Preprint Article Version 1 This version is not peer-reviewed

Improving Seasonal Prediction of East Asian Summer Rainfall: Experiments with NESM3.0

Version 1 : Received: 29 August 2018 / Approved: 29 August 2018 / Online: 29 August 2018 (13:42:45 CEST)

A peer-reviewed article of this Preprint also exists.

Yang, Y.-M.; Wang, B.; Li, J. Improving Seasonal Prediction of East Asian Summer Rainfall Using NESM3.0: Preliminary Results. Atmosphere 2018, 9, 487. Yang, Y.-M.; Wang, B.; Li, J. Improving Seasonal Prediction of East Asian Summer Rainfall Using NESM3.0: Preliminary Results. Atmosphere 2018, 9, 487.

Journal reference: Atmosphere 2018, 9, 487
DOI: 10.3390/atmos9120487

Abstract

It has been an outstanding challenge for global climate models to simulate and predict East Asia (EA) summer monsoon (EASM) rainfall. This study evaluates the dynamical hindcast skills with the newly developed Nanjing University of Information Science and Technology Earth System Model version 3.0 (NESM3.0). To improve the poor prediction of an earlier version of NESM3.0, we have modified convective parameterization schemes to suppress excessive deep convection and enhance insufficient shallow and stratiform clouds. The new version of NESM3.0 with modified parameterizations (MOD hereafter) yields significantly improved rainfall prediction in the northern and southern China but not over the Yangtze River Valley. The improved prediction is primarily attributed to the improvements in the predicted climatological summer mean rainfall and circulations, seasonal march of the subtropical rain belt, Nino 3.4 SST anomaly, and the rainfall anomalies associated with the development and decay of El Nino events. However, the MOD still has notable biases in the predicted leading mode of interannual variability of precipitation. The leading mode captures the dry (wet) anomalies over the South China Sea (northern EA) but misplaced precipitation anomalies over the Yangtze River Valley. The model can capture the interannual variation of the circulation indices very well, but the bias in the circulation-rainfall connection caused predicted rainfall errors. The results here suggest that over EA land regions, the skillful rainfall prediction relies on not only model’s capability in predicting better summer mean and seasonal march of rainfall and ENSO teleconnection with EASM, but also accurate prediction of the leading modes of interannual variability.

Subject Areas

East Asian summer monsoon, Seasonal prediction, dynamic prediction, summer rainfall prediction, NESM3.0, ENSO teleconnection

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