the east coast in the winter it's convective dominated score so these waves they mix up very quickly and it also has an impact on how strongly the sea surface impacts we take that into account and then we do for example you can see these pictures here they are the wind speed calculated for I think this one is empire wind and the other ones in new york bite we have them for all the lease areas calculated and you can see an example of how big is the impact we calculate this picture every hour for the whole period that we are simulating so we have varying wind direction, varying humidity conditions and get a good measure of how the sea surface is impacted and it takes nearly as long to calculate these ones as it does to calculate the whole 3D model because of this yeah I think this one can move if I'm lucky here this is just an example you can see yeah this is a little bit artificial example you can see how the impact on the stress it changes with time so that's it let's go here now to the real world as I said we did the first study that's the mesh on the here that's the first study where we set up the model here what we do is set up a very specific model try and do it as accurate as possible just like Jen is doing then we implement the wind turbines and then we look at what is the changes that is the way we work as engineers the next model that's the one that's ongoing now is this one it covers the whole area from Nova Scotia down to Florida basically and has all the leases inside so it's a more heavy-duty approach but we think we have learned a lot with this let us see here if we go down a bit here yeah so this is the way we work we develop this validated baseline have that as good as we can put in the turbines different scenarios and then we simulate here a historic period which is I think we have contracted up to one to three years it's more say cost of computing time that is really the issue here when we do design wind turbines we do nearly the same exercise as the baseline and then we do 40 years of simulations hourly to get all the statistics right but for this purpose here we started with say one to three years we do it with a high dynamic model 3D model that has temperature, stratification, flows all important stuff and we do it with a wave model that calculates basically wave spectra also on the same grid as I said we are in the first study we touch have some downstream effect on fish and larvae this is the way we calibrate the model we look at each parameter this is water levels we have measurements they are shown on the map here just a few examples here we do time series calculate these scatter plots which show measured on the axis here and the model up here and then we can see if they follow the straight line here everything is good and if there is a lot of scatter then well that's the uncertainty when we do that for I think we have 20 stations here along the coast and we do it for typically for one year where we use that for calibration the next one that is for currents here that is up in New York by that these two stations and I said have two high quality light up voice with also ADCP that we have used and we have used all of us this measurements and a lot of measurements from developers covering pioneer we also used and observers observatory but still if you look at current observations they are scarce they are nearly nothing to have a good coverage of current measurements in the same period that is a dream so we take all we can get our hands on so that's also why if we can get someone to collect some more current measurements that will be important yeah and then if you look at this this is time series measured and modeled these are directions this is the current speed and then is the direction upward so we can see there are two little bit dominant directions here in this and this they are the tides but they are not very strong in New York Byte and these are current roses is measured and black or gray is from the model and I would say for example this the quality of this plot here that is typical for what we get for current measurements this is not an exact science it is nothing there is a lot of uncertainty if we take the next these are for waves waves are a little bit easier so you can see the match is better but still wave roses significant wave height how it fits distributions we also do the same for wave periods and other wave parameters and for waves there are many stations I think we have more than 20 or 30 stations where we look at periods about say one year and calibrate all over to get a good idea of the representation of the model okay but now we have a baseline that we think is the best or is a good representation of what happens in real life but as I say if Glenn looks at it I'm sure he can point his finger to many places say this here is not what I know but there is life and the way we quantify high dynamic impacts is that I said we implement these turbines in different configurations different configurations and different strengths we also for each turbine we have this operation curve they are caught in with 3 meter per second cut out 25 meter per second so what is really important for the wind turbine impact that's not the extreme situations that is this normal operation situation because that's where the wind turbines they operate and that's when they don't operate they have minor effects on anything these are just very few examples there if you look in the report you can see all the details I didn't want to take them up here but for example these are a 75 percentile difference for this is for currents depth average currents where we look at different scenarios I think scenario two is the one with full build out of the Tom he can remember all these things with full build out for the Rhode Island Massachusetts and you can see the impacts here or the kind of what is the say the change of this the current speeds and they are here for current speeds they are within say 10 percent that is I don't remember if I have waves also no so if we look at waves it's also it's below 10 percent most of the time it's not zero there is an impact but it's about that magnitude yes Tom you will say a little bit about the next because who cares about waves and currents no one ask anyone they care about are my fish gone where are the scallops I need to catch that's what really concerns people are my beets disappearing so you will move on when I ask so just very briefly we are going to go through some of the how we did the agent based modeling we use the super agent methodology because when you look at the fecundity of scallops or flounder or silver hape you couldn't do every egg and model it so we basically collapse these millions of eggs per spawning season into a number of super agents and then follow those super agents as they were dispersed it reduces the computational load and but we can still monitor and update them over time next so the the three species that we did in the first study that was completed in 2021 was this an agent based model or ABM of the sea scallop larvae silver hape and summer flounder and we took those customized ABM templates and then ran them through the hydrodynamic model and then what we were looking at basically was the differences in where these larvae settled and when you look at the graphic on the right that is for summer flounder summer flounder were a little bit different than the sea scallop and silver hape larvae because they had a certain motility and would sense basically egg tides and flood tides and would swim towards the shore at a certain development stage so that's why you see the differences are mostly in shore next the conceptualization basically this is the whole reason you do these agent based models how these were all conceptualized and built are based on these papers that are talked about here in this slide they're just settlement rate and population abundance how do you parameterize that what's the settlement of probability and basically what is the substrate material and the environmental variables that allow the larvae to survive the dispersal patterns and recruitment basically in different synced areas and their swimming speeds and then vertical migration patterns of larvae basically for function of daylight and tidal conditions so all those things are built into these templates and basically parameterized based on observations from experts for each of the different species next and then just to give you a flavor of what we found there were basically determined oceanic responses for sea scallops there was a shift in settlement this is a full build out with 15 megawatt wind turbines in the Massachusetts Rhode Island area we had basically four scenarios the one that has the biggest impact because they're the biggest turbines and so they reduce the wind speed the most and they have the biggest foundations sticking through the water column so we chose that one to present here but basically it shows a shift based to the southwest of the offshore wind farm build up area there's discernible or notable increases south of block island that's the blue east of Long Island and then there's some distinct areas of decrease which is south of Martha's Vineyard and to some degree in the Nantucket Shoals so this is a very very brief review of how we do our agent based modeling but these are all integrated models