A5067909384- Climate variability and models
- Meteorological Phenomena and Simulations
- Tropical and Extratropical Cyclones Research
- Oceanographic and Atmospheric Processes
- Cryospheric studies and observations
- Environmental and Agricultural Sciences
- Plant Water Relations and Carbon Dynamics
- Hydrological Forecasting Using AI
- Antenna Design and Optimization
- Environmental Changes in China
- Metamaterials and Metasurfaces Applications
- Atmospheric and Environmental Gas Dynamics
- Arctic and Antarctic ice dynamics
- Remote Sensing and Land Use
- Antenna Design and Analysis
- Structural Analysis and Optimization
- Precipitation Measurement and Analysis
- Advanced Antenna and Metasurface Technologies
- Aeolian processes and effects
- Ocean Waves and Remote Sensing
- Magnetic Bearings and Levitation Dynamics
- Climate Change and Health Impacts
- Flood Risk Assessment and Management
- Evaluation Methods in Various Fields
Peking University Shenzhen Hospital
2024
China Meteorological Administration
2011-2024
Peng Cheng Laboratory
2024
Peking University
2024
National Center for Climate Change Strategy and International Cooperation
2023-2024
Lanzhou University
2021-2022
Beijing Normal University
2016
Based on the idea of using historical-analogue information to predict prediction errors model, a new method named analogue correction by predictable component （FACEPC） was developed. This is adopted identify predicable components for which result relatively not quite sensitive initial values. And then components, an associated scheme chosen selection and error correction. further applied experiments operational seasonal model National Climate Center. By selecting suitable analogues schemes...
Abstract The most predictable components of the El Niño-Southern Oscillation (ENSO) evolution in real-time multi-model predictions are identified by applying an empirical orthogonal function analysis model data that maximizes signal-to-noise ratio (MSN EOF). normalized Niño3.4 index is analyzed for nine 3-month overlapping seasons. In this sense, first component EOF1) decaying phase ENSO during Northern Hemisphere spring, followed persistence through autumn and winter. second evolution, with...
Abstract Increasing intense landfalling typhoons (LFTYs) are of great coastal threatens to southern China. However, changes in genesis location and frequency western North Pacific (WNP) LFTY dedicated China remain unclear. Here we identified such LFTYs during peak summer found that most formed south 20°N the locations over WNP have also experienced a sharp interdecadal shift since 1998, which mainly attributed large‐scale environment induced by Mega‐La Niña‐like climate shift. (=...
ABSTRACT The western Pacific subtropical high ( WPSH ) and sea surface temperatures have experienced marked interdecadal changes. However, whether the relationships between temperature forcings SSTFs also an transition remains unclear. This study analyses shift in relationship . results clearly reveal occurrence of two transitions leading empirical orthogonal function modes, which represent intensity : one approximately 1976–1977 other 1993–1994. positive first principal component is closely...
In this paper we extract components in extended-range forecast for the coming 10-30 days by Butterworth Band-pass filter using NCEP/NCAR reanalysis daily data of geopotential height from 1978 to 2007 and January 6th February 4th, at same time basic function climate state empirical orthogonal (EOF). And use way deal with during snow storm event 2008 Filter. We contribution rate explain variance EOF elements which influence weather process a period 1030 days. Stable can be divided into two...
Abstract This study examines characteristics of Meiyu during the season from June 1 to July 31 for 1998–2017 using two observational analyses (i.e., Tropical Rainfall Measuring Mission [TRMM] and Global Precipitation Climatology Project [GPCP]) four reanalysis data sets Modern‐Era Retrospective Analysis Research Applications, Version 2 [MERRA2], ERA5, JRA55, NCEP/DOE). The mean precipitation GPCP is slightly larger than TRMM but has smaller variance as compared with TRMM. MERRA2 ERA5 are...
Anomalous subsidence over the western part of Pacific subtropical high (WPSH) caused record-breaking precipitation anomalies Yangtze-Huaihe River catchment in early summer 2020 (June–July 2020). The meridional circulation (MC) made a positive contribution to this anomalous subsidence, while zonal (ZC) negative contribution. quantitative contributions MC and ZC were approximately 110% –10% June, 130% –30% July, 120% –20% for mean June respectively, suggesting that played dominant role WPSH....
Using a method of calculating the entropy based on relativity spatial fields to give correlative index having statistic characteristic discrete fields, we discuss inherent rule drought/flood and their distributions in China. The result gives associations from 1470 2000, shows that actual distributed is relative not stochastic, being different random by matrix latent values. every year's degree association with other ones. greater is, bigger vice versa. similitude climate state has steady...
Abstract Sea surface temperature anomalies (SSTAs), including their spatial patterns and temporal evolution, are an important source of potential predictability for climate anomalies, especially on seasonal to interannual timescales. In this study, the evolution tropical SSTAs identified by applying extended empirical orthogonal function (EEOF) analysis observed data from autumn following spring. The positive phase first EEOF mode (EEOF1) displays El Niño–Southern Oscillation (ENSO)...
The intraseasonal variations of summer precipitation anomalies in the Meiyu area East Asia are analyzed by applying a combined empirical orthogonal function (CEOF) latest meteorological reanalysis data ERA5 European Center for Medium-Range Weather Forecasts period from 1991 to 2020, and circulation structures sources variability CEOF also investigated. first mode shows an in-phase pattern over June, July, August, accounting 22.2% total variance anomalies. positive (negative) CEOF1 is...