of infrastructure Over the last decade and a half at time of a water. I learned a thing or two how these seemingly unrelated Two aspects are related I lead the planning and decision support group planning planning is basically looking at the future with our supply The decision support is Who's doing the modeling now typically people don't Really remember about us as long as there is shortage or there is a bill which coming up because of infrastructure Hey, your water bill is going up Then people really remember what we are doing. So most of the time what we do is behind the scene It's okay, but that's how we do To give you a perspective Grant mentioned his bias for california My bias is for florida and he's actually generous enough to give you the whole map I'm not showing the whole map of u.s. Even Time of the water is at West central Cost you can see we have we are whole shared water delivery for three counties and three cities The right side you will see that it's just Some of our infrastructure. So we have a very diversified portfolio Groundwater than the one in the left top panel. You see is the ground water a typical well filled And then also surface water withdrawal Off-site reservoir and a desalinated sea water. We used to say we are The largest in america, but san diego came back and we now we are saying the largest in the east coast Which still works So the challenge is that 20 years ago We are actually celebrating our 20 years now 20 years ago. Everything was coming from groundwater Because of that shift to diff to diversify our portfolio. We actually increased our risk profile Now we have to depend on climate forecast hydrology to be able to supply water So from 100 ground water today, we are about 65 groundwater about 30 35 surface water And then 5 to 10 percent desalinated sea water now We have a multi-scale decision support tool. So i'm not going to go there and if you guys want I have a reference here That starts from week to week operations and then monthly operations Seasonal to multi-decade So we try to come up with all these hydrologic models at a different time scale and make decisions the one on the left you see is Typical skater operations. So my group typically what they do does is it forecast the next week's demand and supply Optimize from where source we come provide and send it back to the operators who actually Make that happen The table which is very difficult to see but i'm going to show you what gets in is a seasonal allocation level decision support tools So in the morning, we heard about some of the probabilistic forecasts which are available how we get there for us is As you know, most of the time what we get is a large-scale indicator So that bias correcting downscaling and making it to something that's useful local That's what we have been spending our time. So typically what we do is we use this large-scale ENSO or probabilistic Forecast and then we generate some rainfall which is consistent with our area and that feeds into the stream flows And then that will be a decision-making every month We get together and the first thing we talked about is about climate. What's going to be what's the ENSO state? What do we expect for next two three months and so on and on the right side? You can see actually a Uh A report so this is from november 1 and this is what comes from november 1 and this is like Summer in christmas time. It doesn't typically happen like this for us But this is because we are expecting a lino or we are told so So we have to use that information to come up with forecasts for stream flows So in addition to stream flows, then it has to go to other works of the agencies if this doesn't play out I'm going to blame you guys because it comes from all those climate information um, the next one I want to show you is and then We also use there was a great question. How seasonal operations is tied to infrastructure investment This is key. I want to mention. So we have what we call a residual risk management tool The idea is that we know 20 years from now. What is the demand? We'll forecast at least As much as good as what they currently economists say that's another by the way Uncertainty for us. There is economic uncertainty where we forecast our demand Supplies forecasted also and then you try to mix that supply gap You wouldn't be I wouldn't be working in time of a water if I if I say hey, we have to build For 99.9 reliability of water So what we do is that we select start some point of reliability And then we try to match the rest as we call it a residual risk management or water shortage mitigation plan Now this tool actually looks three months ahead. This is a typical Flow we generate through our reservoir and based on this is just an example from 2007 So the green and the red are certain Alarm levels if it passed actually below the red, it's called the water like crisis So everybody has to conserve water and so on now we put ourselves in a way That we want to use this nine months ahead and we are declaring actually before this happened nine nine months Nine days ahead. So as you can imagine, we are using this tool And if this tool doesn't get buy-in Because the people watch every day what we do every month what we do And we cannot just trigger the whole area is in shortage and suddenly it's not the case. You don't want to lose the trust from the the consumers, but that is how we tied up a short term Operations into a long-term planning. In fact, we are trying to do we are doing research right now How we can see our risk of failures and we we have some planning risk of failures So when we reach that risk of failures, maybe a trigger to bring a new supply source So there is a lot of things going on with this kind of model But the issue is how good is our projection? So we so any advancement that we heard in the morning will be useful for us So another typical example, I'm giving one example here also Last year the operation came and they told us, you know, we want to draw down the reservoir Sometime in July and we want to do these operations and then tell us we will be okay by the beginning We can go for the next water year. That's at the end of the summer Whether we should be full reservoir or not Well, Akademika, this is exciting for us. It's whoa. We can crunch this number You have probabilistic forecast and we told them what you see here actually is the greens are your probability of feeling the reservoir by the end of the summer And we are starting at May So as you can imagine, there's a lot of challenge on getting this kind of information We told them, hey, you have about 18 percent to get there. So you guys want to move this or not So and that's the challenge first We have to come up with something that to give them some actionable So the right side is is an example of we have these huge pumps of operations So depending on flows condition, they want to to know am I going to operate? 30 days 90 days this huge pumps and there's a lot of cost and the one so all these are based on What we do at the seasonal level all the projections So what's important for us is not to lose the trust of those people. There was a question in the morning I'm almost done. I'm going to give it back regarding the 2014 El Nino So I can give you an example of the 2018 La Nina so 2017 it was perfect. We forked the forecast was good. We told them we will be in trouble Everybody was ready. We were good But the 2018 as some of you know was actually at the beginning it was an El Nino then it turns out to be a La Nina So I was there without my group say we are expecting this after two months to say, what is that El Nino? I don't know Ask somebody else. So those are the things and in a way we like to use all this information But when things may not play out then we have to be careful on that so that we don't lose a trust from them So it's not all me. I have a bunch of people there actually dedicated staff who are doing all this work So I would like to give them a shout out to all the people who are in my department. That's all So Dave is up next some bureau of automation Good afternoon and thanks for having me This is an exciting time. I think in this area And what I hope to communicate is a variety of things But yesterday I had the opportunity to speak to a smaller assemblage of you all and one of the things I pitched then that I'm going to pitch now in a slightly different way but similarly Was again a focus on the need to bring your community or the community of research Into a way that is more directly informing practice or operations types of activities Not a new concept of the bridge from research to application But I think there is an opportunity in this organization is the right one to do that That's a vague concept. So let me pitch something more specific based off of what I've heard today As well as just thinking about how I wasn't helpful with that concept yesterday And that is that uh, I think in a short term one way to do that is simply to have another meeting Or workshop or conference whatever you want to call it Whereby the federal community and states and locals frankly Can can share real world decision making from policies to tools because I think that there Is a lack of communication and that would hopefully better set a target for research practices to inform those things I don't think it's fair for the federal community or others to simply say we're not being informed We need to educate better. Uh, so that would be my pitch as a as a quantitative outcome from from this meeting Whereby we can tell you which tools we use where we use them how we use them Which policies go into these things? Where are the constraints and and helps set the target for your future research? And to that extent, I think that's what I hope to share here Today to a certain to a certain I'm going to start at the end And move backwards Now is an exciting time for this topic Um as you already heard this morning from sonoma Fero forecast informed reservoir operations or the use of sub seasonal to seasonal forecasting to actually inform Water management in the united states now is the time lake mendicino is one of the first In the western united states It's something that ties together Aspects of flood control the core of engineers primary responsibility and water supply, which is a local in this case state local type of responsibility But reclamation at federal reservoirs, which mendicino is not Not a reclamation reservoir We have that same type of goal And f2s is really the bridge Whereby we can work with the core Or the constraints from supply and demand in one unified way So mendicino was talked about i'm not going to take some of my precious time on that Uh, here we go Another a good example of the time is now is fulsome. It was mentioned earlier The joint federal spillway project at fulsome is essentially complete in terms of construction Operations are taking place Anticipated the water control manual May be signed as early as january of 2019 Just this morning. I got a copy of the october 2018 Preview of that document And this is probably the largest forecast informed proposed operations in the united states Depending on where you're counting how you're counting that sort of thing, but it's a big deal And what's being proposed here is a very static rule curve That the core of engineers Have been using forever And if you're if you're a engineer within the core, you've been doing that very successfully Very I don't know of a lot of examples when you have evacuated a flood A flood pool per core guidance and how to flood that caused damages or significant damages The way that they've done it is super great if you're interested in flood control if you're interested in water supply Anytime that there's empty space at the end of that flood control season. You're not doing a good job So at fulsome, uh, the the concept here is that there's a static Flood control pool and then there is this variable And then there's this variable space that's shown there between 400 and 600 That allows for a significant amount of storage capacity that's informed through Forecasts not necessarily season or seasonal or sub seasonal in this case. This