in the mic system I know someone said something about open source this morning and we sell our software but for the bone project everybody should know if you are investigating anything that has to do with these two projects following on for I think five years you can get a hold of the models so we have got that in the contract so that deals with the open source issue perhaps deals with the open source issue where the models will be made available to consultants to bone or people that want to review our models through the bone studies next slide so we also have to acknowledge boom this is one of the mandatory slides that we have to put in these are our contract numbers and some of our sponsors are sitting here in the room today so thank you very much we appreciate your support okay thank you questions yes very nice talks very very informative and I'm really curious about the super agent modeling there one of the things I notice you said that area for scenario four with the buildup of the Scalaplarve there was that kind of Southwest oriented local maxima there that went up to Block Island was that overlaying the Buried River Channel there that goes up through Cox's ledge by the way I'm obsessed by that channel I don't know Glenn I'm sorry to say that that's outside of my knowledge of that of that area so we'd have to go back because it took me a number of years to realize that when we were having the fishing vessels collect CTD profiles for us there was this huge concentration right along that that that little depression there and it turns out that trapped a lot of organic matter because that was a river bed during the Ice Age when sea level was much lower for our modeling it would be it would be a deficit in current speed most likely that would cause more settlement there than in another place so that's we were looking basically at the differences in the settlement of these larvae and so what we found was when you when you look at the current patterns and how they changed it's pretty much overlays where the changes are excuse me where the changes are in the settlement patterns and also that channel actually is an important onshore offshore seasonal migration pathway for different species monkfish they catch with gillnets along the bottom there so I had never realized how important that feature was there but the fishing community I guess had three or four hundred years to work this out yes please nice talk a couple questions you said current and waves are not important where they are driver the driver of the Asians based on modeling so I'm curious about the subgroup effects that you mentioned that you say use energy relationship to parameterize the effects of the structure on the flow field so can you elaborate that it's the work of the drag force that we feed into the model so that gives a resistance in the model in that cell then we say the work of the drag force that gives us say the change in the input to turbulence so is your turbulence a scheme also affected by the structures it's affected by structure and also by the stratification the closure the turbulence a scheme yes it's affected there's an input into that from the production of turbulence around that structure so what's the typical resolution for your structures it's about one kilometer one kilometer of your but then you have the subgroup effects that you feed into that into that cell we feed that extra turbulence and also that extra resistance how accurate is that it's pretty accurate if we do comparison to experiments it's spot on because that's the way it's calculated so it's basically to calculate the drag ratio for a cylinder structure that is pretty accurate if you try to calculate the drag I saw you cited several CFD models in our papers so have you compared your model with that CFD model so we don't know we used the CFD and we used some experiments we did a lot of experiments when we did the femur bridge for say mixing induced by structures in stratified flows because no one knows what that is but we did a lot of experiments and then we also did a lot of CFD calculations of that kind of problem and out of that came the calibration of these drag relations it's more since formula you can say it's a kind of steady flows so it's accurate because we force it to be accurate but you cannot go 20 meter downstream the turbine and see the variations that change you for example because it's all into this pixel because we need to both model say the details have the correct impact of the structure but we also need to model more than one year in an area that is huge so it's to compromise how should we do that it's not possible for us to do a CFD model of every single turbine and calculate that for more than 20 seconds absolutely that's just curious about how you parameterize that so called subgrade mixing subgrade effects using energy principles now there was some there was some papers cited you can go back and look you know I had a comment for scholar about the model so have you considered any behaviors because scuba larvae they have observation show semi-diana and diana behavior on the mix layer when it's swanning so they can back reach in the mix layer two times per day or sometimes one times per day if you include behaviors you see the settle down can be completely different so we do consider we do the diana behavior and semi-diana behavior we don't know which ones are correct both observation found that so then you look because migration in the water can mix layer so then after 40 days settle down they can be completely different pattern yeah the answer is yes we take that into account I was trying to let the MIDI ask questions first so this is a bit of a challenging question I think we have to respect either the modeling teams as a developer we have to develop our permitting documents and consider information like this and what as a non oceanographer and non modeler I'm hearing what you're having to say and seeing opposing results right from the models and that is a bit concerning and so I guess two questions one question for you both is can you discuss differing results and then second just a comment to the committee as you're developing the report to please consider and advise folks like myself and regulators how we interpret this variability because this uncertainty does I think really some regulatory challenges for us that concerns us and we obviously want good science that's validated but I don't know how to deal with this conflicting information thank you just a caution this is not like structural engineering where you can do a calculation ask three people and they'll get nearly the same this is still development this is very new science coming up and it's very very complicated because there's so much uncertainty in the real world Glenn will know that everyone will know that so that is part of the background why we get different results so we use slightly different methods and then we get different results so I'm not sure we can promise anyone that we can come up with something that is completely consistent where you can go anywhere and get that you need to have certain knowledge certain insights of someone to go in and make it but I see this opportunity here and also what we do otherwise as an effort to try and converge things and exactly to get results that are kind of agreed that we can everyone regulators developer can say okay this is the ballpark we're talking about because I have the same feeling as you have that today if I look in one paper the world will go upside down if we build this and in another paper nothing will happen and where are we in between that and you can say at least that's what I try to is to try and find sensible numbers that are in the ballpark maybe not within 10 decimals but still something that's in the ballpark and find realistic numbers but it's not easy sorry okay I think Josh and then Richard yeah this is a I guess kind of a follow up to all the the modelers and something that I wrestle with it you're showing and this is I think related to the point that Laura just raised is there a way you've done validation both groups so far and I know there's a third one to come have shown validation is that what's learned through the validation is that accounted for in the derived fields that are shown that the groups are shown or is there a way to include that so that you can understand the derived forms or the images don't show the uncertainty so maybe there's a way to address the concern raised before and I don't know if that's possible with the validation that's done but I think it would be helpful to the community to understand what the uncertainty is in these fields given what you know about the underlying data that went into the calculation of those fields can I answer that so I have two things one that's your responsibility that is that we need more data it's really crucial that we get more data for calibration for validation it is very important I'll just respond to that really quickly and just say I would put any other place on the planet up against our Min Atlantic as a place to look for validation data there's not many places in the world that have more Glenn talked about all the different systems that are in the place and they don't have the entire coverage of the model which is why we need the models there's a HF radar field that provides hourly