MEL: All right, good morning, everybody; my name is Mel Kunkel; I’m a senior atmospheric scientist for the Idaho Power Company here in Boise, and over the last day and a half, we’ve seen a lot of really great presentations on utilization; of everything from containers, Unix, Python, how you get started in that, to some of the bigger picture presentations that cover data management all the way up to how NSF looks at projects.
My portion today is to give you a little bit of an idea from an application point of view. How do we use some of the data from high-performance computing systems?
[Image of service areas in Idaho with kW amounts those areas consume: Hells Canyon – 392MW, Oxbow – 190 MW, Brownlee – 675 MW, Cascade – 12 MW, Swan Falls – 27 MW, C.J. Strike – 83 MW, Bliss – 75 MW, Lower Malad – 14 MW, Upper Malad – 8 MW, Lower Salmon – 13 MW, Upper Salmon – 35 MW, Thousand Springs – 7 MW, Clear Lake – 3 MW, Shoshone Fails – 15 MW, Twin Falls – 53 MW, Milner – 59 MW, American Falls – 92 MW]
So today, I will talk about Idaho Power, our cloud seeding program, and how, say, 610,000 customers but, in reality, around 200 or 2.5 million people that we service. This is because those individual customers may have anywhere from one person to 500 people that are attached to it, and as part of that, we run our operations with 17 different hydro dams as well as thermal units such as gas and coal plants. One of the unique things about us is that we were one of the first companies to come out and issue a clean energy mandate. Meaning that by 2035 we expect to be a hundred percent clean energy going away from coal and some of the other aspects of that.
[Donut chart of Idaho’s 2022 energy mix: Hydroelectric – 31.1%, Wind – 10.0%, Solar – 3.8%, (Geothermal, Biomass & Other) – 2.3%, Coal – 19.9%, Natural Gas – 12.6%, Market Purchases – 20.3%]
This shows last year’s mix of energy, and you’ll notice that we had a little over 30% hydroelectric. We’re meant to be a little over 50% hydroelectric in our energy mix, but everybody in this area knows the last couple of years have been kind of a drought. So we wound up going into the market and buying electricity to cover some of the missing hydroelectricity we typically have.
[Donut chart of national average energy mix: Hydroelectric – 6%, non-hydro renewables – 13%, Nuclear – 19%, Coal – 22%, Natural Gas – 38%, Other – 2%]
When you compare this to the national average, this is what it looks like. You can see hydroelectric is about 6% and when you look at ours, we stand at around 50%. You can see how reliant we are on water and on, in this case, very specifically, snow.
So today, you’ll do a quick overlook of what cloud seeding is, how it’s done, and why we do it. Then we’ll look at a research project called SNOWIE that was conducted here in Idaho. Then we’ll move into some of the modeling and stuff. Those sections will be on benefits and other topics I’ve moved to the far end, and if we have time, we’ll cover that.
Let’s get started; so what is cloud seeding? Basically, cloud seeding is, for a lack of better words, it’s weather modification to produce more precipitation of one form or another, and there are two types. These include cold clouds, which are dependent on the abundance of super-cool liquid water, and I’ll explain that in a minute. Then there’s a warm cloud type which is basically the collision of small droplets to form bigger droplets. Cloud seeding helps to assist those processes and is defined as a mechanism to either produce raindrops or produce more snowfall.
The term cloud seeding is used across a large area of things, but it’s been used specifically for fog… to reduce it at airports, different things like that, to accomplish this a team comes in, they use a ground-based item, and through either dry ice or a different formats, they’re able to reduce the amount of fog at the airport to allow for greater aviation use. Health suppression is widely used in the Midwest and up in Canada, and the whole purpose there is to get those big thunderstorms that come through to not be so devastating. At times they produce hail that is devastating by being anywhere from golf ball size to softball size, and it can have a billion dollars of damage out of one storm, mostly by taking out crops. Interestingly enough most of the health depression programs that are run, whether in the U.S. or in Canada, are funded by insurance companies… because they’ve determined that it’s much cheaper to spend a million dollars on a cloud scene than to pay one or two big damages out of a thunderstorm in a year. Without intervention, that could equal up, in some cases, over two billion dollars.
Then we have a couple of different other ones, but the key portion is basically snowpack enhancement, and that’s what Idaho Power does because, as I showed earlier, we have many hydro dams. That’s what the backbone of our generation Fleet is. If we can produce more snow in the mountains, it lasts longer throughout the year, we have more generation through hydropower, which is a very low carbon unit, and we have the side benefit that it maintains the base flows in our river systems throughout the year so that they don’t drop so low that we have warming conditions that kill fish and impact other species in the summer.
