What can computer models tell us about Earth's future climate?

good evening everybody um thank you for coming out to uh tonight's uh lecture by uh dr ross dixon uh and also i hope you have a chance if you haven't been upstairs uh to love north to see the exhibit it'll be there until the end of the semester so if you have time tonight go see it if you haven't already or sometime when you're cruising through campus stop and stop in and visit the exhibit that's uh the reason for this talk so um dr dixon joined the faculty uh uh at unl uh january a year ago he's been here for a little over a year now um he's a regional climate modeler and uh that's the reason we recruited and hired him uh ross uh spent uh well i should start i guess at the beginning right not that far back got his bachelor's degree and master's degree in physics and atmospheric physics uh respectively at university of maryland baltimore county uh and then went on to the university of wisconsin for his phd which you received in 2017 that's right yeah and then he spent two and a half years at the national center for meteorological research in toulouse france i didn't try to pronounce the french name for the center because that would just be awful for everybody and then after he finished that he happened that he stopped by lincoln and interviewed for his job and then went on to another postdoc at the university of arizona uh before he came back for the faculty position uh in january of 2021 so ross is going to talk today about climate models and how we use climate models to project future climates for earth so without any further ado thanks for that kind introduction clint and thank you all for coming out tonight i know the weather might not be the the nicest tonight so i really appreciate you coming out um for my talk uh as you said i'm ross i'm uh really interested in climate dynamics atmospheric dynamics and climate modeling so it's a real pleasure to be here tonight to tell you a bit about what computer models can tell us about earth's future climate we uh need to click here there we go we live in the changing world you might be aware of this uh this figure here comes from the most recent ipcc report which was released last summer from the first working group and it shows change in time for several different parts of the earth system so at the for example at the top here we've got the atmosphere one important component is the carbon dioxide concentration and so here we've got an increase a dramatic increase in co2 concentration with time in the cryosphere there's observed glacial mass loss in the the recent past the ocean is increasing in heat content we see sea levels rising all of these things are connected uh especially through global surface temperature which we can see warming and these colors blue colors are are cooler here red colors are warmer and i really want to focus down here into this global surface temperature let's look at this this data in a different lens this might be easier for some people to to picture we've got changes in global surface temperature on the y-axis here relative to the 1850 to 1900 period and what's been observed in these observational records is around one degree celsius of warming since that period which ends in 1900 and if we extend our record back 2 000 years using proxy data for temperature from ice cores tree rings and and other records which we can derive temperature from we can see that this warming is unprecedented in more than 2000 years right this is this is a global signal that we can observe in the climate record this is another way of looking at these global temperature changes i don't know if if you've seen these before this was a what was called the warming stripes um this was put together by ed hawkins and it's essentially the exact same data from this figure here um but we've put the warming colors right colors that are uh a positive on a figure like this in red and ones that are negative in blue the averaging is done over a slightly different period so you're going to see red and blue in slightly different places but the signal is clear warming towards the end of this time series dramatic warming in the next couple of slides i want to flip through and think about going to uh smaller and smaller regions because when you think about it it's really important to think about what global temperature change is going to be but it's even more important to think about what the change that's happening in your own area is right no one no one wakes up and says well you know i really noticed that the global temperature was a little bit warmer what they notice is how temperature is changing for them so this is what a similar plot looks like for the entirety of the united states since uh 19 sorry 1895. and what we see is the same pattern warming towards the end of the record but there's more noise here right there's a lot more variability in the year-to-year variations in warm and and cooler years and this continues as we look at the state of nebraska and and so you can see the same signal warming towards the end of the record but there's some really really strong warm years towards the earlier period some cool years mixed in here this is kind of highlighting how understanding regional climate is a serious challenge and is is so important for understanding human impacts if you really enjoyed these visualizations make sure you come by adele hall learning commons on april 27th from 3 to 5 pm the library is helping organize some visual histories um woven visualizations of texture using yarn and i'm i'm super excited about this i've seen some examples from the past and and this is going to be a really cool activity i'm i'm definitely planning on on swinging by okay so this is what these global warming stripes look like and regional global national regional warming stripes look like what are some other important observed signals observe changes in climate we can think about precipitation changes so this is an image taken from the third national climate assessment uh and what i want to draw your eye to in this figure is that there's a lot more spatial variability here in terms of the green colors which represent an increase in precipitation in terms of percent uh here and the brown regions which is a drying a decrease in precipitation and what they've done here in this climate assessment is separated the