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Seasonal prediction skill and Biases in GloSea5 Relating to the East Asia Winter Monsoon

Advances in Atmospheric Sciences 2023年第11期40卷 2013-2028页

作者： Daquan ZHANG Lijuan CHEN Gill MMARTIN Zongjian KE China Meteorological Administration Key Laboratory for Climate prediction Studies National Climate CentreBeijing 100081China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China Met Office Hadley Centre Met OfficeExeter EX13PBUK

The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon(EAWM),as well as the associated atmospheric circulation,was investigated using the hindcast data from Global Seasonal Forecast System version 5(GloSea5),with a focus on the evolution of model bias among different forecast lead *** GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well,systematic biases exist,including a cold bias for most of China’s mainland,especially for North and Northeast ***5 shows robust skill in predicting the EAWM intensity index two months ahead,which can be attributed to the performance in representing the leading modes of surface air temperature and associated background ***5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation(ENSO)and the Arctic Oscillation(AO)on the EAWM,especially for the western North Pacific anticyclone(WNPAC).Compared with the North Pacific and North America,the representation of circulation anomalies over Eurasia is poor,especially for sea level pressure(SLP),which limits the prediction skill for surface air temperature over East *** representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.

关键词： East Asia winter monsoon(EAWM) Global Seasonal Forecast System version 5(GloSea5) El Niño–Southern Oscillation(ENSO) prediction skill model bias

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Intraseasonal Variability of Summertime Surface Air Temperature over Mid-High-Latitude Eurasia and Its prediction skill in S2S Models

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Journal of Meteorological Research 2021年第5期35卷 815-830页

作者： Jing CUI Shuangyan YANG Tim LI Key Laboratory of Meteorological Disaster Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environmental Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)Nanjing University of Information Science&TechnologyNanjing 210044China International Pacific Research Center and Department of Atmospheric Sciences School of Ocean and Earth Science and TechnologyUniversity of HawaiiHonoluluHI 96822USA

Features of the dominant modes of surface air temperature(SAT)on the intraseasonal timescale over the mid-highlatitude Eurasia(MHE)during boreal summer(June-September)are investigated based on the ERA5 reanalysis data from 1979 to *** intraseasonal variability(ISV)of SAT over MHE is primarily characterized by an eastward propagation along 60°N,which is found to impact the regional weather in China,including summertime extreme hot and cool *** forecast skill and potential predictability of the ISV of SAT over MHE are assessed for 5 dynamical models that have participated in the subseasonal-to-seasonal(S2 S)prediction project,by analyzing12 years’(1999-2010)model reforecast/hindcast *** using the principal component(PC)index of the leading intraseasonal SAT modes as a predictand,we found that the forecast skill for ISV of SAT can reach out to 11-17 days,and the ECMWF model exhibits the best *** the S2 S models tend to show 1)a relatively higher skill for strong intraseasonal oscillation(ISO)cases,2)a systematic underestimate of the amplitude of the SAT ISV signal,and 3)different skills during different phases of ISO *** of potential predictability based on the perfectmodel assumption reveals a 4-6-day skill gap for most models,and the skill gap also varies among different phases of ISO *** results imply the need for continued development of operational forecasting systems to improve the actual prediction skills for the ISV of SAT over MHE.

关键词： surface air temperature(SAT) intraseasonal variability(ISV) mid-high-latitude Eurasia(MHE) subseasonal-to-seasonal(S2S)prediction prediction skill predictability

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Why Are Arctic Sea Ice Concentration in September and Its Interannual Variability Well Predicted over the Barents–East Siberian Seas by CFSv2?

