Podcast & Show Notes - Louisiana State Climatologist Barry Keim
Thu, 7/7 10:20AM • 22:27
SUMMARY KEYWORDS climate, meteorologist, weather, datasets, forecast, calls, tool, cone, storm, drought, meteorology, convective, hurricane, data, storm prediction center, track, severe weather, Louisiana, Louisiana State University, forecasting
[00:00:03] Drew Hawkins: This podcast is a production of a research project at Louisiana State University, funded by the Louisiana Sea grants called Communicating Climate Tools to Coastal Stakeholders, or CCTCS. Researchers from the Department of Communication Studies the Manship School of Mass Communication, and the Department of Geography and Anthropology examined communication challenges during extreme weather events.
[00:00:34] Drew Hawkins: When people think of extreme weather and climate communication, chances are they probably think of meteorologists, the folks who broadcast information on television or over the radio. But there's another group of scientists known as climatologists who play an important role too. To find out more about what a climatologist does and how they help inform emergency managers and meteorologists, we sat down with Dr. Barry Keim, a professor of geology and anthropology at Louisiana State University, who was also the Louisiana state climatologist.
[00:01:20] Drew Hawkins: Alright, thanks for sitting down and talking with us Dr. Keim. How are you today?
[00:01:23] Dr. Barry Keim: I'm doing very well. Thanks. It's good to be here.
[00:01:25] Drew Hawkins: Great. So why don't we start real simple and just, you know, tell us your name, your title, and give us a little bit of your background and work history.
[00:01:33] Dr. Barry Keim: Okay, so, again, my name is Barry Keim. I am a professor in the Department of Geography and Anthropology at Louisiana State University. I also have another role as Louisiana State Climatologist for the state of Louisiana, obviously. And my research area of specialization is extreme weather, and in particular, heavy rainfalls, hurricanes, and storm surge. And I also work quite a bit at least historically, dealing with the interpretation of climatic data, especially as it relates to climate change.
[00:02:09] Drew Hawkins: Can you maybe describe your understanding of weather and climate information? Generally real broad sense?
[00:02:16] Dr. Barry Keim: Well, you touched on something there in terms of weather and climate, and that also
brings up meteorology, which are three things that, obviously, you know, if you do
the Venn diagram, you know, there's a lot of overlap between these things, but there
are nuanced differences. Some, and some are, you know, even more than the nuances.
example, you know, just to start with meteorology: Meteorology is the short-term forecasting of the weather, and to be a meteorologist, you know, you would go and you'd study the, basically the physics of the atmosphere, and you use a lot of computers, obviously, to simulate this kind of stuff. And, but the ultimate goal is to predict the weather, say, next hour, next day, maybe even out to, you know, a week or 10 days, but it's all about forecasting, and how the weather is going to change and interact with other weather systems. So, in the realm of climatology, rather, climatology is essentially everything else involving the weather, it's looking at the historical past, seeing what the averages are, what the ranges of extremes are.
[00:03:36] And I would also argue that it brings in like the realm of probability. For example, if you want to know what a 10-year, 50-, or 100-year rainstorm is, and you know, how much rainfall is associated with 100-year storm event over 24 hours or 72 hours? That's climatology. So doing that kind of work, dealing with the historical past is, I would argue, in the realm of climate. Coping with climate change, how are the averages going to change into the future? What you know, what is the average temperature going to look like in July, 100 years from now? And you know, what are the causes for those changes? And, you know, why might they increase or decrease?
[00:04:19] So, of course, we're looking at increases right now, with global warming. How many more 90-degree days or 95-degree days,100-degree days are we going to have into the future? That's climatology, trying to understand how these, these long-term averages might change. And you know, what's the probability of a category 3, 4 or 5 hurricanes rolling up on our shores here in Louisiana? I would argue that's also climatology. So, so that's kind of this distinction between meteorology and climatology. And of course, then we have the weather. The weather is what's happening outside right now. The weather is what you talk about in line at the supermarket. It's what's happening at any given instant at any given place. And of course, climate is the totality of the weather over long, long periods of time. And then the Meteorology is the forecasting the weather over the short term.
