Understanding Past Weather to Improve Future Predictions
| Gilbert Compo, Jeffrey Whitaker, Prashant Sardeshmukh Science Writer: Barb DeLuisi |
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Introduction |
Climate change on Earth and its possible causes have become major "hot topics" of scientific research over the past few decades. Recently, climate researchers have come to realize that in order to better understand changes in our global climate, we must improve our understanding the day-to-day weather variations. Many important things could be learned from analyzing our past climate over a period of at least 100 years. Unfortunately, there is not a lot of accurate global climate data beyond the past 60 years. So what's a researcher to do? One solution is to compile the scant observations that are available and combine them using physical relationships to produce a more extensive and improved dataset. By analyzing these data, it might be possible to figure out the patterns in the atmosphere that created past weather conditions. Although this idea initially had skeptics, researchers Gilbert Compo, Jeffrey Whitaker, and Prashant Sardeshmukh of the Earth System Research Laboratory and CIRES set out to prove that it might work. Why? With the availability of more accurate data, better computer simulations of past climate and weather can be made. This information could be used to study how and why our climate has changed. Or it could be used to examine "climate catastrophes," such as the Dust Bowl of the 1930s, figure out why they happened, and determine whether they are likely to happen more frequently as the climate changes.
The idea of studying the past weather from the historical observations seems like a logical approach, so why hasn't it been done before? First of all, the needed technology didn't exist. Luckily, our modern weather prediction tools have advanced enough to make this a possibility. Second, we did not have the daily observational data in a digital format.
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