Climate Forecasts: A Vital Tool for Policymakers

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May2013_Forecast_15July2013

This map shows a seasonal probability forecast for precipitation in South America issued in May 2013. The data depict the probability that rainfall in a given region will be below-normal, normal, or above-normal over the ensuing three months – in this case, June, July, and August. The International Research Institute for Climate and Society (IRI) issues these forecasts monthly, and has done so for more than a decade.  Recent efforts have focused on documenting the value of this type of forecast for decision making. The case of Uruguay in December 2010 is a notable example.

At the time, reports showed that many areas of Uruguay were headed for drought, based on data from a number of organizations indicating low estimates of available water in the soils in these areas. The IRI seasonal precipitation forecast map issued in November 2010 showed that these at-risk areas of the country were likely to experience less rainfall than normal in the following months, further contributing to drought conditions. In response to the combined data and forecasts, the Uruguayan government declared a State of Emergency and quickly directed interventions to address the crisis and mitigate the potential consequences.

Map showing drought conditions in Uruguay, winter, 2010

The government of Uruguay used this map and others like it as inputs for policy decisions, including the declaration of a State of Emergency, based on forecast of continuing drought conditions in winter of 2010.

The probability forecast maps issued by the IRI can be a powerful tool for policy and decision makers concerned with agriculture, energy, water, and other climate-sensitive sectors. Focusing on near-term probabilities can also aid in decreasing vulnerability to future climate uncertainties. For example, a new project in Uruguay funded by the World Bank and the International Development Bank will address potential vulnerabilities to future climate variability and change (mainly temperature and rainfall) by focusing on assessment of and adaptation to current climate-related vulnerabilities. The IRI’s role in the project, beginning this summer 2013, will be to incorporate seasonal forecasts in order to improve current monitoring and early warning abilities in Uruguay. Although efforts are not exclusively focused on agriculture, this is the area of main focus– the agricultural sector has a multiplying factor of three on the country’s economy (in other words, a one million dollar impact on the agricultural sector results in three million dollars damage to the economy).

As temperature and rainfall probabilities change in conjunction with climate change, it will become even more critical to use forecasts to guide decisions in a range of economic sectors—so that society will be able to maximize the benefits and reduce the impacts of both short- and long-term climate variability and change.

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This blog is part of the Map of the Month blog series produced by the Center for International Earth Science Information Network (CIESIN), this month featuring work by the International Research Institute for Climate and Society. Text was provided by the IRI senior research scientist Walter Baethgen, with communications coordinator Elisabeth Sydor. The map was adapted by geographic information specialists Linda Pistolesi and Tricia Chai-Onn.

 

 

 

 

 

 

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One Response to “Climate Forecasts: A Vital Tool for Policymakers”

  1. Dang tin viec lam says:

    The analogy I like to use is with gambling in a casino. There’s no way to predict if you’ll win a given bet, or come out ahead on a given day or a given week. But if you play long enough, it’s a pretty safe prediction that you’ll end up losing money. Or with the stock market – it can do anything on a given day or given week. But over the long-term, it’s a safe bet that it will go up.

    The long-term predictions are easier to make because the short-term noise becomes less prevalent the longer you look into the future.

    What deniers like eric don’t understand – because they don’t want to understand it, because they need AGW to be wrong – is that climate models don’t make projections over timespans of less than a decade. Over those short periods, short-term effects like ENSO, which are impossible to predict, dominate. The reason the planet hasn’t warmed much over the last 8 years is that there have been mostly La Niña cycles over that period. No, climate models didn’t predict that. Nor did they attempt to.

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