current since 2007 at every 6 kilometers so there are data out there so I think if we're going to do something like this this is a great place to do it but it has another one that's it's also one of the most complicated places so we need more data reaching the model with the quota data it has the 10 years so for the block island side just in the Nantucket block island they get a sweet quota there we make an 80 year comparison but it really depends on how you compare for tidal simulation the model and the position match the wordware but for low frequency really question so we can get a very good comparison for monthly averaging but then you do like an hourly comparison really tough because the quota they have an uncertainty mostly not for speed mostly for the direction because the quota measurements the average uncertainty for direction is about 20 degree but sometimes if you look recently in the Radical University publishing quota data the whole region so you can see a lot on the short big region uncertainty is most 80 degree 80 and 100 degree angle was a short big region but in the near short region long island side region if you look at the map I have the data I can show you long island region is a pretty good measurement but you will call it the goal of shore the signal error bus is really big so you have a very hard to compare so when we do the comparison we choose the whole measurement one year we choose the high accuracy data they have a certain number there you compare the subtitle and the title current they come out really good but however you have to consider uncertainty in the measurement but the quota is hard to compare most of the good data comparison is more in data the more in data because the uncertainty is really small you can get a good comparison I don't want to defray the conversation I did my PHD on HF radar I am very familiar with it I was making a comment that you all showed validation and I think there is an opportunity to take what you learned from that validation with whatever data you had and actually put it into the results here so we know if velocity has a certain uncertainty in comparison to whatever data you chose to validate the model against how does that impact where larvae might go in the model projection that's just the suggestion I think that would be very helpful we can have conversations about which data sets are good or bad for validation but when you chose the data set you validated against and you got some numbers so how can we take that and put it into the file they get so many ADCP close you can see more than 10-year data cross-region results show a big region so we do compare we know the uncertainty but interestingly we can send you the comparison they also intrude sometimes the model depends on how you model if you get a simulation you get a very good comparison sometimes you feel the simulation you don't get a very good comparison but in the shallow region you have to remove the ties but either comparison that's pretty good I'm pretty sure you see that the comparison was pretty good okay I think did you have a response to that Richard and Christina there was one more answer that was about the uncertainty when we do these design studies it's a little bit easier you can say modeling wise to get accurate results but there we do 40 years typically and we do a lot of effort to quantify uncertainty because that goes into design and money it's also important as it is here so it's something we do but it's not straightforward to do I think Richard and then Christina so one thing that I'm curious about is how we compare between models based on what we see of the spatial extent of the outcome sort of the model run so in Chen's example that was just the project 501 Vineyard Wind correct? what we saw of your project was basically the model runs for project 501 Vineyard Wind project what type? for scalps, for distribution of scalps I don't get a question sorry sorry I didn't get a question so the project you use the 100 turbines that was basically Vineyard Wind no the wind tide because it's a nesting model we run a global model we're reaching the model reaching the model comes from a handcast but you were not modeling the full build out for all the projects south of the Vineyard and the Nantucket no I just saw for the one 100 yeah whereas what we saw from y'all was the full build out yeah that was crossing areas it's kind of hard to compare the results of those two and I think some of us are probably curious about how you see the results of a single turbine you can't extrapolate that to a whole project or obviously so you can expand out to the whole a project like 501 or Vineyard Wind and that has an effect but I'm really curious about what the overall effect is going to be from the full build out from yours but do you have any chance what you saw with 501? that was one of our scenarios I know it was one of the scenarios right now? but it's in our report that would be the I think someone picked up the difference in the distribution of scallops that's very different in change results than in yours it could simply be the spatial scale of the model you know the 501 no key usual difference separation scale because when you put the wind turbine into a system separation scale between the turbine is critically important so now the industry agree they have one necromine separation scale when we do the bound project of 2014 the separation scale is a fine necromine so we consider whole region but only put 135 turbine into a system but separation scale separation scale is a larger influence is completely different for separation scale smaller so they consider about we get 100 wind turbines just in one design the wind the small area put 100 separation scale is the one necromine if you put a whole region it is a separate scale the influence can be different I understand that the full build out may look very different than your results I think Christina we can come back to your question unless it's a quick question that's scallops I'm concerned about running out of time I want to give York a chance to tell us about a third model DELF 3D York is a senior researcher and advisor in hydraulic engineering at DELTARIS and please tell us about DELF 3D I'll just open my presentation while everybody's going for a body break and getting some water a break is after your talk so they're not excused from the classroom right now everybody's excusing themselves explicitly concerned I want to compliment our everyone I'm visible let's start then model number three has often been referred to in the previous talks also commonly known as DELF 3D in this case now we'll talk a bit about the same topics that my predecessors talked about using this modeling suite to assess ecosystem effects of offshore wind installation so to tell you a little bit about DELTARIS I think we have a rather similar company profile as DHI we are also an independent institute for applied research in the field of water subsurface and infrastructure and we do a lot of offshore wind related work together with both universities but also with the industry so for example the nice photo you see in the background of a turbine getting attached with a very big wave is from a physical model that's performed in our delta flume within a project consisting of over 20 consortium partners dedicated to develop guidelines for sky protection methods culminating in a broad industry supported handbook the mission of DELTARIS is enabling delta life and offshore winds of course vital and I think the past 10-20 years we're all dedicated to making offshore winds affordable we're more or less there now so the challenges for the future are in upskating are in multi-use and of course also in ecosystem impact so to say a little bit more about what we do in offshore wind it's consisting of all these topics not limited to so for example we do also met ocean studies we have geotechnical backgrounds swell corrosion and water replenishment that's also something we do every now and then for Bowen and of course one of the bigger topics is ecological impact both positive and negative and in that framework we quite often hear terms like nature inclusive design or net positive impact so nature inclusive design is really to integrate your design in such a way that you can alleviate pressure on the ecosystem and depending on how you do it you may even strive for achieving a net positive impact so you leave the ecosystem in a better shape than you found it and of course that's all in the eye of the world but those are all topics at the moment so when we talk about nature inclusive design I'd like to sketch the framework before going on to DEL3D and its capabilities because of course ecological impact already starts with the installation I don't know if you ever had the privilege to be witness of a pilot installation I only had that in a physical scale model experiment but it's very very noisy in wildlife marine life is impacted by the installation so you want to achieve more noise mitigation or silent installation techniques for example as a way of mitigating impact on the ecosystem then once your pile is there then we see at the moment that with scout protection installed you create new habitat and that results into an enrichment of marine life around foundation structures that can go of course on a local scale so per