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Tropical Cyclone Research and Review 2012年第2期1卷 177-183页

作者： TRAN QUANG NANG Analyzing and prediction of tropical storm Pakhar at national center for hydro-meteorological forecasting of Viet Nam (NCHMF)

Tropical storm Pakhar appeared as a low pressure system over the south China sea on March 26, 2012. It then became a tropical storm a few days later on March 29, 2012. Pakhar was really an abnormal tropical storm activated over the south China sea in March which seldom appeared at that time. The movement of Pakhar was not very complicated because it mainly moved under the steering lines of subtropical high pressure systems. However, its intensity was still a problem for many typhoon centers, especially when Pakhar experienced a rapid intensification within 12 hours at 00 Z on March 30. At that time NCHMF and JRTD(Japan) warned it as a tropical storm, while BABJ(China) and JTWC(Us navy) warned as severe tropical storm and typhoon respectively. Pakhar decreased quickly when approached the onshore areas of Viet Nam. At 08 Z on 1 April, upon analyzing the radar data at Nha Be station and the half-hourly observations along the coastline, NCHMF downgraded Pakhar into a tropical depression, while other typhoon centers maintained Pakhar’s intensity as a tropical storm untill 00 Z on 2 April.

关键词：

THE DOWNsCALING FORECAsTING OF sEAsONAL PRECIPITATION IN GUANGDONG BAsED ON climate FORECAsT sYsTEMs PRODUCTs

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Journal of Tropical Meteorology 2014年第2期20卷 143-153页

作者：李春晖林爱兰谷德军王婷潘蔚娟郑彬 Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather prediction China Meteorological Administration Guangdong climate and Agrometeorological center

The climate Forecast systems(CFs) datasets provided by National centers for Environmental prediction(NCEP), which cover the time from 1981 to 2008, can be used to forecast atmospheric circulation nine months ahead. Compared with the NCEP datasets, CFs datasets successfully simulate many major features of the Asian monsoon circulation systems and exhibit reasonably high skill in simulating and predicting ENsO events. Based on the CFs forecasting results, a downscaling method of Optimal subset Regression(OsR) and mean generational function model of multiple variables are used to forecast seasonal precipitation in Guangdong. After statistical analysis tests, sea level pressure, wind and geopotential height field are made predictors. Although the results are unstable in some individual seasons, both the OsR and multivariate mean generational function model can provide good forecasting as operational tests score more than sixty points. CFs datasets are available and updated in real time, as compared with the NCEP dataset. The downscaling forecast method based on the CFs datasets can predict three seasons of seasonal precipitation in Guangdong, enriching traditional statistical methods. However, its forecasting stability needs to be improved.

关键词： CFs Optimal subset Regression mean generational function Guangdong precipitation downscaling

Implications of diurnal variations in land surface temperature to data assimilation using MODIs LsT data

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Journal of Geographical sciences 2020年第1期30卷 18-36页

作者： FU shiwen NIE suping LUO Yong CHEN Xin Department of Earth system science Tsinghua UniversityBeijing 100084China Numerical Weather prediction center China Meteorological AdministrationBeijing 100081China National climate center China Meteorological AdministrationBeijing 100081China

Based on the Beijing climate center’s land surface model BCC_AVIM(Beijing climate center Atmosphere-Vegetation Interaction Model),the ensemble Kalman filter(EnKF)algorithm has been used to perform an assimilation experiment on the Moderate Resolution Imaging spectroradiometer(MODIs)land surface temperature(LsT)product to study the influence of satellite LsT data frequencies on surface temperature data *** assimilation results have been independently tested and evaluated by Global Land Data Assimilation system(GLDAs)LsT *** results show that the assimilation scheme can effectively reduce the BCC_AVIM model simulation bias and the assimilation results reflect more reasonable spatial and temporal *** variation information in the observation data has a significant effect on the assimilation *** LsT data that contain diurnal variation information can further improve the accuracy of the assimilation ***,when assimilation is performed using observation data at 6-hour intervals,a relatively good assimilation result can be obtained,indicated by smaller bias(square-error(RMsE)(s larger than ***,the assimilation using 24-hour data generally showed larger bias(>2.2K)and RMsE(>4K).Further analysis showed that the sensitivity of assimilation effect to diurnal variations in LsT varies with time and *** assimilation using observations with a time interval of 3 hours has the smallest bias in Oceania and Africa(bothse of 24-hour interval observation data for assimilation produces the smallest bias(<2.2K)in March,April and July.

