Copula-based uncertainty modelling: application to multisensor precipitation estimates

The multisensor precipitation estimates (MPE) data, available in hourly temporal and 4 km × 4 km spatial resolution, are produced by the National Weather Service and mosaicked as a national product known as Stage IV. The MPE products have a significant advantage over rain gauge measurements due to their ability to capture spatial variability of rainfall. However, the advantages are limited by complications related to the indirect nature of remotely sensed precipitation estimates. Previous studies confirm that efforts are required to determine the accuracy of MPE and their associated uncertainties for future use in hydrological and climate studies. So far, various approaches and extensive research have been undertaken to develop an uncertainty model. In this paper, an ensemble generator is presented for MPE products that can be used to evaluate the uncertainty of rainfall estimates. Two different elliptical copula families, namely, Gaussian and t-copula are used for simulations. The results indicate that using t-copula may have significant advantages over the well-known Gaussian copula particularly with respect to extremes. Overall, the model in which t-copula was used for simulation successfully generated rainfall ensembles with similar characteristics to those of the ground reference measurements. Copyright