Journal article

On the Joint Calibration of Multivariate Seasonal Climate Forecasts from GCMs

Andrew Schepen, Yvette Everingham, Quan J Wang

Monthly Weather Review | American Meteorological Society | Published : 2020


Multivariate seasonal climate forecasts are increasingly required for quantitative modeling in support of natural resources management and agriculture. GCM forecasts typically require postprocessing to reduce biases and improve reliability; however, current seasonal postprocessing methods often ignore multivariate dependence. In low-dimensional settings, fully parametric methods may sufficiently model intervariable covariance. On the other hand, empirical ensemble reordering techniques can inject desired multivariate dependence in ensembles from template data after univariate postprocessing. To investigate the best approach for seasonal forecasting, this study develops and tests several stra..

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University of Melbourne Researchers