Tuesday, 11 February 2003: 9:30 AM
Temporal disaggregation of probabilistic seasonal climate forecasts
Seasonal climate forecasts are issued by NOAA/CPC for average temperature and total precipitation over 3-month overlapping periods covering the coming year. Many crop and hydrologic models employ weather generators based on monthly statistics to produce stochastic realizations of daily weather (e.g., air temperature, precipitation, solar radiation). To make the forecasts immediately useful for applications employing weather generators, the forecasts for 3-month periods need to be disaggregated into 1-month, non-overlapping increments. Previous approaches based on algebraic inversion of the overlapping forecast sequence have produced unrealistic results, with strong forecast anomalies erroneously propagating into periods with zero forecast anomalies. These unphysical results are a consequence of the manner in which the forecasts are generated at this time, and will be characteristic of all such algebraic inversions. As an alternative approach to the problem, heuristic approaches to the disaggregation have been developed that produce physically plausible sequences of 1-month non-overlapping forecasts, which also re-aggregate to a good approximation of the original sequence of 3-month overlapping forecasts. Two heuristic approaches to disaggregation of 3-month overlapping seasonal climate forecasts are presented with illustrative examples.