foundation but that accumulates over an entire wind farm you need to take into account of course the entire system we have cables that emit radiation and heat that have an impact on the environment in certain offshore wind development areas you also have migrating sand waves that could lead to clogging of the pore space you created so it's an entire system talking about an entire system of course the turbines they impact also the hydrodynamics by creating more turbulence realizing more mixing all these things that we have already talked about but it's accumulating of course on the scale of an entire basin within the monopile of course microclimate and bringing all of that together in an integrated fashion where you combine modeling monitoring to establish your impact that's what we mean with this nature inclusive design for offshore wind farms so I will now talk a little bit more about hydrodynamic modeling in general I'd like to sketch a framework for the approach and go into a bit more details of DEL3D so outlying its base assumptions and limitations and from those assumptions I will show you how we have applied this model to assess impact of offshore wind development to give you an idea of what you can do with it but also of course on what you cannot yet do with it and that's equally important so of course there are various types of models that you can utilize to assess impact of offshore wind so far we have mainly talked about process based numerical models but of course there's physical models as well numerical models but also more simple engineering tools and of course they're depending on what you want and not all models are equally fit for purpose and of course we focus now on the numerical model approaches and there you can also choose from different flavors where you depending on the complexity and detail that you want to layer you can make similar choices so for example we have this 1D network models that you could use to model rivers or maybe even tidal channels going into more complex 2D 3D area models and we talk about tidal inlets seas offshore wind farms or even more detail more complexity local high resolution CFD model and that's typically on the scale of single structures and the actualization of a CFD simulation that was used to assess the impact of a slamming wave on the loads in the secondary steel structure that's the level of detail another thing that has not really been mentioned today or at least implicitly but a model is a tool and it should therefore be fit for purpose what do I mean with that well if you try to drive a screw into the wall with a hammer you're not doing yourself a big favor for a job so you always need to ask yourself what do I want to model and what is the level of complexity required to achieve my goals and that means that when you can go simple go simple and if you have to go complex then you have to go complex right so it's different flavors what do I mean with that we'll get there so on to Dell 3D Dell 3D is a multi-dimensional hydromorphodynamic simulation program that can calculate non-steady flow and transport phenomena resulting from tidal and meteorological forcing that's a mouthful but it means that it is very well suited to model for example tidal in its estuaries waves morphodynamic processes I used it myself to model a mangrove forest but I also used it to model bar dynamics in the surf sauna that was only during my student time it's very versatile and it can do a lot it makes use of curvilinear grids in combination with unstructured elements so it uses the best of both worlds in terms of flexibility but also in terms of formants talking about computational speed and accuracy a very nice example where we combine curvilinear and have a good layout in tidal channels with unstructured grids to combine different parts because if you want to do this with only curvilinear you're going to have a very ugly grid so here we combine it with unstructured elements to get a very nice looking numerical grid that also leads to good performance it makes use of the shallow water assumption and I think most of the models that have been discussed here do that means that we assume that one of the three dimensions is much smaller of scale than the other two so the depth is much smaller than the horizontal scale that's what you see here in reality we talk about water depths of 30, 40, 50 meters in wind farms and we talk about horizontal scales of kilometers of course your vertical dimension is much smaller than your horizontal dimension but it comes also with an hydrostatic pressure assumption right so in the vertical dimension you do not solve the full momentum equation you solve a hydrostatic pressure equation so that also means that you do not explicitly model vertical acceleration your vertical acceleration is assumed relatively small compared to gravitational acceleration so that means in DelphiD vertical velocities are computed using continuity relation it makes use of a Boussineski approximation so the effect of variable density is only considered in terms of horizontal pressure gradient so vertical variability in density is taken into account by the model and vertical mixing is computed making use of diffusion eddy diffusivity and eddy viscosity coefficients but in terms of the impact of density variations on the pressure it's only taken into account in horizontal pressure gradient in terms and last but not least it uses Reynolds averaging for turbulent fluctuations so that means that you resolve for your mean flow velocities and you take model schematization for your time average part so you make a decomposition into a mean and a time average part and then the model makes use of an eddy viscosity concept where the impact of turbulence is modeled as an eddy viscosity and as an eddy diffusivity and DelphiD also makes an anisotropy in the turbulence which means of course that the horizontal eddy viscosity are typically much larger than the vertical eddy viscosity so that means that vertical mixing processes are very well represented in model but on a mid too far field skill so not on very very near field skill so that's good to realize here so it has a bottom boundary and a free surface boundary both an impermeability boundary kinematic and a free surface at both free surface and a bed and the momentum boundary condition of bed shear stress at the bed and wind shear at the free surface now of course offshore you do not have only flows you also have waves and DelphiD also explicitly takes into account wave current interaction where the wave processes are modeled with a separate model that is coupled to the flow module which is called S1 simulating waves approaching the shore and these wave processes are accounted for in a wave average manner so your wave induced forces they are imposed as gradients in your radiation stress and to account for vertical non-uniformity in those velocities it makes use of a generalized Lagrangian mean method and it does affect the addition of bed shear stress component so it's a high level of detail and of course what we know or we have seen figures like this and so we know that in offshore wind areas in seas in general there can be sediment transport and we know that turbines have an impact on sediment transport and you can imagine that if you have sediment concentration in your water column that may have an impact on the ecology by simply determining how much light can penetrate through the water column so it's quite important that your sediment transports are also taken into account in the computation so DEL3D computes both bed load and suspended load for both non-cohesive and cohesive sediments and it can also do morphological updating if needed now the flow module can be coupled to a water quality model and that can also be applied as a process based model so it can be applied in a more passive way so that for example nutrients or pollutants are modeled as passive tracers so they are then affected by the flow but you can also use it in a more let's say complex manner where you take also all the various processes that are outlined here into account are coupled in an online manner so that means that you can simultaneously with your flow and wave computations and with the vertical mixing of your water column also all these processes are considered we are now looking at the chain of effects associated with not only wind developments but coastal seas in general factors, human pressures for the climate discharge, shunt mining and there somewhere in between comes offshore wind below we look at the ecosystem and all the various interlinks between all the processes there and of course we know that offshore wind it has a direct impact on current waves and wind and maybe a slightly less direct impact on the bed and all these processes they also influence each other so that means that you can already draw out the lines where you expect there to be an influence on the ecosystem and this is the way that we do it so we go from the environment towards the ecosystem so that's called a bottom up approach and we work together with partners who start on the other end of the spectrum so with the birds and mammals and they work that's called a bottom I have top down approach and somewhere they have to meet right, somewhere they have to meet and they are complete so we know that there are many different