Edward Plumb: Okay, well, I'm gonna go ahead and get started. I know we got a few more people trickling in, but good morning, everyone. And welcome to this month's ACCAP webinar, From Sensors to Safety, How Arctic Observations Are Shaping Coastal Flood Resilience here in Alaska. So today's event is being hosted by the Alaska Center for Climate Assessment and Preparedness. We're also known as ACCAP, and we're located at the International Arctic Research Center on the University of Alaska Fairbanks Troth Yeddha campus. ACCAP is part of the Regional Integrated Sciences and Assessment Program, which is funded by the NOAA Climate Program Office. So, for nearly 20 years, ACCAP has worked with communities, tribal organizations, various agencies, researchers, and a variety of other partners across Alaska to provide weather and climate information that supports resilience, preparedness, and adaptation to a changing environment. So, thank you all for joining today. This topic that we're going to discuss is near and dear to my heart from my previous job at the National Weather Service, before I came to ACCAP. And so, coastal flooding continues to be one of the most significant natural hazards facing many here in Alaska and Alaska communities. While we've made a ton of progress in forecasting, mapping, monitoring coastal flooding. There are still many important gaps in the observations and information needed to provide earlier warnings, improve long-term planning, and better support community decision making. So, today's webinar will highlight a new technical brief developed through the U.S. Arctic Observing Network that takes a comprehensive look at current state of coastal flood observations across Alaska. We'll hear about many organizations and partnerships working together, including state and federal agencies, Indigenous knowledge holders. Community observers, to turn observations into practical tools such as flood forecasts, inundation maps, and post-storm recovery resources. We'll also discuss where additional investments and observations could have the greatest impact on improving coastal resilience across Alaska. So before we get started, I'll cover a few quick webinar logistics. Everyone has been muted and your video is turned off. We will have a Q&A session and a discussion, towards the middle half end of the presentation, and at that time, I'll allow you to unmute yourself and turn on your video if you want to ask a question directly to the speaker. Otherwise, feel free to put any questions into the chat. And we will try to answer them as we go along, and any questions we don't get to, we'll bring up in the Q&A session and discussion. The presentation is being recorded and will be on our ACCAP website later this afternoon. I will also, I'll send an email out to everyone that registered, with the link to the recording, so you've got it in your email. For those of you new to the ACCAP webinars, you're gonna be prompted, if you're not familiar with this, you'll be prompted for a brief survey at the end of the webinar. If you're using Zoom in a browser, please hit Leave Meeting rather than just closing the browser tab in order to get prompted for the survey. We really appreciate if you can take just a few moments to answer four very short survey questions. Okay, at that, for those of you who I haven't met before, my name's Ed Plumb, and I'm the Weather and Flood Hazard Specialist here at ACCAP. And today, I'm pleased to introduce our speaker, Sandy Starkweather, the Executive Director of the U.S. Arctic Observing Network. And Sandy brings together expertise in engineering, Arctic climatology, science policy, and science policy to strengthen partnerships that support Arctic observing. She spent more than a decade conducting and supporting field research way up in Greenland, and has also helped advance national Arctic research priorities through the U.S. Interagency Arctic Research Policy Committee. Her work focuses on bringing together researchers, agencies, communities. Indigenous knowledge holders, all to ensure the Arctic Observing systems better meet the needs of those who depend on them. And joining Sandy today are several contributors to this technical brief, who may offer, who may also offer some additional perspectives and answer questions during the discussion. With that, Sandy, I'll turn it over to you. Sandy Starkweather: Great. Thank you so much, Ed, and to ACCAP for, including us in your webinar series, and for those of you taking time out of a busy summer. To come to, to hear our talk today. I also want to really underscore the role that Hazel Shapiro has played in this work, and, while Hazel's not, co-presenting with me today, she is in the call, and, and I, I think we'll, see her stepping in to field some questions as well. Okay, so I guess, with the introduction of ourselves and, and the topic, I just want to briefly acknowledge that, Hazel and I are supported, by, NOAA's, Arctic Research Program on my side, and NSF, on, her side through the Interagency Arctic Research Policy Committee. And we're grateful for their support for those efforts. So, I'm gonna start, and my slides seem to want to do something a little different today, so hopefully this works. I want to start not by talking about, sensors, or safety, but talking about the most important thing in a lot of our lives that sits in between those things, and that's people. And, this photograph taken after the results of Halong in western Alaska really emphasizes the impacts that these events have on communities in Alaska, and so I just really want to hold space for this as we go through our talk, and hopefully highlight the important role also that people play in solving this problem. And so, I think what many of us can recognize is that these high impact events, are really stories about people, and also about specific solvable, and I really want to emphasize solvable needs that require collective action. And so. I'll talk more about our organization, USAON, at the end, and the role that we see that we can potentially play in generating specific and solvable solutions with collective action. But first, I just kind of want to talk more about how we think about this problem, how we work our way through this problem, and how our organization has chosen to work through this problem. And so, I'm gonna kind of center this question, how do we generate collective voice? And how do we do that around the types of problems For which we need environmental monitoring to assure societal benefits like, human safety, human security, and resilience. And so, I'm gonna throw out a concept that we've used a lot in the USAON framework and also internationally