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Journal of Meteorological Research 2024年第1期38卷 53-68页

作者： Yifan XIE Ke FAN Hongqing YANG School of Atmospheric Sciences Sun Yat-sen Universityand Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai)Zhuhai 519082

To further understand the prediction skill for the interannual variability of the sea ice concentration(SIC)in specific regions of the Arctic,this paper evaluates the NCEP Climate Forecast System version 2(CFSv2),in predicting the autumn SIC and its interannual variability over the Barents–East Siberian Seas(BES).It is found that CFSv2 presents much better prediction skill for the September SIC over BES than the Arctic as a whole at 1–6-month leads,and high prediction skill for the interannual variability of the SIC over BES is displayed at 1–2-month leads after removing the linear ***2 can reasonably reproduce the relationship between the SIC over BES in September and such factors as the surface air temperature(SAT),200-hPa geopotential height,sea surface temperature(SST),and North Atlantic *** addition,it is found that the prescribed SIC initial condition in August as an input to CFSv2 is also ***,the above atmospheric and oceanic factors,as well as an accurate initial condition of SIC,all contribute to a high prediction skill for SIC over BES in *** on a statistical prediction method,the contributions from individual predictability sources are further *** high prediction skill of CFSv2 for the interannual variability of SIC over BES is largely attributable to its accurate predictions of the SAT and SST,as well as a better initial condition of SIC.

关键词： sea ice concentration the Barents-East Siberian Seas Climate Forecast System version 2(CFSv2) prediction skill predictability source atmospheric and oceanic factors initial condition

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Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

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Acta Oceanologica Sinica 2024年第1期43卷 1-10页

作者： Ting Liu Wenxiu Zhong State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519082China School of Atmospheric Sciences Sun Yat-Sen UniversityZhuhai 519082China

Upper ocean heat content(OHC)has been widely recognized as a crucial precursor to high-impact climate variability,especially for that being indispensable to the long-term memory of the *** the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate *** developed retrospective forecast experiments,based on a Community Earth System Model ensemble prediction system,offer a great opportunity to comprehensively explore OHC *** results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction *** spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill,indicating that the persistence of OHC serves as the primary predictive signal for its *** decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean,particularly within tropical ***,notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC *** potential predictability of OHC generally surpasses the actual prediction skill at all lead times,highlighting significant room for improvement in current OHC predictions,especially for the North Indian Ocean and the Atlantic *** such improvements necessitates a collaborative effort to enhance the quality of ocean observations,develop effective data assimilation methods,and reduce model bias.

关键词： ocean heat content prediction skill retrospective forecast experiment

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Subseasonal prediction of Early-summer Northeast Asian Cut-off Lows by BCC-CSM2-HR and GloSea5

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Advances in Atmospheric Sciences 2023年第11期40卷 2127-2134页

作者： Yu NIE Jie WU Jinqing ZUO Hong-Li REN Adam A.SCAIFE Nick DUNSTONE Steven C.HARDIMAN China Meteorological Administration Key Laboratory for Climate prediction Studies National Climate CenterBeijing 100081China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Severe Weather Institute of Tibetan Plateau&Polar MeteorologyChinese Academy of Meteorological SciencesBeijing100089China Met Office Hadley Centre Exeter EX13PBUnited Kingdom University of Exeter Exeter EX13PBUnited Kingdom

Northeast Asian cut-off lows are crucial cyclonic systems that can bring temperature and precipitation extremes over large *** subseasonal forecasting of Northeast Asian cut-off lows is of great *** 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 *** models are shown to have good ability in representing the spatial structure of cut-off lows,but they underestimate 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 *** 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 *** 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.

关键词： Northeast Asia cut-off lows subseasonal prediction skill jet stream

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Progress of MJO prediction at CMA from Phase I to Phase II of the Sub-Seasonal to Seasonal prediction Project

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Advances in Atmospheric Sciences 2023年第10期40卷 1799-1815页

作者： Junchen YAO Xiangwen LIU Tongwen WU Jinghui YAN Qiaoping LI Weihua JIE Center for Earth System Modeling and prediction of China Meteorological Administration Beijing 100081China

As one of the participants in the Subseasonal to Seasonal(S2S)prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S *** study evaluates the models’capability to simulate and predict the Madden-Julian Oscillation(MJO).Three versions of the Beijing Climate Center Climate System Model(BCC-CSM)are used to conduct historical simulations and re-forecast experiments(referred to as EXP1,EXP1-M,and EXP2,respectively).In simulating MJO characteristics,the newly-developed high-resolution BCC-CSM outperforms its *** terms of MJO prediction,the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M,and further to 24 days in *** the first forecast week,the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction ***,during forecast weeks 2–3,EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–*** at initial phases 2–3,EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection,leading to the highest prediction skill of the *** results reveal that,during the participation of the CMA models in the S2S Project,both the improved model initialization and updated model physics played positive roles in improving MJO *** efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times.