united states down into further regions and created these bar graphs here we see the united states average um with each of these bars representing a single decade and each of these different regions so you might be interested in finding a region that's of particular interest to you my eye is drawn of course to midwest where i lived for a a good amount of time and of course the great plains north where i i currently am uh and we see that for several of these regions there has been an increase in precipitation in the last century perhaps a more important thing to look at is a change in heavy precipitation because these extreme precipitation events are of particular interest to human impacts flooding all right signals that really have strong implications for human health and well-being so if we think about these indices for very heavy precipitation we can see that there's also a tendency for there to be an increase in these heavy precipitation events in the observed changes in climate precipitation temperature these are important for agriculture as well i wanted to show you this figure of hardiness zones produced by the national arbor day foundation if there are any uh gardeners in the room i'm sure you're familiar with how important the understanding of the hardiness is right the lower numbers the the cooler colors indicate regions where the the winters are cold and you can't over winter plants um certain plants and what we see between 1990 and 2015 is that these hardiness zones have shifted northward meaning that winters aren't as cold and harsh as they were as have a look at nebraska where in 1990 there was a lot of blue and green and in 2015 it's pretty much all green now right what are some of the other sort of human implications why do we care about these changes that we see in the the climatic record well these are just a couple of news articles i grabbed from the last couple days as i was preparing this talk we've got lake powell's water level plummeting due to the extreme mega drought that's being seen in the southwest that has a fingerprint from anthropogenic climate change climate change has challenges to the outer banks barrier islands um there's a very a lot of economic sort of decisions to be made here he waves at both of earth's poles alarm climate scientists this has just been going on the last several days is very interesting and uh terrifying signals better being seen and of course the ipcc is discussing new reports and new information and suggestions for policy that will be coming out uh in the next couple weeks if you have want to explore more about different observed signals and human implications would highly recommend you check out the traveling exhibit i'm sorry this was really driving me crazy um can i perhaps just use the thank you is that all right i'm sure it was driving some of you crazy as well um i would highly recommend checking out the exhibit on the second floor of the love library we'll be here to the end of the semester called real people real climate real changes it's a traveling exhibit that was put together by the national center for atmospheric research and it digs into some of these ideas a little bit further but what i where i want to go is what are the causes of these observed changes in climate okay right we've seen that there's observational evidence for these changes what's causing them and so i want to start with this image which is a time series of carbon dioxide concentration in parts per million taken at the mauna loa observatory it's a great place to get a good record of well-mixed carbon dioxide in the atmosphere because it's in the middle of the pacific ocean right away from a lot of major sources of carbon dioxide and what we can see in this figure is since they've started taking records back in 1958 nice long-term record carbon dioxide concentration has increased from around 315 parts per million all the way up to over 420 this is a really large increase in carbon dioxide and this is driven by burning of fossil fuels anthropogenic causes you burn fossil fuels for energy and greenhouse gases including carbon dioxide are emitted so what does this have to do with temperature uh the third national climate assessment put together this this cool figure where we see a this solid curve is our carbon dioxide concentration placed on top of the changes in global temperature and so you can probably see that there is some sort of similarity in these two signals and you might be thinking well well what if that's just a coincidence so in order to really connect anthropogenic human emissions of co2 to temperature change we can run climate simulations and force them with just natural forcings and different human forcing so that's what's shown in this figure we have global surface temperature change since 19 sorry 1850 on the y-axis and time on the x-axis and the observations you've already seen this black curve a couple times in this talk we see this increase of around one degree celsius since the beginning of this record and what's shown in the colors are model simulations of the global temperature with different forcings applied so this green curve here only has forcings from natural causes forcings like volcanic activity changes in solar activity sunspots etc right so when we look at the green curve we aren't able to reproduce the observed record we need to add human forcings from human activity into our global climate models if we want to reproduce the observed temperature record and this includes the emission of greenhouse gases which are shown in the red here this has a tendency to warm the global climate and aerosols particles which are also created during the combustion part process which reflect energy and result in a cooling of the climate system and if we put all of these things together natural causes and human we end up being able to reproduce well the observed warming pattern we can use these simulations to think about future projections of climate so this figure here shows temperature global surface temperature on the y-axis and projecting these temperature changes into the future for several different emission scenarios right what our choices we make now in terms of how much carbon we're going to put into the atmosphere are going to have implications for how much warmer the climate system is going to get so if we're able to curb our emissions perhaps