I like puddles, and I have become more interested in them lately. Why?

On 29 May 2002, we took observations of the heating and moistening of the lower atmosphere using an aircraft and surface sites observations in the Oklahoma Panhandle (The Western Track in Figure 1). Two days before we took our data, a heavy rain brought 80 mm of rain to the point labeled 1, with the points labeled 2, 3, and 10 getting 30 mm or less.

Figure 1. Map showing the location of aircraft flight tracks (white lines) and sites where we took special measurements (numbered 1-10). The observations I write about are along the Western Track, on the left side of the picture. The long white lines outline part of the state of Oklahoma.

We have been trying to see how well a land surface model would do in predicting the observed heating and moistening, given the weather conditions – temperature, solar radiation, wind, rainfall, and so on as input. And the model didn’t work very well near Site 1. No matter what we did.

We have an idea why: Puddles.

As you can see from Figure 2, there were puddles near the southern end of the flight track. In fact, one road was blocked by water. And the land surface model didn’t account for evaporation from puddles. We think this could explain why the measurements showed more moistening (and less heating) of the air than the model did.

Figure 2. On 29 May 2002, photograph of puddles near the southern end of the Western Track, shown in Figure 1. The spots are on the aircraft windshield.

I decided that I had better learn more about puddles. So the first day there were puddles outside my office, I went outside and took puddle temperatures with a GLOBE infrared sensor (see the GLOBE Surface Temperature Protocol).

I was surprised – the puddles were warm compared the ground around them. This is not what I expected. Puddles like those in Figure 2 were cooler than the surrounding ground on 29 May. So I became even more excited about puddles. There is nothing more fun – and sometimes more awful! – than taking measurements you don’t understand.

I’m starting this project by just trying to figure out how fast the puddle disappears. On an asphalt surface, this tells me how fast the puddle evaporates. I’m also measuring the temperatures of the surface around the puddles.

Figure 3 is a picture of the puddle that I measured. The chalk rings are drawn around the puddle so that I can see how fast it is drying out.

Figure 3. Puddle with outlines of water’s edge. The lines alternate between light yellow and light pink. Yellow or pink dashed lines are where the chalk is too light to see easily. By the time this picture was taken, the puddle was almost gone, with shallow water in a few places in the small left circle. Times are when the lines were drawn. UTC = MDT + 6 hours.

What did I learn? Figure 4 showed results more like what I had expected. As the sun got higher in the sky, the asphalt surrounding the puddle warmed more than the puddle itself. And the difference between the puddle temperature and the asphalt temperature got bigger, until around 11 a.m., when it started to get cloudy. After that, the temperature difference became smaller.

Figure 4. Temperature of the puddle in Figure 3 as a function of time. The skies were mostly clear until about 11 a.m. MDT. After that, the sky got cloudier with time. It was overcast by 11:50. Local solar noon (when the Sun is highest in the sky) is around 13 MDT.

Does this offer a clue to why the first puddle I looked earlier at was warmer than the surrounding surface? I think it does. That day, it was also cloudy in the afternoon.

If this puddle had lasted longer, AND if this puddle cooled more slowly than the dry asphalt once the skies were cloudy, then this puddle might have ended up warmer than the asphalt. And maybe it has something to do with the fact that water stores heat well.

So I need to look at more puddles. And, while doing this simple experiment, I noticed that I could have done some things better:

• I didn’t want to use the oven mitt on the radiation thermometer, as recommended for the GLOBE Surface Temperature Protocol, so I kept the radiation thermometer outside so that its temperature was the same as the air temperature. But I soon discovered that the air temperature where I kept the radiation thermometer was different enough from the puddle site that the measured surface temperature changed rather rapidly for about five minutes (the differences weren’t that bad). So I’m not too sure about the temperatures before 8 a.m. After 8 a.m., I still left the instrument outside but oven mitt on – and the measurements were more consistent.
• Toward the end of the observations, I realized that I had made a bad assumption: that all the asphalt outside the puddle was the same. It wasn’t. The puddle was in a place that had been repaired. You can see the difference in Figure 5. The area to the north of the puddle was up to 3 degrees cooler than the area to the south of the puddle! ). So I only use the temperatures on the south side in Figure 4.
• I had carefully drawn chalk rings around the puddle, so that I could see how fast it evaporated. But I forgot to take an important observation – how deep the puddle was! So – even though I could tell that the puddle was evaporating, I couldn’t tell how much water was evaporating – and I wanted to know that.
• If clouds are important, as they would be if the puddle stays warm after the skies cloud over, but the surface around it cools off – I need to be more careful about writing down when there were clouds.
• Fourth, once the puddle got quite shallow, it was basically wet asphalt. I should have taken the temperature of the wet asphalt as well.

