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Relating anomaly correlation to lead time: Clustering analysis of CFSv2 forecasts of summer precipitation in China
2017
Journal of Geophysical Research - Atmospheres
Global climate model (GCM) forecasts are an integral part of long-range hydroclimatic forecasting. We propose to use clustering to explore anomaly correlation, which indicates the performance of raw GCM forecasts, in the three-dimensional space of latitude, longitude, and initialization time. Focusing on a certain period of the year, correlations for forecasts initialized at different preceding periods form a vector. The vectors of anomaly correlation across different GCM grid cells are
doi:10.1002/2017jd027018
fatcat:2frugvrasbaojo4frscudctpqe