[00:05:10] Drew Hawkins: So, moving into some of the tools that you use in your profession, can you talk about which ones you mainly use to assess the extreme weather and climate conditions? And maybe talk about why you prefer them over others, and why you use the ones that you use?
[00:05:27] Dr. Barry Keim: Okay, well, first and foremost, unlike Josh Eachus, who, by the way, was one of my PhD students, Josh is a meteorologist, okay? So, he uses different sources of information to do his work to do forecasting, while I use different sources in my work to do climatology, because what he does is meteorology, when I’m doing this climatology, I sort of drew out those differences earlier, as to what those are. So, you know, I’m looking at long-term historical climatic datasets, and looking at probabilities, past experience, analog kind of forecasting, where we look at how things set up in the past, and will they play out again, in the future. And like coming up with lots of probabilities. You know, what are the chances, like I said, New Orleans–or Baton Rouge is going to see winds of 60, 70, 80, 90 miles an hour? I mean, it doesn't happen often. But it does occasionally happen. And what are the chances of that happening?
[00:06:35] So we look at it more from a long-term preparedness perspective, if you're going to put in building codes, how do we need to build these buildings, so that they can sustain what they what kind of winds they may possibly see over a 50-or 100-year life cycle. That's a very different kind of thing than predicting whether the hurricane is going to make landfall at Grand Isle, or over at Morgan City. So, I'm trying to draw out those differences. So the datasets that I use would be very different from what Josh Eachus would use, but the foundation of everything we do in climatology is historical climate data. So, I look at these long-term records for, you know, stations that have these long-term records, and most of the kinds of analysis that we do to try to understand, you know, weather patterns are changing, or what's the probability of this or that. So those are the kinds of datasets that we use.
[00:07:37] Now, there are also a lot of specialized datasets. For example, the Hurricane Center has a dataset called HURDAT, and this stands for hurricane data, HURDAT. And that data set, I mean, we've--I've used that for a whole number of different hurricane type projects. And what the data set is, in essence, is all the hurricanes that we know of back to 1851, what their tracks were, and what their strength was all along that track. And with that, you know, we're able to do lots of research on those particular data. We at LSU, have built a storm surge dataset, we call it SURGEDAT, which we like to think of as a companion dataset to HURDAT, whereby we have all the--as many as the surge observations as we can find, put into this giant database and it serves as a clearinghouse for all surge information. And then, of course, we have all these datasets that the National Weather Service and NOAA have collected over many, many, many decades. And in fact, you know, I have a graduate student right now working on rainfall in New Orleans, all the way back into the 1840s. So, we have, you know, like 180 plus years of data for a site in New Orleans, which is just invaluable, and you don't see that very often. But normally, you know, our data sets can go back a little over 100 years. But in this case, we have almost 180 years for the city.
[00:09:14] Drew Hawkins: Right, that's fascinating that much data going back that far. There was a survey that we did over at the Department of Communication Studies about the climate tool use and this may or may not be relevant to you so I'm going to run the most used climate and weather tools that we found were Convective Outlook, the Cone of Uncertainty, and the Drought Monitor. Are these anything that you use?
[00:09:37] Dr. Barry Keim: Absolutely, absolutely.
[00:09:39] Drew Hawkins: Absolutely. Can you talk about maybe--actually, you know, what, give a one to five scale of you know, one being, okay, five being the best about the quality of these tools. And then maybe talk about what you would like to see to improve the communication of these tools or make these tools better if you have any thoughts about that.
[00:09:56] Dr. Barry Keim: Okay, let's take these one at a time and keep me on track here. So, we have the Convective Outlook, the Cone of Uncertainty, is that right?
[00:10:07] Drew Hawkins: Yes. And the Drought Monitor.