is informed directly by um River forecast center no a product looking out at um a number of days to a week that informs that type of thing But again, uh, the time is now. This is a significant um I don't know if improvements are right word But approach that the federal government is taking particularly these agencies and the On these timescales in terms of forecasting are informing real-world decisions right now. Um, and I think that's great Going backwards doesn't help when you have a picture coming after the slide, but that's uh fulsome in the jfp Again, uh real-world needs on this timescale the colorado river basin Is experiencing historic Uh, not tree ring historic, but historic drought Many of you focus on that here The colorado river is informed by real-world management is informed by Outlooks two-year outlooks a 24 month study that uh has official release dates twice a year You guys are all Uh, I don't know all of you, but you all seem smart enough to do the math that If you're looking out 24 months two times a year, uh, you need a forecast that has uh some range to it Currently and historically There's a switch from where we think we have knowledge to climatology within that 24 months Uh informing those processes would certainly help manage that system If we improve outlooks and timescales on the colorado river Right now There has never yet been a shortage declared on the lower colorado There is a significant chance of that happening for the first time in history since Hoover and me have been built Looks like there's a picture being taken i'll wait The last thing I wanted to talk about again We recognize the need for these types of improvements and i'm glad that you do as well One thing that i'd like to highlight with the remainder of my time, which I have no idea how much there is Five minutes three minutes Five minutes five minutes. Thank you I take it out of rogers time by the way Is uh something that we started um last This project we started last year, but in the past four or five years reclamation Has embarked on prize challenges um prize challenges if you think The x project x prize An award to for the first private entity to put a rock into space We're not we're not talking that scale But the concept here is that the federal government puts out a purse For somebody to achieve something you only pay the purse if somebody is able to do it Um and From an economic standpoint. It is a great investment to federal dollars We get asked at all levels of the budgetary process. Why is this good? It's good because if you count the number of intelligent people spending hours working on our projects It's far outweighs the investment that we're making far outweighs So one thing we focus on our biggest prize challenge to date. We did last year We called it the forecast rodeo. It was a year long real-time sub-seasonal forecasting Contest the total number of prizes available for this were 800 thousand dollars of federal dollars It seems like a lot of money And what what what the requirements were are these bullets, but essentially Competitors had to produce a one by one degree grid for the west in the united states projecting temperature and precipitation At two different outlooks three to four week and five to six weeks They had to produce these forecasts every two weeks for 13 months And again the domain in the 17 western states basically west of the mississippi To be eligible to win a prize A competitor had to beat Two different benchmarks one being a damp persistence model and the other being noah's cfs version two so state of the art Weather or climate model depending on what you want to call it and a very fundamental basic damp persistence statistical approach To win the prize as well competitors had to submit their code documentation and produce the hindcats verification So it was a complicated project for a competitor to be a part of But our hope was that by that there was enough incentive there if that people would want to compete And what we found is a complicated slide But so this completed in june of this past year june of 2018 that was the end of the 13 months of the competition and Just to show Kind of what was out there is again So there's four variables temperature and precipitation for two different outlooks So week three and four temperature precipitation you see in bold the two benchmarks To damp persistence and cfs version two. So there were three competitors that beat the benchmarks Which I think We hope to learn quite a bit from but we're very happy for this outcome It means that there are very innovative people out there that can beat The big dogs in the room basically, I mean that's cfs version two. That's a significant federal investment in time that goes into that Similarly for weeks five and six temperature, we had one competitor beat cfs version two for weeks three and four precipitation there were three competitors that beat Benchmarks and for precipitation There were a number of competitors that beat precipitate beat the benchmarks So this was our prize challenge We can talk a lot about this and dig into it But the pitch I'd like to make again to all of the smart people in this room Particularly the academics who can compete in this is we're going to launch the same prize challenge again And we'd love to see more competitors This next round Interestingly, we had a competitor A part of this that felt that they Were better off not taking a significant portion of the potential award money because they They believe that the monetary value of their product Is more outside of what we offer in the prize And we did not take ip intellectual property associated with this prize challenge But we took the right to see it And that even that was enough That the value was more to this This team or individual To seek privatization which from our perspective is a fantastic outcome to I mean our job in the federal role is to Encourage the development whether it be in the private sector or in the federal government So for those of you in this room That seek grants seek opportunities We think that there's a lot of economic value to these things And we encourage you to participate in the competition in the next round I believe that's my five minutes And I'll end with my opening comments, which is We would like to help set the target for research And I think there's a fantastic opportunity To discuss exactly what the target looks like in federal water management I think it would be educational perhaps disheartening to some of you But certainly educational in terms of what the real world practice is Throughout the united states. So thank you very much for this opportunity Great. Thank you, david and we all love a good competition. So Next up is jenny jones from california department water resources Okay, good afternoon everybody. I know that this is the after lunch time slot So I will make a point of being provocative enough to hopefully keep you awake Actually, when I talk about that this subject, that's not hard So we ask this question every year about this time of year What's the water you're going to be like because this is very very important for those of us in the western us There we go. So The question was asked earlier about can they do better than the old farmers almanac? Well, here is cpc's Report card on their skill score for their seasonal outlooks two-week lead precipitation for djf Which is a very the most important part of our water year in california in terms of precipitation um Well, the good news is that some parts of the country have a an enzo signal not california Not of anything of any significance from the colorado river basin So we think of el nino as el no show and basically This is a skill of zero realistically speaking. It has no value for water management at this point So that's not a good thing So we've wanted better forecast of an s2s time scale for a long time. We did a great report at dwr Following up a big drought in the 1970s desirable to develop additional skill in forecasting the weather a month tense What's really needed for on m of a complex water supply project is a long-term projection at least here in advance With a high degree of reliability So, you know, please get on with it But even as recently as 2015 when noa published its first ever service assessment for drought for the california drought in 2014 They went out and interviewed a wide cross section of stakeholders. The number one comment they got was Hey, we need seasonal precipitation forecasting capability. Well, hello. It took you that long to figure that out You know, this is basic and fundamental and something that we could really use for our decision making So taking a riff here off of noa's research funnel, which Seems to resonate With them. This is the seasonal water management funnel for decision making in california The top of the funnel the beginning of the wet season is where decisions have the most value We're talking about decisions on the order of hundreds of millions of dollars particularly for the drought Should we go to the legislature and ask for major infusions of emergency drought money? Should we do a state water banking program drought water bank program as we have done in past droughts? Should we put a whole lot of money into water conservation programs do local agencies negotiate temporary water transfers? But as the season goes and at the beginning of the season You have quite a bit of discretion in terms of being able to put something in place with enough lead time for decision making Lead time is golden and that's why we're really focusing on precip here is we need the lead time runoff forecasts are good We actually do relatively well on them Particularly in comparison to those longer term precip forecasts by the time you get down to the end of the wet season You have no discretion left to play with and you're down to business as usual in terms of the value in your decision making So grant and his remarks was talking about just the value of getting something out to two weeks You know, that's a weather time scale Imagine if you could get that to two months three months Now I know obviously your forecast certainty tends to get much better as you get into shorter lead times But we don't want you to have the easy challenge. We want you to have the stretch challenge Which is give me these answers at a seasonal schedule And we were asked to talk about challenges opportunities and research needs in these remarks So my challenges well, obviously the federal government needs to put more research money into this S2s has really been the poor stepchild of research in my opinion You know a lot of investment at the longer term climate change time scales through the You know work over several decades In that area, you know money has gone into weather forecasting, but not a whole lot into s2s So we were delighted to see when the weather research act was passed in 2017. It was a good first start However, it needs to be reauthorized now because it was only a two-year authorization Another challenge given the what was teed up in the weather research act is Well, how exactly does that fit in Noah's organizational structure? One of the challenges for us has been figuring out how we readily engage Noah where you have little pieces of s2s sort of Scattered across a variety of different places than Noah on the research side as well as on the operation side And frankly, we need a really focused effort within Noah something similar to the hurricane Forecasting improvement project, which I think is probably one of the best models out there that we could look at And so I said that working with Noah was a challenge. Well, it's even harder to work with academia All of the work that we have been doing in california to try and advance the cause of s2s forecasting I almost put in a slide of the cartoon with a big game hunter Socking something with a dark with a tranquilizer dart gun the target for that tranquilizer dart gun would be an atmospheric scientist It's been very difficult to find folks in the atmospheric science community who are interested willing and able To work with us to do useful things as opposed to oh, well, let's publish