Zobrazeno 1 - 10
of 91
pro vyhledávání: '"CLDAS"'
Publikováno v:
Gaoyuan qixiang, Vol 43, Iss 2, Pp 464-477 (2024)
This study utilized the 2020 -2021 China Meteorological Administration （CMA） Land Data Assimilation System （CLDAS） hourly surface air temperature （T2m） product in combination with the T2m forecast data from the CMA Shanghai Rapid Update C
Externí odkaz:
https://doaj.org/article/0d10484b42034072ac353381adde28e2
Publikováno v:
暴雨灾害, Vol 42, Iss 4, Pp 479-487 (2023)
Enshi is a foggy area in Hubei Province with complex terrain and large spatial difference in fog. However, the meteorological stations in this area are sparse, making it difficult to study the spatio-temporal distribution characteristics of fog. This
Externí odkaz:
https://doaj.org/article/433e3dd9418d4081a6d0accf1d40154e
Autor:
Jieli Liu, Chunxiang Shi, Lingling Ge, Ruian Tie, Xiaojian Chen, Tao Zhou, Xiang Gu, Zhanfei Shen
Publikováno v:
Remote Sensing, Vol 16, Iss 11, p 1867 (2024)
Before 2008, China lacked high-coverage regional surface observation data, making it difficult for the China Meteorological Administration Land Data Assimilation System (CLDAS) to directly backtrack high-resolution, high-quality land assimilation pro
Externí odkaz:
https://doaj.org/article/14c06bad1d364a3ca4eb63eb441e6b6c
Publikováno v:
Frontiers in Marine Science, Vol 10 (2024)
The non-uniformity of the evaporation duct has a significant impact on the propagation of electromagnetic waves. Based on the near real-time dataset from the China Meteorological Administration Land Data Assimilation System (CLDAS) and the National C
Externí odkaz:
https://doaj.org/article/1742cb8bdf0a4ffaa897c396584aaf7e
Publikováno v:
Gaoyuan qixiang, Vol 42, Iss 2, Pp 472-482 (2023)
Using hourly data from automatic observation stations in Guizhou Province， the China Meteorological Administration Land Data Assimilation System （CLDAS） temperature and relative humidity products have been evaluated and linearly corrected in 20
Externí odkaz:
https://doaj.org/article/9737646ae11149509a2985bde5ba20d3
Publikováno v:
Gaoyuan qixiang, Vol 42, Iss 1, Pp 197-209 (2023)
Utilizing four nested domains of large eddy simulation with Weather Research and Forecasting Model （WRF-LES）， this paper carries out wind simulation test in Chongli area， where is one of the host locations of 2022 Beijing Winter Olympics.Base
Externí odkaz:
https://doaj.org/article/3806d5dbfedc415e9c82c4f40b22c620
Akademický článek
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Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 7124-7134 (2023)
To improve the finesse of the temperature-humidity index (THI), this study applies four machine learning methods in THI downscaling, including multiple linear regression, random forest (RF), support vector machine, and gradient boosting machine. The
Externí odkaz:
https://doaj.org/article/47c95e18c5194e5a94b6061f8cabe49d
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 4414-4422 (2023)
Soil moisture (SM) is an important parameter in all environments because it affects the relationship between the land surface and atmospheric processes. Therefore, finding products that can accurately measure SM is critical to improving drought manag
Externí odkaz:
https://doaj.org/article/0a3ba97000654808ad9c7b0ad19e1f82
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1516 (2024)
Satellite precipitation products (SPPs) are of great significance for water resource management and utilization in China; however, they suffer from considerable uncertainty. While numerous researchers have evaluated the accuracy of various SPPs, furt
Externí odkaz:
https://doaj.org/article/4dd6974316344469911703576284e5f1