processes acting on many different lengths and time scales we have on the scale of an entire history we have stratification due to density differences related to fresh water and saline water but also of course related to temperature then on the scale of a wind farm or of singular turbines we know that they lead to differences in mixing so they lead to increased sediment transports around the base so you have different suspended metric concentrations in the wake of the turbines and the mixing can negate the impact of stratification so there's a lot of things going on and of course very locally we also have maybe the formation of a new ecosystem due to the hard substrate that's introduced in the area and due to the structure itself so we want to quantify all that in one single model but it also in every means you have to make choices because there is so much variation between the length and time scales if you want to capture that in one single model and explicitly resolve everything you need a very very good supercomputer and a lot of patience so you need to make choices I'd like to show an example of how we did that this is in the WOSEP project that I referred to earlier it stands for wind at sea ecological program and it's a large scale research project funded by the Dutch government to assess the impact of large scale of wind developments in the North Sea this model that you see on the right is the Dutch continental shelf model and it's a model of the entire North Sea basin it's a 3D model with a finest grid resolution I mean it varies over the model but with the finest resolution of roughly half a nautical mile it can calculate temperature and salinity stratification and it does so quite well as you can see in this figure the water temperature for example is quite close to what is measured it can also calculate fine sediment concentration so here you see for example the difference between the summer surface mud concentration and the winter surface mud concentration so you see there's very clear seasonality fine sediment concentration predicted by the model and it also being coupled to the water quality module it also is capable of modeling primary production and here you see a comparison of the calibrated model with measurements performed I think it was at Nordwijk in front of the Dutch coast it then makes use of dynamic energy budgets to assess the impact on wildlife so that means that for different umbrella species we can assess what is going to happen if you go for a large scale of your wind development in the region one thing that still needs to be implemented is a direct coupling so that's one of the shortcomings of the model at the moment and it's being worked on this year so that's a development step for the present year another development step for this year is to incorporate zooplankton and of course we want to reduce the gap between the bottom-up approach and the top-down approach another very important aspect that has been discussed already is the parameterization of the foundations because of course you can imagine with resolution of half a knot we do not explicitly model the foundations we use a similar approach as our colleagues from DHI we parameterize the impact of the foundations as track coefficient but that involves a very direct coupling of course between very local processes and large scale processes and one thing we do here as well is that there's a coupling between scales is highly relevant you have these very complex flow phenomena around the wind turbine and that's in the order of centimeters to meters so you need a very fine grid resolution to capture this accurately whereas of course on a large scale we talk about kilometers and that never matches if you want to make a prediction of the impact over multiple years you don't have the computational power to do that on a very small scale so especially if you want to model the impact of offshore wind development on an entire basis which you can see in the right so you want to have good insight into all these small scale processes what they do with salinity mixing, with temperature mixing so with your stratification but also with your suspended sediment concentrations in the wake of the foundation so for that we use a more detailed local model as a research tool so here we see the results of a CFD simulation for example to get the correct relations for a parameterization and to get the right impact it's very similar to what our colleagues from BHI does and there's the consistency between all the model approaches and we compare it with actual field data so we supplemented with actual field measurements so this is from a recent campaign performed last year and here you see for example in the wake of a monopile that there are horizontal gradients in both temperature and salinity in the wake of the pile so it's also very relevant to take those impacts into account in your parameterization so it's not just the drag coefficient but it also has an impact on your stratification but also in your suspended sediment concentration and these need to be parameterized a lot so you have all these puzzle pieces wind, waste, current, sediments nutrients, light, temperature see that your foundations and maybe one or two unknowns you don't need to have all those pieces in place to solve the question of what the impact of offshore wind development can be for example here we also see an image where you do not have all the pieces available but still you can see that this is a tree maybe somebody knows exactly what kind of tree this is of course if you want to know who is walking next to the person in front of the tree you need more information but with the information we have we can already see that there's probably somebody walking next to that person so you don't need all the pieces to make useful predictions and that's the way I think we all do it now that we accept that the model is not perfect but it's good enough, it fits for purpose so you can focus your efforts both on model development and application, right, the DEL-3D model it's also not yet complete it doesn't incorporate explicitly the effect of wind flakes it doesn't incorporate to a plankton but that doesn't mean that we cannot use it to make useful predictions at the moment by following this scenario based approach that DHI showed as well and for example within the WOSA project we looked at a couple of scenarios unexpected developments but also on for example an extreme upscaling scenario where we fill almost the entire North Sea basin with offshore windparks and if you compare that to a reference scenario without any turbines for example and you validated that school word it gives a very good impression on the impact of different scales of offshore wind development and that also shows that scale does matter so one windpark may not do that much but 20 windparks do a lot and the North Sea is of course a special case it's kind of like a bathtub so there is not much room to develop maybe in the US coast it's a bit different because you have the Atlantic Ocean adjacent to your developments but still a scale matters that's one of the important messages here so that also means that to know what happens or if you want to know what's going to happen at the Nantucket Shoals I'd say it's also a good idea to take it to account all the other wind farm developments that are going to happen along the US coast simply because scale matters in the North Sea we see that the impacts vary per region and it really depends on the local dynamics and so in the Central North Sea we see that this stratification is something that is dominant in the German Bight which is a very complex area and suspended matter is dominant we see that you have we know from that area that there are a lot of fine sediments there so it stands the reason that offshore wind development in that area has the largest impact or on suspended matter on the English coast and the Watern Coast we see that there are relatively minor effects of the upscaling in the Rhine-Rofi area where Rofi you've seen the term before in one of the previous presentations stands for region of freshwater influence and we have the Rhine River which has a huge impact along the entire Dutch coast there offshore wind has mostly an impact on suspended matter transport it has an impact on these stratifications so it leads to different suspended matter transports and on the Darger Bank so far we noticed that the impact is relatively minor to make the final step to an application at the Nantucket Shoals as our colleagues we also have a model of the greater area this one is the Massachusetts Bay Model which was developed for the Massachusetts Water Resource Authority to assess the impact of wastewater on recirculation in the Bay so they have to make yearly predictions showing that what they do is acceptable so we have a local very refined grid and it's just a little bit more south of it is the Nantucket Shoals but of course that means you can do a refinement in the area of interest that's always something that's possible because the offshore boundaries are very well established and the model has been validated with available data of the area and it is already equipped with a full water quality model so if the impact also plankton is implemented in the model as we have it now that means that you have a rather direct link with the