a paper on something So the social scientists folks use the term push versus pull So from our perspective on this it's been all full and it also appears to be a really small research community because Hello researchers follow the dollars and a lot of the dollars have been going in other areas Opportunities I mentioned the weather research act. That's a huge one We need to get that reauthorized and we need to use that act to get going on some geographically focused pilot projects You saw the cpc map of skill scores that I showed Some areas in the country have a little bit of skill some don't well Hey, the u.s. Is a big country you would expect that some phenomenon Give you more predictability in parts of the country versus others for us in the west coast atmospheric rivers So we think of geological things to start doing some specific pilot pilot projects to get skill in those areas where there is Not skill such as winter precip in the western u.s. Or you know for the ag folks in the midwest summer precip for them Perhaps is important Noah we would suggest that in order to take advantage of implementation of the weather research act We need Noah to develop a some kind of cross line office organizational structure That brings together a very specific focus within Noah on this because for example We just executed a contract with Noah for work in week zero to four So we go out two weeks into sub seasonal 750k a year for five years to fund Noah to improve some of its Basically weather-ish stuff as opposed to s to s stuff But it was quite a discussion to figure out well who and Noah do we contract with I'd initially approach Dave DeWitt and I want to give a big shout out to Dave for his willingness to work with us and to Be our partner in this but you know a lot of that work was actually being done in s-roll So we ended up doing the contract with s-roll But you know there's also a relationship with gsdl which i'll touch on in a minute So you know how do we bring this together in one place and have kind of a one-stop shopping and decision point for s2s and Noah Um, I mentioned you know from our perspective one thing we can do as a state even though we are not a research funding entity Uh, we can fund folks to do specific projects for us that may add value So we have a contract with Wayne for example at uh on behalf of nasa jpl To develop some experimental forecasts of atmospheric rivers for us going out week three week four And we're now amending that to do experimental forecasts of west coast ridging Because if we have a strong ridge in place in the west coast that probably means we're not getting rain And that may have more prediction skill than trying to forecast atmospheric river probabilities And that was actually analogous. I was very interested to see the slide that andy showed this morning in his talk We have a contract that we're negotiating now that will involve scripts and suny One component of which since this is a question that came up this morning was about the use of limb One of the tasks in that contract will be about the use of linear inverse modeling to look at a six-week Experimental forecast for atmospheric rivers or the ability to do so So we are you know trying to um Come up with as many things as we can particularly the other question It was asked this morning about bridging the gap between qpf's and the seasonal outlooks. Well, maybe it sees experimental Forecasts three four five six weeks out on ars. That's something that we've been tracking at this point So, you know, I'm not going to tell you what my science research needs are because you guys literally wrote the book That report was a 10-year vision for um the forecast on s2s timescale being as useful as the weather forecast today So I just need the research that answers those two questions accurately And could we please do this within five years because we do have water management challenges in california and we you know Like to get this moving along just saying And to point out this is we have many atmospheric scientists in the audience I you guys always have to have the cool graphics So this is a cool graphic that I stole from dwayne And this is actually an example of one of the work products that he's doing for us under our contract And he actually showed another version of this in one of his slides this morning But just an example of the kinds of things that we're trying to Pursue in working with the research community in getting very targeted products that could be useful And another example of something that I think is an Interesting tending opportunity that's coming up some recent research that gfdl published Regarding the ability to seasonally predict western snowpack, which would be so hugely useful for us and Dave and sarah catnip and Tom hamill and others at my request work together to put together a perspective So what would it actually take to do this not just quote-unquote study western snowpack? But develop a target with a plan a process a schedule and an idea of cost Of what would what could you do in five years with this and at my request? They presented at our recent western states water council fall meeting This is the kind of thing that we need to see from noa from the research community Specific products specific time periods specific tasks. What does it take? It makes it much easier to sell the research in our world So with that I would just to point out not just a california perspective I'm here also on behalf of western states water council We see a huge need for improving s2s forecasting and we're very interested in working with folks Including the folks who signed noa's budget to try and get resources into this task. So that's where I wrap up Great. Thank you, janine And last rogers up About 15 minutes hopefully yay greetings, uh, so i'm roger for already i'm going to talk a little bit about the issue of drought and What a supply and demand there's a lot of work a lot of partnerships We have with the western governors with janine who helped us lead a lot of this stuff But the whole idea is what's the breadth of the kinds of questions we're trying to deal with Cross time scales and then specifically S2s and why that's the what kind of challenges that poses a lot of these fit into very Direct networks that we've developed for early warning around the country that's made up of watershed managers a very diverse group that i'll point to in a second but watershed managers ecosystem managers certainly Even broader issues such as lower and upper basin challenges in the colorado river And then some international aspects So i'm going to mention the big challenge we have in the drought world on this time scale, which are flash droughts I'll talk about the focusing event the thing that really brought the attention of short-term Drought expansion and severity Into our thinking then something that happened in the upper midwest that leads to some of janine's questions That we did not predict which is the upper midwest drought in 2017 And then something that's beginning to challenge a lot of our stakeholders and our partners the issue of compound events droughts to floods and back and then the combination of drought and heat And why that matters and we're getting a lot of attention from the health community on exactly that question And some the cases i'll show our combination of national and international applications in ag and the famine early warning system network And all of these are work we've done to develop through not only in the national integrated droughts information system with the international drought management program At wmo and the scientific basis therein Finally it'll be where the research and information products advances actually needed So there's a big list. There's the billion dollar droughts affecting the consumer price index done by ncei And why do we care well across timescales? You can see where we have drought related risks and where they tend to impact The consumer price index this is the first time an analysis like that has ever been done for a whole Long time since the 1930s drought We've always thought of drought as an agricultural impact and boy You could get the insured losses and when you look at the billion dollar disasters You almost see nothing in the west from a billion dollar disasters from drought yet. We know That the cost as it filters through the water systems and everything else are in fact in the billions in fact We estimate that the 2012 drought when you accumulate all of the risk and we this work with munich re was actually 100 billion dollars An hurricane sandy was about 60 to 70 billion. It's just all happened at once So we have to keep in mind these ideas of the cumulative impacts and cumulative risk And of course as people mentioned won't revisit the other issue that this is central to wildfires And we can go back we did a full analysis of why we're seeing some of the Explosions not just in the long-term trends, but what the short term means in the context of explosive events So drought is typically the largest driver of crop disaster assistance And indemnity payments we estimated in 2012 about nine billion dollars was paid out Even though the cumulative impact losses were about a hundred billion dollars. So what does this mean for us? What actually happened this focus event the reason why I call it that that led to the creation of the national drought resilience partnership A multi agency group that is functioning Now chaired by the epa head of water davros and bill northy who's from the usda conservation authority And here's the drought. There's 2011 There's may 2012 july 2012 january 2013 And the jump we can see from around may to july Went from about 30 it actually ended up being 66 by september of the aerial extent of drought Now that's pretty dramatic from the standpoint of the evolution of a drought event I always tell people when dealing with drought the onset is not quite the issue the onset we have got Markets we've got storage It's when we've used up those buffers and a drought has intensified that you actually have the risk and where we're seeing The importance of the s2s timescale is in terms of the intensification in short periods relative to drought So there's that big leap and this was done through the no drought task force the percent of us experience monitoring to say severe drought suddenly increased But even a perfect sea surface temperature prediction would likely have captured much less than half of the total variance And what is the rest? A complete explanation of droughts and both not just the ocean boundary forcing But also the particular sequence of internal variability And this is what we focus on in the context of trying to get the sense of why those leaps have occurred One of the indices we've developed and it's a parallel to the evaporative stress index is The thirst of the atmosphere how much water does the atmosphere pick up? There's the two-week evaporative demand drought index There's the us drought monitor next to it as you can see the atmosphere is trying starting to pull water out of the system by june by july and there's august And so due to these land oh atmosphere feedback the evaporative demand actually reflected the surface moisture conditions much ahead of even the drought monitor and it happened over this time frame that is so critical to whether or not We saw the ballooning of this drought event. But why did that matter? For a lot of decisions and we worked with usda and others on this the reserve Forward supply going through the year people were reducing herd sizes weaning calves early Purchasing feed renting additional pasture one of the strongest adaptive mechanisms We have in the united states is actually the conservation reserve program 2.4 million acres that were put aside after the dust bowl to give us some buffer in the system the application for government assistance incorporating yearly the yearling livestock And then stocking conservatively these are actual decisions that people make and then it matters a great deal To where they get the loans to do these things so the banking industry has taken now a big interest on whether or not Loans are