[Image of atmospheric precipitation monitor on the new slide]
All right, so supercooled liquid water is, basically, water that exists in the atmosphere that’s not frozen but can be well below 32 degrees. We all think freezing of water occurs at 32 degrees, and it can, but that’s typically not pure water; that’s water that has little dust particles and stuff in it, and those impurities make it freeze quicker. We’ve been able to monitor in Idaho and in many other places liquid water remaining in the atmosphere at minus 20 degrees, and you’re like, “Well, how does that work”? Well, it’s just a natural process if it’s really pure water or water vapor, it can continue to stay at that level until that minus 20 degrees. Unless something interacts with it, that interaction is typically salts, dust, or something along that line. This can occur naturally either through dust storms, interaction at the coast where you get salt up into the atmosphere, and what cloud seeding does is it adds extra particles.
[New slide: Cold Cloud Seeding Method]
It’s done in many different ways, but for us, we do cold cloud, which is considered glaciogenic. You can use several different methods to help promote that growth, and part of that is you can use silver iodide, which is what we use; you can use dry ice or liquid propane. Both dry ice and liquid propane are ways to flash-freeze the moisture in the air. Silver iodide in the form of vapor attracts moisture to start forming snowflakes.
[New Slide: Diagram showing a microscopic dust particle in the shape of a circle and forming around that circle in the next step of development is a hexagon. After the shape grows, which can occur at different rates, branches come off the hexagon at its corners, forming lines that connect to other hexagons. This structure is now referred to as a snow crystal.]
So if we look at a picture of how snow crystals typically form, you have that condensation nuclei, whether that’s dust, salt, RK silver iodide, or water, that starts to attract to it… as it moves through the air, the vapor pressure around that brings more moisture to it. It begins to grow and, at certain points, develops little crystal type of shapes, and then they continue to grow through time. This can either lead to the snow flack falling or continuing down through the atmosphere colliding with others which will cause it to break up, and each one of those individual little crystals will continue to form more snowflakes. At some point, they get to where they’re large enough to fall out of that atmosphere.
[Next slide: Image of Remote Cloud Seeding Generator top to bottom – burn head, temperature probe, ignition coil, valve box, tower, satellite communication, solar panel, computer box, nitrogen, solution tanks, work platform, batteries, and propane tanks in the background]
So we do two types of mechanisms for cloud seeding. We do ground-based mechanisms with a generator type of system like the one that we have here. Basically, it has propane, and has a burner up in the top portion if you look in the top area there, you see a little orangish dot that’s basically just a propane flame. We have a pressurized system with nitrogen that pushes the silver iodide up to the top of that flame, and then it goes through an atomizer, and then it burns as vapor in that flame. So what we have here is we have a couple of things; we locate these generators typically up in the higher elevations on Hillside. This allows wind flow to come up those Hills, and that helps to produce an uplift to carry the silver iodide up, and then we get a thermal lift out of the flame itself. Those typically are running between 500 and 700 degrees Celsius. So quite hot, so we can get a lot of lift up there.
[Next slide: Image of modified aircraft that has a lit flair on the left wing]
The other side is to do an Airborne, which allows a lot of flexibility to move the aircraft where we need it to get to the best place to cloud seed. This aircraft has been modified in two different locations. On the wing tips, there are canisters that hold flares that burn. We have a picture of one that shows a burning flare, and this is just an illustration. When they’re actually burning the silver iodide, it’s colorless, you don’t see anything but they used some road flare type of stuff. So you could actually see it, allowing you to get a feel of how that worked, and then on the bottom, there are more canisters that can eject little flares going straight down. We do not operate these aircraft; we contract with a company that runs them. They work worldwide. So they’re experts in cloud seeding. Atmospheric scientists such as myself help determine where they fly; we interact with the aircraft, provide them fly to safety type of information, and ensure that they’re seeding in the most efficient area and way.
[Next slide, 5-step process: 1 Cloud – air flows over the mountain, forming a clod that may contain supercooled liquid water, 2 Release – Silver iodide particles are released by an aircraft or ground-based generator, 3 Dispersion – Silver iodide particles reach the targeted cloud (airplane in image dropping silver iodide), 4 Ice – The silver iodide forms ice crystals, 5 Snow – The ice crystals grow at the expense of supercooled water and become large enough to fall and create snow, and lastly extra information – Ground-based seeding has additional criteria that impact dispersion (wind direction, atmospheric stability)]
So, how does cloud seeding work? Basically, clouds form around mountains in different areas as the wind comes up and over. In effect, the air is lifted, condenses, and as it goes up it cools; forming a cloud. This cloud then moves across the mountaintops, and what you typically get is at a certain point, saturated enough clouds that lead it to rain or snow. The silver iodide helps to start this process a started a bit early, so we cloud seed with an aircraft or one of the generators. When doing so it puts the silver iodide into the atmosphere, it starts to build those snowflakes just a little bit earlier than it would and then allows them to fall out sooner or continue on down through the atmosphere. During this process, they merge together and then the ice forms and the snow starts to develop or starts to drop out. The silver iodide works starting around minus five degrees Celsius. This process becomes very efficient between -6 and -8. Efficiency remains until about -15 and even continues to 20, but the efficiency level drops off after -15. The two key portions of that are the temperature for the silver iodide to nucleate and the availability of that super cool liquid water.