we can keep warming to one to two degrees celsius but if we continue to emit at higher very high levels we're thinking more um around more around five uh degrees celsius by the end of the century and but i bet some of you are thinking to yourself well hold up this last couple of slides have relied completely on model simulations why must we rely on computer models well we only have one earth there is no second earth so there's no way for us to you know set up another earth and and say well let's uh let's change the the carbon dioxide concentration in it and see how that planet changes right there's no planet b no secondary there's no way to run controlled experiments the goal of climate modeling is to think about representing the earth system is to think about representing the earth system as accurately as possible these simulations are not earth but the goal is to create simulations that best represent earth so that we can investigate many different climate scenarios so this is what i really want to talk about in this talk what are the fundamental concepts in climate science and how do we use them to build useful models of global and regional climate and i want to start with a very simple model and think about after we build this model you'll be aware of three things that control the equilibrium temperature of a planet the first one is how much solar energy arrives at the planet how much of that energy is reflected back into space and how much of the energy that that planet emits is absorbed by its atmosphere and trapped so the simple model we're going to create is just a simple energy balance model this is a model for the average temperature of the planet so we're thinking about a average over the entire planet which is going to have some sort of surface and a surface temperature t sub s and then we're going to consider the energy coming into this system and the energy leaving the system and we're going to equate them energy in equals energy going out think of this like your bank account right if you have money coming in and money going out and those things are equal your savings doesn't change at all and so in this situation if we have energy in is balanced with energy going out our surface temperature is going to have an equilibrium so what are these sources of energy in for this simple model what's the source of energy that that um that that warms the planet well it's energy from the sun the sun produces a tremendous amount of energy and the planet intercepts some of it and so we're just going to call that f sub s here this is the say energy flux of the sun this value changes if the sun has different amounts of solar activity and outputs more or less energy this number also changes as the orbit of the earth changes and gets closer or further from the sun at a 100 000 year time cycle so of that energy some of it is absorbed by the surface and some of it is reflected back into space this is a satellite image of the earth which shows that there are a lot of climate features which are light and reflective clouds and ice and snow and those aerosols that i was talking about in the earlier figure that are often emitted by combustion and volcanic activity these things reflect incoming solar radiation back into space this is the albedo of the planet so we represented this with a letter a times our solar flux here and the final thing we have to consider in this model is energy that's being emitted by the planet right so some of this energy from the sun is absorbed and warms the surface the surface has a temperature all things that have a temperature emit radiation and it goes to the the the amount of energy that's emitted is proportional to temperature to the fourth power so that's what's represented here and so now we've got these three different um energy fluxes we can do our energy n equals energy out and come up with this equation you don't need to worry about what this equation um says but i wanted to put it here so that you all know that i'm just not making this stuff up we know what the solar flux is we can measure that we can measure what the albedo of the planet is and so we're able to compute the temperature of this system the surface temperature and we get a number of 255 kelvin we like to use kelvin uh in in science right because the absolute sorry sorry the zero point is absolute um but i've also placed the temperatures here in celsius and fahrenheit we have negative 18 degrees celsius and zero degrees fahrenheit so what's the problem here this is this is really cold life on this planet would not exist as we know it um if if this was the temperature so what are we including in this model we didn't include the fact that our planet has an atmosphere so if we enter just a simple slab atmosphere which absorbs all of that outgoing radiation from the surface and then re-emits it to space and back down towards the surface we can do this energy balance again and we find that we have an equilibrium temperature of 303 kelvin or around 85 degrees fahrenheit well this is too hot because it ends up that the atmosphere doesn't absorb all of the outgoing radiation from the surface it only absorbs part of it and if you take that into account then you're able to get much closer to what the observed temperature of the planet is and of course how much of the radiation that's outgoing is observed is absorbed by the atmosphere depends on the constituents of the atmosphere carbon dioxide water vapor or greenhouse gases this is the atmospheric greenhouse effect which causes the surface of the planet to be warmer than it would be if there was no atmosphere so to go back to this idea the three things that control the equilibrium temperature of a planet how much solar energy arrives at the planet our sun spots the orbit of the planet how much of that energy is reflected back into space ice snow clouds these aerosols and then finally how much of the energy that the planet emits is absorbed by the atmosphere entrapped this is our atmospheric greenhouse effect that depends on the composition of the atmosphere so you're probably thinking oh and and this is this is not a new idea right we've been using these simple energy balance models for over a hundred years here's a paper by arenas on the influence of carbonic acid in the air upon the temperature of the ground carbonic acid is our carbon dioxide here um and so this is