actually Viable can they prove the premium on them and this is actually a critical thing from the time frame of how these decisions are made But something else was going on as people in this room No, the grain and oil seeds dominate the salt bone traffic on the on the Mississippi Accounting for one about half a million Half of the 80 million metric tons if we amortize all of the traffic that goes up and down Each year and including repeat traffic just the cost of things that travel on the Mississippi back and forth It's over a trillion dollars a year Just things that move all the way along the Mississippi It is the most economically viable is the most economically important watershed in the world and During that event we had huge impacts both from dredging in the short term and most significantly In the very short term the inability of grain elevators to load things onto barges Even though it had been low coming from may to july everything just dropped altogether So as a result the mississippi river cities and towns initiatives the coalition of 70 over 70 mayors is working with us very closely on What does it mean for their communities when a large-scale event like that happens? What it matters to the trade footprint of the united states and the usda is helping to fund this and how this then filters into the activities for relief and for alternative sources of Not just employment, but recreation On these 80 towns that's actually happening and in progress right now came out of this event And it's all because of that Surprising jump at that time So we're talking about why we need to know this stuff for a little bit Why we need to know those time frames and of course another one of those and we saw in california as well in 2016 2017 Was this issue from too much too little and back From 2010 2012 those were three years in which corneal fell for the first time since the dust bowl We have little sense of how things shifted From very wet to very dry so quickly and that transition from wet to dry Is actually one of the most critical things in the context of planning. We've seen other things like that in 19 early 1990s We had events like that on the colorado river. It's just that 87 to 92 was a dry period And so the reservoirs refilled we saw it again in 1983 When the when lake the reservoir on Lake powell almost broke the idea here is what changes as we see droughts to floods and back again And that rapid transition actually occurs on this time frame and we have little sense of how that happened So in the nightest reauthorization and in the new bill that has been approved by the senate and is in the house right now There's strong and actually quite honestly and give janine a lot of credit for this as well A lot of language on including research related to the role of extreme weather events and variability in ameliorating drought or In making us think we've ameliorated drought as I always like to tell people early warning is Like taking your car to the mechanic and she says I couldn't fix your brakes. So I fixed your horn It's a warning. It doesn't mean we're doing anything about it, right? And so the idea though is putting this kind of information into our early warning system But we have a predictability problem the upper midwest drought onset was not forecasted lead time sufficient for early warning To lead to early action. No mistake on our parts everywhere. CPC psd. All of us were using the best available science but we could not pick this one up and it led to a lot of impact and barley and wheat production on In this part of the world, right But the real issue that happened In there was this rapid soil moisture decline And we do not yet know why that happened Look at the time frame on which it happened in a matter of weeks to about two months in which you saw that very rapid Decline in soil moisture and that's a question for us to think about in terms Of the types of questions we want to answer So In another area of work that we do we're very closely with the famine early warning system network We help create the international drought management program that deals with drought risk and drought impacts When we go from emergency and response We're usually behind the curve by the time the drought appeals occur And by the time a drought response happens it's too late and the question is What does Research on the srs timeframe give us in terms of being able to manage this process And I can go in great detail about this particular case This is one of the successes of the use of a forecast on that time frame Understanding the and so signal and then what that meant not simply for a wetter or drier season But what events the number of events within that season that led to being wetter or drier There's the food security map In february 2016 and there's the food security map in june 2016 a lot lower risk for food security The whole idea Was that this drought in ethiopia was actually the worst drought in 60 years worse than the 1984 drought that was You know live aid and band aid and everything else right which killed the 400 to 600 thousand people in this case This humanitarian crisis actually did not occur Because of the work of usgs nasa noa And partners on the ground on mapping household food security being able to get food in place on this time frame We did not see A collapse in ethiopia as a result you didn't know about this It happened in somalia because it did not become a crisis And so that occurred actually on the time frame that we're talking about So widespread acute food insecurity was avoided in ethiopia in 2015 2016 because of early warning of sub seasonal potential food insecurity And the social safety nets that had been put into place as a result of fuse net and so on the coordinated information system and services Actually led us to be able to assess food insecurity and support Resource prepositioning and that link Occurred the new director of fuse net was actually my my deputy at night There's a strong link between these two framings and how we think through these issues Something else we're beginning to see and this is a really cool study from a mirage kushak and others is exactly the droughts Warming faster than the average climate But what we're seeing are more heat waves when we do have a drought And so the heat wave question becomes a big issue for the health community And we're seeing it throughout the united states that idea of the temperature shifts When you do have a drought is actually not simply a health issue as people in the room know It affects what you see in vegetation. It affects what you see in evapotranspiration We estimate Dave we lose about what one one and a half to two million acre feet of water from just heat on all the reservoirs on the colorado basin And how does this impact us? the outside of tropical hurricanes The combination of drought and heat is actually a mortality risk in the united states that we don't fully appreciate All those three thousand deaths from those the percent frequency and the costs are much higher than we actually think when we add these two together $240 billion calculated over that time And we're seeing this There's the southwest for the temperature changes that you see all throughout this period And then when you have drought clearly a link between drought and heat Yeah, that's obvious until you begin to think in terms of heat waves being the heat that you're actually constructing during that time There's just an example. There's a fifth precipitation for For 2014. It was the fifth on record but the thing that happened was the warmest November to April mean temperature that combination certainly played a role in exacerbating the california drought There's an increasing set of things. I sit on something called the national drought resilience partnership across that group homeland security Energy and others are beginning to look at how drought-related critical infrastructure Hazards are affecting us on the water energy food nexus And I can go through the list of things on infrastructure And this is all new because for a long time We thought of drought as simply affecting agriculture We're beginning to see it affecting the functioning of infrastructure Not just transportation, but the functioning of our electric lines things like that when you get the combination of heat waves and drought So what are the research needs for monitoring and a lot of this comes from work from dave de witt and a whole host of others Using new observations soil moisture getting the land surface initialization. I'll mention that in a sec Identifying the sources of predictability on these timescales given a changed base state and improvements in in By using multiple models and a set of initial conditions that I'll mention in a second And there it is our case is really beginning to get a better sense of the not only the systematic biases in the models But how the land surface initialization is occurring because once that feedback starts happening We see these ballooning of large drought events So from the operational climate prediction monitoring products This is from dave and a whole host of others certainly anso and mjo monitoring the link between the seasonal and how that modulates The week three to four temperature and precipitation outlooks the drought monitor But really the monthly and seasonal outlook and the role That evaporate transpiration and evaporative demand both plays and the land surface conditions that affects our outlooks So taking that from that standpoint, there's the sources of predictability the way we look at it But the main p thing is the fault is brutus is not in our stars, but in our boundary conditions Thank you. Thank you. Thank you Great. Thank you. Roger. Um, so great Presentations there and I think a lot for us to think about for uh discussion. We've got about an hour Assuming we go till 3 p.m. Um, so I'll take questions. But before um, We do that. I wanted to say I contacted a Colleague at NCAR and there's two papers that are out on the national water model The early papers and they're I guess they're in the process of drafting more but I sent them to ravi and kathy So we'll make those available. So the ones in journal of hydrology And one is in jarra. So there are two papers kind of from early development of the national water model. So those will be out there Um, so with that, I guess we'll open it up for questions I do have some questions that I kind of came up with there's a few of my colleagues on the on basque And they're put up there. Um, I think that third bullet We heard a lot about kind of timeframes at least from uh, genean and what's kind of needed for her Agency and group But these are some things to keep in the back of the mind A lot of the first ones are kind of like what are your what are your needs? In from the agencies and stakeholders from us A question about uncertainty quantification and the products that you're using um modeling capabilities and observations needed Currently that you think we can provide or help develop And then I I kind of wanted to end hopefully with a little bit on workforce development And what do you see as kind of needed in your future employee those of us that are academics in the room? You know What skills do you see that your employees need what's lacking? I mean something for us to think about if we go back to our institution So with that I'll open it up for questions And maybe we need a coffee break All right, so rabbi you can start us rolling This is absolutely a fascinating session Um, not just because roger spoke Yeah I had a kind of system question It occurs to me that the way you manage water Maybe it's akin to the way you manage uh other utilities in some ways Multiple sources of water multiple Issues and how you deal with it do you See that as a model for dealing with it, you know Let let me be more specific for example Tampa Bay Do you have enough capacity in desalination? To take up for any loss you might have in other systems Now yeah So right now it's only five to ten percent of the The total that come from desalinated sea water In the future one of the planning we're looking is expanding that source as well as other