Figure 5. The puddle and its environment. Note the puddle lies on the south (right) end of an asphalt square that was slightly warmer than the darker asphalt to the right. (Although dark things are usually warmer than white things, the warm temperature could have something to do with different materials being used, or the thickness of the asphalt layer.)

I have some of the other data below. You’ll notice I may have made a few mistakes! (It’s important to keep track of them, so you can learn from them). The times are important because I might want to check other weather data I can get from the Web or from the automatic weather station on top of our building.

Next time I will be more thorough. I’ll let you know what happens. In the meantime, think about how you can use measurements or simple observations to describe some things that are happening around your home or school.

Table: Puddle measurements on 6 May 2007.

The work of Roger Pielke, Sr., discussed in the last blog, suggests that thunderstorms might be more common than they were 100 years ago. Are they?

My first job in science was as a college student. Ten hours a week, I worked on putting together a ‘tornado climatology’ for Professor Grant Darkow at the University of Missouri. To do this, I had to find out when and where tornadoes occurred in my home state of Missouri. I used records from the U.S. Weather Service (Monthly Weather Review, for more recent years, Storm Data), and weekly newspapers from small towns around the state.

Why? We wanted to see if we could learn more about how tornadoes form by knowing better about:

• When tornadoes form
• Where tornadoes form
• How big they are
• How long they stayed on the ground
• What time of day they happen
• What direction they come from

This information usually came from eyewitness reports of a funnel cloud and damage reports that lined up along a narrow track that lined up with the funnel cloud. Ted Fujita, who is known for the Enhanced Fujita Scale of tornado intensity, developed methods for associating damage patterns with tornadoes.

What did we find out? We found out that there were more tornadoes where there were more people. If there are more people, the chances go up of someone seeing a tornado. And tornado damage is more obvious (at least when you aren’t looking for it) where there are houses than in an open field. Also, if there are enough people, there is often a small newspaper to report the tornado.

The area around St. Louis, Missouri, had the most tornadoes per unit area. This was not only because there were a lot of people in and around St. Louis, but there was a storm chaser and scientist named Ed Brooks who found and reported tornadoes that no one would have known about otherwise.

Looking at the map in Figure 1, there also seems to be more tornadoes on the west side of the state than the eastern side, although Kansas City (where the Missouri River reaches the west side of the state) probably accounts for some of the high numbers there.

Figure 1. Number of tornadoes in Missouri by County between 1916 and 1969. St. Louis is on the east side of the state, in the county that has 33 tornadoes. Kansas City is at the north end of the straight-north-south part of the state’s west border. Figure Courtesy of Grant. L. Darkow, University of Missouri-Columbia.

We also found out that the number of tornadoes went up with time, with a rapid increase in the 1950s. Some of this is related an increase in the number of people and newspapers with time.

Also, the Weather Service (then the Weather Bureau) started tornado forecasting in the early 1950s. So not only were people reminded to look for them, but weather forecasters would look for evidence of tornadoes to check to see how good their forecasts were. About the same time, the Weather Service started to publish summaries of tornadoes and other severe weather in Storm Data, making the information much easier to find.

Apparently my hard work between about 1965 and 1968 didn’t increase the number of tornadoes counted – aside from a big peak in 1967, the number of tornadoes was about the same as in the late 1950s.

Note that the tornado deaths stayed about the same in spite of the increase in population. If the number of tornadoes really had increased, a steady death rate might mean better tornado warnings. But we felt that the small change in the number of deaths meant that the number of destructive tornadoes hadn’t changed that much (and thus probably the total number didn’t either).

Figure 2. For the state of Missouri, tornadoes and tornado deaths by year. Note the big jump in the mid-1950s, which corresponds to when the Weather Service formally started recording storm occurrence in Storm Data. Figure courtesy of Grant L. Darkow. University of Missouri-Columbia.

Tornadoes occur with strong thunderstorms, which usually produce lots of rain. An easier question to answer is whether there are more heavy rainstorms.