this is not a new idea and you're probably thinking to yourself well that's great that we have a simple model for the global temperature but the planet doesn't have the same temperature everywhere this is something that that you're probably thinking of well how useful is this model really so let's think about expanding this model and thinking about um spatial variations in temperature so here's a map that shows that the tropics are warmer and the um the the warmer colors and the poles are cooler and the cooler colors so let's see if we can create a simple model that will allow us to reproduce this temperature distribution and so we're just going to think about this temperature distribution latitudinally by thinking about just averaging across the the horizontal direction on this plot here the zonal direction there's a latitudinal plot of energy in and energy out what we see is the energy in there's a lot more energy in in the tropical regions then in the polar regions this is due to the curvature of the earth and energy out has a much flatter curve right it's depending on temperature that t to the fourth relationship so in the tropics there's a lot more energy in and energy out there's an energy surplus here and in the polar regions there's a lot more energy out than energy in we have an energy deficit and if there wasn't anything that was able to rearrange energy on the planet what would end up happening is that the tropics would just get warmer and warmer and warmer and the poles were colder and colder and colder until they were extremely cold and the tropics were extremely warm but fortunately there is energy transport from the tropics to the poles north and south energy transport by atmospheric and oceanic motions this is the general circulation of the atmosphere and ocean and you could spend an entire course uh thinking about the complexities of the general circulation of the planet but what i want us to think about is just a simple sort of transport of energy between latitude and low bands and we can think about breaking the system up into discrete regions right create a bunch of columns here and for each of these columns we're going to consider energy in energy out and transport in the north south direction this is a latitudinally dependent energy balance model and this was a technique that was used in the late 1960s this is one one paper that produced a model like this uh william sellers a global climatic model based on the energy balance of the earth atmosphere system i wanted to show just one of the pages from this paper this is the whole model okay so this is we've gone from one equation to a page of equations and when you use this equation the dots here are the output from this model compared with the line which is observations it reproduces the latitudinal distribution of temperatures really well and at this point you're probably thinking okay well is this much better we now have uh an idea of going from a global to now we've got different latitude bands how can we continue to add complexity to this system what about cool things that like convection and clouds and storms how are these things how might we represent these processes in a model and so i grabbed this image this is over um some islands in indonesia we see clouds and convection upward motion uh there's precipitation i'm sure occurring under some of these um how do we split this sort of system into areas which we can model we can't just take this continuous system and model every particle every little bit of this system we have to think about breaking this domain into some sort of grid just like we just took that latitudinal domain and sliced it into latitude bands we're going to take this horizontal domain and split it into different boxes and what you'll notice is that i've outlined uh regions of around 100 kilometers this is around the resolution of um current climate models global models and what you'll notice is that there's a lot of stuff that is happening at a smaller resolution than that hundred kilometer grid box right some of these boxes have um you know are all ocean but some of them have some land and some ocean right we've got some that have these small lower level clouds some of them have a large amount of convection but it's only confined to half of the how do we think about taking these complex things which are happening at scales smaller than the grid that we're modeling and represent them properly these are what's known as our parameterizations in models and a useful tool for developing them and understanding how how they represent different processes in the climate system is a single column model so we're just going to think about taking one of these grid boxes here i've outlined this one in yellow and creating a vertical column of boxes this is a single column model consider the the globe here and then taking just a region and just one place in that region and building a vertical model um for for the that um for the atmosphere this was a a very popular tool in the early stages of model development this is a very famous paper by manabe and weatherhall where they use a single column model and they apply various changes which i've outlined in red here changing the solar constant changing carbon dioxide concentrations ozone concentrations and cloudiness and why do you think they chose these things to change in the model these are the three knobs that we discovered were important forcing for important drivers of climate in our energy balance model right we've got the solar constant this is energy in from the sun we've got cloudiness which has to do with that albedo the reflection of of energy back into space and we've got constituents such as co2 ozone which are important for the greenhouse effect and what they were able to show is changing is how vertical temperature profiles so here we've got temperature along the x-axis and height along the y-axis how these temperature profiles changed when you were to alter these different drivers of um of of climate and this one here is for carbon dioxide with the the triangle line here with is 150 parts per million and the circles 600 and we see cooling in the stratosphere warming in the troposphere and that these signals were much stronger when you were able to take moisture feedbacks into account and these is a very simple model right that has that energy balance but also