[Next slide, animation: An animation of two generators, on a mountain top, producing silver iodine, below two clouds, and a plane flying overhead deploying silver iodine. This leads to the clouds expanding and then starting to snow. The mountain then gets covered in snow, and forms rivers when heated to liquid form.]
Now this is an animation that I hope it works, but basically, this would be a picture of a region, like around Boise in the fall. All right, we either have a generator that starts to emanate silver iodized or an aircraft that comes across. Silver iodide enhances the development of snowflakes. It falls into the area, develops a pack on the mountains, then as time goes on in the summer, it starts to melt, and goes into the reservoirs. As we get in the summer the snow’s melted out, we start to need irrigation, it starts to fill into the farmland, and then we start the whole process again.
[Went to next slide – a US state map showing which states cloud seed: cold season(Idaho, Wyoming, California, Nevada, Utah, and Colorado), warm season(North Dakota, Texas, Alberta (Canada)), and fog suppression(Oregon)]
So it’s pretty basic but an interesting fact. Throughout Idaho or throughout the western United States cloud seeding is done in a number of ways. In this picture, the blue indicates where we do cold cloud seating for snowpack, and the green is either rain enhancement or, the hail suppression type of cell. Not only is it done in the Western United States in Canada, but it’s also done in 35 other countries throughout the world. That includes everyone from very large programs in Australia, and Chile to, India, and China. It’s fairly widespread and growing in detail.
[Went to next slide: Idaho Power’s Cloud Seeding History]
Now I’m not going to go through this whole slide because you guys really don’t care, but basically, Idaho Power started investigating Cloud City in 1993 based on a shareholder because we were in a very severe drought, he was at one of the meetings, and he said look, “California has been doing public seating since the 50s, why are we not doing it”? We spent 10 years developing a program, and it kicked off in the Payette River Basin in 2003 and has continued to grow across the Southern Idaho area to the point that now where it’s a collaborative program where it includes the state of Idaho and it includes nearly every Irrigation District and water district in Southern Idaho as well as many of the conservation districts. So it spread and is doing quite well. Due to this outcome, we continue operations at this time.
[Went to next slide: SNOWIE meaning Seeded & Natural Orographic Wintertime clouds: the Idaho Experiement]
Snowie, now, this is the fun portion. Snowie was an NSF-funded project that was done in the Payette River Basin here in 2017 and designed for January through March. The goal was to look at the processes that occur in wintertime snow development and what occurs when you do cloud seeding. It was a fairly large effort, there were 4 PIs, 11 co-scientists, and then there were approximately 55 grad students at the masters and Ph.D. levels. We’ve now had 25 Ph.D. students that graduated with their dissertations based upon Snowie. A lot of collaborative effort between a number of universities. Boise State participated in that. We had Sean Benner and his crew on the ground collecting snow samples and analyzing those in his Laboratory.
[Next slide: two Doppler on Wheels Radar systems with an image showing range – 20 km range rings from PI, first 20km DOW pack, and second 20km ring is DOW Snow.]
All right, so how this works out, it’s a little bit difficult to see, but if you look on the right-hand side, there’s a picture of the Payette River Basin, there are concentric purple circles and a couple of dots, and those are Doppleron Wheels Radar systems. So if you’ve ever watched The Weather Channel and they’re out chasing tornadoes, and they’ve got this big radar set up. These are the exact same ones. They came in and set up in October before it really started to get… snowing in the area. The project was designed to go through the end of March, and the researchers that came in confidently told us that we would complete the research project by April 15th, they would move these to a project that was starting April 30th in the Midwest, and we told them that wouldn’t happen… and they were very confident and told us they would have no problem, and I think this is a key thing for future researchers anybody that’s developing projects. It’s beneficial to look to take the time to listen to your local people. They may not be researchers, but they live it.
[Next slide: an image of a snowed-in Doppler on Wheels Radar system.]
So every time they went up there this is what they saw, and they spent literally 10 between 5 and 10 hours a day digging these out
[Next slide: an image of a partially snowed-in Doppler on Wheels Radar system and a person shoveling snow off the system.]
so that we could run these machines every time we wanted to do a project. What you don’t see though but right over its head in the very back there’s a little black straight line. That’s their porta potty, so you know they were up there for 24 hours doing some digging to get there and they had to continue to do it through the time. They moved these things out on June 12th… two months after they expected to.
