Analysis of atmospheric temperature data by 4D spatial–temporal statistical model

Abstract The meteorological data such as temperature of the upper atmosphere is ssential for accurate weather forecasting. The Universal Rawinsonde Observation Program (RAOB) establishes an extensive radiosonde network worldwide to observe atmospheric meteorological data from the surface to the low...

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Autores principales:	Ke Xu, Yaqiong Wang
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/79add7a6286a48c4a7f04fab8b545d09
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spelling	oai:doaj.org-article:79add7a6286a48c4a7f04fab8b545d092021-12-02T18:48:09ZAnalysis of atmospheric temperature data by 4D spatial–temporal statistical model10.1038/s41598-021-98125-22045-2322https://doaj.org/article/79add7a6286a48c4a7f04fab8b545d092021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98125-2https://doaj.org/toc/2045-2322Abstract The meteorological data such as temperature of the upper atmosphere is ssential for accurate weather forecasting. The Universal Rawinsonde Observation Program (RAOB) establishes an extensive radiosonde network worldwide to observe atmospheric meteorological data from the surface to the low stratosphere. The RAOB data data has very high accuracy but can offer a very limited spatial coverage. Meanwhile, ERA-Interim reanalysis data is widely available but with low-quality. We propose a 4D spatiotemporal statistical model which can make effective inferences from ERA-Interim reanalysis data to RAOB data. Finally, we can obtain a huge amount of RAOB data with high-quality and can offer a very wide spatial coverage. In empirical research, we collected data from 200 launch sites around the world in January 2015. The 4D spatiotemporal statistical model successfully analyzed the observation gaps at different pressure levels.Ke XuYaqiong WangNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ke Xu Yaqiong Wang Analysis of atmospheric temperature data by 4D spatial–temporal statistical model
description	Abstract The meteorological data such as temperature of the upper atmosphere is ssential for accurate weather forecasting. The Universal Rawinsonde Observation Program (RAOB) establishes an extensive radiosonde network worldwide to observe atmospheric meteorological data from the surface to the low stratosphere. The RAOB data data has very high accuracy but can offer a very limited spatial coverage. Meanwhile, ERA-Interim reanalysis data is widely available but with low-quality. We propose a 4D spatiotemporal statistical model which can make effective inferences from ERA-Interim reanalysis data to RAOB data. Finally, we can obtain a huge amount of RAOB data with high-quality and can offer a very wide spatial coverage. In empirical research, we collected data from 200 launch sites around the world in January 2015. The 4D spatiotemporal statistical model successfully analyzed the observation gaps at different pressure levels.
format	article
author	Ke Xu Yaqiong Wang
author_facet	Ke Xu Yaqiong Wang
author_sort	Ke Xu
title	Analysis of atmospheric temperature data by 4D spatial–temporal statistical model
title_short	Analysis of atmospheric temperature data by 4D spatial–temporal statistical model
title_full	Analysis of atmospheric temperature data by 4D spatial–temporal statistical model
title_fullStr	Analysis of atmospheric temperature data by 4D spatial–temporal statistical model
title_full_unstemmed	Analysis of atmospheric temperature data by 4D spatial–temporal statistical model
title_sort	analysis of atmospheric temperature data by 4d spatial–temporal statistical model
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/79add7a6286a48c4a7f04fab8b545d09
work_keys_str_mv	AT kexu analysisofatmospherictemperaturedataby4dspatialtemporalstatisticalmodel AT yaqiongwang analysisofatmospherictemperaturedataby4dspatialtemporalstatisticalmodel
_version_	1718377632207208448

Analysis of atmospheric temperature data by 4D spatial–temporal statistical model

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