关键词： land surface data assimilation land surface temperature MODIs diurnal variation

The extreme Northeast China cold vortex activities in the late spring of 2021 and possible causes involved

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Advances in climate Change Research 2022年第6期13卷 787-796页

作者： Jie WU Ying LIU Yong-sheng LI Jin-Qing ZUO Yu NIE Qing-Quan LI shuai ZHANG Dong-Qian WANG CMA climate studies Key Laboratory&CMA-NJU Joint Laboratory for climate prediction studies National Climate CenterChinaMeteorological Administration(CMA)Beijing 100081China Collaborative Innovation center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science&TechnologyNanjing 210044China Heilongjiang climate center Harbin 150030China Institute of Urban Meteorology China Meteorological AdministrationBeijing 100089China

Record-breaking numbers of Northeast China cold vortex(NCCV)occurred during the late spring(April-May)of 2021,which provided favorable background for more severe convection weather(such as hailstorm and tornado)happened and struck Jiangsu and Hubei provinces,China,causing heavy casualties and property *** better understand the possible causes of extremely abnormal NCCV activities,the external forcing and dynamical analysis was *** results show that the extreme NCCV activity is regulated by the preceding sea surface temperature(ssT)anomalies in the tropical Pacific,the snow conditions over the Tibetan Plateau,and the wave-mean flow interaction over the Eurasian *** the preceding autumn and winter in 2020,a moderate La Niña event occurred over the tropical Pacific,which triggered the Pacific-North America teleconnection pattern(PNA)like wave train and further dispersed the Rossby wave energy downstream along the mid-latitude westerly jet,forming a zonal wave train over the Eurasian ***,the second minimum snow depth was recorded over the southeastern Tibetan Plateau during the boreal winter of 2020/2021,which induced a concurrent local anomalous anticyclone and a cyclone over northeast Asia in the following ***,the anomalous circulation is capable of achieving energy from the mean state through barotropic energy conversion and strengthening the downstream wave train *** study highlights the joint impacts of external forcings and internal atmospheric processes on the NCCV activity.

关键词： Northeast China cold vortex(NCCV) Wave train La Niña event snow depth Barotropic energy conversion

Indian Ocean ssT modes and Their Impacts as simulated in BCC_CsM1.1(m) and HadGEM3

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Advances in Atmospheric sciences 2018年第8期35卷 139-152页

作者： Bo LU Hong-Li REN Rosie EADE Martin ANDREWs Laboratory for climate studies National Climate Center China Meteorological Administration Beijing 100081 China CMA-NJU Joint Laboratory for climate prediction studies Institute for Climate and Global Change Research School of Atmospheric Sciences Nanjing University Nanjing 210023 China Xin Jiang climate center Urumqi 830002 China Department of Atmospheric science School of Environmental Studies China University of Geoscience Wuhan 430074 China Met Office Hadley center Exeter EX1 3PB UK

The sea surface temperature anomalies （ssTAs） in the tropical Indian Ocean （TIO） show two dominant modes at interan- nual time scales, referred to as the Indian Ocean basin mode （IOBM） and dipole mode （IOD）. Recent studies have shown that the IOBM and IOD not only affect the local climate, but also induce remarkable influences in East Asia via teleconnections. In this study, we assess simulations of the IOBM and IOD, as well as their teleconnections, using the operational seasonal pre- diction models from the Met Office （HadGEM3） and Beijing climate center [BCC_CsMI.I（m）]. It is demonstrated that the spatial patterns and seasonal cycles axe generally reproduced by the control simulations of BCC_CsM1.1 （m） and HadGEM3, although spectra biases exist. The relationship between the TIO ssTA and E1 Nifio is successfully simulated by both mod- els, including the persistent IOBM warming following E1 Nifio and the IOD-E1 Nifio interactions. BCC_CsMI.I（m） and HadGEM3 axe capable of simulating the observed local impact of the IOBM, such as the strengthening of the south Asian high. The influences of the IOBM on Yangtze River rainfall are also captured well by both models, although this teleconnec- tion is slightly weaker in BCC_CsM 1.1 （m） due to the underestimation of the northwestern Pacific subtropical high. The local effect of the IOD on East African rainfall is reproduced by both models. However, the remote control of the IOD on rainfall over southwestern China is not clear in either model. It is shown that the realistic simulations of TIO ssT modes and their teleconnections give rise to the source of skillful seasonal predictions over China.