Why is this? First, there are lots and lots of rain gauges. But they are not everywhere, so scientists lump together several gauges in an area. Obviously, the time changes will be more accurate if the area is large enough to have lots of rain gauges with records for a long time.

But the areas you look at should be small enough so that you can see how things vary from place to place. By very carefully combining rain gauge records and measuring how accurate the resulting trends are, Pavel Groisman and his colleagues at the National Climatic Data Center found out that they can detect an increase in very heavy rainfall in the east-central United States. In other places, the trend is too small to say for sure using their methods.

Since thunderstorms clouds are cumulonimbus clouds, you could count observations of cumulonimbus clouds to see whether there are more thunderstorms. (To see what a cumulonimbus cloud looks like, see the cloud chart.) Between the early 1950s and the early 1990s, when human observers were replaced by automated weather stations, there was a good continuous record of cloud-type observations by U.S. Weather Service human observers. (Now, students like you take observations for GLOBE-related projects like the CloudSat mission for “ground truth.”) During this time, the number of cumulonimbus cloud observations increased during the spring and fall, but the reports didn’t change much during the summer. The authors suggest that the spring and fall increase is related to more warm days as winter gets shorter.

So the small number of clues here suggests that there are more heavy rain events in some parts of the country, and there are more thunderstorms clouds – in the spring and fall. But we really can’t see whether there are more – or fewer – tornadoes.

And the much harder question is to answer is, “why?”

My sincere thanks to Grant Darkow for checking my facts and allowing me to reproduce his figures. And I wish to dedicate this blog to the people of a beautiful town I visited and enjoyed very much about 10 years ago - Greensburg, Kansas, which had a devastating tornado last week. Best wishes for a full recovery - and no tornadoes for another 100 years - at least.

Do you ever hear something you just can’t stop thinking about? About ten years ago, I heard a talk by Roger Pielke, Sr., where he compared the weather over northern Texas for two days, 100 years apart. The weather – high and low pressure areas, temperatures, and humidity – started out the exactly the same on two days in the world created by his version of a computer weather forecast model. But the land was different. It’s like someone took the weather from a 1991 TV weather map and put the highs, lows, and fronts on the United States of 1881, when there were only 44 states, and the land was prairie. And there was no television.

He picked a day when he knew there had been a strong thunderstorm – it had been observed and very carefully documented in 1991 by scientists during a field program. Since the storm already happened, he knew where the storm would form. And it’s a common place for storms to form – along a line where warm, moist air from the Gulf of Mexico meets dry hot air from the southwest United States. This line is called the “dry line.” It commonly forms in northern Texas. Storm forecasters watch the dry line closely to see whether new storms are forming.

Why the dry line? When air from two places flows together, something has to happen. The air can go sideways and “squirt” out of the way, or it can go up, or it can move sideways and up. This isn’t enough detail to know whether a storm will form, though. For a storm to form, the air has to go up over a small area, somehow. And it has to be moist enough to make a cloud.

That’s just the first step—the rising air cools. When the air gets cool enough, water starts condensing around tiny dust particles, and you get a cloud. If the air continues to rise – which it will if it is lighter (warmer) than the air at the same level outside the cloud – a very big cloud can form. And rain. Add to the mix a little wind change with height – we want the cloud to tilt over so the rain won’t fall into the updraft and kill the cloud. There is a very nice animation of a cloud forming on the GLOBE online Cloud Module.

We use computer models that describe how air behaves to predict where and how much air will rise. The model used by Pielke and his colleagues also describes how the soil and plants heat and moisten the air.

In the first model run, he put prairie into the model. In the second run, he put modern land use – including irrigation. After very carefully making sure that the beginning conditions are similar, they ran the model twice, once with the “old” land use and once with the “new.” The results were surprisingly different.

The “modern” computer run formed the strong thunderstorm that was observed. But the 1891 computer run formed much smaller clouds. Why?

The “modern” surface types heated at different rates. This leads to patches of warm air that start rising; and cool patches of air that move in to take their place. A “circulation” is set up with the updrafts over the warm region. This circulation helps get an updraft – and hence – a cloud, started in one place. This means the moist air near the surface can go up in one place, instead of many, concentrating the “energy” into one big storm; in this case, right on the dryline, where the air was already flowing together.

Next time – are there more storms than there used to be?

Thanks to Roger, Pielke, Sr. for supplying with journal articles on this topic.