North Atlantic right wheel if you can model the impact of offshore wind development on zooplankton relatively I'm not going to say easy but a relatively straightforward coupling to what may happen or what the impact could be on the habitat of the North Atlantic right wheel so to kick up with a couple of conclusions I hope I stay roughly within time the DEL3D modeling suite is I think very capable of assessing the impact of offshore wind development on the environment it captures all the relevant three-dimensional processes suspended matter concentration and is equipped with a water quality module that can also be extended to include ecosystem modeling but we still need coupling with other models and model approaches to get a complete picture and that's still required and of course the model doesn't need to be perfect it needs to be good enough it needs to be fit for purpose the term impact that needs a very clear definition impacts in the eyes of Walder and there's a lot possible in terms of mitigation and maybe even creating that positive impact but that also means that you need to very clearly define terms like positive and negative in a very early stage as early as possible and of course you cannot enhance or restore or protect everything everywhere at once I think that's an Oscar-winning movie so you have to make choices and an integrated approach is required here so that means that you need to think very well about your legislation for permitting and decommissioning and this one it seems like a side note but this may be quite important that stakeholder engagement is maybe as important as the technology so I'm very happy to hear that you have been talking with the fishermen for almost 20 years now that's extremely important we see it in the North Sea as well everybody needs to be heard and that's my final say thank you for your attention okay thank you alright questions for York make sure I look around yes go ahead yeah thanks thanks very interesting and this question I guess is really a two for all the modelers one is with respect to Scour and the other one is about Zoplankton and New Fousins and we can just discuss we've heard a lot about the sediment impacts but do they take into account various Scour strategies whether that's from putting down Scour protection itself or another nature-based solutions for Scour protection which includes planting seagrass and things like that so that's one and then the other one is I guess probably for most particularly for DHI has anybody done agent-based models for Zoplankton or New Fousins that actually have the ability to move themselves against currents if you allow me to respond to the Scour question then I'll leave the agent-based modelling question to DHI so it's quite typical to have Scour protection around your foundations but in high current areas you still see that there is an increase in sediment transport in the edge of your Scour protection so you cannot protect the entire Seabed so at some point you stop and edge-cour that can depending on your flow conditions extend quite far outside of the footprint of your Scour protection and that we're not talking about meters of Seabed level lowering but just enough to increase the sediment concentration in the water column every now and then and there are indeed efforts on alternative Scour protection systems so now it's just loose rock and that works quite well because it introduces hard substrate and it turns out that marine life likes hard substrate and with a couple of small adjustments like choosing larger rock to create more pore space or introducing luxurious material to facilitate oyster developments there's a lot of possibilities in terms of inclusive design artificial protection systems are being developed we also see that what I understood from my ecological colleagues is that seagrass growth on depths of typical offshore wind farms is a rather nonexistent because the amount of light that reaches the Seabed is not sufficient so there are some alternative Scour protection systems that make use of artificial vegetation but that's plastic it's plastic fronts it may also create a habitat that's suitable for marine life but I also know that not everywhere in the North Sea you can get a permit for those kinds of systems simply because they're plastic yes are those results in the report anywhere we can find some talk to the guys we do whales for example they move but they move quite differently than you thousands and still the corpus they move to cause up and down but they also get affected and Mary or Brian may want to jump in here so all the projects Doug have to do submit transport modeling so if you look at any of the cops you can find a modeling that's project specific as well as a description of the Scour protection that each project takes on so it is project specific and I don't know Mary if you want to add any any other questions or comments when we did the study first when we discussed about this whether we should include the Scour protection I think we actually include Scour protection in the resistance calculation for because they also take up some but how important they are for the accumulated impact on a larger scale right on the hydrodynamics itself yeah maybe a little bit that changes the resistance anything else any other comments just an observation it seems like that what we could benefit from would be the equivalent of the community model intercomparison project for the different models that are being developed for offshore wind energy development but anyway that would be a pretty interesting project I would think yeah as Jorik said we are a little bit tweens institutes because we have same history and has competed all our lives and we have compared results for different projects they have been compared very very closely and I think we can agree pretty close that would be although I do think that in the North Sea we were just a little bit better here we go who's doing Dutch water right now so maybe with that we'll take a break alright yeah let's not do that okay maybe a 10 minute break return and okay okay alright okay we're going to hear we've got two topics to cover here after our break and the first one is going to be from Christina Archer from the University of Delaware and looking at atmospheric modeling for wind turbines, wind turbine effects on the wind stress we certainly heard a great deal about that already today and so now we're going to hear even more so Christina please should I use this microphone so the people online can hear you so thank you very much for inviting me and it's my pleasure today to talk to you about atmospheric wind turbine wakes so we're switching from the water to the air and that's where I'm going to stay for the rest of my presentation I'm going to show you some modeling as well and some observations of these wind turbine wakes but I would do a disservice to wind turbine wakes if I didn't show you these two pictures these are actually photos so they're taken with regular photo machines and as far as I know they are the only two examples of naked eye visible wind turbine wakes in the world today so you all now know just as much as any expert in the world about what wind turbine wakes really look like to the naked eye they're basically almost impossible to see naturally these were very special days in the offshore environment of Denmark this is the horns rev the two horns rev farms and as you can see from the dates they were taken eight years apart so that's how rare they are so next year maybe we're going to get another photo or something like that so they have to be the right conditions of humidity, stability and temperature for those to be visible but the main point is that you can see how these wakes are regions or plumes that form downstream of wind turbines these are not pollution plumes there's no emissions there's no pollutant in there it's just water vapor that's condensing but it kind of shows you the features the cylindrical nature of the wakes sometimes they expand and become very very large and sometimes they stay kind of tubular but this is what we're going to talk about where we can observe we can also observe wind turbine wakes via LiDAR systems and these are examples of what these wind speed deficits look like LiDARs are basically electromagnetic waves that are safe to the eye that pick up movement of particles and the Doppler kind of effect can tell you what the wind speed was and behind the turbine you will see this wind speed deficit meaning that there is reduced wind speed with respect to what the wind speed was upstream so in the first figure in the middle you can see a vertical cross section of a wake this is the colors are like the more red the faster the wind speed so blue is kind of like indicative of a deficit and the same color scheme is pretty much in the other in the other animations in the other picture the picture on the left is taken from the Lewis turbine of the University of Delaware we own a GAMESA to megawatt turbine on the marine campus in Lewis it's been operational for some 10 years and we sell basically excess electricity to the city of Lewis for a profit I guess and the funds have to be invested in research on wind so we can fund some students and initiatives related to research so it's a very cool initiatives that because of the turbine another way that I can