sources do But I will tell you right now. It's almost four times expensive than the groundwater And that's the most expensive source. So we have to figure out how to Balance and people doesn't want to pay anymore Yeah, the last seven years we haven't increased one thing And it seems that people are getting used to this no more increase and that's the challenge I'm sorry to push on this but you know people seem to pay for gasoline Past changes much larger than that and we can do without gasoline for significant amounts of time But not without water So it seems to me there's something that's missing in that equation In other words in all the different water management systems Do you have redundancies and multiple? kind of Sources of water that you manage You know the saying you get what you pay for Large water utilities have the capacity because they have large rate payer bases And typically a lot of staff resources to afford higher levels of reliability of supply In california where we see our immediate public health and safety impacts with respect to drinking water and droughts Tends to come from small water systems Particularly small water systems on fractured rock groundwater That may only have a few hundred or a couple thousand connections Because they don't have a large enough rate base to be able to afford reliability And that's where we end up going in as the state and perhaps doing emergency response actions during a drought such as water haulage bulk water haulage Even drilling wells etc of four local agencies. So it's very much a locally specific impact Other comments from the panel on that or David Just to reiterate janine's comment again and At a lunch conversation on the opposite end of the spectrum are things like the southern Nevada water authority Which has a very large rate base has recently spent close to a billion dollars in terms of ensuring some reliability through adding a An additional intake into lake meat such that they saw the risks of Of lake meat elevations exceeding their risk tolerance and had the rate base to Increase reliability through that standpoint And i'll just add speaking to this morning's conversation on the Importance for lack of a better word of aquifers is that the federal government has provided subsidies for decades? um on In times of drought, what are we going to do? We're going to drill more wells um, it wasn't until recently that policies have shifted to discourage additional well during times of drought and shifting the funding for drought preparation That doesn't solve the issue But the historic response has been to build reliability by tapping into those aquifers Robbie, I think there's a fundamental backdrop, you know the base question that I think you're asking which is The effort to which we have Redundancy in our system and the effort to which we have pricing in our system And and it's pretty clear That whenever we have created redundancy in water systems We have then developed enough to use that redundancy in other words Whenever we think we've saved something development has pushed forward to use that saving One of the things we sort of need to get a little bit as you're leading us to think through here Is as people know everyone in the audience we have in fact Lord the amount of water that we use in total since about 1975 across the united states and it has not shown a blip in gdp or in productivity From that standpoint if we can ask the question That the idea of reclamation or the idea of efficiency Is not simply a question of using the last drop but actually You can do upfront savings to give you upfront benefits Then you get over the hurdle of what's the barrier to the upfront cost That is the major barrier to adaptation that we have Sure, absolutely. Okay. The reason I asked those questions If you were to think from the academy's perspective of if you want to study Of any kind related to this issue Who are the other players that have to be involved in this? I mean, it's not just the water studies or you the economy remember the economist The economist of water So water is a heavily subsidized entity in the united states and it's not managed by any one Thing It's in the west it's First in time first and right in the east it's Adjacency There are crop subsidies that affect demands There are repayment repayment Differences with respect to the federal infrastructure in the united states that dates back a hundred years This is The questions you were asking about the water systems and their reliability Are an economics question So so I want to bring it back to why the s2s timescale matters To a question like that because if you're asking a long-term Resilience and sustainability question we should ask whether or not the s2s timeframe offers an entry point For us What do we need to get ready to be act to act in that time frame, right? And and within the work we're doing with the world bank and elsewhere There's a feature called the sovereign liquidity risk Which is how do you do an investment that gets you the research you need On the near term that also helps you with long-term planning So I just want to bring us back to why this time frame matters to both the boundary as well as dealing with the extremes and responses to those that there's There's a criticality for the types of science and partnerships that you heard from the panel and from people earlier That needs to be in place to act during those time frames I should also add The reservoir for example, we have Is and within the year so we drain we fill within the single year which is completely different from the west So going back to writer's point the the ability to forecast and managing that resource is huge and and that will Also increase the trust of of decision makers operators on our ability to forecast and manage that resource if not They will just say hey, let's go and invest and we are trying to figure out We can we manage as we go through and we bring infrastructure only when we have to Because the last thing you want to do is you build something and that's an extended asset Maybe you're going to use once in 20 years So that's the the balance that you're reliability on one side and then the That you're willing going to have to pay for that reliability All right, we'll move on to the next question david and then I have dav and then david so it's the three davids Wait Yeah, i'm gonna On jonathan i'm going to sneak two in here because I can't imagine i'll get another chance for a question We'll let you do that, Dave. You have one question with too far The first one is about the s2s and who's missing from this discussion that might be useful if the academies thinks forward about a study and two groups that come to my mind are the u.s. Military and then people who think about farm commodities prices or insurance risk and i'm kind of curious if people have ideas of other federal agencies or people in the private sector who would want to Be involved in a future study or or research of this nature and the other question Is for roger because you made a comment about economic damage associated with droughts and I think a hundred billion dollars or something like that and I don't think that's Generally well understood or accepted and I wonder if you could amplify on that and and tell us what the Naysayers who disagree with that might might say to that assertion Yeah, then you can add So the answer to the first part of the question on defense and on financial services Definitely, I just didn't want to make it the comment just about economics because part of the issues so much of our values Are tied up in water that is beyond just that the Case I was pointing to in Ethiopia actually had a lot of repercussions back with our partners in defense Because in in staving off a humanitarian crisis, you may have staved off a conflict When it comes to that large number and my reason for putting it out there as a in it was um The way munich recalculated What in fact had been lost Not simply by the insured loss to the crops But the fact that barging started to lose money That recreational systems started losing when they put it all together and there has to be double counting in it Because we have no models that actually can get us A full sense other than in plan and which is only state level a full sense of the cumulative impact of a drought risk over time We don't actually anybody that makes gives you a number like that is wrong They we do it and when they took the insurers took the numbers for what was lost in the markets internationally They came up with a hundred billion dollars over that time But but flipping it around someone else made more more money on crop right? So when you do so when you do a net and that applies everywhere right if you build next to levy you've lost The where people would have built so when we amortize risk over a large region In in a certain input output sense we're adding up pluses and minuses all over the place the question is Why and to what extent is something locally significant that drives our understanding of risk? Because we could do pluses and minuses and we do this all the time for the especially the reinsurers That can end up to be wherever somebody loses somebody else benefits But what i'm interested in is whether or not people suffer as a result of that benefit and you can't amortize suffering That makes a I mean Okay, david over here one I have a question for Janine and others may want to Jump in on this so janine you were talking about the difficulty in finding partners and tools and I Suspected at least part of that challenge is the need for very local forecasting you know a lot of projects take place on specific sites in specific locations and I can think about the kind of resolution we seek for urban rainfall on trying to address Issues related to a combined sewer overflows and the like So I the need for very local forecasting and the role for empirical models Based on historical trends if we have data in particular locations versus physics based mechanistic models over large areas and You know you find both of those in the literature and I The empirical approach Doesn't get as much attention, but may be more appropriate for the kind of local forecasting needed and then and janine if you'd comment on that and and for janine or anyone side-by-side comparison of models for very localized forecasting it's there a need for that how much of that have been done Well keeping in mind the present accuracy or lack thereof of s2s forecasting And the fact that when you're looking out longer term, you're really not looking event-based You know you're looking at a probability of having something happen over a fairly large space because You know as water managers, we like to think in watersheds But the reality is the climate system operates in a much broader scale So from perspective of say state of california and looking at drought I would be delighted if they could get it down to northern california versus southern california at an s2s timescale You know, uh, I have no illusions about Getting a probabilistic event based forecast at six weeks out. Let's say, you know, it's not in the cards But generally the will it be wet in this winter We've gone through halfway of the winter now. What's the rest of the winter going to look like? So I can make decisions about managing groundwater storage putting into place late season water transfers Those kinds of things. So I am much less worried at an s2s scale about localized Just regional would be very good if they could get the the skill on that And you know statistical or empirical models versus numerical weather models There are folks in the room who know the long history of that better than I with statistical models eventually Me coming shall we say displaced by the numerical weather models, but When I look at NOAA from the perspective of an outsider Due to their budget limitations They really haven't kept up on some of the statistical modeling or statistical post processing that would support or compliment the numerical weather models And frankly some of the little research projects that we're going after Are more statistically focused for example or in