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Seasonal Rainfall Forecasts for the Yangtze River Basin of China in Summer 2019 from an Improved Climate Service
- 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.
- Subjects :
- 010504 meteorology & atmospheric sciences
media_common.quotation_subject
Flooding (psychology)
Flood forecasting
Forecast skill
Structural basin
010502 geochemistry & geophysics
01 natural sciences
Climatology
Service (economics)
Yangtze river
Environmental science
China
0105 earth and related environmental sciences
media_common
Downscaling
Subjects
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