Evaluation of Forecast Performance of Asian Summer Monsoon Low-Level Winds Using the TIGGE Dataset

Abstract

he forecast performances of the East Asian summer monsoon (EASM) and South Asian summer monsoon (SASM) by six THORPEX Interactive Grand Global Ensemble (TIGGE) centers during the summers of 2008?13 were evaluated to reflect the current predictability of state-of-the-art numerical weather prediction. The results show that the EASM is overestimated by all TIGGE centers except the Canadian Meteorological Centre (CMC). The SASM is overestimated by the European Centre for Medium-Range Weather Forecasts (ECMWF), the China Meteorological Administration (CMA), and the CMC, but is underpredicted by the Japan Meteorological Agency (JMA). Additionally, the SASM is overestimated for early lead times and underestimated for longer lead times by the National Centers for Environmental Prediction (NCEP) and the Met Office (UKMO). Further analysis suggests that such biases are likely associated with land?sea thermal contrasts. The EASM surge is overestimated by the NCEP and CMA and mainly underestimated by the others. The bias predictabilities for the SASM surge are similar to those of the SASM. The peaks of the SASM and EASM, including their surges, are mainly underestimated, whereas the valleys are mostly overestimated. Overall, the ECMWF and UKMO have the highest forecast skill in predicting the SASM and EASM and both have respective advantages. The TIGGE centers generally show higher skill in predicting the SASM than the EASM, and their skill in forecasting the SASM and EASM is superior to that for their respective surges. Moreover, bias-correction forecast skills show improvement with higher correlation coefficients in raw forecast verification.