within sustaining Arctic Observing networks about generating collective voice. And, but I'm gonna start with a question that I'm gonna ask you to sort of carry with you through the talk. And that question you can read for yourselves. You can feel free to type your thoughts in the chat about what you think these things might have in common. Aviation safety, coastal flood management, wildfire management, and landslide prediction. What do these things have in common? They have a lot of things in common. We're going to talk about a few of them, and I'm curious to hear what you think these things have in common. But I'm going to start with an answer that many of you probably aren't thinking about as your first answer, and the first is that all of these are what we would call polycentric systems. Polycentric systems require a specific kind of approach in order to identify solutions and amplify those solutions and bring collective voice, behind those solutions. So let's look for a second at what we mean by polycentric systems, and as soon as you see, the breakdown of what this means, this'll feel less like an ambiguous term and more like, oh, I have a problem like that. I hope, I venture to guess that everybody in this webinar is working on problems that are relatable. And it really just means that there's many centers in this case, of partial authority, partial responsibility, partial capacity, that need to get drawn together in order to create more holistic solutions and to, identify shared needs and shared problem orientations. And so, in this case, we're not looking at a coastal flooding example, we're looking at the example of wildfires. And what we can recognize is that, you know, breaking it down as we often do across different scales, the local level, the regional level, the global level, there's different organizations who have different objectives in these spaces. They have, part of the resources, they have part of the decision-making authority, but they don't have the whole picture. And so the challenge with, improving Arctic Observations, improving the concept of an Arctic Observing network, is that we need to find ways to weave these diverse organizations together, and to help them identify shared objectives in order to pool resources and collectively, get the work done that needs to be done, whether it's improving observations, improving data sharing, improving the kinds of capacities we need for prediction, forecasting, and planning. And so, one of the things that, sorry, my, oops, no, I won't transition back to that. Sorry. And so, what I want to say is that, you know, in looking at this kind of problem orientation, what's been helpful is that there, polycentricism is something that's been talked about, in economic circles, in education circles, in policing circles. It's a concept that appears in many places, which also means that solutions of all also emerged from different sectors, and so even this paper that, that we drew some of this thinking from, Morrison et al, they were looking at coral reef systems, in the Pacific Islands, and they found that the tools presented to solve polycentric problems were really useful in those cases. And so, we're drawing from a kind of a lineage of thinking, when we present some of the things that we're going to look at here next. And, now I've got it right. Okay, and so one of the things that falls in this space, I mentioned shared objectives, and kind of coming together for shared decision making. There are tools that have been developed both inside federal agencies, outside agencies, and many, other settings that support what's known as multi-criteria decision making. How do you get these complexes of organizations to come together, identify shared, societal needs, shared objectives, and begin to converge on, on the kind of decision-making that's going to get us where we want to go, from sensors to safety. And one of the tools that USAON was inspired by in its work and started building out some methodologies around is this document that was created in 2017 by Sustaining Arctic Observing Networks, which is an international organization concerned with advancing observing and data systems. And it's called the International Arctic Observing Assessment Framework. It is, it is a tool that is known as a societal benefit framework, which means that it has taken, the types of areas and issues where you would want an observing system to be effective, where it should be delivering value, and group them into 12 large buckets, known as societal benefit areas. And under each bucket, it further delineates more specific benchmarks and key objectives that should happen under disaster preparedness, environmental quality, food security, in order to, in order to, have targets to meet for observing systems. And so this helps us work our way backwards from the societal benefits into the observing system to say, where do we need to improve things to improve the societal outcomes? There's a lot more we could say about the framework itself and how it was developed. That's probably an interesting talk in and of itself, but a few things to note about it is that it was developed as part of the Arctic Science Ministerial process. And so, as a result of that, it is Arctic-specific. So, for the region, it was largely developed from, national policies, for the Arctic region. but also with input from other kind of regional and local-level voices as well. So it has an Arctic specific flavor, and it helps us work in this space, this Arctic polycentric space, to improve, outcomes. Sorry, it's asking me to use a weird tool on my computer that keeps making me go backwards. And so, what USAON, was inspired to do with this specific benefit framework was it, was to apply it to value chains for information, which is really what it was designed to do. And those value chains take us from observations Through understanding the value-added processes of the data products that are created from them and what they support, through what we would call key products, services, or outcomes, use cases for information, that are more public-facing, that are accessible, and support things in those key objectives that we identified in the societal benefit framework. And so this very specific diagram that you're looking at here, it's called a Sankey diagram. It is, part of a tool that we developed and a methodology that we developed. The tool's housed at the National Snow and Ice Data Center. And it helps us engage with subject matter experts to do this mapping, where we can understand a lot of different things about what observations are critically supporting these functions, where there are, issues with