[Next slide: an image of a map showcasing two connected redlines and a couple of locations. These include – 4AW, NASA1 Radiometer/SLW Sonders(yellow pin), PJ disdrometer (yellow pin), DOW Packm DOW Snow, SB disdrometer (yellow pin), PCASP NCAR MRR (yellow pin), NCAR Radiometer (yellow pin), CU MRR (yellow pin), Crouch, WMI Radiometer (yellow pin), NASA2 Radio meter (yellow pin), 4AE, and Lowman]
To give you an idea of how the project went, we utilized an aircraft for seeding; we had a research aircraft out of the University of Wyoming, the research aircraft had profiling radars that shot both up and down and lidar, which gave us both very precise location and elevation, but it also has the capability of being able to measure some atmospheric conditions associated with moisture along with the radar. If we look at the picture on the right-hand side of this, you’ll see that line right through there, and generally, what we would expect is, in this case, with all of these types of instruments shown by the yellow pins. Everything from weather instruments to profiling instruments, it was one of the most highly instrumented river basins in the world for about three months… and the aircraft would fly parallel with the wind flow, so in this case that’s being shown up here, they would fly up and down on that red line to be able to capture what’s happening in the atmosphere to get a very detailed 3D type of picture that includes everything from precipitation moisture, temperature humidities, and movement which is really very important.
[NCAR airborne seeding simulator – graph of longitude points showing Agl Number Path (m-2) through color. White is at 1, and red is labeled as 1E10. The shape the colors make is a circular object with a red “M.” The colors then go from white to red, leading into the “M” shape.]
Now, we fly the aircraft perpendicular to the wind, so if the winds coming from the West, we fly a north-south track, and the goal is that wind is going to take that silver iodide the seeding material, and carry it and distribute it over the area that we’re interested in seeding. In this case, the pay at River Basin and hypothetically from a model, when you simulate, it is kind of what we were hoping to see. The concentrations of silver iodide would leave the aircraft as it was going up and down that line, and that line would move down and start to spread out and disperse as it was taken up by the available moisture.
[Went to next slide: circle of green, blue, and purple specks and a yellow line labeled track 2B at the middle bottom of the circle.]
Now this event you can kind of see there’s a little yellow line right there that comes up from the bottom goes and then goes towards the kind of Northwest comes back down it loops around and starts back, and then there’s a red dot. So at this time frame, that’s where the aircraft is at. The research aircraft had already been flying for about 30 minutes; they went up and down and up and down to get a baseline. What are the conditions like right now before we do anything?
[Continued going through slides]
So if I click this, you can see that there was a little bit of movement of those Blues, which was natural precipitation. The aircraft went up to the top, and they started back down;
[Continued going through slides]
You can see over time that this is occurring. Now when they did this, they did two types of seating. I told you earlier we had the wingtip ones that are continuously burning, and then we have the ones that drop, and they burn for a certain length of time, but they fall straight down. The wing-tip one stays with the aircraft; we started this process, we were doing both of them, then at a certain point, they stopped doing the wingtip ones and only went to dropping flares every 30 seconds, and then at a certain point they came back and started doing the continuous flares again. So right about this time, we’ve been up there for a little bit down by the aircraft just kind of the northeast of it, you’re starting to see just a few little instances of precipitation developing. We’re sitting there in our operation center watching this; I’ve got about six researchers that are senior researchers at incar or national centers for atmospheric research, the University of Madison, Wyoming, and a bunch of others. These guys have been researching cloud seeding for most of their lives since they did their dissertations, and at this point, they were getting excited. So you’re you know you’re talking old guys like me 60 65 and they’re literally up jumping on their chairs because this had never been recorded.
[Continued going through slides]
So we’re watching it, and at this point, you’re starting to see those lines develop as we had theorized in the modeling.
[Continued going through slides]
Now you can really see the development of those lines and those develop and about here is where we change to just dropping the flares
[Continued going through slides]
and if you start noticing there’s individual development or plumes of snowflakes starting
[Continued going through slides]
and I will say that there was a poor Master’s student at the University of Wyoming. It’s been about three months calculating based upon the aircraft speed, the time, and when they were released that these, in fact, were developed by the objectable flares it was going
[Continued going through slides]
and then we went back to the burning place ones and they continue, and then we stopped.
[Went to next slide: animation of previous slides]
You can see the aircraft is gone now and then as they proceed through the atmosphere coming down, they moved across the river basin, and in real time it’s a little bit better. The unique thing about this was, we were able to capture it with the radars here, which were those Doppler on wheels that we showed, but we have the aircraft going through with the profiling radars and the lidar. So they are capturing it from a separate point of view, and we had Sean Benner’s crew on the ground collecting snow that was able to verify that the silver iodide that we released was in the snow that occurred at the sites they were at. So it was the first time it’s ever been recorded to that extent. So right now, I think there are 20-something peer-reviewed papers out of this and a whole bunch of dissertations. It’s continuing to the point this originally was designed as a three-year NSF-funded project; it’s come back, NSF funded it for another three years because it was so much data collected that there’s just continuing research to be done.
[Went to next slide: Atmospheric Sciences and Cloud Seeding]
So that was kind of the cloud-seeding. Some pretty visible evidence that it at least produces snow. Now we wanted to kind of tie it back into what we’re doing here. Atmospheric sciences and cloud seeding and how research Computing impacts that.