关键词： Indian Ocean ssT teleconnection simulation seasonal prediction

3-D rheologic model of earthquake preparation (Ⅱ): strain field and its applications

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Acta seismologica sinica(English Edition) 2004年第2期17卷 131-143页

作者： sONG Zhi-ping(宋治平) YIN Xiang-chu(尹祥础) MEI shi-rong(梅世蓉) Earthquake Administration of shanghai Shanghai 200062 China Center for Analysis and Prediction China Earthquake Administration Beijing 100036 China Center for Analysis and Prediction China Earthquake Administration Beijing 100036 China

On the basis of the three-dimensional elastic inclusion model, the analytic expression of viscoelastic strain field is derived, i.e., the analytic expression of viscoelastic strain at an arbitrary point (x, y, z) in x-axis, y-axis and z-axis produced by three-dimension inclusion in the semi-infinite rheologic medium defined by the standard linear rheologic model, namely the normal strains exx(r, t), eyy(r, t) and ezz(r, t), the shear strains exy(r, t) and eyx(r, t), eyz(r, t) and ezy(r, t), exz(r, t) and ezx(r, t), and the bulk-strain q (r, t). By computing the spatial-temporal variation of bulk strain on the ground produced by a spherical rheologic inclusion in a semi-infinite rheologic medium, we obtained some significant results that the bulk-strain variation with time produced by a hard inclusion has three stages (a, b, g) with different characteristics, which are similar to those of most geodetic deformation curves, but not the case for those by a soft inclusion. It is meaningful that these theoretical results have been applied to explain preliminarily the characteristics of stage variation of spatial-temporal evolution, the pattern and quadrant distribution of earthquake precursors, the changeability, spontaneity and complexity of short-term and imminent-term precursors. It offers a theoretical base to found the physical model of earthquake precursors and a reference to predict physically the earthquakes.

关键词： elastic inclusion theory rheology inclusion theory strain field analytical solution for viscoelastic problem earthquake precursor

skillful prediction of winter Arctic Oscillation from previous summer in a linear empirical model

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science China Earth sciences 2021年第1期64卷 27-36页

作者： Hong-Li REN Yu NIE state Key Laboratory of severe Weather Chinese Academy of Meteorological SciencesBeijing 100081China Laboratory for climate studies&CMA-NJU Joint Laboratory for climate prediction studies National Climate CenterChina Meteorological AdministrationBeijing 100081China Department of Atmospheric science School of Environmental StudiesChina University of GeoscienceWuhan 430074China

The winter Arctic Oscillation(WAO),as a primary atmospheric variability mode in the Northern Hemisphere,plays a key role in influencing mid-high-latitude climate ***,current dynamical seasonal forecasting systems have limited skills in predicting WAO with lead time longer than two *** this study,we design a linear empirical model using two effective precursors from anomalies of the Arctic sea ice concentration(sIC)and the tropical sea surface temperature(ssT)initiated in preceding late summer(August)which are both significantly correlated with WAO in recent four *** model can provide a skillful prediction of WAO at about half-year lead started from previous summer and perform much better than the dynamical *** a significantly prolonged lead time is owed to the stable precursor signals extracted from the sIC and ssT anomalies over specific areas,which can persist from previous August and be further enhanced through autumn *** results show that this model can produce a 20-year independent-validated prediction skill of 0.45 for 1999–2018 and a 39-year cross-validated skill of 0.67 for 1980–2018,providing a potentially effective tool for earlier predictions of winter climate variations at mid-high latitudes.