different data products related to their performance, and what becomes most critical, in creating the kinds of outcomes we're looking to get out of our observing system. So here, the color scale is helping us understand how this subject matter expert, in this case Jen Schmidt from the University of Alaska Anchorage rated the performance of different inputs into an Alaska wildfire exposure GIS that they support. So, Jen herself did these ratings. She said, this is how well these things are meeting or satisfying my requirements for them, and then the line thickness indicates how critical these things are. And so, in moving from a tool like the IAOAF into the benefit tool, what we've really enabled is the ability to kind of crowdsource around these key products, services, and outcomes a growing understanding about what the components are of the Arctic Observing Network, or the de facto network. That are supporting the societal benefits that we think the tools, or that we think should be supported. The, tool itself also allows for other things, like object reuse. We have more than 650 observing systems, data products, tools already in that object library, and through reuse, we can begin to build up a richer picture of what something like VIIRS, for example, is able to support and accomplish. And then through the growing library of assessments, we're able to build up a better systems-level view and start moving towards more of a collective voice about what subject matter experts think the key strengths and the key gaps are inside our observing system. I just want to point to two references, so for more information about the methodology itself, Hazel has led, a methodologies paper, and then the tool, and the DOI can be found for that, that was developed at NSIDC, and so Ed's going to make these slides available for everyone. And so, the status on this work right now, as I said, we've got about 50 plus assessments in our tool right now, working towards that collective voice, that, that systems-level view. And we've applied it towards, what we're going to talk about today, one of the things we're going to talk about today, which is a broad, topic-wise assessment. Ed used the term technical brief. We've been creating these broad technical briefs around, larger topics of importance. We also do some project-based work with these, and in other modes, we also look at in more of a design mode, what the future state of the system could look like. I'm not going to talk about those today, but there's a lot of different things we can do with this tool. I'm going to talk about a specific way that we applied it towards this coastal flooding issue, and why. So the, U.S. Arctic Observing Network sits inside of the Interagency Arctic Research Policy Committee. The, the IARPC, which I think many people on the call are probably familiar with, produces a plan every 5 years to lay out, some key deliverables for the research enterprise to collectively work on to improve our, our multi-agency and outside partnership approach to solving critical problems. In this case, a deliverable in the plan asked USAON to apply the benefit tool towards assessments related to important risk and hazard topics in the state of Alaska. So, some of you have maybe seen, past webinars where we talked about our scoping process and our content analysis process, which was the first few phases of this work. I'm just gonna really briefly recap them here to say that we engaged more than 60, partner organizations in a scoping exercise about what critical topics they wanted to talk about in these assessments, what 3 to 4 topics we should prioritize. I really want to acknowledge the work of John Orr, formerly of the IARPC Secretariat, to help us increase tribal organizations and their voice in this process. We still have longer to go, but we were really grateful to John for helping us find specific ways to engage in those conversations. And the result of that scoping and analysis process, can be seen on the left here, and you can see the different types of organization types And what key hazards they were most concerned with and wanted to see addressed through our assessment process. And without going into a lot of detail on any of this, I just want to highlight that you can see weather events and conditions combined, were the highest rated set of information, but there was an intense concern around flooding. And so, because of that, this became really our first topic that we, really wanted to start assembling from those partners, the subject matter experts who had come forward and identified themselves, and the kind of products and services that would be important to assess. And so that's how we got onto this topic here. And so, we went about the process of assembling these many centers, and as Ed mentioned at the beginning, part of our scoping process was also not just to think about the topics. but the different kind of domains and emission areas within those topics. And so, we didn't want to just talk to forecasters or people concerned with planning or response. We wanted to bring them all together. And so Ed really emerged first as our champion for this work when he was still at the National Weather Service. Through, we progressively brought in Rich, and Taylor, and AOOS, and Erin, and Maddie. I mean, who wouldn't want to work with this group of people? And ultimately, Nora, to help us inform the assessment, that I'm going to walk you through next. And so, this group was really committed to this process, really, like, the diagrams I'm about to show you were the result of a lot of deliberation, and really thinking about how one person's work in this matrix feeds into another person's work, and what is, what do we really mean? You know, I used these terms earlier, performance. mean about how these observations are performing. For this group, like, a really important kind of common ground to find, and I think Erin was instrumental in leading us there, was to say. hey, these instruments, where they're installed, where they're operating, they work great. What we really have is, large spatial gaps. And so we don't want to tell a story where we're saying our performance is low, that could be interpreted as meaning, these instruments don't do well. They're exceptional, we just need more of them in more communities, and that's going to be a the theme you see repeated. There was also, there's also a lot of context, that goes into these individual diagrams, and so we didn't put a lot of time into trying to come up with a strong cross, cohort unification, for everything, but we did have some really critical conversations throughout this very iterative process that I would