Zobrazeno 1 - 10
of 204
pro vyhledávání: '"atmospheric motion vectors"'
Publikováno v:
Remote Sensing, Vol 16, Iss 23, p 4561 (2024)
The ever-increasing capacity of numerical weather prediction (NWP) models requires accurate flow information at higher spatial and temporal resolutions. The atmospheric motion vectors (AMVs) extracted from the Advanced Geostationary Radiation Imager
Externí odkaz:
https://doaj.org/article/df2783648cb24793b624b8d4b9da7b21
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 7577-7591 (2024)
Typhoons' rapid variation makes effective hazard prevention difficult, which remains a challenging research topic requiring novel observation technology and analysis methodology. We developed an automatic methodology for mining the information on the
Externí odkaz:
https://doaj.org/article/4662cf5242854486995371e2adc3b3f8
Publikováno v:
Remote Sensing, Vol 16, Iss 18, p 3522 (2024)
Meteorological satellite remote sensing is important for numerical weather forecasts, but its accuracy is affected by many things during observation and retrieval, showing that it can be improved. As a standard way to measure wind from space, atmosph
Externí odkaz:
https://doaj.org/article/72a9fb06350a4ecb865bb37d37cfea3d
Publikováno v:
Remote Sensing, Vol 16, Iss 9, p 1562 (2024)
Atmospheric motion vectors, which can be used to infer wind speed and direction based on the trajectory of cloud movement, are instrumental in enhancing atmospheric wind-field insights, contributing notably to wind-field optimization and forecasting.
Externí odkaz:
https://doaj.org/article/d225683b4efa4d16b85675be2b524dec
Autor:
Russell L. Elsberry, Joel W. Feldmeier, Hway-Jen Chen, Christopher S. Velden, Hsiao-Chung Tsai
Publikováno v:
Atmosphere, Vol 15, Iss 3, p 353 (2024)
Four-dimensional COAMPS Dynamic Initialization (FCDI) analyses that include high-temporal- and high-spatial-resolution GOES-16 Atmospheric Motion Vector (AMV) datasets are utilized to understand and predict why pre-Bonnie (2022), designated as a Pote
Externí odkaz:
https://doaj.org/article/0244ee8bfd934b458d1a96b6b98a65b8
Akademický článek
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Akademický článek
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Publikováno v:
Atmosphere, Vol 14, Iss 11, p 1606 (2023)
Based on atmospheric motion vectors (AMVs) derived from the Fengyun-4 meteorological satellite (FY-4), in this paper, integrated multi-satellite retrievals for GPM precipitation and reanalysis datasets and the vertical distribution characteristics of
Externí odkaz:
https://doaj.org/article/976e0c73ce49408cb63f03e433c9b534
Publikováno v:
Remote Sensing, Vol 15, Iss 8, p 2154 (2023)
The stereo-winds method follows trackable atmospheric cloud features from multiple viewing perspectives over multiple times, generally involving multiple satellite platforms. Multi-temporal observations provide information about the wind velocity and
Externí odkaz:
https://doaj.org/article/ccbdc28e9c534b4abfba915e635fb53d
Autor:
Xin Xia, Jiali Feng, Kun Wang, Jian Sun, Yudong Gao, Yuchao Jin, Yulong Ma, Yan Gao, Qilin Wan
Publikováno v:
Atmosphere, Vol 14, Iss 3, p 565 (2023)
Hybrid data assimilation (DA) methods have received extensive attention in the field of numerical weather prediction. In this study, a hybrid gain data assimilation (HGDA) method that combined the gain matrices of ensemble and variational methods was
Externí odkaz:
https://doaj.org/article/50aefd192b0f47dda73897f4040130b0