conversations with a researcher at university of california urvine about What is essentially a statistical seasonal model for precip for california as an experimental product because it is a different approach than that used by the numerical weather modeling folks and I probably shouldn't say this in front of a bunch of atmospheric scientists, but given the the skill of the outlooks at this point Which as I said was non-existent. Well, okay, so you have a multi-model ensemble I could do as well with a multi-model ensemble of magic eight balls at this point given the skill at that longer lead time So I am very interested in considering any tool that offers a promise to skill Including the statistical ones And I should add I cannot emphasize enough in terms of Doing localized Information that's exactly what we try to do time of day water Florida has a very unique conditions, you know, we have both sides and convective rents and so on We try to work along when these here with university of Florida as well as Florida state in Climate scientists One of the things I can tell you a big challenge is that since we get almost more than 60 percent of our rain During the four months of summer When that rainy season start is huge. It can be anywhere from May 26 to 22 to July Once the rain starts the climate scientist tells me that the way the convective system works Even people we have no idea my wife can't tell you tomorrow at three o'clock It's going to be tender and and it works like that during summer That predictable once you are into that rainy season, but the challenge is how can I predict? Way before a few months when that summer start and we don't have so much time to To harvest that like I said, we have only three to four months to feel the entire reservoir That we deplete during spring So I can't emphasize more in terms of localized knowledge and how you can use And maybe if something you said triggered a thought with me a follow-up, so You know, one of the other areas we're exploring is So that's one thing to say take a weather modeling approach, which is an initial condition problem and trying to Torture that to the limits of predictability there The other aspect is to take the climate side and try and bring it down and get the two to meet in the middle Because we say as to as is the bridge between weather and climate Something that we're very interested in starting to explore in california Is can we do something to predict regime shifts or transition within the wet season? And that's why as part of our our task with NASA JPL we're asking them to give us experimental predictions of west coast ridging Because if we have a ridging condition that sets up for Weeks to months at a time that is the big trigger for droughts for us. We have a ridge there It's not going to be raining most likely and it may be easier or more skillful or more Meanable to other tools to be able to forecast those transition states And one of the tasks that we have for our uc Irvine researcher is we've actually Given her a set of years in which we had a significant flip in the climate system during the winter time and say Can you as an initial step diagnose what happened and then let's see if we can tease some predictability out of it Let me just follow up really quickly. Um, if any of the morning speakers our modelers want to follow up to Janine's comment about Can the models be better right or how are we first statistical versus our deterministic versus our probabilistic? Forecast should we are you going to address that? No, I'm not dressing it, but I I would like to Get some input from you. I mean, I'm really delighted to see how much of these interests in this it is in some ways that prediction community has struggled for a long time And the statistical model or you know, you will say parametric a model based on statistic correlations Hurricane forecast has told us that failed right so over so many years They tend to try to tell you this year going to be Bob normal and And you know As the end of the study recently show it's no better than toss the coin Over so many years because it still is irrelevant To this s2s so now to s2s components of this is that It is a multi-school phenomenon You have a background of insult or not and so what faces And the triggering time and things so in a way that I don't know if we know enough to Tell what is a predictably on that because all of these are still kind of rare events If you would have to say I like to do a daily weather forecast So in that sense we're accumulating that knowledge But my question to the panel is that how Much you see the future is that a dynamic model is coming online The s2s database Sort of a store in the european center now with multi model world model reforcast the last 20 years or so That can be used as a training site So right now many of the research community go into that world Try to see what kind of application we can go with But this requires a local statistical downscaling using that dynamic forecast model So do you see that as least the next few years experimental product can be tried out? I'm going to give you 30 second answer to that But first I just need to apologize. I'm going to have to run and catch a plane here in just a second But any follow-up I'd love to communicate with any and all of you in the future My answer to that goes back to part of the discussion this morning is I don't care You know, I won't tell you how to do the research I'll set the target you guys Give me the answer.  You probably know my job better than I know my job So Yeah, I don't care I just need the the the forecast So yeah, and I have to say that I too am totally agnostic as to how you get the answer just as long as you get the right answer But you know, I think the the problem with the dynamical modeling right now Really harkens back to a lack of sufficient investment You know why for example is the european weather model so much better than the u.s. Weather model I think if this suddenly saw a whole lot more resources Going into it and I think one of the things I've learned from my conversations with dave over the last couple of years is From his perspective the critical need for more supercomputing resources for the research to support the research on s2s and You know, I didn't realize that was going to be a limiting issue But so I think it's as much a resource issue as anything and you know one of the Things about statistical models is in a warm and climate. We are pushing the boundaries and Stephanie could you hold up the brochure with the rocks on the cover? Yes. Thank you So that's a handout that I put out in the table. It's our wrap-up of our last water year The subtitle on that brochure is hot dry and on fire Which very much summarized california's Water year last year But in there there's a graphic that shows if you plot precip versus temperature by climate division in california All of the 21st century data are one standard deviation off of the observed historical means So, you know, clearly we are going forward in a condition where we're At the bounds of our observed data set. So, you know, that's a risk we have to think about when we look at statistical models I just wanted to add one quick thing. I mean if we're dealing with the idea of extremes across not just extremes from Subseasonal to seasonal but the number of extremes in that setting And we think in terms of the spread around the pdf around the initial conditions And whether or not that can actually produce extremes outside of the pdf it started with started with I don't think dynamically That's possible. I think as a result you're going to have to use both To understand how the distribution is shifting as you're moving through time So I think it's unavoidable to use not only the stochastic parameterization around the the The processing but also from the standpoint of saying how do these anomalies track during time? And I think you have to do that statistically Question just follow up this My point is that this is a new area that needs to join learning process Because right now a lot of the things that academic do is a sort of some exercise The end that we think it is to do but then at the same time there are things belong to what predictable Large-scale dynamic pattern is more predictable than precipitation itself So we would let them learn from your experience locally. What kind of things that would drive that joint the learning curve But but I think that's technically a really good question And and what the question is but what Janine was also offering is what space should that happen in? How is that organized supported and funded because otherwise we will come back to this discussion as to you know Is it limb or is the dynamic and and so I think where we make those decisions The help from the academy is creating that brokering to try to get at the organizational model janine pointed at We kind of have to move beyond the sort of um, I know it's it's seductive to say just tell me what you want And I'll go back and do the research. Well, that's about a 40 or 50 year old model about how science really occurs So we kind of have to get over But first we have to find some academic some folks in academia who are willing to work on this. That's the hard part Okay, I've got david johnson and annie. Do you have a response on the modeling or? Okay, why don't you come up to that'd be great Yeah, just just a quick comment on the statistical versus dynamical So from our experience at iri, I mean we've always Come from the standpoint whatever whatever works because we're trying to be trying to improve You know seasonal forecast for decision making and what we found in the end is well It's normally it's a mix of the two So it's it's hybrid approaches where we often call that post-processing So it's developing statistical techniques that will use some predictors I mean those predictors might be antecedent ones coming from a purely statistical model or they may be coming from the dynamical model So I think you know is resonating from many things has been said this afternoon about You know large-scale dynamical patterns and so forth But how can you make use of the information in the dynamical model through statistical methods? so the the development of statistical empirical methods is is extremely important from from You know our ongoing work and our experience and from the seasonal forecast Great, thank you your response So just hit the right button there speaker Yeah, I should add I should add that so what we are talking from from the climate side But there is a cascade of Uncertainties that will be going through by the time we as the weather utility You know managers make a decision. So for example At time of the water we use this largest scale forecast of enzo and so on How enzo translates to the probability of rainfall is another question It's not a slim dunk 70 80. Yeah, we'll there will be rain by how much that's a different story So once we get that rain and then we translate into another hydrologic Which has its own uncertainty and it too which we propagate Then we are using those to make a decision. So it's uh, sometimes, you know, when we We speak we tell them. Ah, we think it's a weak La Nina or a weak El Nino But at the end of the day what matters is the rain that comes associated with that large scale signal Okay, I've got david then jonathan and and please uh visitors along the wall too sitting in chairs you're welcome to ask questions We've got a microphone. So uh, just flag carly down. So we'll go to david Thank you and thank you panel and the one from this morning. I think you guys have really brought to bear for us The amount of data and information that's out there the need to do a better job of integrating that data and finding ways to build the tools necessary for the For the public and the private community to use it more effectively My question more goes to so i'm going to take a little bit Of a deviation from the current line of the discussion and go more to your bullet five up there great On how do we are the agencies ready for big data, etc? I have in my career I've had to spend a lot of time trying to interpret science For policy