A dataset representing more than 30 years of quasi-global rainfall can serve as an early warning system for drought, making it easier to aid people in developing countries. The dataset, developed at the University of California at Santa Barbara, is called CHIRPS (for Climate Hazards Group InfraRed Precipitation with Station data). It spans 50° S to 50° N latitudes (and all longitudes), incorporates 0.05° resolution satellite imagery with in situ station data.
In Ensia, Eric Holthaus writes, “The global rich have stable governments, savings accounts, insurance, and more to fall back on when disaster strikes. People in poorer countries don’t, so they’re often faced with tough decisions in times of drought: Sell the only ox for food and plow by hand next year? Take the kids out of school and put them to work chopping firewood for extra cash? Abandon the farm and family to look for work in the city?”
CHIRPS, he adds, can help development agencies respond more effectively to impending drought conditions to “…more effectively activate adaptive strategies such as food aid and insurance.”
Holthaus notes that the dataset combines information from sources ranging from satellites to dusty paper records from old weather stations.
Of course, identifying impending drought conditions doesn’t solve the related problems. Holthaus quotes Pete Peterson, a developer of the dataset, as saying, “Now, we can accurately identify how horrible things are.” The next step is targeting appropriate assistance.
Holthaus reports that Chris Funk, one of Peterson’s colleagues, had worked in Ethiopia in the early 2000s for the U.S. Agency for International Development’s Famine Early Warning System Network (FEWS NET). The experience led him to recognize the importance of early warnings in helping aid agencies respond quickly.
For example, writes Holthaus, forecasts last May suggested El Niño could shift Ethiopia into drought conditions, allowing organizations ranging from the United Nations to Oxfam to respond.
He adds that the dataset can help subsistence farmers buy insurance against the effects of drought. The problem up to now is that the data necessary to accurately set rates and determine payouts has been lacking.
