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Seasonal Rainfall Forecasts for the Yangtze River Basin of China in Summer 2019 from an Improved Climate Service

Authors :
Min Liu
Peiqun Zhang
Nicola Martin
Nick Dunstone
Ying Liu
Leon Hermanson
Philip E. Bett
Nicola Golding
Hong-Li Ren
Joanne Camp
Chaofan Li
Chris Hewitt
Adam A. Scaife
Gill Martin
Source :
Journal of Meteorological Research. 34:904-916
Publication Year :
2020
Publisher :
Springer Science and Business Media LLC, 2020.

Abstract

Rainfall forecasts for the summer monsoon season in the Yangtze River basin (YRB) allow decision-makers to plan for possible flooding, which can affect the lives and livelihoods of millions of people. A trial climate service was developed in 2016, producing a prototype seasonal forecast product for use by stakeholders in the region, based on rainfall forecasts directly from a dynamical model. Here, we describe an improved service based on a simple statistical downscaling approach. Through using dynamical forecast of an East Asian summer monsoon (EASM) index, seaso-nal mean rainfall for the upper and middle/lower reaches of YRB can be forecast separately by use of the statistical downscaling, with significant skills for lead times of up to at least three months. The skill in different sub-basin regions of YRB varies with the target season. The rainfall forecast skill in the middle/lower reaches of YRB is significant in May–June–July (MJJ), and the forecast skill for rainfall in the upper reaches of YRB is significant in June–July–August (JJA). The mean rainfall for the basin as a whole can be skillfully forecast in both MJJ and JJA. The forecasts issued in 2019 gave good guidance for the enhanced rainfall in the MJJ period and the near-average conditions in JJA. Initial feedback from users in the basin suggests that the improved forecasts better meet their needs and will enable more robust decision-making.

Details

ISSN :
21980934 and 20956037
Volume :
34
Database :
OpenAIRE
Journal :
Journal of Meteorological Research
Accession number :
edsair.doi...........fe431d06add03f171c5a889b6b16df77
Full Text :
https://doi.org/10.1007/s13351-020-0049-z