[Went to next slide – two layers of grided planet with a physical processes in a model: Horizontal gird (latitude-longitude), vertical grid (height or pressure). The physical model includes the atmosphere(snow and rain over a continent), momentum(going up from the edge of a mixed-layer ocean of water), heat(going up from the same body of water), water(going up from the same body of water), sea ice(creating terrestrial radiation), solar radiation(being absorbed by the mixed layer ocean), and an advection (pointing in up-down-right-left)]
So nearly everyone has a big idea of what atmospheric science is and how we model the weather, but you know, really what it is, is a whole bunch of gridded models that cover the world, and those grids can be anywhere from 500 miles to being centimeters across. Depending on how much computing you want to do and what each one of those little blocks does is details of all the physical processes that are occurring, and that includes interaction with the hydrology on the bottom, of the soil, to the upper atmosphere, and everything around that. For temperatures, moisture motion,
[Went to next slide – a grided planet with sections reaching to the atmosphere and labels: Vertical exchange between levels & In the atmospheric column(three blocks down of single grid section lifted), at the surface ground temperature, water and energy fluxes, horizontal exchange between columns on three by three git reaching into the atmosphere(time step ~ 30 minutes & Grid spacing ~ 3 by 3 degrees)]
and when we look at it, we’re modeling each one of those little Columns of air based on that grid, and we always talk about utilizing high-resolution models because it’s really important, and people go. Why?
[Went to next slide – map showing wind farms and RUC40(low spatial resolution public data in 40 km): Benson Creek(wind farm), Durbin Creek(wind farm), Jet Creek(wind farm), Prospector(Wind farm), and three points of RUC40 starting from top left, bottom left, and bottom right.]
Well, this is a picture; the green is where we have some wind farms that we take a generation from. These little blue dots that are up here, and this is the Snake River just past the Horseshoe Bend area over in Oregon. So if you would be following the interstate if you went just past that parade kind of see at the bottom. North is to the top of typical east-west and south to the bottom, and the blue is a lower resolution called The Rock Rapid update cycle model. It’s 40kilometers in distance. So these little blue dots are where the center of each one of those grid sets.
[Went to next slide but kept original map info – a slanted to the left grid with blue lines was placed on the map.]
So the squares are kind of where those grids represent. So you have, for example, if you were up in that top right-hand corner, you see that the elevation of the Snake River is a little over 2,000 feet The Mountaintop where that Point’s at is a little over 7,000 feet, so five thousand feet difference and that one grid point is supposed to explain the weather in that entire grid. virtually impossible if you think about it. It’s very similar to if we had a grid Point right here and we described the events that were occurring up on Bogus Basin. We know they’re different I mean, they got 148 inches of snow up there; we’ve got, thankfully, nothing. So you can see that that would be tough to use to determine what’s going to happen.
[Went to next slide but kept original map info – red dots placed in a grid with 1.8 km spacing from each other covering the entire map are indicating high spatial resolution IPC data.]
You look at high-resolution modeling like the WRFs that we run on Bora, and I’ll explain what the WRF is. This is where all the grid points are. So if I’m looking at those same little agreed dots to explain what the generation is there. Now I have a representative spot that’s 1.8 kilometers from side to side, nearly on top of each. Much more likely to be able to capture the events that are going on there.
[Went to next slide – Weather Research and Forecasting (WRF)]
All right, so WRF, which is the weather researcher forecasting model, is used by numerous people worldwide. I could literally say hundreds of thousands, and I would be right. Developed by the National Center for Atmospheric Research. It’s a community model means it’s shared. It’s free, but you have to calibrate it, bring it in, and run it somewhere, and that’s where high-performance computing comes in.
[Went to next slide – air temperature in celsius: 0 is green while 9 is brown. Air temperature fluctuates but mostly gets warmer the further down right you go.]
Now, this is an example of some of the data that we get from it. This is the 700 millibars,s so if you look 700 millibars, that’s about 5,000 feet up in the air, depending on the location, and this is the dew point depression and air temperature. So it tells us where there’s moisture and where there’s no moisture and depending on how much and then the temperatures in there and so we can look and see is it conducive to be cloud-seeding or if we’re doing a forecast for a hydro forecast is it going to produce enough precipitation to increase the stream flow or whatever.
[Went to next slide – composite radar showing DBz from white to black.]
It can also produce things like this, which is a simulated radar to give us an idea of where that rain is and how much is going to fall
[Went to next slide – a graph showing hectopascal on the y-axis and degree Celsius on the x-axis. A black line from 300 hectopascals goes down until 0 degrees Celsius; a red line and blue line follow this pattern but are a bit wavier. Also, a green line goes from left-top to bottom to 0 degrees Celsius. ]
or for weather geeks like me, a Skew-T is heaven, and that’s what this is. This is a 2D description of the atmosphere at this one point. This is Haley from there up to like 50,000 feet in the air. It’s the red line is the temperature the blue line is the dew point. So I can look at this and see where we’re saturated, where clouds are going to be, where I can look on the right-hand side that’s winds, I can look at where turbulence in the air is going to be, how fast the wind is going to carry our Cloud City material, and I can tell by looking at the structure and then the map itself, is it a stable one are we going to get an inversion there, is it going to produce thunderstorms. You can use it for a ton of stuff, so it’s pretty simple looking, but man, it gives you a lot of information
[Went to next slide – one graph showing heat index, dewpoint, and temperature in Fahrenheit. Similar to a sin wave over the time period of 2 am to 11 pm x-axis and a y-axis of 80 degrees Farhenhiehgt to 20 degrees. The second graph shows gusts in miles per hour and surface wind in miles per hour. Also similar to a sin wave, dots are placed between time intervals across the x-axis or 2 am to 11 pm.]
and out of that, we pull something like this. We can give you information that shows the temperatures, the dew point, how much precipitation kind of probability of it, what the winds are, or how fast that is.