makers and for legislative purposes And an example and roger. Thank you for drawing to the reference to the drought in 2012 on the mississippi river You've never lived until you've had a line of Iowa soybean farmers show up at your door Demanding that you go give direction to the core of engineers to go blow up rocks in the mississippi river So they can get the barges upstream to get the soybeans and downstream to get it to market to the ships in norlands general peabody came in and he Asked specifically can congress give me some cover so I can do this because I don't feel I have enough Ability just to go out and blow rocks up in the mississippi river. The point of all that is is that policy and how our federal and state governments Utilize science Is often a two-edged sword they will use it as far as they think they're Um covered to use it, but they also are in demand so my question is and it's for roger for you as a Both a science agency and as a regulatory agency through the national marine fishery service Dave if he was here for an operations perspective and maybe janine You could reference it because your state does a lot in terms of water management Is it a function of we don't have the right science or maybe we don't have an integrated that science correctly Or are we lacking the ability for the agencies to use that science in a policy format? Say yes roger I want to take on the last Right because that's a critical thing when ravi and others were asking who else do you need and you know We like to rush to say economists. Well, look, we released a femur report That's what I thought right see that's what I was going to say not right But but what i'm getting at is not that there's something so wrong with that It's just even when we show the value of upfront action or actions still don't aren't commensurate with knowing that value We've shown that from disasters What you're asking Is a fundamental question in adaptive management From the standpoint of yes, we we spent the morning and we have a lot of reports And we have the s2s report telling us what the science is what we might know We're coming to the terms with the fact that yes, we need both You know the stochastic as well as deterministic aspects But when it comes to what legitimizes a piece of information for use with the public That's where the academy needs the partnerships of people who study the organization and legislative aspects of what allows us to get at How can uncertainty quantification not simply be accounted for but be used in decision making It can be accounted for but it'll never be certain. So how it can be used What we do not have is an agreed upon mechanism that says Until we get this right there is usable until we we figure out what the the limits to predictability are on this time frame That we can't act using the information. We do not have a mechanism that allows the agencies to use this because We have fixed rule curves. We have fixed and you know, there's better than anyone. We have fixed deliveries to me and the question is How do we get at working with janine with grand with others on what is an acceptable outcome If we've used all the best available information and how is this part of the best available knowledge? And I think that gives you the sort of decision making leeway That is not just an idealized Bayesian approach So from Tampa Bay water perspective And I should caution that Tampa Bay water is not an example of a utility at all Maybe a couple of utilities in the u.s. That kind of uh, you know tools and academy So we when you say big data, yeah If if that big data is for the whole u.s. No, but if that big data is covering our area, florida We can use those kind of information probabilistic. We have our own Internal cloud computing using a lot of machines running parallel the things I was showing you I've tried here Runs like 80 or so uh parallel computing. We run the whole thing a maybe Three hours if it wasn't a simple computer, it would be like a couple of years So the the agency make a conscious decision on investing. I'm talking a few million dollar Allowing us to do this kind of work So that we are demonstrating that We may be able to push some of our investments in infrastructure. We demonstrate already if I push two two years That's a 40 80 million dollars of investment So our my agency did that, but how many of those in the u.s. That's you know, that's the problem how we can Translate what we learn on this scale for other utilities who are not fortunate enough to have the Computing power as well as the skill You know professional like us One follow-up comment The folks up on the hill here they they deal in the issue of risk How much risk am I being exposed to are my constituents being exposed to by the decisions I make? And I think that's where I'm trying to to get a sense of Using the science to reduce risk and make better decisions But also making sure the agencies have the tools and policies To do the right science to make sure we're getting the right information for the public. Thank you worth pointing out that um Often a forecast or something along those lines is only one small piece of many things that go into a decision You could have statutory things coming into play that have nothing to do with the forecast regulatory considerations operational requirements for endangered fish species many many other things When I showed the research funnel or research funnel the weather management the water decision funnel relating to forecasting you know some of the Decisions that have the biggest economic value or the biggest cost better put Are ones that are essentially Really no risk decisions. They're not public health. You know, it's not a life safety decision to say that Well, gee, we will we we it looks like we will have a significantly dry year Therefore we will invest in spinning up a drought water bank to mitigate impacts You know that can be a very expensive decision to take but there's really no downside risks to it other than You know from public safety perspective. It's always better to over prepare For a disaster let's say than it is to under prepare So I am less worried about that aspect. I suppose then perhaps you might be Great. Thank you Jonathan thanks for your patience Sure I'm intrigued by a lot of what I've seen today It's really been very interesting. So thank you for your for your presentations And roger, um, I wonder if you could enlighten me. I hope this isn't too naive a question I'm certain there's a level of naivete in it But what's the state of dynamical understanding of the flash drought event of 2017 and through so What's the state of a dynamical understanding for the variability of the onset of the rainy season in the Tampa Bay area? So aside from models, how do we understand how these things even work? I think the fundamental question What what you're asking on 2017? We have a paper coming out on what we understand about what happened But when it comes to that, um, what drove the fast drop-off and soil moisture We saw the precipitation shut off But the classic sort of setting up of a, um, you know, dynamical high over the region wasn't identified early It wasn't there and so as a result the extent to which this becomes a driver from internal atmospheric variability Is really the question yet my answer to your question is We're not sure about the process based understanding as yet. We've been able to identify post hoc some of the drivers But I think you're on point and it's one of the reasons why I raised it after showing something that we did do A job on was to be able to say that, you know, without that sort of process based understanding We're going to constantly need to be able to do both the stochastic and deterministic And then be able to deal with the piece of uncertainty that neither captures Okay, so my point is we don't understand it fully So and that's thank you. That's frank answer and from my perspective as an academic research scientist And this goes to janine's comment a couple of times. I'm very interested in trying to understand how those things work So that's a place where we could work together If there's any possible way to make that happen and I don't know if there are ways to do that. So thanks Can I just I think you're asking as well the question Ravi is coming back to which is I Appreciate your question We've tried to create groups like the Reese's and others to make help this work the regional integrated sciences assessment But how we get at fundamental questions like that in a partnership With the academy with the private sector with the the fed is not something we've worked out organizationally as well So rather than it not be just a one-off either Okay Yeah, but from tampe water, I think I'm the wrong person to to answer that I know the challenge and in fact, there is a paper coming in nature one of our partners from climate scientists We know that when that Season starts we you know historically we can define we can define its uncertainty But the challenge is predicting it when that transition from Dry season we call it from october to may Transition so that really I cannot tell you in terms of the process driving that but it is important for us Okay over here. Can you introduce yourself? Uh My name is Andy Miller. I am with the american meteorological society For a long time today, we talked about how Forecasting of temperature and precipitation affects humans and how we can manage that I was wondering about the opposite side because it struck me that it would be basically impossible To forecast the river flow in sonoma county unless we knew that they were going to release A ton of water over a few days So how much do we need to invest in forecasting human behavior and understanding that because it seems to be a really critical part of the flow in any any one of these spaces forecasting human behavior The analogs with forecasting the physical system and the word forecasting in human behavior do not mean the same thing And do we need to know how the decisions? That are being made influence what's in the stream and and you know how you do releases such as You know being able to store for fire or on others to me. Those are decision making Questions I think you have to take into account the types of things they wrap and they do which is What's the withdrawn water what's being put back and so on but I'd rather not go out on the forecasting human behavior components So water agencies invest very large amounts of water as Tampa Bay is done and have we is have done in california on all kinds of water operations models that work at different timescales so if we Given what we think is coming down the pike we can run that through our system that simulates You know the legal requirements for industry flows for water rights Expected demands all those kind of things. That's our bread and butter job and we do that all the time Okay, another question over here Great, and if you could please introduce yourself, that'd be great Hi, I'm Ari Dursman with uh yukar And I I think it's self-evident, but it's worth mentioning And I just wanted to respond to Janine's point about how difficult it is to access NOAA vis-a-vis S2S forecasting because it seems to be all across the agency and and you mentioned how it would be helpful to access it in a manner that people might access h5th and I think it's worth talking a little bit about the fact that Hurricanes are individual phenomenons and that there are researchers who address just hurricanes whereas S2S is a scale And that you're looking at a number of different phenomena with a number of different drivers of predictability across that whole scale and that Saying that it would be valuable to access an agency for that information is A difficult thing for the agency to respond to and so what I think I'd really encourage the board Both boards to to do is to Isolate some phenomena Specifically and and I thought shui's point on qpf Is is really it but to to isolate the phenomenon and then build An improvement program around the phenomenon at the S2S scale and that might be Valuable and I'm just curious about you know yours and Roger if you'd respond to that