some simple representation of convection and for the work that uh manabe and and others did in the 60s for the physical for developing physical modeling of earth's climate quantifying variability and reliably predicting global warming he was awarded with with other researchers the nobel prize in physics just last year this is really important uh work that was done so we've gone from a global model for climate a latitudinal model for climate a very local one a single column model for climate how do we go back to a full global model which is perhaps more complicated well if you can imagine a single column you might be able to imagine lots and lots of columns that are all next to each other so our global earth system model the atmospheric component is going to consist of a lot of these columns right which are able to exchange uh energy and and mass in the vertical direction in the horizontal direction turning the earth into a gridded space um and so there so so we've gone from from something that is well yeah kind of simple to something that's much more complex here are all the different things not all not all of them this is a sum of the important things that need to be considered when you're developing a global earth system model we no longer call them climate models because we're trying to capture all of the important components of the earth system for example the ocean circulation deep ocean circulation ocean ice snow and aspects of the biosphere which are important for for climate convective clouds stratiform clouds these aerosols right in the stratosphere in the troposphere that i was talking about fluxes between all these different components and of course the constituents which are important for radiation and that forcing that we were just talking about water vapor co2 greenhouse gases and so here's a schematic so what does this actually look like when you you put together a climate model here is the schematic for the community earth system model this is the model that's developed at ncar um and a lot of scientists have been working for a long time on developing this model here are just all the different components in it we have atmosphere sea ice land ice the ocean river runoff land and of course biogeochemistry the importance of life and all these are coupled together this code is or at least it was as of several years ago 1.5 million lines of code and i know it is many more lines now so we went from a single equation to a page of equations so now we're talking about a model which is millions of lines of code in order to try to represent all the processes in the earth system which are important for understanding past present and future climate so you're probably thinking to yourself well this is probably an extremely computationally expensive thing to run and you would be correct this is the machine that's being used at ncar right now this is cheyenne it's a computer that's able to do 5.34 petaflops this is is fun to say what is a petaflop well a flop is a floating point operation per second so and and peta is um a quadra 10 to the 15th a quadrillion so 5.34 quadrillion calculations per second in 2016 when it was put online it was the 20th most powerful super computer in the world and currently it's about to be replaced by an even stronger machine known as an even faster machine known as derecho which is around just under 20 petaflops an incredible amount of computing power we are fortunate here at unl to have the holland computing center which also has some very strong high performance computing equipment the machine here is 1.2 1 petaflops which is less but it's nothing to sneeze at this is a really powerful resource and i've run simulations on on this machine and if you're interested in high performance commuting would highly recommend checking uh out their their different courses and um and and figure out ways to to learn more about about this so where are these earth system models being developed and run this figure here shows all the different modeling groups which have contributed simulations to the coupled model inner comparison project all these different places are developing and running their own climate simulations just like the csm but they've used different techniques to represent these um subgrid scale processes and large-scale dynamics but they run these simulations all with the same sort of experiment the same type of forcing so then they can be compared and this is important because like i said none of these simulations are earth they're all earth-like planets they're all the the our attempt to create a simulation which as close to earth as possible so instead of relying on just one it's important for us to have a large number of these simulations to think about what might what might occur in the future so what are these what does this ensemble of simulations show for the future one way we can think about this is by breaking the earth down into different regions this is new in the most recent ipcc report uh just taking the earth and turning it into a bunch of regions and then thinking about how many of those regions have high or medium confidence in the change and increase or decrease in different uh climatic drivers that we're interested in for example mean surface temperature extreme heat heavy precipitation and flooding hydrological drought and so what we can see in this chart over here is that these ones which are associated with temperature there are a lot more regions with high or medium confidence in an increase or decrease in our future projections than for some of these which are more focused on precipitation for example mean precipitation hydrological drought agricultural ecological drought the there's a lot more uncertainty in these simulations in terms of precipitation change so what do i mean by uncertainty because this is what my research is really about is understanding regional uncertainty and projections of climate um and so here's a figure from a recent paper showing the ensemble mean precipitation change for a large number of these cmip models from the end of this century minus a historical period the green colors show where precipitation is expected to increase and the brown colors show where it's expected to decrease but this this hatching that goes across here indicates regions where models agree where the um the sign of the change in many of these simulations