Guest Opinion: Dr. Tim Ball
My overall career interest is the impact of weather and climate on human history and the human condition. Much of this involved the impact on primary industries like agriculture, forestry, and fisheries. For 17 years I produced monthly columns titled Weather Talk in the largest circulation farm magazine in Canada, Country Guide. Despite the popularity with the farmers and agribusiness, I was fired because I wrote about what was wrong with the science of the global warming issue. Shortly after ending with Country Guide I began a similar column in a magazine called The Landowner and have produced monthly columns for several years now. Beyond the sin of disagreeing with the official government position on anthropogenic global warming (AGW), I spoke out about the failure of Environment Canada to improve forecasting for farmers or even consider their specific needs. While they were doing that, the Auditor General of Canada identified they spent $6.8 billion in a seven-year period (1998-2005) on climate change that produced nothing. It produced worse than nothing because a portion of the money was spent on the Canadian climate model that contributed to the IPCC amalgam of models; as Ken Gregory showed, its projection was the worst of all of them (Figure 1).
Farmers know that part of their success involves finding a balance between government regulations and reality. They also knew they needed better more practical information, and many went about doing it. They know as well as any group in society the limitations of government weather forecasting. Naturally, they extended their cynicism of the weather forecasts to climate forecasts.
I received a measure of the farmer’s interest in the weather and climate early in my career of speaking at farm meetings across Canada and in the northern US. My wife determined that I drove every paved highway on the Canadian Prairies over a 30-year span. I suspect farmers maintain more long-term weather diaries than any group and purchase more micro weather station, like the ones Anthony Watts sells at ItWorks than any others. At a farm meeting near Magrath (south of Lethbridge) in southern Alberta in the early 1980s, I finished my presentation that included a little on historical climates and asked for questions. A farmer stood up, and I could tell by the audience reaction that he was well known in the area. He asked if I could comment on the connection between the Little Ice Age and the Maunder Minimum. After the meeting, he explained that he was a mixed dryland and irrigation farmer and his interest developed from studying all the work done on precipitation patterns, and hydrologic models for efficient irrigation. This led him into the wider field of climate change.
My interests produced some unique areas of research. Severe thunderstorms and hail are a major problem for farmers across Canada but especially on the Prairies. It is why a hail suppression research center was located at Penhold, in southern Alberta. The problems created for agriculture are the damage from hail but also the capricious tracks of rain-bearing clouds. The annual pattern of summer precipitation involves two types. First, the steady 2 and 3-day rain systems from large low-pressure systems of the spring and fall as the Polar Front moves across the region; and second, the showers of the summer months. These result in streaky tracks of rain with one farm getting adequate precipitation while a neighbor gets none. It is a vagary of such precipitation patterns that when you get adequate rain, you also get a greater risk of hail.
An almost predictable forecast in the summer on the Prairies is, clear in the morning, clouding over in the afternoon with a chance of showers and thundershowers in the evening. The sequence is triggered by early morning differential heating of the ground, mostly determined by differing albedo. I realized how much when I bought a car with an external temperature device. I also realized that even small communities, upward of 5000 showed a small heat island effect, especially on cold winter mornings.
Adiabats form and rise and at the lifting level of condensation (LLC) the water vapor evaporated from the surface is converted to visible water droplets (clouds). This is an interesting phenomenon that is one of the few places in nature where an energy and phase change is visible (Figure 2).
Notice that the base of the clouds is all at the same altitude, which is the LLC. The dark bottom to the cloud indicates the density of the water droplets and their ability to block sunlight.
Each cloud can develop vertically, which depends on the amount of moisture and potential energy within the adiabat (bubble). Energy is transferred both directly from contact (conduction) with the surface as it is forming, and latent heat used for evaporation that is released into the adiabat with condensation. Some develop into a different cloud classification known as Cumulus + (or CU+). Figure 3 is a good example. The LLC is visible but also an indication of showers under the cloud. Often, on a really hot day, you can see the rain evaporating before it reaches the ground, a process called virga.
Eventually, some of these clouds develop into massive and powerful thunderstorms (Cumulonimbus) with heavy rain, hail, and under certain circumstances, tornadoes (Figure 4).
This is the classic ‘anvil head’ cloud and another place where a line of energy balance is visible. The cloud flattens out in a distinctive line when its vertical development meets the top of the Troposphere, the Tropopause. Notice there is a bulge of cloud beyond that line because the vertical winds were so strong they punched through into the Stratosphere.