say lasted about 6 months, for what we're about to share with you. And so, I'm not going to have these folks jump in at this moment as I look at their diagrams, but they are here for discussion, and we can return to them. And so, let's start with, the Weather Service, Flood Products and Decision Support, and this was a diagram that was led by Ed. And kind of getting back to that spatial, that spatial gap issue, one of the first things Ed really struggled with was he wanted to, in some ways, make one diagram that showed the communities that have all the tools they need, and how well it works in a community that has all the tools that they need, and then do another diagram for the communities that don't have all the tools that they need. What we ended up doing instead is kind of more what I described, is in areas where spatial gaps are the issue, we would scale performance back to reflect spatial gaps. And so here, Ed looked at two, different aspects of, flood watch and warnings and decision, one was Flood Watch and warning advisories, and the other was decision support. And you can really see this interesting complex of information that flows forward, supporting the National Weather Service from community observations through, products produced by USGS, products produced by DGGS, etc, resulting in the kinds of outcomes that you're looking for these things to support. You can also see where the gaps are, where the lines are yellow and green. And so, A few key takeaways. I really got at the first one already is the spatial gaps. The second is the inconsistent datums, and so a lot of water levels, as we'll see in the next diagram, are collected by, by, not heavily, standardized instruments, and so there's a big challenge that happens to get everything referencing the same datums. Observations aren't the only place where there's spatial gaps. The Weather Service really relies on the USGS and its product, CoSMoS, that we're going to take a look at. CoSMoS, following, Merbok, was, developed intensively for a subset of communities, so it's not, it's great where it's developed, and it's not in all communities. And again, bringing people back into this conversation, communities themselves, people observing water levels in their own communities, post-flood events in their own communities, a critical source of information in the, in the whole of the observing network. Next, Alaska Water Level Watch, and you can, if you're not familiar with some of these efforts or organizations, the caption under the diagram, describes what the diagram is centering on. In this case, Alaska Water Level Watch, collaboration across many organizations. AOOS now has Water Level Watch Coordinator, Taylor, who developed this diagram. And here we can see that in addition to the National Water Level Observing Network, or NWLON stations, those high standard, gold standard stations. Alaska Water Level Watch is really working on deploying and standardizing much less expensive, sensors, acoustic GNSS, the radar ones, the bubblers. And so, the key takeaways from this individual diagram, again, we need to expand the high-quality stuff, but we also need to recognize that it's urgent to fill the gaps with the non-standard stuff, and that the work of a group like Water Level Watch to try to bring those into better coherence for forecasters and other users. Critically important partners, partnership with communities, this is going to be a repeated theme, also critically important. This one, really visually intense, very interesting. Aaron and Maddie, developed this assessment, to really demonstrate the, the reach of, coastal mapping Topobathy LIDAR. So they actually had developed this diagram as part of a student project we led before the larger cohort came together. And so their diagram, and this is true of anybody who comes and works with us. We want these diagrams to meet the goals of the subject matter experts, in addition to contributing to this collective voice and the bigger picture. And so here, you can see the, from the, from the LIDAR DEMs, the reach into so many partners, so many agencies. takeaways. Again, Topobathy LIDAR, this is a coverage issue. Erin's going to give us some updates about, how that coverage issue is being addressed when we move into the discussion. But also the important work that's being done at UAF to, integrate these products with, satellite and climate data, so that they can, continue to expand their reach and be more effective. From USGS, CoSMoS, came, has already come up in several of the diagrams, so again, these things are all flowing together. CoSMoS also itself highly reliant on things like topo Bathy LIDAR and DEMs, but also other kinds of Bathy data and topo LiDAR. Wave buoy data figured very prominently in this work, as well as the NWLON water stations. And so here, again, the, it's not just needing to expand the observations into more communities, it's expanding the modeling into more communities. And seeing something that has shown up as being high-performing and widely beneficial, where the work that needs to be done, again, a specific solvable problem, is expanding the work into more communities. And last, DGGS, so this, from their Coastal Hazards program, Nora was able to show us a number of the products that they support, and again, how you can really see how integrated and interactive this community is. And I will re-emphasize, Alaska Water Level Watch is a huge convener in this space, and has done a lot of work to Build up, the level of collaboration you see reflected in these diagrams. So here, the state is not just interested within water levels, but also that kind of post-flood, like, how high did it get? What's the recovery picture, what kinds of planning and resources are we going to need to support communities, moving forward from the flood event? Again, you'll see the community ops really highly critical to everything that's being done. At the state level. So, coming back, we had, we did this individual work, there was a lot of interaction around the individual work, and then we had to move towards more, kind of, synthesis takeaways, because there's, as you can see, a lot of detail, a lot of dimensions, that get captured in the expert elicitation for this work. And, So, the Synthesis product, came into this technical brief that Ed referred to at the beginning of our talk. We call these Arctic Observing Storylines. Hazel's done an amazing job, turning these into readable, approachable, digestible, technical briefs. You can find them on our resources page. And we, we use these to try to sharpen two very specific messages. One message is the story of advancement. What are the things that are