from the NOAA perspective it would be helpful So what I was speaking to is not so much at the Down in the weeds research level but at the organizational level a little bit higher because we're not going to tell NOAA How to do its job? But I know there are many pieces of NOAA in the room here from math to cpc to the labs Etc that all have a piece of some kind of S2S And the question is how do we get those organized internally within NOAA so that then they can come together and Let's say design an h5p type Experiment whatever that is I'm focusing at that organizational level not at the the science level And I understood that. Thank you. Great. Okay. I think the last question is going to go to margaret Unless somebody has a dying need to ask another question. Yeah, I just can't Can't not comment on the behavior issue So it is a nascent area, but there are groups working specifically on Dynamical models that bring human behavior decision making it in line with some climate change models Is it a very early stage? One of the issues is there are dozens of theories on Behavior change so things like theory of plan behavior Certainly going beyond the rational actor etc etc And you know, I have maintained and brought up several times that these aspects I think that the National academies could play a really important role in trying to bring some of those groups together It's also true with respect. I believe they refer to it as or you refer to it. Roger as adaptive management, but Really, this is there's a lot of work really good work going on around adaptive governance structures And in what conditions do we see changes made that get beyond some of the impediments you made and I think us beginning to think about Bringing biophysical scientists like us together with those groups really makes a lot of sound Can I can I can make a quick response to that because I do I do want to mention that when I you know Words like adaptive governance or anticipatory governance are to me redundant because good governance is both of those But the reason why i'm saying this is Is the reason why i'm saying this on the operations research aspect We could look at what janine said about how um, you know, the shape of Of flow down the river filters through the system But I think even more Than the rational actor standpoint We need folks who understand the values behind why we choose some outcomes over others And that's not necessarily something that I would just say the answer is to add a human model to a physical model We've failed in doing that an integrated assessment And so I would really we were to add another component. There is how do people perceive risk? How do people act on it? Yeah, we know that about decision making But how does that then matter to the usability of the s2s forecast? And I think we need to target it to what's that people like david and they were into data before it was big All right. Well, I think roger got the last word On janine, you know that never happened So with that I'd like to thank the panel again for their time and energy put into this and I thought it was a really great discussion


Hey what's up y'all, it's your boy Dom from The Dive Show in France and we're back for another video. Now today it's not a Kpop video, today we are on my new playlist, we are going to be doing some reactions to some of the dope dancers in the community out in the world. So we're going to get started today with like a dance compilation, it's like different dancers from around the world getting in and I'm just going to do a review and a reaction to it. So let me know what y'all think, if y'all like this please leave comments and if you see videos out there that you want me to watch, excuse me, I had a little burp in me. If you see any videos that's out there you want me to watch, hey do me a favor, put the link in the comment and I will watch it. That really helps me if you just do it like that, alright. But today I'm about to get started on this, make sure you hit the like button, make sure you share it, make sure you subscribe and read that bell, let's get it in. Alright, this is the first one, let me make sure the volume is together, alright here we go. And three, two, one, yikes, I wonder where she at, she a little girl getting in.  It's like one thing, it's one thing to like literally just do a move, but to put a character behind it, put some feeling behind it and it becomes real. The girl eating right now, stop playing with her.  Now we all have our days where we might mess up in a move, but you have to continue to practice that every single time, and young man, this young man right here, I cannot wait to see what he does, like I am a fan, I've never seen this video online and I see everybody was going crazy because he was little, but it was like it's not about him just being little, it's the fact that it's like you make you think about who taught him, you know what I'm saying, it makes you think about how much work this kid put in and how authentic and raw he has in him, that's a God-given gift man, I just cannot wait to see this young man on the floor, this house, his house crazy, and I'll tell my house dance, and so for the community that doesn't know, I'll tell my house dance, and his lot gang, funky, and he didn't stop, it just got better, and his musicality, I may come on, what more do you want, oh, oh, oh, oh, and then another thing about this, that was what's crazy, what was dope, what was just wild, is that all his move was right at the competitor, and what's no time, no time at all, he literally went directly at the other competitor, and the young man that's watching, I believe that was a boy, I can't, I had to check, but I had to double check just to make sure I respectfully say it right, but young Willis, oh, hey, that's how you ate it baby, yes sir, yeah, they might as well put, give him that song, give Willis that song, and let him get the rights to that song, because that's ridiculous, all right let's see what we work with, this is nice, ooh, I see the musicality, that's okay, let's go, that was crazy, he got rock moves, this is crazy, this is a tight game, his threads are stupid too, spazzing, spazzing, spazzing, oh, stop, stop, stop, stop, stop, what we not gonna do is just let that go, and tap it, let's go back, watch the setup, watch the setup of him spazzing, it's like he had it like really just black out, and get that flow, just being on that beat working with the wrist, like that was crazy, and that's not easy, like he's very, very clean, that's what's crazy right here, let's go, let's go, okay, okay, with the hand puppet, okay, look at the setup, got his legs set up, set him up, you know that move coming, if that was a battle, that's crazy, he smacked you with that, you gotta respond with something nasty, I think it'd be fun to be in the lab with him, I'd love to be in the lab with him, see what he working with, oh yeah, he almost fell right there, just a little bit, but he's still killing it though, man, people are getting real creative with the tuts, people are really getting crazy creative man, respect, respect, respect, respect, oh snap, Kazuki Rock, shout out to the B-Boys, shout out to the B-Boys, oh, let's go, oh my god, oh my god, go back, we know about to just see here and act like we didn't just see that, that's, what, look at the setup, let's go, watch this hold round, the setup of this, you know what I'm saying, he about to wild out, get the setup going, already off the riff, the first like five seconds, he start getting nasty, come on brown work, oh, oh, respect, respect, we'll know what to tell y'all, I don't know what to tell y'all, just, I don't know what to tell y'all, I'm sorry, I don't, what do you want me to say? What do you want me to say, if you never saw this before, don't act like up man listen go back can we just take a moment to watch this can we watch the mood that I would never be able to do okay cool come on this is stupid bounce right off his shoulder go back go back look at this look how he bounced over here it comes should be coming up right about now slide slide slide pink come on and then hit you with that that's that was crazy sitting here boom boom boom work work work work hold up hold up and there's more see ya bam now we'll talk technically that move has been done before especially with like if you watch cheerleading and you see them like go up and do the split but what's crazy about this b-boy right here is when he went up with the split in the air he was on his heel he was kind of on his toe and his heel like he on his like that if that was his right leg I really want to just I really want to pay attention to this bop okay right now he's like on the balls of his feet he's already out that fat look where he's landed at now you on the side like on the side of his foot some people would have really bust their ass doing that what and I'm looking at the judge car who's the judges godly you got those judges oh Jesus good good lord and then don't he got done whoop and landed without breaking his leg of dance man you gotta love dance all right we gonna watch this one and then we're gonna we're gonna stop because we're gonna do a part two watching this dance compilation so last one is gonna be fiction I never met fiction before okay I like that okay okay okay got a lot of like one thing about fiction you know I know this is a battle where you most of the time right now we see a lot of battles that fiction is in and you know it takes a lot of heart to battle I don't care who you are and how long you've been doing it takes a lot of heart to battle for real and so he has a lot of like material movements like he got a lot of setups and it's like you know I would love to kind of see what he does with that in different dance like in the world of like with a different flow and groove sometimes you know I'm saying like cuz he gets crazy sometimes sometimes the stuff you be seeing I'd be like damn that was actually nice but I but fiction one of dancers I would love to see his journey in so many different dance styles like for real for real and that's what I mean it's like it's certain dancers like I really be like damn I wonder what they look like if they was a crumper I wonder what they look like if they went into house I wonder what they look like if they went into like full-out popping or they became like somebody in Detroit Jit and or you know Memphis Juke it like I always be curious about what another dancer would look like with a different dance style like right now my journey is salsa I'm getting to the world of salsa Kizuma trying to see how that world is for me and when I watch fiction sometimes I'm like dang I wonder what that look like if he was a full blown crumper and now what I do know is he is studying in crime I don't know his everyday life but I did see a couple videos of him really getting to the crime community so let's see what he does all right let's finish this video shot to fiction like look all his creator setups he has but he really be he doesn't waste no moves you know I'm saying fiction doesn't waste moves like look at his setups but he always have like creative movements greater ideas of his material yeah like that's really tight so that's what I'm you see what I'm saying like if I were to see him in that like now we're gonna stop right there we're gonna do a part two because the next video we watch it is actually one of my homies Arsenal man got a lot respect for him man so part two is Arsenal and then we're gonna finish who else we have on this compilation but listen I'm gonna stop right there y'all let me know what you think of this video I want to be doing choreography I'm gonna be doing battles I'm gonna be doing showcases and I just want to take you around what I love watching honestly it's all about what I love watching so other than that y'all we're gonna stop right there if you like this please leave a comment of what you want me to watch when it comes to dancing and I definitely watch it but other than that I'm gonna get a body here because my sightness is whooping on me right now and I'm about ready to sneeze and clear my nose all right I'll see y'all later peace