In the 1960s, 70s, and 80s, various projects were undertaken with very different objectives, but using the same understanding of the mechanisms. One was cloud seeding to increase the potential for precipitation in drought-stricken areas; the other was cloud seeding to induce rain to remove the energy source from the cloud and prevent development to the stage at which hail forms. These were called hail suppression experiments. Three major areas of experimenting included Canada, the US, and the Soviet Union. There is little interest in either any more for several reasons.
You did not know how successful the operation was because you didn’t know how much it would have rained without the intervention. As I recall, the best-claimed results were a 17% increase. You could not control where the increased precipitation would occur, so there were legal liabilities. The costs made the results a poor investment. One company I spoke with were cloud seeding on behalf of insurance companies after hail did extensive damage to cars in Calgary. They were not amused when I pointed out it would be cheaper to buy every car owner a heavy blanket to lay over the car. They were even less amused when a drought occurred to the east of Calgary and farmers in that area blamed the seeding for stealing their precipitation.
Across western Canada, most crop insurance against hail and other damage was provided by government agencies. I decided that the claims for hail insurance should reflect the geographic pattern of the thunderstorms and I could use them as proxy data for determining the atmospheric mechanisms in play. Working with a graduate student, we obtained the hail insurance claims for Manitoba over many years.
Initially, they were loath to give us the information. We received it with the condition that we could only use it to plot climate data. Data was by township and used to give each a rate from 1 to 7 depending on the number of claims. Not surprisingly, it provided a very distinctive plot that showed the extension of what is known as Tornado Alley (Figure 5). This explained the pattern in the context of the more extensive circulation, but we also identified a region along what is called the Manitoba Escarpment. This is a 2000-foot geologic ridge that formed the western shore of what some believe was the largest freshwater lake in the history of the world, Lake Agassiz (Figure 5). Note that Lake Winnipeg is just a remnant, and yet is the 13th largest lake in the world by area today.
The Escarpment triggers increased thunderstorm activity, and, in the region, it was most pronounced the aboriginal people had as sacred hill they called ‘thunder’ hill.
The record covered more than 30-years but was insufficient to detect any trend. We ran into one problem with the record, and it illustrates the potential dangers of proxy records kept by humans. The rating, and therefore the cost of insurance for each township for the following year, was determined by the number of claims for preceding years. This meant it was based on climate, not the weather from year to year.
At this point, we discovered why the limits were put on our use of the data. I assume it is safe to talk about this now because the statute of limitations is long over, and the people will have retired. It is also important to note that I don’t think what happened was a function of it involving government. We discovered what they were doing was that if the claims decreased enough that the formula dictated a decrease in rates for the following year they altered the numbers. They dropped the most recent year with the low number and substituted the highest claims year in the record. As I recall, it was 1949. This guaranteed the price would not decline.
Figure 6 (modified by the author)
Fortunately, we caught the error, and they admitted to what they were doing. However, in this case, we determined the few adjustments were within the margin of error of our data and did not negate our results.
Whenever I spoke with a farm group, I always prefaced my remarks by saying they knew more about the weather and climate on their farm than anyone else. All I could do was provide a picture and explanation of what was going on in the region, the continent, the Hemisphere and the Globe. They could then determine if the changes they saw were part of the larger picture or because of a local change. The climate research term for this is relative homogeneity. It is why you can never determine climate change from studying one station because you cannot identify and separate out what is only local change.
From an operational point of view, the Weather Service in any country doesn’t provide the information farmers need for better planning decisions. For example, they need ‘real time’ data, which is not available in most regions. They need better than one-week, six month and annual forecasts yet none of those are available. Instead, they waste time and trillions on conditions 50 and 100 years from now. They need better precipitation forecasts, but all the attention is on temperature. That was one objective of our study beyond anticipating the demand for hail forecasts.
Over the years I helped many farmers set up weather stations on their farms and always urged them to have a sensor at the same level as the ‘official’ Stevenson Screen (Figure 7) for accurate comparison with their local station.
I also urged them to put sensors right at the surface because conditions are so different there, and it is what happens in that 1 to 1.25 meters that are critical because it is where most of their crops grow (Geiger’s Climate Near the Ground was a superb source). One example where it is critical is the weather service does not consider moisture from condensation as precipitation. In many years, it produces enough moisture to make a difference in the success of the crop. Of course, farmers also know that later it can delay harvesting.
All the trillions of dollars spent on AGW have not improved forecasting one bit. Instead, it diverted money that could have helped those large, primary sectors of society and economy that need better and more appropriate information. It is time to close all government weather offices or at least reduce their function to data collection determined by the end users.