[Next slide – WRF Weather Modification Module]
Now for cloud seeding, we piggyback on that; we run WRF straight with no interaction there, and then we utilize the weather research and forecasting weather modification module that in-car built for us, and basically when you run this…
[Next slide – Real-time cloud seeding guidance system: Observations going into NCAR Web Display, WRF forecast model goes into control outputs that lead into NCAR WASCA, then going into NCAR ASPEN, which outputs into seeding outputs, ending up in NCAR Web Display.]
little diagram that gives you all this information but basically, what it does is it runs that first model run that has no interaction. The module sits on top of it and looks for the proper conditions. Precipitation is capable of systems that are coming in when temperature and then it runs it and then it runs it again and inputs what would occur if we actually cloud-seeded at the time it identified in potential.
[Went to next slide – text file holding seeding information]
So it gives us a lot of guidance and something like this. It tells us today that there’s a potential due to airborne seeding and the Boise and the Wood River bases, but if we look at the top portion and the Payette River Basin out east, there is no real potential, and we don’t see any potential to do ground seeding, and that’s because of the temperatures when you came in while earlier today it really wasn’t that cold it wasn’t freezing. So you’re not at a level more than likely that’s going to meet that optimum minus 6 degrees Celsius to do well
[Went to next slide – 12 graphs with text too small to make out.]
and then we get visualizations out of it. If we look at things like this, I won’t go into all of them, but basically, these are constructs of seeding areas that look at the temperature, the amount of relative humidity or precipitation with respect to the ice, how much stability is in the air, how much precipitation is going to occur, and then if conditions come together, you get that black line there. It says this is the optimum time to see.
[Went to next slide – More on Modeling]
So it gives us a lot of information.
[Went to next slide – two graphs: The first shows Height in kilometers on the y-axis and an unlabeled x-axis. The second graph shows height with kilometers on the y-axis and another unlabeled x-axis.]
So more on modeling, so this is a type of modeling that we do it says GC features and GC features is generating cells, and if you also look under that GC features it says a 2 or a 20 meter LES. Well, Les is a simplified model, but it allows us to do at a much finer resolution the modeling of the atmosphere to see what happens at those minute terrain features and stuff like that. So instead of looking across 1.8 kilometers like we do. This model set that Incar did for us looks at what happens across that mountain range in 30-meter blocks. So you can identify where the winds are going up, where they’re going down, where clouds are developing, and if you look on the left-hand side of this, you see the clouds are being developed there across that as moisture is being brought in. The right-hand side shows upward and downward vertical motions that are occurring as winds go across this rougher Terrain. Now how do we use that?
[Went to next slide – has one graph and one model: The graph measures height in kilometers for the y-axis and x g/kg for the x-axis. In the middle, at around 0 for the x-axis, there is ~ .3 on the color scall, which is bluish at that point and almost 3 kilometers. The model, also in the graph at point 0 on the x-axis, shows an air current pushing against a hill and an opposite current opposing it. This seemingly creates a cloud. ]
Well, we can see in the left-hand side here the development of a generating cell that’s moving up the winds coming across that mountain; it’s helping to push it up into the air,
[Stayed on the same slide – an animation appeared showing air currents in a terrian]
and what we get is something like this. What we’re seeing is a natural development
of clouds over those mountaintops that are coming up, it’s a little slow, but you gotta take into account that there are about 1.8 billion or million cells for each one of these time steps. So that’s a little bit slow, but it is producing what’s naturally occurring. So an example like Snowie, where we had the aircraft that was out there flying, and we had observers out there before anything was happening, we can collect all the information that shows what’s happening in an atmosphere and then what actually happens and then compare that to calibrate our models with.
[Went to the next slide – three models and an animation are on this page. On the left is a model showing the terrain height of the US; below are two models showing very similar measurements in different locations. The animation shows the air current’s direction and a gas release that may affect it.]
So a very similar type of thing, we’ve got the wonderful Skew-T tea over on the left-hand side. Winds coming across this side, and it’s simulating in just a minute where silver iodide is released from ground generators, and you can see the release of that and the dispersion of that based upon the winds.
