A new algorithm for seasonal precipitation forecast based on global atmospheric hydrological water budget

Abstract

Precipitation forecast has been identified as one of the central issues in climate research. However, the underlying mechanisms of precipitation are far from being understood. In this paper, a new algorithm of forecasting precipitation based on law of conservation of mass in hydrological cycle is proposed and its feasibility is verified. The algorithm mainly include three steps: in the first step, the area we employ is divided into a number of sub-areas, the precipitation source and evaporation whereabouts equations for sub-regions are established, and the rationality of them can be verified by checking whether the precipitation source and evaporation equations meet a self-consistent relationship or not; in the second step, a conversion equation for sub-regional precipitation prediction will be established, which characterize the relationship between precipitation and evaporation in the sub-areas; in the last step, if the regional evaporation, precipitation and moisture divergence (convergence) function keep stable in a certain time scale, then precipitation forecast is achieved by evaporation anomalies and moisture divergence function, which can be predicted according to the prophase sea surface temperature and atmospheric circulation. Finally, the northern and southern hemispheres seasonal precipitation, evaporation and moisture divergence (convergence) weighting coefficients are calculated using this algorithm based on European centre for medium-range weather forecasts (ECMWF) interim re-analysis (ERA-Interim) dataset, which well verifies the feasibility of the algorithm. The obtained results may provide new insights for precipitation forecast in the future. © 2015 Elsevier Inc. All rights reserved.

DOI: 10.1016/j.amc.2015.06.059

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Cite this paper

@article{Wu2015ANA, title={A new algorithm for seasonal precipitation forecast based on global atmospheric hydrological water budget}, author={Yong-Ping Wu and Guo-Lin Feng}, journal={Applied Mathematics and Computation}, year={2015}, volume={268}, pages={478-488} }