Climate Data in the News: Afghanistan Drought

By Elisabeth Gawthrop

An article last week from Stars and Stripes reports on recent migration within Afghanistan, citing violence and drought as the main drivers forcing people in northwestern Afghanistan to flee the countryside for the outskirts of Herat, the third largest city in the country.

The story includes commentary from IRI’s Colin Kelley, a climate scientist who has studied the links between drought and conflict in Syria and the Fertile Crescent. Kelley notes in the story that severe droughts can cause displacement and potentially conflict, particularly in agrarian societies strongly dependent on rainfall. The story also provides examples of possible feedback between conflict and drought specific to Afghanistan, such as soldiers deserting the Afghan National Security Forces if they aren’t getting enough to eat.

Wheat is a major crop in Afghanistan, and in the country’s northwestern region much of it is grown during the winter rainy season from November to May. Farmers in the story say they lost their crops and livestock due to dry conditions during the 2017–18 wet season, in addition to floods late in the season that provided too little too late and led to deaths of both people and livestock. Analysts are predicting low crop yields this year across the country, the article noted.

So, what does climate data show about the dry conditions reported in the story? Using the IRI Data Library, I pulled the three-month Standardized Precipitation Index (SPI) for the region over the course of the rainy season:

Brown shades indicate drier-than-normal conditions, green shades indicate wetter-than-normal conditions. Data source: NOAA NCEP Climate Prediction Center, CAMS_OPI. Map and details available through the IRI Data Library here.

The SPI normalizes rainfall data according to the average rainfall in an area. This allows you to look at different areas regardless of their climate — if you were looking just at a deviation from average in millimeters, it may not be obvious whether that deviation is significant or not. For example, being 30mm below a monthly average of 50mm would be rather dry. But falling 30mm short if your monthly average is 200mm is less of a deficit. The SPI takes this into account.

When looking for evidence of drought, it’s generally good practice to use three-month averages instead of shorter timescales, since drought is typically the product of dry conditions over several months’ time. But, sometimes it’s useful to know if a critical time period in a crop cycle, for example the month when a crop is typically planted, was below average in terms of rainfall.

It’s also a good idea to compare several datasets if available. Particularly in countries with fewer resources and those with conflict, weather data may not be frequently reported, or there are may be swaths of land without a weather station. Without enough quality data, rainfall estimates can be inaccurate. Comparing several datasets is one way to get an indication of the uncertainty of the rainfall estimates that are available.

Here’s a look at October 2017 to April 2018 in Afghanistan and the surrounding region, month by month, using a different dataset from the figure above and using mm/month instead of SPI for units:

Brown shades indicate drier-than-normal conditions, green shades indicate wetter-than-normal conditions. Data source: UCSB CHIRPS v2p0. Map and details available through the IRI Data Library here.

The two datasets can’t be directly compared, since they use different units and a different timescale, but both indicate dryness, especially in the north and western portions of the country and during the beginning and middle of the season.

Did forecasts see the dry conditions coming? Yes and no. Here’s the seasonal forecast for January — March 2018, issued in December 2017:

Yellow to brown shades indicate likelihood for drier-than-normal conditions, green to blue shades indicate likelihood for wetter-than-normal conditions. Accessed here.

The forecast caught some of the dry conditions in the north, but not the dry conditions indicated in the southwest by both of the observational datasets. The November forecast of the December — February period showed only a slight chance of below-average in the north, while the October forecast of the November — January period looked similar to the forecast shown above. (See all forecasts on our site.)

The above figures are not a complete analysis of the drought situation. A report from the UN Food and Agriculture Organization last year indicates food security was already an issue last fall. Looking at longer term climate data would provide additional context for the severity of the recent reported drought.

If you see a climate impact in the news and have a question about the climate data related to that impact, send an email to media@iri.columbia.edu.

P.S. If you’re interested in using the IRI Data Library to download maps, here’s a quick example using the SPI dataset. The maps are downloadable as PDFs (editable in Adobe Illustrator), KML, GeoTIFF and other image formats.

Written by

International Research Institute for Climate & Society uses climate science to benefit society. Tweets by @fiondella & @egawthrop. http://facebook.com/climatesociety

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