Long-range forecasting in support of operations in Pakistan
DeHart, Jeremy A.
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Skillful long-range forecasts (LRFs; leads times of several weeks or longer) are a critical component of mission planning for both military and nonmilitary operations. This is especially true for countries that are susceptible to persistent climate variations, such as Pakistan. The environmental, economic, and political impacts of climate variations can be severe--particularly for countries that are economically and politically unstable, or at risk of such instability. The United States (U.S.) has characterized stability in Pakistan as a priority for U.S. national security. These considerations led us to investigate the potential for skillful LRFs of climate variations in Pakistan summer precipitation. These variations can lead to floods and droughts, and major economic impacts, as demonstrated by, for example, the extreme flooding in the summer of 2010. In this study, we developed methods for long-range forecasting of Pakistan precipitation during the main precipitation period of July-August. We investigated the correlations between regional and global scale climate variables and Pakistan precipitation to identify the processes associated with extreme summer precipitation events in Pakistan. From these correlations, we identified a set of 850 hecto-Pascal (hPa) geopotential heights (GPH) in the region surrounding Pakistan as a potentially skillful predictor. We developed several LRF approaches based on this predictor and linear regression, tercile matching, and optimal climate normal methods. We tested these approaches by conducting independent hindcasts for the 41-year period of 1970-2010, and found good skill in predicting above and below normal precipitation events. We also determined that using sea surface temperatures (SSTs) as a predictor of the 850 hPa heights has the potential to provide skillful LRFs of Pakistan July-August precipitation at lead times out to six months or longer. We propose that additional research be conducted using statistical and statistical-dynamical forecast methods to develop and validate a long-range forecasting system for operational use.
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