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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 | The Seasonal Prediction of the Exceptional Yangtze River Rainfall in Summer 2020显示文摘During June and July of 2020,the Yangtze River basin suffered from extreme mei-yu rainfall and catastrophic flooding.This study explores the seasonal predictability and associated dynamical causes for this extreme Yangtze River rainfall event,based on forecasts from the Met Office GloSea5 operational forecast system.The forecasts successfully predicted above-average rainfall over the Yangtze River basin,which arose from the successful reproduction of the anomalous western North Pacific subtropical high(WNPSH).Our results indicate that both the Indian Ocean warm sea surface temperature(SST)and local WNP SST gradient were responsible for the westward extension of the WNPSH,and the forecasts captured these tropical signals well.We explore extratropical drivers but find a large model spread among the forecast members regarding the meridional displacements of the East Asian mid-latitude westerly jet(EAJ).The forecast members with an evident southward displacement of the EAJ favored more extreme Yangtze River rainfall.However,the forecast Yangtze River rainfall anomaly was weaker compared to that was observed and no member showed such strong rainfall.In observations,the EAJ displayed an evident acceleration in summer 2020,which could lead to a significant wind convergence in the lower troposphere around the Yangtze River basin,and favor more mei-yu rainfall.The model forecast failed to satisfactorily reproduce these processes.This difference implies that the observed enhancement of the EAJ intensity gave a large boost to the Yangtze River rainfall,hindering a better forecast of the intensity of the event and disaster mitigation. | Chaofan LI Riyu LU Nick DUNSTONE Adam ASCAIFE Philip EBETT Fei ZHENG | 2021 | Advances in Atmospheric Sciences2021，38，12： | 5 |
| 3 | Seasonal Forecasts of the Summer 2016 Yangtze River Basin Rainfall显示文摘The Yangtze River has been subject to heavy flooding throughout history,and in recent times severe floods such as those in 1998 have resulted in heavy loss of life and livelihoods.Dams along the river help to manage flood waters,and are important sources of electricity for the region.Being able to forecast high-impact events at long lead times therefore has enormous potential benefit.Recent improvements in seasonal forecasting mean that dynamical climate models can start to be used directly for operational services.The teleconnection from El Ni ?no to Yangtze River basin rainfall meant that the strong El Ni ?no in winter 2015/16 provided a valuable opportunity to test the application of a dynamical forecast system.This paper therefore presents a case study of a real-time seasonal forecast for the Yangtze River basin,building on previous work demonstrating the retrospective skill of such a forecast.A simple forecasting methodology is presented,in which the forecast probabilities are derived from the historical relationship between hindcast and observations.Its performance for2016 is discussed.The heavy rainfall in the May–June–July period was correctly forecast well in advance.August saw anomalously low rainfall,and the forecasts for the June–July–August period correctly showed closer to average levels.The forecasts contributed to the confidence of decision-makers across the Yangtze River basin.Trials of climate services such as this help to promote appropriate use of seasonal forecasts,and highlight areas for future improvements. | Philip E. BETT Adam A. SCAIFE Chaofan LI Chris HEWITT Nicola GOLDING Peiqun ZHANG Nick DUNSTONE Doug M. SMITH Hazel E. THORNTON Riyu LU Hong-Li REN | 2018 | Advances in Atmospheric Sciences2018，35，8： | 3 |
| 4 | 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 |
| 5 | Dynamical Predictability of Leading Interannual Variability Modes of the Asian-Australian Monsoon in Climate Models显示文摘The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide.Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences,especially for the second mode.The first AAM mode,from various seasonal sequences,coincides with the El Niño phase transition in the eastern-central Pacific.The second mode,initialized from boreal summer and autumn,leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring.Our findings hint that ENSO,as an early signal,is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes.Still,the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features.The multimodel ensemble(MME)mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features.The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes.The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services. | Lin WANG Hong-Li REN Fang ZHOU Nick DUNSTONE Xiangde XU | 2023 | Advances in Atmospheric Sciences2023，40，11： | 1 |
| 6 | Skilful Forecasts of Summer Rainfall in the Yangtze River Basin from November显示文摘Variability in the East Asian summer monsoon(EASM)brings the risk of heavy flooding or drought to the Yangtze River basin,with potentially devastating impacts.Early forecasts of the likelihood of enhanced or reduced monsoon rainfall can enable better management of water and hydropower resources by decision-makers,supporting livelihoods and major economic and population centres across eastern China.This paper demonstrates that the EASM is predictable in a dynamical forecast model from the preceding November,and that this allows skilful forecasts of summer mean rainfall in the Yangtze River basin at a lead time of six months.The skill for May–June–July rainfall is of a similar magnitude to seasonal forecasts initialised in spring,although the skill in June–July–August is much weaker and not consistently significant.However,there is some evidence for enhanced skill following El Niño events.The potential for decadal-scale variability in forecast skill is also examined,although we find no evidence for significant variation. | Philip E.BETT Nick DUNSTONE Nicola GOLDING Doug SMITH Chaofan LI | 2023 | Advances in Atmospheric Sciences2023，40，11： | 1 |