关键词： Madden-Julian Oscillation(MJO) Subseasonal to Seasonal(S2S) prediction skill improvement initial phase

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A new nudging scheme for the current operational climate prediction system of the National Marine Environmental Forecasting Center of China

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Acta Oceanologica Sinica 2022年第2期41卷 51-64页

作者： Xunshu Song Xiaojing Li Shouwen Zhang Yi Li Xinrong Chen Youmin Tang Dake Chen State Key Laboratory of Satellite Ocean Environment Dynamics Second Institute of OceanographyMinistry of Natural ResourcesHangzhou 310012China Southern Marine Science and Engineering Guangdong Laboratory(Zhuhai) Zhuhai 519080China Environmental Science and Engineering University of Northern British ColumbiaPrince George V2N 4Z9Canada National Marine Environmental Forecasting Center Beijing 100081China College of Oceanography Hohai UniversityNanjing 210098China Key Laboratory of Marine Hazards Forecasting of Ministry of Natural Resources Hohai UniversityNanjing 210098China

A new nudging scheme is proposed for the operational prediction system of the National Marine Environmental Forecasting Center(NMEFC)of China,mainly aimed at improving El Niño–Southern Oscillation(ENSO)and Indian Ocean Dipole(IOD)*** with the origin nudging scheme of NMEFC,the new scheme adds a nudge assimilation for wind components,and increases the nudging weight at the *** the nudging weight at the subsurface directly improved the simulation performance of the ocean component,while assimilating low-level wind components not only affected the atmospheric component but also benefited the oceanic *** experiments showed that the new scheme remarkably improved both ENSO and IOD prediction *** skillful prediction lead time of ENSO was up to 11 months,1 month longer than a hindcast using the original nudging *** prediction of IOD could be made 4–5 months ahead by the new scheme,with a 0.2 higher correlation at a 3-month lead *** prediction skills approach the level of some of the best state-of-the-art coupled general circulation *** ENSO and IOD predictions occurred across all seasons,but mainly for target months in the boreal spring for the ENSO and the boreal spring and summer for the IOD.

关键词： climate prediction system initialization prediction skill ENSO IOD

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Contrasting the skills and Biases of Deterministic predictions for the Two Types of El Nio

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Advances in Atmospheric Sciences 2017年第12期34卷 1395-1403页

作者： Fei ZHENG Jin-Yi YU International Center for Climate and Environment Science Institute of Atmospheric PhysicsChinese Academy of Sciences Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science and Technology Department of Earth System Science University of California

The tropical Pacific has begun to experience a new type of El Nio, which has occurred particularly frequently during the last decade, referred to as the central Pacific(CP) El Nio. Various coupled models with different degrees of complexity have been used to make real-time El Nio predictions, but high uncertainty still exists in their forecasts. It remains unknown as to how much of this uncertainty is specifically related to the new CP-type El Nio and how much is common to both this type and the conventional Eastern Pacific(EP)-type El Nio. In this study, the deterministic performance of an El Nio–Southern Oscillation(ENSO) ensemble prediction system is examined for the two types of El Nio. Ensemble hindcasts are run for the nine EP El Nio events and twelve CP El Nio events that have occurred since 1950. The results show that(1) the skill scores for the EP events are significantly better than those for the CP events, at all lead times;(2) the systematic forecast biases come mostly from the prediction of the CP events; and(3) the systematic error is characterized by an overly warm eastern Pacific during the spring season, indicating a stronger spring prediction barrier for the CP El Nio. Further improvements to coupled atmosphere–ocean models in terms of CP El Nio prediction should be recognized as a key and high-priority task for the climate prediction community.