[Went to the next slide – an animation is playing, showing a gust of silver iodide seeding particles going through ice crystals and creating snow]
This is pretty much the same thing, except for more on a graphical format, and basically, in the upper left-hand side, in a second, you’ll see that one cloud or the darker area. That’s the release of the silver iodide. It interacts with the clouds; it starts producing precipitation, whereas, on the bottom side, there was no silver iodide release.
[Stayed on the current slide – graph of longitude and latitude showing precipitation difference in millimeters appeared on slideshow]
So natural precipitation did occur, but when we look at the models when we run it without seeding and with seeding, what we see is in the one area where we seeded, it’s not a huge difference because it’s a fairly short time, but color coded on the bottom we see about a half a millimeter of additional precipitation that occurred through the cloud seed.
[Went to next slide – text at the bottom says “Questions?”]
So that’s how we tie research computing into cloud-seeding operations. I have a lot of time left, so are there any questions, or did I put everybody to sleep? Yes.
SPEAKER(1): I’ve got a question. I spend a lot of time on Borah extinguishing a lot of data [microphone didn’t pick up question], possibly asking about how cloud seeding affects the accuracy of weather forecasting.
MEL: well, I will back up a little bit from my original thing and say that we’re very focused on our targeting of where we’re wanting to cloud-seed, so let’s say the Payette River base in the Boise River Basin, we only cloud-seed so that it impacts 6,500 feet above, so very much that mid and upper level because that’s where we want the snow, so it lasts longer. From our research in Snowie, we’re very confident in that what we’re doing is where it’s hitting. So from that point of view, what we do, we know that we’re not hitting lower elevations; we know that it’s predominantly hitting the higher elevations. From your point of view, knowing when it’s going to occur, there’s really not much of a chance of knowing that. Even if you see an aircraft up there when we fly, it’s typically overcast skies in the middle of the night. So you generally wouldn’t notice it. From the modeling, very much like we did, let’s say it was a decent storm, and you got you’re at 8,000 feet, and you were going to get a foot of snow, you might get a foot of snow 0.5, but if you take that half an inch and spread it across the entire Basin, turns into a lot of water in the end, and as far as interacting with other agencies we deal with, or we send out seeding forecast to all the involved groups that are Partners or collaborative Partners. So it goes out to all the irrigators and stuff like that, and it also goes out to the Boise National Weather Service and the Pocatello National Weather Service. Very specifically because one, they use some of our data, they like it, but also the guys in Pocatello were like, “We’ve been doing studies, and we can never figure out why our models are wrong,” and when they started looking at getting the forecast they were like “okay now we know” because the days that were quite a bit off and you know, when you’re talking we’re supposed to get two inches versus four inches they were like we can see the difference. So they know it, they take it into account in some aspects when they’re doing their written stuff, but any models you get, say, if you go to Pivotal Weather National Weather Service, any of those. They’re not going to include that additional precipitation, but we do interact with them, and I have a whole bunch of slides under this if we want if we wanted to go into them, but one thing that we do is we monitor snowpack conditions and streamflow forecasts out through time. So if we look at the current snowpack in a region compared historically, we’ve researched and done a lot of analysis to look at when flooding occurs. When we reach certain levels at certain times of the year, we will suspend operations. We want to increase flow but don’t want to increase the flood-type flows. We also have a model that looks at the National Weather Service river forecast models that are publicly available and look at what those look at compared to historical points because they include in their model how much snow is there and Reservoir information and stuff. So it’s we do monitor it from the point of view of Public Safety; it’s very similar to we have suspension criteria; let’s say an area like this year, the Payette River base, and just about all of them have had extreme avalanche conditions, and when we go to extreme avalanche conditions we don’t seed during that time frame. Specifically, because we don’t feel that our little portion is going to help, but when it’s already that dangerous, we don’t want to take the chance, but you know if it’s a considerable or something that additional amount. [mumble] Any other questions? That was a good one, yes, sir.
JASON: [microphone didn’t pick up question]
MEL: Well, when you consider that when the silver iodide is in the mixture when it gets pressurized atomized and then burnt, it’s what’s being distributed is in the area of about five microns per for silver, and the reason we burn it at that temperature and specifically how it’s set up is that five Micron silver iodide and it’s very specific to make sure we say silver iodide is it forms a hexagonal form, just like most of your salts and your sands. So it just replicates what naturally happens where now how much quantifies across that, as far as you know, a gallon of Silver versus so many pounds I honestly don’t know. I do know that the analysis shows that, on average, we increase stream or precipitation that goes to Stream flow unregulated across the Basin, which is about 1.2 million acre-feet of water. That’s about half- and half-upper snake in central mountains, and I don’t think we’ve ever looked at it from the point of view; we know what the project produces, kind of the long-term type of stuff, yeah?
JASON: Yeah, I’m just curious what’s your distribution?
MEL: Yeah, and it’s because it’s such small distribution, basically the different groups that have looked at it say it’s, even over extended periods, it’s hard to see any accumulation across the terrain. Places in California that have been seeding since the 1950s do collection and Analysis like every other year, and they’re still not seeing levels above natural accumulation. Yes sir?