is the same and so i went to the the cmap archive and grabbed a bunch of these simulations and just for this region across the central part of the united states and and mexico i just plotted a couple of profiles of these individual model ensembles so that's what's being shown from 20 degrees to 50 degrees north along this axis the just the change in precipitation at the end of the century and what we can see is that in the southern part of the domain there is this decrease in precipitation right these brown colors here and the hatching which shows that the models are in good agreement and in the northern part we have an increase in precipitation and hatching which shows that most of the models are in agreement but we have a lot of disagreement in terms of where the models are saying there might be an increase or decrease in this transitionary region around 30 degrees north right where there's not a lot of hash marks uh in this plot and so the question is well if you have if you're growing crops in that region and you're interested in what the precipitation change might be in the next few decades how do we think about understanding this uncertainty and this is a really challenging problem because precipitation change is forced by a lot of different things in reality it can be forced by changes in large-scale circulation patterns changes in regional circulation patterns different boundary conditions land usage change and then of course the local physics how clouds um and convection change and in the model we have all these things this is i put commas here instead of plus because this is all very non-linear and these are all interacting with each other in the model we have the same things but we have slight errors and biases in all these fields so to understand model precipitation change we have to consider all of these different forcings for regional precipitation change and in my research i like to use a large variety of model complexities to think about this problem ranging from single column simulations to two-dimensional simulations even using aquaplanets basically taking a global model and removing all land land is a source of complexity so if you can remove some complexity from a simulation it might be easier to understand different drivers of these regional precipitation changes all the way up to using global climate models to run exp design and run experiments to think about controls on local precipitation and i want to show you just one example from my research this is using a two-dimensional model to understand drivers of regional climate one of the regions of research that i'm very interested in is west african climate here we've got a satellite image from august of 20 2006 and this is during the the height of the monsoon season we can see the saharan desert here and of course green across the sahel this boundary the lower boundary of the saharan desert where precipitation falls for three months a year and the the people who live in this region are highly dependent on that monsoonal precipitation so a major question is how is that precipitation going to change as climate changes and it's a complicated region the precipitation of this region is impacted by processes across the saharan a saren desert a low-level pattern a low-level circula a low pressure circulation pattern which develops due to the hot temperatures there regional circulations driven by gradients in sea surface temperature and the temperature across the guinean coast large scale circulations land surface properties it's a very complicated region of the world so how do we think about understanding how precipitation might change one approach has been to create a two-dimensional model so this is thinking about that latitudinally dependent energy model but just for this region that goes across west africa so we're just taking a a north-south um and and vertical transect across the region and we're going to use that and force it with these different large-scale and regional circulation patterns to see how changing each of these individually and then all together changes precipitation in the region and so there's a lot going on this is this is a plot that i actually took from one of my publications so i'm going to slowly walk you through don't freak out okay these plots are showing precipitation change with increased sea surface temperatures so here we have these latitudes from 10 degrees south to 25 degrees north taking that north-south transect across west africa and on the vert the y-axis here we have precipitation this black contour shows precipitation for full global climate simulations and we see what we expect right that precipitation for the month of august is heavy across the the guinean coast and soho region tapers off here at the edge of the sahara however if we warm sea surface temperatures everywhere by 40 degrees celsius that's what's shown in the blue curve and what we see in that precipitation pattern is a decrease in precipitation and a shift of precipitation towards the south so this is a really interesting signal what makes precipitation shift to the south and decrease and so with our two-dimensional model we were able to separate out regional changes in the circulation and large-scale changes in the circulation and apply them separately and together so that's what's shown in the second plot here we have latitude along the x-axis in the same manner and precipitation along the y-axis our control simulation is shown in black here it produces a similar a similar pattern in precipitation as shown in these full three-dimensional models when we apply just a regional forcing to this model by just changing sea surface temperatures and seeing what circulation changes due to that we get a southward shift in the precipitation but also an increase in the precipitation when we only apply large scale forcing without changing any of the regional circulation pattern we're able to see a decrease in the precipitation but not that southward shift in the blue line here it's only when we combine the regional and large scale forcings together we're able to reproduce the signal that's seen in the full three-dimension uh 3d model shown in this orange line here and so this gives us some information about what is causing the southward shift in the precipitation band and what is causing the decrease it's two different things the regional