关键词： ENSO EP El Nio CP El Nio prediction skill systematic bias spring prediction barrier

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Improved ENSO Forecasts by Assimilating Sea Surface Temperature Observations into an Intermediate Coupled Model

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Advances in Atmospheric Sciences 2006年第4期23卷 615-624页

作者：郑飞朱江 Rong-Hua ZHANG 周广庆 International Center for Climate and Environment Science （ICCES） Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 Earth System Science Interdisciplinary Center （ ESSIC） University of Maryland College Park Maryland USA

A simple method for initializing intermediate coupled models （ICMs） using only sea surface temperature （SST） anomaly data is comprehensively tested in two sets of hindcasts with a new ICM. In the initialization scheme, both the magnitude of the nudging parameter and the duration of the assimilation are considered, and initial conditions for both atmosphere and ocean are generated by running the coupled model with SST anomalies nudged to the observations. A comparison with the observations indicates that the scheme can generate realistic thermal fields and surface dynamic fields in the equatorial Pacific through hindcast experiments. An ideal experiment is performed to get the optimal nudging parameters which include the nudging intensity and nudging time length. Twelve-month-long hindcast experiments are performed with the model over the period 1984-2003 and the period 1997-2003. Compared with the original prediction results, the model prediction skills are significantly improved by the nudging method especially beyond a 6-month lead time during the two different periods. Potential problems and further improvements are discussed regarding the new coupled assimilation system.

关键词： ENSO intermediate coupled model prediction skill hindcast

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Representation and Predictability of the East Asia-Pacific Teleconnection in the Beijing Climate Center and UK Met Office Subseasonal prediction Systems

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Journal of Meteorological Research 2020年第5期34卷 941-964页

作者： Jie WU Peiqun ZHANG Lei LI Hong-Li REN Xiangwen LIU Adam A.SCAIFE Shuai ZHANG Laboratory far Climate Studies&China Meteorological Administration-Nanjing University Joint Laboratory for Climate prediction Studies National Climate CenterChina Meteorological AdministrationBeijing 100081China State Key Laboratory of Severe Weather Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijing 100081China Met Office Hadley Centre Exeter EXI 3PBUK College of Engineering Mathematics and Physical SciencesUniversity of ExeterDevon EX44QFUK Secretariat of Jiangxi Meteorological Society Nanchang 330096China Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China

Based on the empirical orthogonal function(EOF) analysis, the East Asia–Pacific(EAP) teleconnection is extracted as the leading mode of the subseasonal variability over East Asia in summer, with a meridional tripole structure and significant periods of 10–30 and 50–70 days. A two-dimensional phase–space diagram is established for the EAP index and its time tendency so as to monitor the real-time state of EAP events. Based on the phase composite analysis, the general circulation anomalies first occur over the high-latitude area of Europe centered near Novaya Zemlya at the beginning of EAP events. These general circulation anomalies then influence rainfall over Northeast China,North China, and the region south of the Yangtze River valley(YRV) as the phases of EAP event progress. The representation, predictability, and prediction skill of the EAP teleconnection are examined in the two fully coupled subseasonal prediction systems of the Beijing Climate Center(BCC) and UK Met Office(UKMO GloSea5). Both models are able to simulate the EAP meridional tripole over East Asia as the leading mode and its characteristics of evolution as well, except for the weaker precursors over Novaya Zemlya and an inconspicuous influence on precipitation over Northeast China. The actual prediction skill of the EAP teleconnection during May–September(MJJAS) is about 10 days in the BCC model and 15 days in the UKMO model based on correlation measures, but is higher when initialized from the EAP peak phases or when targeted on strong EAP scenarios. However, both of the ensemble prediction systems are under-dispersive and the predictable signals extend to 18 and 30 days in BCC and UKMO models based on signal-to-error metrics, indicating that there may be further scope for enhancing the capability of these models for the EAP teleconnection prediction and the associated impacts studies.

关键词： East Asia–Pacific(EAP)teleconnection subseasonal phase–space diagram prediction skill predictability

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