SPEAKER(2): Is there any sort of pushback?
MEL: Each state is a little bit different. California is extremely regulated in how they do it when they do it; as you can imagine, Idaho is far less restricted, but basically, there’s the state of Idaho passed the law two years ago that requires a certain level of licensing insurance and to follow best practices as established by the Weather Modification Association and what’s the there’s an engineering pamphlet I can’t remember the exact name right now but it’s basically that in Idaho that, seeding has conducted within those kinds of established industry standard levels. You have the safety protocols in place for suspension, different things like that, and that you have the license and insurance, and the things like your planes are up to FAA standards for modifications. James had his hand up, and I’ll come back to you.
JAMES: [inaudible question]
MEL: There have been numerous studies across The United States and other places that have looked at quantifying if there are differences in amounts of water content and, in a practical sense, there’s no difference between naturally seeded and naturally occurring and seeded. The only difference is that you get more occurrences when you do seed compared to those that weren’t seeded. Yes sir?
SPEAKER(3): [Inaudible]
[Started scrolling through slides]
MEL: I’m going to skip through this one, and this is why I have an extra paragraph. There we go
[Stopped on – Extra Area Effects]
It’s commonly known as the extra area effect, and if you want to look at it, one effect downrange effects and a scenario that everybody talks about is Rob Peter to pay Paul. If you’re taking our water here, what are you doing downrange? Basically, I’ve got a couple more slides, but there’s been tons of research, whether it’s in California or Idaho or different areas, that show that there are no negative impacts downrange and typically it’s neutral to positive downrange
[Went to next slide – Extra Area Effects with new information]
and one of the most famous ones was the solid that in 2003 he did a fairly extensive program, researching in Southern Idaho. Utah has been doing cloud-seeding since the 80s, and he says if there was a continued improvement downrange from the project up to about 200 kilometers. It started fading somewhere between 160 and 200. Then the North American Weather Resort Consultants built upon that. Basically, they continued to show increases downrange until it faded into the background, and you ask why.
[Went to next slide – Extra Area Effects with new information and pie graph. 80% of the graph is uncondensed water vapor, while 20% has condensed into a cloud.]
Well, from the atmosphere’s point of view, it’s not naturally efficient. it’s all dependent upon temperatures and how many ice nuclei are out there, and we see that, in general, the National Center did this research for Atmospheric Research and a couple of others, but about 20% of the water vapor that’s available is turned into clouds. The other 80% basically just continues on down,
[Went to the next slide – containing similar information and updated the pi chart to include precipitation which takes up around 6% of the condensed into cloud section.]
and if you take winter storms, how efficient they are in producing actual snow, it’s about 30% of that original amount that coalesced, and if you just keep moving on downward
[Went to next slide – containing similar information buts adds cloud seeding effects. Cloud seeding is added to the pie chart as 0.9%.]
range to the point that we impact is about 15% of that portion. So what we’re impacting is about less than one percent of the overall budget of the water availability, and if you looked at the atmosphere is just a straight bucket. You had a bucket of water. If that bucket of water is running across the ground here and I’m dumping water out well when you get down the road, it’s empty, but the atmosphere is very turbulent, it’s continuously mixing as it moves, it picks up moisture from the seas, the oceans, the lakes, and across the land across the snowpack. So in fact, as it’s moving through there and it’s through the turbulent mixing there you can’t really determine where reductions have occurred because of this; it’s so small that it simply kind of blends into the background, and it doesn’t impact what occurs downrange, and we’re pretty confident in that because of all the research that’s been done. There are dozens and dozens of peer-reviewed papers on it that have been in everything from weather modification journals but to, let’s say, BAMS Bulletin of the American Meteorological Society also Nature Geo. You know, fairly high-level ones that are fairly extensive on their reviews, so we’re pretty comfortable in that format. Does anybody else have a question? We have 10 minutes left until the end. Yes sir.
SPEAKER(3): [Inaudible]
MEL: If you take us compared to the west of us, we have a lot less rain or precipitation than, say, the Cascades. So it’s a barrier type of thing; much of the water gets drained out. As we move across our area, we have a rain shadow that reduces the amount of precipitation. It starts to pick up again as we get to the Tetons, the Rocky Mountains, we get that stuff, and then it drops over there, and you have some of those kinds of dryer areas, but the biggest difference over there is they’ve got two additional sources of moisture. You’ve got the Gulf Coast that sends moisture up, and you have moisture that comes down the East Coast or the East side of the Rockies. So it’s basically the availability or increase of moisture that’s out there to utilize. When the systems get set up just right, huge amounts of atmospheric moisture are pushed up into those Midwest and then Eastern states. We are in an area almost as dry as an actual dessert. Well, thanks, everybody I appreciate the time and hopefully was able to provide you with something that tied a practical application that benefits, in our opinion, everybody because it increases our ability to reduce low-cost, low-carbon generation that increases Stream flow while also utilizing the high-performance Computing system through our collaborative efforts with research Computing here in town. Thank you.