Yue Cai-jun

ORCID: 0009-0004-0417-1015
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About
Contact & Profiles
Research Areas
  • Tropical and Extratropical Cyclones Research
  • Meteorological Phenomena and Simulations
  • Remote Sensing and Land Use
  • Climate variability and models
  • Environmental and Agricultural Sciences
  • Environmental Changes in China
  • Oceanographic and Atmospheric Processes
  • Urban Heat Island Mitigation
  • Flood Risk Assessment and Management
  • Marine and coastal ecosystems
  • 3D Modeling in Geospatial Applications
  • Fire effects on ecosystems
  • Electrochemical sensors and biosensors
  • Computer Graphics and Visualization Techniques
  • Data Management and Algorithms
  • Ocean Waves and Remote Sensing
  • Ocean Acidification Effects and Responses
  • Precipitation Measurement and Analysis

Shanghai Marine Meteorological Center
2021-2024

Shanghai Meteorological Bureau
2018-2024

Shanghai Ecological Forecasting and Remote Sensing Center
2021-2022

China Meteorological Administration
2008-2015

Nanjing University of Information Science and Technology
2008-2009

National University of Sciences and Technology
2009

Zen-Noh (Japan)
2008

Abstract To evaluate the abilities of satellite retrievals in reflecting precipitation features related to tropical cyclones (TCs) affecting mainland China, four years 6- and 24-h from three datasets, namely Tropical Rainfall Measuring Mission algorithm 3B42, version 6 (3B42), Climate Prediction Center morphed (CMORPH) product, one based on Geostationary Meteorological Satellite-5 infrared brightness temperature (GMS5-TBB), are compared statistically with direct measurements surface gauge...

10.1175/2009jamc2143.1 article EN Journal of Applied Meteorology and Climatology 2009-04-27

Abstract Urbanization effects on rainfall induced by landfalling tropical cyclones have rarely been studied. Here high-resolution numerical simulations with the Weather Research and Forecasting/Noah/Single-layer urban canopy model system (WRF/SLUCM) are conducted to investigate impacts of land cover building heights heavy Typhoon Lekima (2019) over Megacity Shanghai. The default single category in WRF was updated a new data three categories. Results indicate that WRF/SLUCM captures typhoon...

10.1175/jhm-d-21-0170.1 article EN Journal of Hydrometeorology 2022-04-26

The visualization of a three-dimensional (3D) distribution high-density data for scientific computations with limited computing resources under network environment is difficult. This paper describes the implementation an interactive 3D display air pollutants in using open-source WebGL class library, Three. js. A kd-tree used to find nearest point interpolate grid because source are scattered, which helps locate conveniently at client's end. binary file format save and transfer reduce number...

10.1016/j.envsoft.2019.01.019 article EN cc-by-nc-nd Environmental Modelling & Software 2019-01-27

Abstract A quantitative analysis of torrential rainfall associated with typhoon Haitang (2005) is carried out using a modified moist ageostrophic Q vector and data from Weather Research Forecasting (WRF) model simulation. Four major factors determining the ascending motion have been studied: large-scale convective condensational heating, topographic lifting friction. The results show that heating plays role in process, secondary before landfall Haitang, vice versa after landfall. affects...

10.1016/j.pnsc.2008.07.007 article EN cc-by-nc-nd Progress in Natural Science Materials International 2008-11-22

Land use data with building characteristics are important for modeling the impacts of urban morphology on local climate. In this study, an extreme heat event in Shanghai, China, was simulated by using a WRF/BEP + BEM (Weather Research and Forecasting/Building Effect Parameterization Building Energy Model) model. We incorporated climate zone (LCZ) land that resolved 10 classes parameters. The simulation compared to control case based MODIS (Moderate-resolution Imaging Spectroradiometer) data....

10.1007/s13351-022-2104-4 article EN Journal of Meteorological Research 2022-12-01

The characteristics of 21 tropical cyclones (TCs) and associated high winds in Shanghai from 2005 to 2020 are analyzed based on the TC best track data, surface observations, ERA5 reanalysis dataset. Results indicate that 95% TCs causing were generated during July September, located south for ~80% impact time. Divided into four categories according tracks, show significant discrepancies genesis month location, intensity, size, duration. findings highlight combination effect track, distance...

10.1155/2024/1832172 article EN cc-by Advances in Meteorology 2024-01-01

10.1007/s00376-008-1053-x article EN Advances in Atmospheric Sciences 2008-11-01
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