Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements
The near-surface air temperature (<inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula>) is a principal variable describing energy exchange and water circulation between the land surface and the atmospheric environment. The estimation...
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2025-01-01
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| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
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| Online Access: | https://ieeexplore.ieee.org/document/10767357/ |
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| author | Ronghan Xu Xin Wang Yonghong Hu Lin Chen Suling Ren Guangzhen Cao Di Xian Eston Ranson Mogha |
| author_facet | Ronghan Xu Xin Wang Yonghong Hu Lin Chen Suling Ren Guangzhen Cao Di Xian Eston Ranson Mogha |
| author_sort | Ronghan Xu |
| collection | DOAJ |
| description | The near-surface air temperature (<inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula>) is a principal variable describing energy exchange and water circulation between the land surface and the atmospheric environment. The estimation of <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> by satellite land surface temperature (LST) is challenging due to the variable magnitude of the difference between <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> and LST in both space and time, as well as the restriction of estimated <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> to clear-sky conditions because of the penetration of infrared wavelengths. Moreover, the estimation suffers from low temporal resolution and primarily focuses on daily minimum, maximum, and two instantaneous <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> per day. This study proposes a method for estimating all-sky gridded diurnal <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> at regional scale from FY-4B/AGRI measurements. The multiscale geographically weighted regression model was investigated to establish the dynamic relationships between ground station observed <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> and satellite LST under clear-sky conditions by employing different spatial values for each explanatory variable in localized regressions. A moving window loop based multiple linear regression was employed to establish the relationship between satellite-derived clear-sky <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> and other variables to extrapolate <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> in cloudy-sky pixels. The results showed that the proposed method captures the trend of <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> variations well in hourly profiles with R values greater than 0.95. RMSE was 1.75 °C, 1.38 °C, 1.95 °C, and 2.19 °C in April, July, October, and January, respectively. The demonstration of heatwave monitoring showed that satellite-estimated <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> provide an excellent representation of the spatial and temporal evolution of the heatwave. |
| format | Article |
| id | doaj-art-c5905af04caf48e88ab3af6ea02ec1e5 |
| institution | Kabale University |
| issn | 1939-1404 2151-1535 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
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| series | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| spelling | doaj-art-c5905af04caf48e88ab3af6ea02ec1e52025-01-16T00:00:27ZengIEEEIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing1939-14042151-15352025-01-01181288130110.1109/JSTARS.2024.350685710767357Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B MeasurementsRonghan Xu0https://orcid.org/0000-0003-0490-0199Xin Wang1Yonghong Hu2https://orcid.org/0000-0002-1520-4386Lin Chen3https://orcid.org/0000-0002-2390-899XSuling Ren4Guangzhen Cao5https://orcid.org/0000-0001-6974-1972Di Xian6https://orcid.org/0000-0001-8156-2395Eston Ranson Mogha7Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, ChinaInternational Research Center of Big Data for Sustainable Development Goals, Beijing, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, ChinaKey Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center (National Center for Space Weather), China Meteorological Administration, Beijing, ChinaNational Meteorological Training Centre, Tanzania Meteorological Authority, Dodoma, TanzaniaThe near-surface air temperature (<inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula>) is a principal variable describing energy exchange and water circulation between the land surface and the atmospheric environment. The estimation of <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> by satellite land surface temperature (LST) is challenging due to the variable magnitude of the difference between <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> and LST in both space and time, as well as the restriction of estimated <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> to clear-sky conditions because of the penetration of infrared wavelengths. Moreover, the estimation suffers from low temporal resolution and primarily focuses on daily minimum, maximum, and two instantaneous <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> per day. This study proposes a method for estimating all-sky gridded diurnal <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> at regional scale from FY-4B/AGRI measurements. The multiscale geographically weighted regression model was investigated to establish the dynamic relationships between ground station observed <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> and satellite LST under clear-sky conditions by employing different spatial values for each explanatory variable in localized regressions. A moving window loop based multiple linear regression was employed to establish the relationship between satellite-derived clear-sky <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> and other variables to extrapolate <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> in cloudy-sky pixels. The results showed that the proposed method captures the trend of <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> variations well in hourly profiles with R values greater than 0.95. RMSE was 1.75 °C, 1.38 °C, 1.95 °C, and 2.19 °C in April, July, October, and January, respectively. The demonstration of heatwave monitoring showed that satellite-estimated <inline-formula><tex-math notation="LaTeX">${{T}_{air}}$</tex-math></inline-formula> provide an excellent representation of the spatial and temporal evolution of the heatwave.https://ieeexplore.ieee.org/document/10767357/All-skydiurnalnear-surface air temperatureregional scalesatellite remote sensing |
| spellingShingle | Ronghan Xu Xin Wang Yonghong Hu Lin Chen Suling Ren Guangzhen Cao Di Xian Eston Ranson Mogha Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing All-sky diurnal near-surface air temperature regional scale satellite remote sensing |
| title | Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements |
| title_full | Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements |
| title_fullStr | Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements |
| title_full_unstemmed | Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements |
| title_short | Estimation of All-Sky Gridded Diurnal Near-Surface Air Temperatures at Regional Scale From FY-4B Measurements |
| title_sort | estimation of all sky gridded diurnal near surface air temperatures at regional scale from fy 4b measurements |
| topic | All-sky diurnal near-surface air temperature regional scale satellite remote sensing |
| url | https://ieeexplore.ieee.org/document/10767357/ |
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