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GCM Predictions of North India Winter Precipitation for Its Crops

Paper Reviewed
Tiwari, P.R., Kar, S.C., Mohanty, U.C., Kumari, S., Sinha, P., Nair, A. and Dey, S. 2014. Skill of precipitation prediction with GCMs over north India during winter season. International Journal of Climatology 34: 3440-3455.

The northern part of India - known as the wheat bowl - receives most of its precipitation during the winter season, which moisture, in the words of Tiwari et al. (2014), "is critically important for the agriculture and economy of the country." And in light of these facts, they conducted a study designed to determine whether five different general circulation models or GCMs were capable of correctly forecasting the strength of this important seasonal weather phenomenon. More specifically, they compared GCM outputs (seasonal mean precipitation forecasts issued in November) produced by various organizations with observed high-resolution gridded rainfall data that they obtained from the India Meteorological Department for the period 1982-2009. And what did they thereby learn?

The seven scientists report that (1) "skill of predictions is too low," that (2) "most of the GCMs do not respond to sea surface temperature variability over the Pacific in a realistic manner," that (3) "only two of the five GCMs get the observed simultaneous teleconnection correctly," that (4) "only one of these two models has the observed phase lag with the strongest correlation as observed," that (5) "the GCMs in general underestimate the observed climatology and inter-annual variability of precipitation," that (6) "none of the models is able to depict the observed inter-annual variability correctly," and that (7) "a simple multi-model ensemble approach with all the models getting the same weight does not improve much the forecast skill."

Clearly, the "seven sins" of the five GCMs have yet to be blotted out by appropriate redemptive actions, and, clearly, present-day general circulation models are not up to the task of providing what is needed to properly project future yields in this important food producing region.

Posted 9 February 2015