show you some wakes is via large eddy simulation which is a form of computational fluid dynamics and on the left is a single turbine wake and the rotor is where the circle is and again the color scheme is such that red is fast and blue is weak and you can see how dynamic the environment even around the turbine is so there's turbulence in the wake sure but there's also turbulence outside of the wake on the right is actually the Lillegrund wind farm which is my favorite farm in the world it's it's located between Copenhagen and Sweden and this is a 48 turbine farm and that's an example of a simulation again blue shows you where the maximum wind speed deficit is located and just so you know it these simulations take the one on the right has taken something like a month and a half on 144 processors continuously running for a month and a half and it gave me maybe 20 minutes of results so these are very intense simulations that need to be done you can also use a mesoscale model such as the wharf and use a parameterization such as what other colleagues have used this is a simulation that we have conducted with the wharf model and the Fitch parameterization which is the standard one that comes with the model this is the day of the summer of 2018 we simulated the entire summer the day with the longest possible wakes from all the planned offshore development along the US at that time all the wind energy areas are filled up to the stated capacity and this is basically the worst case with the longest wakes and as you can see they can become rather long maybe reaching 100 kilometers or something like that at times you can see overlap of wakes from different farms, neighboring effects you name it I want to point out how crucial it is in these kind of simulations it's absolutely crucial to have enough resolution in the vertical it's you need to have at least three if not four points below the rotor in order to capture the surface effects enough and this was extremely hard to do so if you only have one point below the rotor you cannot possibly solve the divergence convergence effect that I will describe later and you can probably you will probably get the wrong sign of the heat fluxes and turbulent fluxes at the surface if you don't have enough points below the rotor but also prior versions to I forget the exact version number of Worf but there's been a 10-year the version of Worf over 10 years had a bug a code bug so any results published in the literature during that 10-year period basically has a major bug in the code so there's a paper on this and the community is aware if you've just be aware of that it's possible that if you get some strange results it's because there's a bug in the code why do we care about wakes aside from the fact that they can have you know they can be very long and impact communities but I think the main reason that we care is that they impact power production the most so this is the layout of Lillegrund which I mentioned already before and I'm focusing on that column of turbines column B and let's imagine that there's a south-westerly wind so the turbine 15 is the first one and that is the line here I don't know if I want to dare touch in the screen because my colleagues have had crazy effect but this line one means 100% turbine 15 produces 100% of what it can at the wind at the wind speed of interest but then the pink line after that and I'm not going to touch it but the second turbine which is number 14 does not produce 100% in fact for the wind direction of southwest around 220 it produces 30% of the power of the front of the front turbine and same for the next turbine 13-14 instead of producing 100% they produce 30% of what they could and why is that because of that wake the wake of the front turbine hits the second turbine the second turbine does not produce as much as the first and this goes on and on and on in the farm by what? is the wind direction so the one with the minimum is exactly 217 and then you're around it and so let's take a look at these wakes in more detail and I'm going to show you some literature data and some of my own results this is actually literature this is a wind tunnel experiment and it's actual measurements from a long row of small turbines and the colors that happen to be the same so I really love that so if you look at the blue that's the wind speed deficit and as you can see it touches the ground basically relatively quickly so the wake of the turbines in terms of wind speed deficit indeed reaches the ground pretty much after after every turbine you see the blue shade where there was a higher wind speed before upstream the second issue that I want to point out is something that came up today about how the wind speed deficit is not cumulative and this actually illustrates what I mean you can see that between the first and the second turbine there is more of the blue the dark blue that means that the shade is still he doesn't get any darker in the second turbine than in the first one and then if you actually continue and look if you focus on the dark blue you can see that he doesn't get any darker at the third or the fourth or at the fifth the maximum wind speed deficit kind of like remains the same and if anything the further you go in a wind farm the less of the deficit is so it's not only non cumulative it's very non-linear and very hard to actually predict you can use also large eddy simulations to look at the wind speed deficit these are three cases for three stabilities stable, neutral and unstable and now the color is reversed so you have to look at red for a stronger deficit but it reaches the ground between four, three to five, six diameters so the wind speed deficit reaches the ground translated offshore for the oceanic community it means that the wakes do reach the water the surface which we suspected already for. You can also use Worf again this is a meso scale model with a parameterization and if your parameterization is correctly done you should see the same effect and in fact we do so these are results from the mid-Atlantic wind energy areas and on the left is the deficit at hub height and of course it's the largest so we're expecting that that's where the maximum deficit will be but when we focus at the surface and again you need to have enough vertical levels to really see that there is still an impact at the surface so the wind speed deficit does indeed reach the surface but it's very modest compared to hub height I have the line, the dashed line was 0.5 meters per second that is kind of like to me it's almost like a threshold of detectability, LiDARs have a hard time detecting the difference that's less 0.5, some LiDAR experts might say oh we can get to 0.3 but you know around 0.5 is what we can detect so as far as measurement is concerned you're not going to be able to see anything except the 0.5 line which for the most part is limited to where the wind farms are so on average at the surface you're not going to see wakes in Long Island because of the offshore wind farms offshore of New Jersey everything remains relatively local and we also have some simulations that are more relevant to this community for the offshore wind areas here and again every region is different but for this region there's even less of an effect at the surface it's almost non detectable and this is a three month summer average that we did now we can look at turbulence because if wake remember has a wind speed deficit and added turbulence so how does this added turbulence behave and these are again wind tunnel experiments or measurements for only two stabilities neutral and stable and I want to point out first of all obviously there's a large injection of TKE TKE's turbulent kinetic energy i.e. turbulence large injection of TKE near the upper part of the rotor my face is frozen I don't know okay it's back so so that's where most of the TKE is added and if we focus now at the ground which is where we're interested in look at that we actually see a reduction in turbulence near the ground so there is no enhanced turbulence near the ground in the wake of a turbine if anything there is a reduction of turbulence and this is from wind tunnel experiments by colleagues we can look at more wind tunnel experiments represented in a slightly different way this is a vertical profile of turbulence intensity before and after a turbine and again at the ground you see the green dots are upstream and the symbols are after the presence of a turbine and the turbulence intensity near the ground is reduced we can also do a large eddy simulations and these are some of some of the results in my own team and we can see upstream of this turbine we saw you know reds and oranges and then downstream we saw more greens and again turbulent kinetic energy from other LES simulations show a reduction of turbulence near the ground downstream of the turbine these are some results from my PhD student using yet another LES code and the first row of results is for a single turbine and the second row is for a farm so several turbines in a row and regardless of the stability we see that blue near the ground a reduction of TKE near the ground accompanied of course by a large enhancement of turbulence but that's near the top the rotor tip so again if we look at the with the work model we want to see if this is actually resolved and if you have enough points