The Long View of Weather: Learning How to Read the Climate Several Seasons in Advance
Monastersky, Richard, Science News
Chaos in the atmosphere bedevils weather forecasters. Their primary tool, complex computer models, can look only a few days into the future before countless winds and eddies sweep away any chance of making a skillful prediction. Even if meteorologists had access to an infinitely powerful supercomputer, they could not hope to forecast rain or shine a month ahead of time. The atmosphere is simply too turbulent.
But if they surrender the idea of making specific predictions, meteorologist may succeed in buying some time in the forecasting game. With that possibility in mind, several research groups are now testing experimental approaches designed to anticipate general climatic conditions as much as a year in advance. If such a strategy works, it could warn farmers to expect a withering drought or the kind of persistent rains that flooded the midwestern United States last summer.
"I think this is going to revolutionize the way we think about forecasting. The concept of long-lead forecasting for a region is something that people haven't really worked with before," says David Rodenhuis, chief of the National Weather Service's Climate Analysis Center (CAC). From its home in Camp Springs, Md., the CAC makes the monthly and seasonal outlooks issued by the weather service.
The experimental schemes for long-range forecasting have evolved out of recent advances in understanding the behavior of Earth's climate, particularly that beast known as El Nino -- an occasional warming in the tropical Pacific that develops every four to seven years. Scientists have learned that El Nino and its cool counterpart, La Nina, exert influences far beyond their local neighborhood. Like a rock dropped into a pond, the Pacific's hot and cold spells send ripples spreading through the world's atmosphere, altering weather around much of the globe. For instance, the El Nino that simmered earlier this year inundated southern California with unusually heavy winter rains but dried out northeastern Brazil. The warming even contributed to the summer floods in the Midwest.
In strength, this El Nino pales in comparison to the biggest of the century, which struck in 1982 and 1983. The record warmth in the equatorial Pacific those years redirected normal jet stream patterns, generating floods and droughts that left thousands dead worldwide and caused more than $13 billion in damages.
Spurred by that event, 18 countries invested in a decade of research aimed at understanding how the Pacific waters and atmosphere conspire to bring about El Ninos and La Ninas. As part of this project, called the Tropical Ocean Global Atmosphere (TOGA) Study, scientists have developed computer models for predicting when the tropical Pacific will swing toward warm or cool temperatures. Nature still has the upper hand, however, having fooled almost all of them last year and perhaps again this year with a subtle El Nino that was difficult to anticipate (see box). But major warmings and coolings advertise themselves much more openly, and the models have started to exhibit skill at detecting such events as many as 12 to 18 months ahead of their actual arrival.
Piggybacking on that success, researchers are now looking beyond simple El Nino predictions to forecasts of how these disturbances in the Pacific will actually disrupt weather in the United States and other parts of the globe.
Just down the hall from Rodenhuis' office, Ants Leetmaa is developing a long-range forecasting strategy for the U.S. weather service. Leetmaa uses a tool called a coupled global circulation model (GCM), which simulates how streams in the oceans and atmosphere shuttle heat and moisture around the planet. The model starts with a portrait of the current weather and then projects how temperature, wind speed, precipitation, and other factors will vary with time.
To make a nine-month forecast for the United States, Leetmaa would ideally feed the necessary meteorological measurements into the computer, let the model spin through 270 simulated days, then examine the picture that developed. …