identified as heavily critical, those fat lines in our diagram. But low-performing, the greener, yellow, and bluer colors. And in that category, we know that we need to advance something. Maybe it is a technological improvement need. In this case, it's really statewide coverage. And it's not just the foundational water level observations, but also that geospatial mapping data. And so I'll refer you for the greater details into the technical brief. I'm just sort of synthesizing here. Again, the, advancing the modeling, forecasting, and decision support capabilities the kind of CoSMoS AKFit type of work. We also want to talk about things that are high-performing, and highly critical, the things that might get a little invisible, the stories we really need to tell right now as our federal budgets are coming under so much scrutiny about what kinds of things critically needed to be sustained. And in this case, long-term coastal observing, mapping, modeling infrastructure, both needs to be advanced and sustained. But critically, getting back to the people, these collaborative partnerships, and you can see already the value that collaboration has yielded in this context, and it needs to be sustained and built out for greater reliability. So, I'm gonna work my way back to the question I left you at the beginning, as I'm bringing the talk in for a landing. So, I mentioned that coastal flooding was part of this deliverable to the Interagency Arctic Research Policy Committee's research plan. We ended up applying this process to four different topics that you can see here. I see Jessica Cherry joined our call as well. She and Rick Thoman really heavily engaged in the aviation weather piece. We just released our wildfires piece. Gabe Woken is still work in progress on the landslides. But even, you can see he did already create his diagram, we just haven't done all the write-ups. And so what we can begin to do here is now build up that systems-level view. The collective waste gets bigger, it gets louder, and it gets really focused on, like, what are some key things that are really going to help everybody. And so, in this process, I will give you the second answer to the question. So, from the, and these are the cross-cutting findings, which I know are kind of sparse and high-level on this slide. I didn't want to overwhelm people. But in the, in the base material, a lot of details, a lot of, critical growing evidence based from subject matter experts about shared needs, shared objectives. Working on things that are gonna help everybody. satellite data, key strength, but data science coordination, data and science coordination collaboratives at a time when it's becoming more difficult to fund coordination and collaboration, this was identified as a key strength. Things would not be possible if people weren't working together to improve these data systems. Indigenous knowledge sharing systems and networks, also identified as a huge strength what are we doing to support that aspect of our system? How can we invest more in such an effective part of our system, a key strength? And then the gaps, I will let you read yourself, but also to say that fragmented agency accountability, Has also been identified as a systematic institutional gap, and again, one that we can solve, specific and solvable. All right, so that's my buzzer. I'm going to come in for the wind-up here. So, I hope that gives you a sense of, both the broader work that USAON has been doing in this space. Maybe you yourself have some ideas about how you could get more involved with us in an assessment. We are going to keep this process moving forward to more topics. But for right now, we're, just reporting out that we have found so far that these have been, effective. We'd like them to spend a little more time in the world before we assess how effective they've been. But we also hope that they can be used, by other communities to help build towards that systems-level view, that collective voice that's needed. These initial efforts took a lot of time. We are finding ways that AI tools can start expediting this work and get us moving faster. We also have our own process more figured out. And then the last piece, and I will spend an extra minute of the talk to talk about this, is that it's important that going back to these came from agency systems, this methodology came from agency systems. We've built on it, we've tried to make it responsive to Broad communities outside of agencies, but it's important that it's still in a legible format for agencies to understand. So, A bit about the organization itself. We, when I talk about legible within agencies, the work I've just been describing, in the complex facets of what USAON works on, works on, this infographic kind of reflects our organization. The benefit assessment sits in this community partnerships and task teams facet, but it connects into our federal board, people within agencies who have the, the ability to react to policy, resource, and planning issues, and communicate them up to the heads of our federal agencies in the form of the IARPC principles. I know we have some of our board members on the call today, which is really exciting. You can see who's on the board here, but these guys, they serve as really our champions within the agencies to take these, findings and try to stimulate action from them. And back to this piece about legibility, I'll just give you this quick example. So, I mentioned benefit is derived from NOAA tools. Recently, this summer, we sat down with somebody within NOAA who works on these tools, and we showed them benefit, again, they've seen it a few times, and they very quickly went into their own decision support system, pulled out an example about tsunami warning systems, and generated this Really great diagram in about 30 minutes. So the, what this is kind of helping us to hopefully see and maybe pin some hopes on is that the effort we've put into developing this tool, and trying to do it in alignment both within agencies, but in respect of the bigger picture, we hope yields some good benefits. Sorry, I guess I had a little bit more to talk about. So, coming back to people, I do want to also say that our findings are not just about sensors, right? A lot of those findings were about Indigenous knowledge, community sharing systems, collaborative partnerships. And so, we really hope that this work can bring visibility to that, because it's kind of too often we just talk about sensors, and kind of skip over this important key strength inside these networks. So, I'm gonna just pull up some discussion questions. And we can copy them into the chat as well. I mentioned we have some