关键词： Arctic Oscillation(AO) Winter AO prediction sea ice concentration sea surface temperature Linear empirical model

3D DBsCAN detection and parameter sensitivity of the 2022 Yangtze river summertime heatwave and drought

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Atmospheric and Oceanic science Letters 2023年第4期16卷 15-21页

作者： Zhenchen Liu Wen Zhou Yuan Yuan Department of Atmospheric and Oceanic sciences&Institute of Atmospheric sciences Fudan UniversityShanghaiChina China Meteorological Administration Key Laboratory for climate prediction studies National Climate CenterBeijingChina

极端气候事件的精准识别是机理分析的重要前提.本研究借助无监督机器学习中经典的DBsCAN密度聚类算法,发展了在三维(经度-纬度-时间)空间内进行目标事件识别和参数敏感性分析的研究方案.在2022年长江全域高温伏秋旱事件识别中的应用表明... 详细信息

极端气候事件的精准识别是机理分析的重要前提.本研究借助无监督机器学习中经典的DBsCAN密度聚类算法,发展了在三维(经度-纬度-时间)空间内进行目标事件识别和参数敏感性分析的研究方案.在2022年长江全域高温伏秋旱事件识别中的应用表明,本次天气尺度极端热浪和季节尺度重旱事件的产生发展,空间传播模式不同.天气尺度热浪信号自6月底从北太平洋向西南方向延伸,直至8月中旬覆盖长江全域;季节重旱信号于7月中旬从孟加拉湾陆面区域向东北向延伸,直至9月中旬覆盖长江全域.同时,本研究中亦进行了相关参数敏感性的详细分析,对算法应用,结果理解亦有帮助.

关键词： DBsCAN算法复合气候极值事件高温干旱长江流域机器学习

热带大气季节内振荡(MJO)实时监测预测业务

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气象 2012年第4期38卷 425-431页

作者：贾小龙袁媛任福民张勤国家气候中心北京100081 noaa/NWs/climate prediction center (CPC) 美国

参考目前国际上普遍认可的Wheeler和Hendon设计的MJO监测指标,设计了适合开展实时业务监测的MJO计算方法,初步在国家气候中心建立了逐日的MJO实时监测业务,通过与国外同类监测结果的比较分析表明,监测指标可以很好地描述MJO的强度和传... 详细信息

参考目前国际上普遍认可的Wheeler和Hendon设计的MJO监测指标,设计了适合开展实时业务监测的MJO计算方法,初步在国家气候中心建立了逐日的MJO实时监测业务,通过与国外同类监测结果的比较分析表明,监测指标可以很好地描述MJO的强度和传播特征,与国外同类监测产品有很好的一致性。另外,引入了两种统计方法进行了针对MJO指数的实时预测,对预测结果的检验表明,对MJO在两周内有较好的预测技巧,其中利用滞后线性回归方法(PCL)的预测技巧要高于自回归模型(ARM)。

关键词： MJO 监测统计预报

Detecting Primary Precursors of January surface Air Temperature Anomalies in China

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Journal of Meteorological Research 2017年第6期31卷 1096-1108页

作者： Guirong TAN Hong-Li REN Haishan CHEN Qinglong YOU Key Laboratory of Meteorological Disaster of Ministry of Education/Joint International Research Laboratory of climate and Environment Change/Collaborative Innovation center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science &Technology Laboratory for climate studies/CMA–NJU Joint Laboratory for climate prediction studies National Climate CenterChina Meteorological Administration Department of Atmospheric science School of Environmental Studies China University of Geoscience

This study aims to detect the primary precursors and impact mechanisms for January surface temperature anomaly （JsTA） events in China against the background of global warming, by comparing the causes of two extreme JsTA events occurring in 2008 and 2011 with the common mechanisms inferred from all typical episodes during 1979- 2008. The results show that these two extreme events exhibit atmospheric circulation patterns in the mid-high latitudes of Eurasia, with a positive anomaly center over the Ural Mountains and a negative one to the south of Lake Baikal （UMLB）, which is a pattern quite similar to that for all the typical events. However, the Eurasian teleconnection patterns in the 2011 event, which are accompanied by a negative phase of the North Atlantic Oscillation, are different to those of the typical events and the 2008 event. We further find that a common anomalous signal appearing in early summer over the tropical Indian Ocean may be responsible for the following late-winter Eurasian teleeonnec- lions and the associated JsTA events in China. We show that sea surface temperature anomalies （ssTAs） in the preceding summer over the western Indian Ocean （WIO） are intimately related to the UMLB-like circulation pattern in the following January. Positive WIOssTAs in early summer tend to induce strong UMLB-like circulation anomalies in January, which may result in anomalously or extremely cold events in China, which can also be successfully reproduced in model experiments. Our results suggest that the WIOssTAs may be a useful precursor for predicting JsTA events in China.

关键词： Eurasian teleconnection anomalous temperature in China seasonal climate prediction ssT anomaly western Indian Ocean model experiment