forcing is really responsible for the southward shift and the large scale forcing is responsible for that decrease and in this paper we were able to go through and think about more dynamical mechanisms in terms of moisture transport and temperature transport that were associated with these two different drivers of the regional climate to really understand what processes were resulting in this very interesting signal we see in the full 3d model so i hope this has given you an idea of how models of varying complexity can be useful for understanding regional climate i just wanted to mention one other type of simulation which i'm getting into this is something that is a little bit new for me but i'm thinking about regional climate modeling in terms of running regional climate models um these are models which are only run for a regional domain and in this figure we see some global climate model output this is our standard 100 kilometer output from the the simulations i was discussing earlier these are global simulations but this other figure here on the right shows uh the output from a simulation which is just for the central u.s region these simulations were actually done by an undergraduate student ali berry who worked with me on a ucare project last summer and what you can see is that these have a much higher resolution and you can do different things about how we force them from the boundary conditions to really think about running innovative experiments to increase understanding of climate dynamics and understand the projection of uncertainty into the future they're also useful for creating high resolution outputs which are useful for driving impact models flooding and agriculture so this is a new direction of my research which i'm very excited about there's a lot of knowledge here at unl about regional climate modeling so i'm i'm very pleased to be here and and starting to work on projects like this so in summary hopefully what you've gotten from this talk is an appreciation for for some knowledge and appreciation about how climate modelers think about developing models from the simplest models to the most complex and the importance of understanding the differences between global and regional climate and have come away with the idea that computer models are useful tools for understanding changes in global and regional climate after all we only have one planet to work with here right so we need to use these simulations and we need to consider how the choices we are making are going to end up with climates of the future which someone is going to have to deal with and i know something i didn't mention in this talk is thinking about solutions uh and approaches to solving this idea of of climate change but i wanted to to advertise a fortunately there is a um what is this a virtual event that's occurring next week on march 30th for the solve climate by 2030 organization on campus and would highly recommend checking that out if you're interested in thinking about solutions to climate change and so if you're a student or a member of the community and you have some further questions about climate um modeling climate change or interested in taking courses or doing research about climate change feel free to email me uh contact me i'd be glad to answer your questions or or talk about different opportunities that might be available so with that i'd like to thank you for your time and would be glad to take questions but if there's a question i'll bring the mic to you so we can record the question as well don't be shy i enjoyed the talk ross thanks um so it seems like i read that when people are trying to do shorter range like extending the standard weather forecast from you know the six to seven days to two weeks to one month or whatever there is is there a in terms of computational power are there commonalities to weather forecasting and the line of long range projections that you're making yeah so so in terms of thinking about what computationally is needed for these shorter scale for shorter scale forecasts um and and longer scale they are the the fundamentals are the same but there are a lot of differences in terms of how these models are set up what really needs to be considered if you want a really good forecast of weather or even a seasonal forecast compared to these longer time scale the time scale has a lot to do with it these to run these simulations on a climatological time scale for hundreds of years this is when you start getting into a lot of computational expense so even though weather models can often be run at these higher simul higher resolutions it's because they're being done for much shorter periods that's a great question thank you um you did a very good job and also my question is if us as humans continue to do the same things that we have been doing how do you see the conclusion ending okay well that's um yeah so it is true that it can be rather depressing being a climate scientist there's a lot of singles that are extremely troubling um but there's also a lot of human ingenuity and and resilience so it's it's a hard question it depends on whether i'm feeling being an optimist or a pessimist in the day but but ultimately we need to think about how to stop emitting carbon dioxide and greenhouse gases into the atmosphere and think about developing technologies to remove greenhouse gases right people come up to me and say oh you're a climate scientist you're going to solve climate change no that's that's not really my job my job is to think about understanding how that climate change is going to impact people where i where i have hope and i know that there's a lot of debate and discussion about this but that perhaps technology might be able to lend a hand but uh we've been saying this for a long time now so thank you for that question and on that note thank you again for coming out tonight really i really appreciate your presence and if you have other questions feel free to email me or come up and ask thanks thank you again ross

Channel: NSF NCAR & UCAR Science Education

Views: 719

Keywords: atmosphere, Earth science, STEM, science research, education, climate, climate change, sun, weather, computers, UCAR, NCAR, Boulder, supercomputing, NCAR Explorer Series, University of Nebraska, Traveling Climate Exhibit

Id: KkuANWazqR4

Length: 56min 25sec (3385 seconds)

Published: Mon Mar 28 2022