Quantifying overlapping and differing information of global precipitation for GCM forecasts and El Niño–Southern Oscillation

Abstract

While El Niño–Southern Oscillation (ENSO) teleconnection has long been used in statistical precipitation forecasting, global climate models (GCMs) provide increasingly available dynamical precipitation forecasts for hydrological modeling and water resources management. It is not yet known to what extent dynamical GCM forecasts provide new information compared to statistical teleconnection. This paper develops a novel set operations of coefficients of determination (SOCD) method to explicitly quantify the overlapping and differing information for GCM forecasts and ENSO teleconnection. Specifically, the intersection operation of the coefficient of determination derives the overlapping information for GCM forecasts and the Niño3.4 index, and then the difference operation determines the differing information in GCM forecasts (Niño3.4 index) from the Niño3.4 index (GCM forecasts). A case study is devised for the Climate Forecast System version 2 (CFSv2) seasonal forecasts of global precipitation in December–January–February. The results show that the overlapping information for GCM forecasts and the Niño3.4 index is significant for 34.94 % of the global land grid cells, that the differing information in GCM forecasts from the Niño3.4 index is significant for 31.18 % of the grid cells and that the differing information in the Niño3.4 index from GCM forecasts is significant for 11.37 % of the grid cells. These results confirm the effectiveness of GCMs in capturing the ENSO-related variability of global precipitation and illustrate where there is room for improvement of GCM forecasts. Furthermore, the bootstrapping significance tests of the three types of information facilitate in total eight patterns to disentangle the close but divergent associations of GCM forecast correlation skill with ENSO teleconnection.