Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Chunxiang, Shi"'
Autor:
Yi Zheng, Jun Liu, Nongping Feng, Jing Wei, Xiaohong Jia, Lu Luo, Ruijun Xu, Chunxiang Shi, Rui Wang, Hong Sun, Yuewei Liu
Publikováno v:
Ecotoxicology and Environmental Safety, Vol 287, Iss , Pp 117289- (2024)
Interstitial lung diseases (ILDs) lead to increased morbidity and premature deaths, imposing a significant burden on public health worldwide. Recently, several studies have linked ambient air pollution with the acute exacerbation of certain ILDs, but
Externí odkaz:
https://doaj.org/article/16787ddf7e0842dbb0736791986a9148
Autor:
Shuai Sun, Qiang Zhang, Chunxiang Shi, Vijay P. Singh, Tao Zhang, Junxia Gu, Gang Wang, Wenhuan Wu, Donghui Chen, Jianmei Wu
Publikováno v:
npj Climate and Atmospheric Science, Vol 7, Iss 1, Pp 1-8 (2024)
Abstract Although urban irrigation can modulate local hydrothermal conditions and mitigate urban heat island effects, its impact on moist heat stress (MHS) is poorly understood. Employing the Weather Research and Forecasting Single-Layer Urban Canopy
Externí odkaz:
https://doaj.org/article/8dbda887e8cc4f869371b082637f1db7
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7490-7500 (2024)
Himawari-8 satellite, equipped with an advanced Himawari imager (AHI), has been widely employed for cloud detection tasks due to its high-spatiotemporal resolution. In this article, we propose a deep learning model named dual-branch deformable convol
Externí odkaz:
https://doaj.org/article/c093967ab87a4df4a879f6ad4f32d7d9
Publikováno v:
Remote Sensing, Vol 16, Iss 17, p 3327 (2024)
Snow detection is imperative in remote sensing for various applications, including climate change monitoring, water resources management, and disaster warning. Recognizing the limitations of current deep learning algorithms in cloud and snow boundary
Externí odkaz:
https://doaj.org/article/f99c26461feb482ca7587ec57bbbf935
Publikováno v:
Gaoyuan qixiang, Vol 42, Iss 3, Pp 758-770 (2023)
Human life is affected by the intensity of near-surface wind fields， so obtaining high-precision wind field meteorological live products is essential. Precise and accurate wind field simulation can provide data support for real-time weather product
Externí odkaz:
https://doaj.org/article/d2d81b9fcab24d559c2f96afc19e7f54
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:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 1678-1690 (2023)
Deep learning techniques, especially convolutional neural networks (CNNs), have dramatically boosted the performance of statistical downscaling. In this study, we propose a CNN-based 2 m air temperature downscaling model named Terrain-Guided Attentio
Externí odkaz:
https://doaj.org/article/53e55a7cd3be417ca2f3455e8f85760e
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-12 (2022)
Abstract Heatwaves have afflicted human health, ecosystem, and socioeconomy and are expected to intensify under warming climate. However, few efforts have been directed to moist heat stress (MHS) considering relative humidity and wind speed, and mois
Externí odkaz:
https://doaj.org/article/f4ec73e1c5bb412f9b1c9cf89170396b
Publikováno v:
Gaoyuan qixiang, Vol 41, Iss 3, Pp 803-813 (2022)
Cloud is an important factor affecting climate change， and it plays an important role in controlling the earth's energy and water cycle.A comprehensive understanding of the distribution and changes of the total cloud cover is particularly important
Externí odkaz:
https://doaj.org/article/a9086b0a224642779791b02316b9cb25
Publikováno v:
Gaoyuan qixiang, Vol 41, Iss 3, Pp 617-629 (2022)
In order to evaluate the hydrological utility of CLDAS-Prcp multi-source fusion precipitation products and the simulation effect of WRF-Hydro model in small and medium-scale watersheds， Firstly CLDAS-Prcp and IMERG-Final multi-source fusion precipi
Externí odkaz:
https://doaj.org/article/d9b95c58490a4f74895cedb7da3a1efe