[00:10:09] Dr. Barry Keim: Oh, the Drought Monitor. Okay, so let's start with the Drought Monitor. Okay, so with the Drought Monitor, that's a national effort to try and better understand drought across the United States. Its usefulness, I would say, I mean, 0 to 5, or 1to 5is my scale? I mean, I give it a 5. I mean, I give all these 5s, okay? Because these are all very important, very important tools. I use these all the time, okay? In my work, I do a lot of media type calls and drought comes up a lot. So, the way the Drought Monitor works is, there's a group called the National Drought Mitigation Center, they're located in Lincoln, Nebraska, at the University of Nebraska. And they, I mean, they, monitor the climate all across the country, and then they put out a draft report on Monday. So basically, this thing gets updated once a week, okay, just to put some spin on this. But they put out a draft report on Monday, and then of what they do and what they can put together from Lincoln, Nebraska. And then they expect locals to infuse local expertise on what impacts are being felt, and how those boundaries can be tweaked a little bit, you know, based on local knowledge.
[00:11:41] So we, you know, we’ve done a fair amount of that. We work with the Drought Monitor a lot in our shop and the LSU Climate Center. And we do give input and we do help them tweak their boundaries. And, this gets, you know, these things get used for insurance purposes, and things like that, when there are crop failures, and, you know, and impacts from drought. So, it's a very important tool, and we are heavily involved in helping the National Drought Mitigation Center, tweak their boundaries across the state of Louisiana. So, I definitely give this thing a five and I use it all the time. And historically, I have contributed a lot, although somebody who works with me at LSU has been doing the primary chore over the last year or two in terms of giving them input for the state of Louisiana. So that's a long answer to one of those.
[00:12:40] So let's go to the Convective Outlooks. So, the Convective Outlooks come from the severe weather, I guess, the Storm Prediction Center, over at the University of Oklahoma, and they try to basically monitor the climate, doing forecasting, obviously, and there are certain indices in the atmosphere where, you know, great instability can take place, which can lead to tornadoes, can lead to hail, and to severe thunderstorms. And in particular, you know, strong downdrafts out of the thunderstorms. You know, things that we call micro-bursts and macro-bursts and straight-line winds and things like that. So, they monitor that, and when they think that this great instability is going to occur over a certain area based on certain indicators. They'll put out a forecast, and, you know, and they have this rating scale that, you know, from marginal, to non-existent to marginal and into, you know, more severe ratings.
[00:13:57] I guess the only beef I have with that particular scale, I think it's a great tool. I use it all the time. I get calls, you know, when severe weather is in the forecast, asking me to kind of assess what the risks are here, and you know, to put a put a local Louisiana spin on some things, and a Louisiana understanding on things. So, but I don't specifically contribute to that product. That's something that all comes out of Norman, Oklahoma, you know, from the Storm Prediction Center. So that, but again, it's a great tool. And then, from a climatological perspective, they then produce daily maps of where the severe weather occurred. And you can go tap those maps anytime you want. And I don't know how far back in history these things go but you can go back many decades in their dataset and day by day look specifically at where severe weather broke out across the United States. It's a great tool. It's a great climatological tool as well. I tried to understand patterns of tornadoes and hail and, and in high winds. So I, hey, I give it a 5. Great tool.
[00:15:11] Drew Hawkins: And then the third one was the...
[00:15:16] Dr. Barry Keim: Yeah, the Cone of Uncertainty that's issued by the National Hurricane Center. So the way, again, it's a very useful tool, it shows what the extent of the errors are in the Hurricane Center forecast as to where the storm is going to travel. Now, the way that tool works, the Cone of Uncertainty works, is over, say over the last 20 or 30 years, the Hurricane Center monitors how large their errors are in the track forecast before the storm makes landfall. So in other words, they have a 24 hour error so if a storm is in a certain location. And they you know, as they make a prediction of where the storm is going to be in 24 hours, what is that average error? Well, I believe it's around 34 or 35 miles, something like that, in 24 hours. As you go out to 48 hours, obviously, the error is larger, because you're dealing with more variables, more time, there's more erosion in the forecast. So, the error gets larger.
