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| 1 | Seasonal Rainfall Forecasts for the Yangtze River Basin of China in Summer 2019 from an Improved Climate Service显示文摘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, seasonal 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. | Philip E.BETT Nicola MARTIN Adam A.SCAIFE Nick DUNSTONE Gill M.MARTIN Nicola GOLDING Joanne CAMP Peiqun ZHANG Chris D.HEWITT Leon HERMANSON Chaofan LI Hong-Li REN Ying LIU Min LIU | 2020 | Journal of Meteorological Research2020，34，5： | 7 |
| 2 | Predictability of the Western North Pacific Subtropical High Associated with Different ENSO Phases in GloSea5显示文摘The western North Pacific subtropical high(WNPSH) dominates the summer climate over East Asia. The intensity,position, and shape of WNPSH influence the spatiotemporal distributions of precipitation, temperature, and tropical cyclone activities in this region. This paper intends to investigate the performance of the UK Met Office Global Seasonal forecast system version 5(GloSea5) in simulation/prediction of the WNPSH based on a hindcast dataset. Analyses of the hindcast data show a systematic bias in the mean circulation over West Pacific, with negative geopotential height anomalies over the western North Pacific(WNP) and cyclonic anomalies in the 850-hPa winds and water vapor transport, indicating a weakening and eastward shift of the WNPSH. Despite the model’s bias in the climatology, it well captured the interannual variability of the monthly and seasonal-mean intensity of the WNPSH and the position of its ridge line in boreal summer from 1993 to 2015. The seasonal hindcasts indicate that there is significant prediction skill at up to three-month lead time for both the intensity and position of the WNPSH ridge line. The relationship between the WNPSH and different phases of the El Nino–Southern Oscillation(ENSO) in both the observational data and GloSea5 hindcasts was then investigated. The model captured the summer WNPSH anomalies well during most of the ENSO phases, except in the La Nina decaying and neutral summers. The intensity of the anticyclone in the WNP is weak in the decaying phase of El Nino in the GloSea5 hindcasts compared with the reanalysis data. GloSea5 is capable of representing the lagged teleconnection between El Nino events in the previous winter and the intensity of the WNPSH in the following summer. Regression analysis reveals weakened negative sea surface temperature anomalies(SSTAs) over the WNP in GloSea5, which reduced the gradient between the tropical western Pacific and the tropical Indian Ocean, resulting in a weaker easterly anomaly and stronger westerly anomaly, contributing to the weak anomalous anticyclone over the WNP and the weakened WNPSH relative to the reanalysis data. | Daquan ZHANG Gill M.MARTIN Jose MRODRIGUEZ Zongjian KE Lijuan CHEN | 2020 | Journal of Meteorological Research2020，34，5： | 2 |
| 3 | Erratum to: Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin显示文摘The article[Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin],written by[Gill M.MARTIN,Nick J.DUNSTONE,Adam A.SCAIFE,and Philip E.BETT],was originally published electronically on the publisher’s internet portal on[10 December 2019]without open access. | Gill M.MARTIN Nick J.DUNSTONE Adam A.SCAIFE Philip E.BETT | 2020 | Advances in Atmospheric Sciences2020，37，9： | 1 |
| 4 | Predicting June Mean Rainfall in the Middle/Lower Yangtze River Basin显示文摘We demonstrate that there is significant skill in the GloSea5 operational seasonal forecasting system for predicting June mean rainfall in the middle/lower Yangtze River basin up to four months in advance.Much of the rainfall in this region during June is contributed by the mei-yu rain band.We find that similar skill exists for predicting the East Asian summer monsoon index(EASMI)on monthly time scales,and that the latter could be used as a proxy to predict the regional rainfall.However,there appears to be little to be gained from using the predicted EASMI as a proxy for regional rainfall on monthly time scales compared with predicting the rainfall directly.Although interannual variability of the June mean rainfall is affected by synoptic and intraseasonal variations,which may be inherently unpredictable on the seasonal forecasting time scale,the major influence of equatorial Pacific sea surface temperatures from the preceding winter on the June mean rainfall is captured by the model through their influence on the western North Pacific subtropical high.The ability to predict the June mean rainfall in the middle and lower Yangtze River basin at a lead time of up to 4 months suggests the potential for providing early information to contingency planners on the availability of water during the summer season. | Gill M.MARTIN Nick J.DUNSTONE Adam A.SCAIFE Philip E.BETT | 2020 | Advances in Atmospheric Sciences2020，37，1： | 1 |
| 5 | Seasonal Rainfall Forecasts for the Yangtze River Basin in the Extreme Summer of 2020显示文摘Seasonal forecasts for Yangtze River basin rainfall in June,May–June–July(MJJ),and June–July–August(JJA)2020 are presented,based on the Met Office GloSea5 system.The three-month forecasts are based on dynamical predictions of an East Asian Summer Monsoon(EASM)index,which is transformed into regional-mean rainfall through linear regression.The June rainfall forecasts for the middle/lower Yangtze River basin are based on linear regression of precipitation.The forecasts verify well in terms of giving strong,consistent predictions of above-average rainfall at lead times of at least three months.However,the Yangtze region was subject to exceptionally heavy rainfall throughout the summer period,leading to observed values that lie outside the 95%prediction intervals of the three-month forecasts.The forecasts presented here are consistent with other studies of the 2020 EASM rainfall,whereby the enhanced mei-yu front in early summer is skillfully forecast,but the impact of midlatitude drivers enhancing the rainfall in later summer is not captured.This case study demonstrates both the utility of probabilistic seasonal forecasts for the Yangtze region and the potential limitations in anticipating complex extreme events driven by a combination of coincident factors. | Philip E.BETT Gill M.MARTIN Nick DUNSTONE Adam A.SCAIFE Hazel E.THORNTON Chaofan LI | 2021 | Advances in Atmospheric Sciences2021，38，12： | 1 |
| 6 | Predictability of South China Sea Summer Monsoon Onset显示文摘Predicting monsoon onset is crucial for agriculture and socioeconomic planning in countries where millions rely on the timely arrival of monsoon rains for their livelihoods. In this study we demonstrate useful skill in predicting year-to-year variations in South China Sea summer monsoon onset at up to a three-month lead time using the GloSea5 seasonal forecasting system. The main source of predictability comes from skillful prediction of Pacific sea surface temperatures associated with El Ni?no and La Ni?na. The South China Sea summer monsoon onset is a known indicator of the broadscale seasonal transition that represents the first stage of the onset of the Asian summer monsoon as a whole. Subsequent development of rainfall across East Asia is influenced by subseasonal variability and synoptic events that reduce predictability, but interannual variability in the broadscale monsoon onset for East Asian summer monsoon still provides potentially useful information for users about possible delays or early occurrence of the onset of rainfall over East Asia. | Gill M.MARTIN Amulya CHEVUTURI Ruth E.COMER Nick J.DUNSTONE Adam A.SCAIFE Daquan ZHANG | 2019 | Advances in Atmospheric Sciences2019，36，3： | 1 |
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