contributors online. We'd like to understand how this work has maybe helped them since they undertook it. I'm happy to hear anything from all of you, and then really think about where we can move forward on actions, both with this technical brief information and some of our other technical brief information. So, thanks so much for your time, and really looking forward to discussion. Edward Plumb: Great, thanks, Sandy. Let me, click the button so people can unmute themselves if they want to ask you directly. But, I, if you bring up the, the National Weather Service diagram, I have a few comments I can make to that as part of this process. Sandy Starkweather: Will do. Okay. Edward Plumb: While I find the tools to, Sandy Starkweather: Sorry, it's one of, for some reason, my, my thing won't let me get to my tabs, so I'm gonna just have to do it this way, the old-fashioned way. Okay, there you are. Edward Plumb: Okay, first off, I have allowed everybody, you can unmute yourself or turn on your video if you want to ask a question or get involved in the discussion. Otherwise, just drop a comment into the chat there. So as Sandy mentioned, I had worked on this diagram, I think you probably came to the Weather Service initially, when you were starting on the Coastal Flood side. The one thing I wanted to point out, this, this is a really good exercise just to kind of see where there are gaps in the process of producing reliable and accurate and timely forecasts and warnings for coastal flooding. So, at the National, I don't work for the Weather Service anymore, but the mission, the primary mission is, to provide forecasts, warnings, and decision support for the protection of life and property. So, I kind of lived and breathed that for almost 30 years as a forecaster at the Weather Service, based in Fairbanks. So, this, this exercise, as I mentioned, observations are absolutely critical to providing an accurate forecast. First of all, from a forecaster's perspective, just knowing what is currently happening at that community right now. Also, those observations go into the forecast models that project out into the future, so that's critical to have those initial conditions. So back in the day, probably even 10 to 15 years ago, we had very few observations, and really absolutely no flood inundation maps, so we really relied on community networks and working with, people in communities across western coastal Alaska, to get observations, whether they gave a phone call initially, or when social media became, you know, more popular, we got a lot of observations from social media, and then as more observation platforms started to go in, that was extremely helpful, and then the DGGS started creating inundation maps, which we could actually see what was impacted during, you know, different, at different water levels. So, a couple things I just want to point out in this diagram. As Sandy mentioned, the, the darker purple ones are, indicate the performance. So, there's one in the middle that says DGGS AKFIT, so that's the Flood Inundation tool. So, these are maps produced by the DGGS showing, Inundation mapping in different communities. So I had these highlighted as purple, so these were unbelievably valuable for forecasting and alerting communities to what parts of the community are going to be impacted during an event. And so, you know, is it going to be a small event, or is it going to be a big event? So that's why I've, included that as, like where we have them, as Sandy mentioned, not all communities have these maps, but where we have them, they're unbelievably incredible from the forecasting perspective. And so, those were used in watch warnings and advisories, and then also in site-specific decision support to communities. On the other end, you see some yellows, like USGS CoSMoS, I know that's come up in the chat there. That's a new tool being developed by USGS, but at my time of leaving Weather Service, that had not been integrated into operations yet. There was a lot of potential for that tool, but I rated it, performance rating, I rated yellow or low, because we weren't actually using it in the forecasting operations at that point. And one other thing I want to point out, the Alaska Water, the AWLW portal, Alaska Water Level Watch, which is, with AOOS, where they're pulling in all these different observations from different platforms, and as Sandy mentioned, there are different types of sensors, they're reporting in different types of datum. So, this is one, I know the Weather Service has been working on this to provide the Weather Service one datum. This was a gap, because we had different datums, and we were forecasting in one particular datum, so we would get all the same information, but conveyed in a different number. And so, as a forecaster, we need to have everything in the same datum that we were putting out our forecasts in. So that was a gap, and I know that has been worked on with AOOS to come up with having everybody, or have the platform report in the same datum, so apples to apples, basically. That's all, that's all I wanted to say. I appreciate you taking the time to, present this, Sandy. Sandy Starkweather: Yeah, thanks for that extra detail on that, Ed. I don't know, Erin, if, I saw Erin and Li were both on the line as well, and while Lee didn't, create the CoMSoS diagram. She, and Maya, I think, as well, they both were really supportive in helping review this work. Erin Trochim and Maddi McArthur: Hey, Sandy. Yep, Maddie and I are both on the line right now. Awesome, yeah. Do you want me to give a little bit of feedback about our, or some of our takeaways, Sam? Sandy Starkweather: Yeah, that would be great. Erin Trochim and Maddi McArthur: Awesome! Yeah, so when we were, when we were looking at, our, our, societal benefit analysis, my, my first takeaway is that man, we need to update it already a year later, actually. So, but, yeah, like Sandy mentioned, we used this to do a more comprehensive, mapping for our program, and we had been, thinking about this from the initiation of our project. But also, as we have been working through the various stages of it. And so, our program primarily focuses on, what was the Jabel Tech, and now is, iAtlas Topobathy LiDAR data. We don't do the collection. We do a lot of the research that goes around the products now, in terms of characterization and usage in Alaska. And then, in the last phase of our project, we did a lot of work, with our fellow agencies. And also, with, some communities that we worked with. to understand how the different pieces fit together, because especially with something like Topobathy LiDAR or elevation data period, it has a multiple multitude