[00:16:24] And I don't know what the number is, specifically, but it's going to be a lot bigger than 35 miles at 48 hours, and it gets even bigger yet at 72 hours. So, you end up with this big cone, okay. The closer you are in time, the less error there is, the further out in time, the prediction is, the larger the error. So, the way the cone is drawn is formulaic, in that the 24 hour, they take the average 24 hour error, and then they make that, you know, that's what the error is, 24 hours. They take the average 48-hour error over time, you know, historically. And that's what the 48-hour error is in terms of the cone. Now, what you also have to realize about the cone, though, is that the cone basically is telling you--it's telling you that the storm has a 67% chance of staying within that area during its track.
[00:17:28] So we know it's not foolproof, sometimes the errors are larger than the average, right. And because of that, you know, the cone of error is also not perfect science. Sometimes it's wrong. But two-thirds of the time, it's right. So, you have a two thirds chance of that storm staying somewhere within that cone before landfall, which gives you some semblance of where the storm is likely to make landfall. But again, you got to realize one-third of the time is going to be outside of that cone. So that again, that's one of these, going back to one of the original questions, or one of my original answers about crying wolf syndrome, this is one of those things that we have to deal with.
[00:18:17] Whereby, you know, let's just say a 50-mile error in a 48-hour forecast may be a pretty good forecast. But it doesn't make it easy for emergency managers, because a 50 mile difference in where the storm makes landfall could lead to dramatically different conditions from place to place within these watch and warning areas. So, this is what makes that so difficult, and trying to convey all that to the public. But again, education is the key, the more people understand what they're looking at and can process it, the better off we are. But you know, the flip side is we know we can't get every person to be trained like a meteorologist. So that's the dilemma but the more education that we can get to people and have them understand what they're looking at, obviously, the better.
[00:19:08] Drew Hawkins: Right, so the key takeaway here for me is education. Is there, is there anything else you'd like to add that you know, something we didn't talk about or something you wanted to make sure you mentioned as we kind of wrap this up?
[00:19:20] Dr. Barry Keim: Well, I mean, those three tools that you mentioned are, three that I use a lot in my work for a whole variety of different things. The Convective Forecast, I will admit I don't do any pure research on that information. But having said that, I get a lot of calls from radio stations I work some with television and so on. And I do use those a lot when impending weather is we know is coming and to try to understand what the risks are and to try to help convey that information to the public. So, I use that a lot in my outreach. However, the data that are archived, all the tornado tracks, all the high wind, where hail occurs. Once that gets put into an archive, I mean, I've had students study tornadoes and tornado frequency and track length and all this kind of stuff. So, you know, the ultimately the data that comes out, that comes from those storms that are archived by the Storm Prediction Center, do get used quite a bit in the realm of climatology.
[00:20:31] So, but the others, you know, well, the Cone of Uncertainty obviously, is a forecasting tool. But all that historical track information and track data and errors in the forecasts and things like that, are things that we do look at. And of course, the Drought Monitor is, you know, drought is one of those risks that people kind of overlook, because it's kind of a slow creeping kind of thing. It's not, it's not an event like a tornado, or a hurricane, it's something that starts out slow and continues to build over time. And it kind of just creeps along and intensifies. And to the point to where we end up with some very serious problems.
[00:21:17] A great example is what's going out in the southwestern United States right now with these really low reservoirs. And, you know, Lake Mead, at historic low levels and mean, it's a pretty interesting things going on. But these things happen very slowly over long periods of time, especially with the Lake Mead issue. But drought is just again, one of those things that that can just kind of creep up on you. And the next thing you know, you have a pretty serious problem on your hands. And when I say slow, I mean, it's not always years. Sometimes these things can actually manifest themselves over weeks. But it's, you know, it's sort of a day-by-day creep, and you just keep expecting rain to come and when it doesn't, it just keeps compounding a little bit more and a little more and a little more until you have a serious problem on your hands. If you're a farmer, that's a big deal.
[00:22:05] Drew Hawkins: Right. Well, Dr. Keim, thank you so much for taking time and speaking with me today. I really appreciate it and have a great day.
[00:22:13] Dr. Barry Keim: Hey, it's my pleasure. Thanks for having me.