| 7 | Subseasonal Prediction of Early-summer Northeast Asian Cut-off Lows by BCC-CSM2-HR and GloSea5显示文摘Northeast Asian cut-off lows are crucial cyclonic systems that can bring temperature and precipitation extremes over large areas.Skillful subseasonal forecasting of Northeast Asian cut-off lows is of great importance.Using two dynamical forecasting systems,one from the Beijing Climate Center(BCC-CSM2-HR)and the other from the Met Office(GloSea5),this study assesses simulation ability and subseasonal prediction skill for early-summer Northeast Asian cut-off lows.Both models are shown to have good ability in representing the spatial structure of cut-off lows,but they underestimate the intensity.The skillful prediction time scales for cut-off low intensity are about 10.2 days for BCC-CSM2-HR and 11.4 days for GloSea5 in advance.Further examination shows that both models can essentially capture the initial Rossby wave train,rapid growth and decay processes responsible for the evolution of cut-off lows,but the models show weaker amplitudes for the three-stage processes.The underestimated simulated strength of both the Eurasian midlatitude and East Asian subtropical jets may lead to the weaker local eddy-mean flow interaction responsible for the cut-off low evolution. | Yu NIE Jie WU Jinqing ZUO Hong-Li REN Adam A.SCAIFE Nick DUNSTONE Steven C.HARDIMAN | 2023 | Advances in Atmospheric Sciences2023，40，11： | 1 |
| 8 | Predictability and Risk of Extreme Winter PM_(2.5)Concentration in Beijing显示文摘Air pollution remains a serious environmental and social problem in many big cities in the world.How to predict and estimate the risk of extreme air pollution is unsettled yet.This study tries to provide a solution to this challenge by examining the winter PM_(2.5)concentration in Beijing based on the UNprecedented Simulation of Extremes with ENsembles(UNSEEN)method.The PM_(2.5)concentration observations in Beijing,Japanese 55-yr reanalysis data,and the Met Office near term climate prediction system(DePreSys3a)large ensemble simulations are used,and 10,000proxy series are generated with the model fidelity test.It is found that in Beijing,the main meteorological driver of PM_(2.5)concentration is monthly 850-hPa meridional wind(V850).Although the skill in prediction of V850 is low on seasonal and longer timescales,based on the UNSEEN,we use large ensemble of initialized climate simulations of V850 to estimate the current chance and risk of unprecedented PM_(2.5)concentration in Beijing.We unravel that there is a 3%(2.1%–3.9%)chance of unprecedented low monthly V850 corresponding to high PM_(2.5)in each winter,within the 95%range,calculated by bootstrap resampling of the data.Moreover,we use the relationship between air quality and winds to remove the meridional wind influence from the observed record,and find that anthropogenic intervention appears to have reduced the risk of extreme PM_(2.5)in Beijing in recent years. | Jingpeng LIU Adam A.SCAIFE Nick DUNSTONE Hong-Li REN Doug SMITH Steven CHARDIMAN Bo WU | 2023 | Journal of Meteorological Research2023，37，5： | 0 |
| 9 | Prediction of the Western North Pacific Subtropical High in Summer without Strong ENSO Forcing显示文摘The western North Pacific subtropical high(WNPSH) is one of the deterministic predictors of the East Asian summer climate, and a better prediction of the WNPSH favors more reasonable forecast of the East Asian summer climate. This study focuses on seasonal prediction of the WNPSH during neutral summers without strong El Ni?o–Southern Oscillation(ENSO) forcing, and explores the associated predictable sources, using the one-month lead time retrospective forecasts from the Ensembles-Based Predictions of Climate Changes and Their Impacts(ENSEMBLES) project during 1960–2005. The results indicate that the ENSEMBLES atmosphere–ocean–land coupled models exhibit considerable prediction skill for the WNPSH during neutral summers, with successful reproduction of the WNPSH in the majority of neutral summers. The anomalous WNPSH in neutral summers, which corresponds to cyclonic/anticyclonic anomalies in the lower troposphere, is highly correlated with an east–west dipole local sea surface temperature(SST) distribution over the tropical WNP, suggesting an intimate local air–sea coupling. Further diagnosis of the local SST–rainfall relationship and surface heat flux indicates that the anomalous local SST plays an active role in modulating the variation of the WNPSH during neutral summers, rather than passively responding to the atmospheric change. The local SST anomalies and relevant air–sea coupling over the tropical WNP are reasonably well reproduced in the model predictions, and could act as primary predictable sources of the WNPSH in neutral summers. This could aid in forecasting of the East Asian rainband and associated disaster mitigation planning. | Chaofan LI Riyu LU Nick DUNSTONE | 2021 | Journal of Meteorological Research2021，35，1： | 0 |
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