of uses, and when you collect it, it can often seem really disconnected from where it actually ends up in the long run. And so, one of the biggest issues with our Topobathy LiDAR data collection is twofold. A, we fly it with a plane, so the plane has to be in Alaska to be flying. If anybody's interested, you can now see the site, collection in Alaska. The plane is back this summer. It was in Nome as of Friday, so we are going, we're trying to do some recollection on the Halong sites. And we've also been doing some field work on the Kuskokwim River as well, already this summer, in prep for, hopeful, data collection on that, the river mouth as well. And so, but, yeah, it, it's, we also have put together an Alaska EDX class, talking about topo Buffy LiDAR and trying to connect, some of these pieces together. And we're happy to take comments and update it in the future. That's kind of the intention. But what I think our take home from this was is that we really appreciated this effort to help, guide where our research efforts, should be focused a lot more. So we've identified two major ones, and so, issue one that we've been relaying to the iAtlas program. is that the data is just not processed fast enough, between data collection and being available. That's a huge issue. And number two, that we've been working on quite extensively. Is that, we've put, large efforts the last year, and we're continuing into satellite-derived bathymetry to be extending this data, the multi-beam data that's available, into bathymetry products that can be more responsive to the downstream products as well. And so, we've used this, societal benefit analysis I just showed it, actually, at the iAtlas workshop that was in Corpus Christi in June, and I think it really helped our other programs Understand tracing their products, like this, especially the bigger programs, both as strategy for themselves, but as a key communication device for all of our different users, and communities of practice. And then, the other thing that we're doing is, Maddie, who's here, we're actually, we've been building out, ontologies around our data workflows. And this part is also a key area that we're interested in building out. Essentially, we're halfway to an ontology already in doing the societal benefit analysis. And so, for the AI-assisted work that we're interested in, this is super important. And and we're interested in revisiting some of the ideas around performance, ratings to better communicate the nuance that's going into those. Sandy Starkweather: Great, thank you. Jason Laney: Hey, how do I raise my hand? Sandy Starkweather: I think you. Jason Laney: I don't. Edward Plumb: Yeah, you're on Jason Laney: I don't, I don't see it, I don't see it on this thing. Okay. Hi, Joel, Joel Curtis from the National Weather Service. One of the things, I've been doing, coastal flood forecasting for an awfully long time. And, one of the things that has struck me, and it's getting better, but it struck me that very often, I would make a forecast, and then not have any feedback as to how it came out. So, in other words, I didn't get the verification. And, the one thing that, if I could encourage this team the most, is that, The more verification we can get, the, knowing how our forecast came out, because we're issuing the official warnings, the alerts. Knowing that, you learn from it, And, Therefore, you get better at it. And that's one of the things I think is so important about an observing network, is that you can get the feedback that you need to improve your forecasting techniques, to improve your methodology, and get better and make a better call the next time. Thank you. Sandy Starkweather: Yeah, I'm, I really appreciate that comment, and, I have one thought in terms of our assessment, but I'd also like to hear from Ed in particular, having been in that role. We, we recognize that these assessments were done by the people who produce the products and services, and they have to kind of make their best guess at how well these are doing at meeting those key objectives. which kind of gets at what you're talking about. They have to self-assess and say, how well do I think I'm actually supporting This particular type of disaster preparedness. And a step we would like to take in our own methodology, and it's outlined in this paper that Hazel led, is we would like to move to cohorts of subject, of cohorts of really, like, people who are in the world and using these things to do that reflection back so that we can, get that kind of, kind of stronger feedback in the system, that you're describing that's, that's so important. And I also think that that comes from the more, the more involved the community is, the way Ed described, calling up their office, telling them how things are going, the more you, the more you have that engagement and involvement, the more, the closer you can get to a better sense of that. But, Ed, I don't know, is there, is there something there that you want to respond to? Jason Laney: Yeah, I'm gonna, talk just a little bit about the methodology. When I, when I'm, on duty, out on the forecast desk, and I'm trying to, Nail it down, you know, what kind of alerts we're gonna issue. And the first thing is, you know, a pattern recognition, is just taking a look at the overall flow pattern, if you will, the pattern of the atmosphere, where the jet stream is, where the highs and lows and fronts are. And say to yourself, you know, This is, looks like it's getting to be a setup for some, Flooding potential. Okay, I'll leave it at that. And then, Joel, in his methodology, he goes right to the tide chart and looks and see what phase of the moon we're in, and when are the high tides. And then, after that, I start really studying it very carefully, looking at the model output, looking at The aspect of the shoreline, that is, is it, Are you going to have a wind push that's going to go onshore, or are you going to have a wind push, or is it going to be offshore wind, and that will retard the water level rising? So, there's just a lot of methodology like this, and when you finally get down to it, and you add it all up, then you reach a decision that Depending how far out in time you are from when you want to call the event, whether it's going to be, first maybe starting out with a special weather statement, then going to a coastal flood watch, and then finally a coastal flood warning. And one of the things I love that has been done Are looking at the individual community, inundations. And that, for the IDSS that we do in the National Weather Service on an individual community basis, there, that is gold. That is, like, that's, like, the best stuff