1-5 Reading 2: Forecasting Benefits

ASSESSING THE ECONOMIC BENEFITS OF IMPROVED LONG-RANGE WEATHER INFORMATION: Convincing governments to spend money on improving long-range weather forecasting

Abstract

In order for governments to agree to spend money to improve the technology for making long term weather predictions, they must first be convinced of the benefit of these forecasts to the community. Research into how much money may be saved by issuing accurate long term weather forecasts can be used to convince governmental agencies that investing in these projects is useful and important. Although there is some research into the monetary benefits of accurate short term weather forecasts, long term weather forecasting has been largely ignored. The global weather phenomenon of El Niño is helping to show governmental agencies why it is important to invest in accurate long term weather forecasting.

Each year governmental bodies around the world must make difficult choices regarding how to direct public funds. Most money is directed to such areas as public health, education and transportation (see Figure 1, below). The small amount of money that is left may be directed to projects that clearly benefit the community. In making decisions as to where to direct public money, governmental agencies must be convinced of the benefits, particularly economic, of such projects; therefore, research directed at assessing the economic benefits of these projects is very useful to those requesting funds. One such project that requires an investment of funds is improving the accuracy of long-range weather forecasting; however, before governments agree to invest money in this project, they want to see proof that improved accuracy in long term weather forecasting will actually provide economic benefit to the community.

It’s clear that, in order to improve the accuracy of long term weather forecasting, large amounts of money must be invested in developing new technologies and in researching the effects of their use. As mentioned, those requesting the investment of governmental funds must show the benefit of improved weather forecasting, both in terms of human benefit and economic gain. Therefore, systematic, scientific research on the benefits of long term weather forecasting can be used to show governments and other agencies the actual monetary (or dollar) value of improved weather forecasting to the community.

Some research has already been conducted into the monetary benefit of accurate short term weather forecasting. This research addresses the economic benefit of improved weather forecasts to agricultural producers. For example, in two separate studies, Burk (2002) and Katch (2001) assess the monetary value of improved frost forecasts to fruit farmers to be approximately 4 million dollars, annually. In another study, Shave (1999) estimates the monetary value of improved precipitation forecasts to California Raisin producers to be approximately 3.2 million over 2 growing seasons. These studies can be used to show the government how useful it is to the community to invest in projects that improve short term weather forecasting.

Research such as the studies conducted by Burk, Katch, and Shave focus on the value of short term weather phenomena (frost, flood, drought) to producers of a specific commodity in a relatively small geographical setting. However, there is little research into the economic benefit of seasonal or longer term weather predictions. Most economists and farmers agree that climatic variations taking place over several years, such as variations in temperature and precipitation from one growing season to the next can have a great impact on the agricultural profits. They believe that these long term changes in weather can result in changes in agricultural production, prices, and profits, and thus, in national economies. However, there is little systematic research to support this assumption. This is why research into long term weather phenomena such as El Niño is important.

Long-Range Forecasting and El Niño-Southern Oscillation (ENSO)

In many parts of the world, including, but not limited to, Asia, North and South America and Australia, it is possible to trace year-to-year variation in climate to one particular weather pattern, the El Niño-Southern Oscillation (ENSO). The El Niño-Southern Oscillation (ENSO) refers to a periodic redistribution of heat and movement of wind and water currents in the tropical Pacific Ocean (see Figure 2, below). It may present itself somewhere between two extremes, thus disrupting economies such as agriculture and fishing to a mild, moderate or dramatic degree, depending on the degree of variation. In recent years, the ability to forecast ENSO, in particular the more dramatic episodes, has improved to some degree, but more accuracy is needed. These forecasts have economic value because they can inform decision makers in particularly vulnerable sectors of the economy, such as agriculture or fishing.

A recent workshop estimated the potential monetary benefit of accurate ENSO forecasts on the U.S. and Canadian agriculture, forestry, and fisheries sectors at $200 million per year, with agricultural benefit the most significant of the three. This estimate is based on a number of subjective judgments regarding avoidable losses due to ENSO rather than objective analysis of financial information. In order to determine if investments in the research, monitoring, and technology required to achieve improvements in long term forecasting are cost effective, there is a clear need for the systematic assessment of the value of long range weather forecasting of ENSO. This systematic assessment must reflect how decision making is altered when information about the ENSO climatic effect is taken into consideration, and how these altered decisions financially affect both the consumer and the producer.

Estimating Monetary Benefit

This next section will briefly explain the conceptual framework used to estimate the monetary benefit of an ENSO forecast. The benefit of an ENSO forecast to a particular enterprise is measured by the expected increase in profits arising from the use of the forecast in decision making. Such economic benefits occur when the forecast leads to a change in behaviour. In the case of agriculture, without an ENSO forecast, a farmer makes planning and harvesting decisions that perform well under average weather conditions. An ENSO forecast has economic benefit only if the farmer’s decisions are different under the ENSO conditions.

So, for example, under normal meteorological conditions a farmer plants certain crops and expects to harvest a certain amount of what he plants and sell it for a certain profit. If the government issues an ENSO forecast prediction that temperatures will be considerably warmer than usual for the next cycle of two to five years, for example, and there will be considerable more rainfall, then the farmer will decide to grow different types of crops in his fields. He may invest in different machinery and fertilizers in order to produce the harvest. As a result of these decisions, he avoids economic loss by adjusting his crop to suit the climatic conditions. In estimating the monetary benefit of the forecast, first, an estimate is made of what the original crop yield would have been had the farmer not adjusted the type of crop to take into consideration the higher temperatures and precipitation. Then an estimate is made of the crop yield of the adjusted crop type. Finally, the two are compared and the monetary benefit of the ENSO forecast is arrived at.

Of course, this is only an estimate and needs to be confirmed by gathering actual statistical information concerning costs and profits. This information is difficult to gather and assess for a number of reasons. First, it is not always clear that the loss or profit was a result of the altered decision. For example, perhaps there was a problem with the seed; it may have been diseased and this resulted in a low crop yield. Or perhaps the farmer used a different field to plant the crop, and this field was smaller, or had a different access to rainfall or sunlight. Or perhaps a new fertilizer was used, which resulted in a higher yield. Or perhaps there were family problems, such as an illness or a death that resulted in fewer hours allotted to work, which resulted in a lower crop yield. Moreover, it is necessary to collect data over several growing seasons, in order to set baselines of production. This requires that researchers and farmers work closely together and can be problematic for a number of reasons, such as changes in farm ownership, or funding issues. All these variables can affect the analysis and must be considered when drawing conclusions from the data.

Despite the uncertainties, the estimates suggest that the economic value of planned improvements in ENSO forecasts may be substantial for world economies – in the billions of dollars. Economic information from the kinds of studies described above, when combined with cost estimates to achieve this increase in forecast accuracy, can help inform the policy debate in investments in more accurate global weather monitoring and forecast systems by national and international agencies. In a global economy where a drought in one part of the world affects the economy in another, it is important to all of us that governments make funds available for these types of initiatives.