below the rotor it will in fact here we have the TKE added near the rotor top on the left so a lot of TKE added because of the presence of the farms but once you go to the surface you see that the color switches from warm to cool colors and that's because there is indeed a reduction of TKE at the surface so at the surface we're expecting reduction in wind speed as well as reduction of turbulence so do we see this in actual measurements can we see these effects in an actual setup and again I'm going to use the Lewis turbine as my I held a field campaign around there and it shows you where we are so Delaware I can't point but the turbine is shown in the figure down there the way we set it up was that you can't really see where the turbine is let me see if I can go this is where the location of the turbine is we have a radiometer and met tower upstream of it we have LiDARs and we have 15 surface flux stations in the field behind it at the end of the summer the prevailing flow is actually northeasterly and so the flux towers are in the wake of the turbine and there's a lot of measurements that we did on each of those sensors and these are kind of some examples of the wakes that we detected and so some random days and as you can see the wake is pretty long it meanders it's not a straight cylinder axisic symmetric it's very meandering and even in the course of a few hours it can be over different stations so at the second time one it can be over station S1 six hours later it's over station S3 and things like that so to quantify the effect of the wake really correctly it's very important that you take out any other reasons that could cause it changing let's say wind speed so just looking at a station before and after a wake hits it might be it might not be sufficient because there could be other reasons that cause that difference so the way we did it was we used the difference in differences approach basically we always compare two stations at the same time simultaneously and one was under the wake and one was not so we do the measurement of that difference when one is under the wake and then we compare with the measurements when none of them is under the wake and by doing that difference in differences we are positive to isolate the effect of the turbine and so this is an example of how that works for wind speed on the left we looked at stations S2 minus S1 and in green are the wind directions where none of them is under the wake so they are basically there's no difference really between the two so all the dots are around zero when there's no wake they are pretty much measured the same but when S2 is under the wake then there's that oops the difference becomes negative which means S2 has a lower wind speed than S1 and that's due to the wake and so we could look at the effect of stability and it doesn't seem to impact it very much so regardless of stability we saw a reduction in wind speed and the right figure is actually friction velocity which we used as a proxy for turbulence and we were very pleased to see that indeed also turbulence was negative when the wake hits station S2 which means again that the wake causes a reduction in turbulence at the surface we were also interested very much in a lot of other parameters and I'm going to show you a bunch of results here you don't even need to look at the numbers or anything but blue means that the results are statistically significant and they are a reduction so we found a statistically significant difference in wind speed when the wake hits same for friction velocity always you see the blue in the table a statistically significant reduction in heat flux although heat flux is so fluctuating and very difficult to measure differences but anyway we could find some statistically significant reductions and the last one is actually temperature and it's not blue it's red because there is a slight warming that is statistically significant and so we were trying to figure out why that is and first of all we looked at some LES results and we were pleased to actually see the warming in stable conditions also in the LES results on the left for single turbine right from a farm basically a row of turbines and I'm almost emotional when I look at these results because it took so long to get them but first of all it's very important that you notice how there's a bipolar distribution basically so wind turbines do not heat the atmosphere by any kind they don't do that so they just mix and move air masses up and down so if you get warming somewhere you're cooling somewhere else you're taking warm air up or down and so you're bringing it down you're warming here but you've got to cool it somewhere else so it's very nice to see that we did see that so every time you see warming at the ground in stable conditions it tends to be accompanied by cooling aloft so the net effect should be around zero because turbines do not cause a net effect and for turbines you have the more the warming and the cooling can be so in a sense the temperature effect is cumulative whereas the wind speed deficit was not cumulative so you see how there's more red when there's a farm but the last point is also that this warming I have this beautiful figure that seems like there's a strong effect we're talking about 0.1 degrees Kelvin of warming so very hard to even measure it is statistically significant and due to the turbine but it's not large in magnitude and when it's unstable actually you can find maybe a little bit of cooling at the ground when you have enough turbines the little blue shade there and a little bit of warming aloft but when the atmosphere is unstable the effects are very small insignificant so why do we have a reduction of TKE near the ground and to spare you a lot of math the brief story is that if you focus if you focus on the difference between the blue profile which is the undisturbed wind speed profile and the red profile which is the typical bite that the turbine takes out of profile it reduces the shear near the ground and once you have reduced shear the TKE production term is reduced and so you get a reduction of TKE because of that but what about the warming why do we get warming and it took a long time to understand how I can get warming at the surface in stable conditions when my heat flux is actually reduced at the surface that was like something must be wrong but it wasn't and the reason is that just knowing the sign of the heat flux is how if the heat fluxes are actually converging or diverging at the area of interest and so when you have a stable case like this and we have the downward heat fluxes with this distribution so strongest at the surface and weaker aloft and you have an enhancement of TKE in the upper part of the rotor only that means that the heat fluxes there are enhanced so the arrows pointing down become larger downstream near the upper part of the rotor but near the ground they're actually reduced so what happens is that you have enhanced fluxes in the rotor area you have reduced fluxes at the surface you create a convergence below the rotor and that convergence is the reason for the warming and it's also beautiful that vice versa you get the divergence aloft because more more heat fluxes into the rotor area mean that there's a divergence above the rotor and cooling in that region of course when the atmosphere is unstable it's all flipped and it's the other way around and so we were actually able to verify this mechanism with vertex on the MET tower on a few occasions when the wake was the other way around and it was interesting to see that the black line represents the divergence and convergence and you know it's a positive divergence before the wake hits and then in the gray area is when the wake comes and it flip signs it becomes negative so there's convergence and light warming and then the wake leaves and the convergence becomes positive again it was really nice to see that in the observations we looked at LES results of course to look for this and I'm going to spare you the equation but the line that you need to look at is that red line which is the change in the convergence so a positive change in the convergence means more warming and the negative change means cooling and for the one turbine case and the row we see exactly the maximum of that warming and cooling at the locations where we saw the warming and cooling indeed so it looks like this divergence convergence mechanism is really key and it also happens but on a much smaller of much smaller magnitude of thermal cases and then the big surprise we looked at the results from the warf simulations and it's the summertime the atmosphere is stable I'm expecting warming at the surface after 10 years of studying wakes everything was good and I look at the results and it's like what that's slight cooling caused by the wind farms like you've got to be kidding me the model is crazy right and so we're trying to see but is everything else correct and it's beautifully correct everywhere else so look at how above hub height we found the blue the cooling above the above hub height and below the rotor is indeed the warming due to the convergence that we had identified but this warming for some reason doesn't get all the way down to the surface of the ocean and we were struggling with understanding why that was until and by the way there is a direct correlation between