there is, because then you can really help the individual community make those, very critical local decisions that, they can do for you know, maybe evacuation routes, or, where they want to go to shelter in place, or whatever. So, So the answer is, is there's, there's a lot to it. But at the end of every event, I wish I, I want a clear picture of what happened so that I can compare that to what I was thinking, and then learn from it. Thank you. Sandy Starkweather: Great, thank you. Ed, I know we're almost at time. There's a few things in the chat we could address, but maybe we should do a time check with you. Edward Plumb: Yeah, we can, like, just to, to respect everybody's time, I mean, feel free to drop off at the top of the hour, but we will hang on here if there's more questions or discussion. Not a problem at all. And just a couple comments to Joel. I mean, everything, Joel has been around a long time, maybe the longest on station at the Weather Service in Alaska now. I don't know, Joel, I don't know the stats, but they're probably up there and seen a lot of coastal flooding, but I know when I had left the Weather Service last year, one of the, things that came up with all the groups that are working on coastal flooding in Alaska was documenting impacts, because different agencies from the state of Alaska, Division of Homeland Security Emergency Management, were taking in reports, the Weather Service, the DGGS, the USGS, and so, community reports on social media, and trying to make sure that there's timing with photos, so you know, like, so you can go back and be like, what water level is associated with that impact? So, just as Joel said, in the future, then we know if the water gets up to that elevation again, we know what will be impact, or we, I'm speaking for the, what they know will be impacted, at that water level. And so there, there has been an effort, I'm not sure where they're at right now, for trying to come up with some collective place to record all that information, so it's useful to everyone from the community level up to the state level. Sandy Starkweather: I see there was also a question about whether we might address permafrost, moving forward, and, and I think that was from, Jana Peirce, and that, that is high on our list. We, I mentioned that now that we've got the methodology kind of hammered out, and some aspects of the tool, in better shape for group work. Starting in September, we're probably gonna recruit, around two more topics, and Permafrost does seem like one that had a high level of focus and interest. And so if, you know, feel free to reach out to us, And, we'd be happy to discuss, but, we'll probably also return to many of the people that we did those dialogues with. And then I guess there's also some discussion about change over time. And that's, that's a, that's a tough one to grapple with. We, within the tool, you know, we're kind of at a minimum viable product right now. And so while, you know, these are snapshots that are relevant for when they've been created, we try to include that in the context of what's being described. Like, you'll notice one of the, from the, the Wildfire GIS, the NASA land cover database had a really low rating. That wouldn't have been true, I think, 5 or 6 years ago. It's because some aspects of it have been dropped and discontinued, and so it is important to kind of timestamp these and be able to revisit them, and so versioning is something we think about a lot. I think Rick was one of the people who asked the question. We also did apply this towards the same methodology, towards the indicators and the Arctic Report Card, and Hazel included in that also a really nice discussion about the current risks That these observing systems are facing, and how we can use a tool like this to have better discussions about risks and think about, you know, theoretical changes in state and what the impacts of those things might be. Edward Plumb: So, if there's any, any more questions, feel free to jump in. Just looking in the chat, I see that Dana from NOAA put in a link to the high watermark survey form. I will just, I will take all the links and include them in the email I send everyone later today, so you'll have access to those. Sandy Starkweather: I think on that note, an important point to mention is that these technical briefs that we do, we put a big disclaimer in there that we're not looking at every relevant system, we're trying to look at, as many representative systems as we can, and, And speaking of change over time, we're happy to add Kind of more thinking and more systems, to these topics as time goes on. So, you know, just kind of a caveat about the results is that they're partial. Hazel Shapiro: Another thing I would just jump in, thank you, Sandy, for the wonderful presentation, and thanks for the discussion in the chat. I tried to keep up with some of it. I put our email addresses in there, and we would love to, follow up with folks that are interested. One of the things, this is sort of, like, the first, these are the first two that we've gotten out in this format. We've done a couple of these assessments in other formats and with other kinds of topics in the past. And we are, are gonna be looking for feedback, both in terms of Where else can we take this? Who needs to see this? What feels useful from this? What's missing? We've been hearing a lot of that in the chat, but just want to recognize that as we start to put these out into the world, we are looking for that kind of feedback, both what seems to be landing well, what feels important in here, and things that we may have missed. So thank you for starting to do that. If you take a closer look at the brief. And you have feedback, that all will help us inform our future work and try to make this the most impactful, as we can, and that is, Like Sandy said, our, Definitely, our goal here is to try to inform that collective action in a, In a way that's helpful and supportive, and that we can do in a good way from our seats, and support other folks who are, Also doing this work. Edward Plumb: Okay, thank you, Hazel. Thank you, Sandy, and thanks for all the questions and discussion, and, I think we'll, we'll wind it down now, and let everyone enjoy the rest of their afternoon. And I will, once the video processes, I'll get it online and then send everyone an email, so you have all the links and a link to the recording. So, at that, thanks again for coming to an ACCAP webinar, we appreciate it. And if you fill out that survey when you log out, that'd be awesome, and hopefully we'll see some of you again soon. Thanks again. Sandy Starkweather: Thank you. Julia Mickley: Thank you, bye!