Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model
This work gives a first insight into the potential of the Weather Research and Forecasting (WRF) model to provide high-resolution vertical profiles for land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing. WRF numerical simulations were conducted to downscale NCEP Clim...
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MDPI AG
2021-10-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/12/11/1436 |
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| author | Lucas Ribeiro Diaz Daniel Caetano Santos Pâmela Suélen Käfer Nájila Souza da Rocha Savannah Tâmara Lemos da Costa Eduardo Andre Kaiser Silvia Beatriz Alves Rolim |
| author_facet | Lucas Ribeiro Diaz Daniel Caetano Santos Pâmela Suélen Käfer Nájila Souza da Rocha Savannah Tâmara Lemos da Costa Eduardo Andre Kaiser Silvia Beatriz Alves Rolim |
| author_sort | Lucas Ribeiro Diaz |
| collection | DOAJ |
| description | This work gives a first insight into the potential of the Weather Research and Forecasting (WRF) model to provide high-resolution vertical profiles for land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing. WRF numerical simulations were conducted to downscale NCEP Climate Forecast System Version 2 (CFSv2) reanalysis profiles, using two nested grids with horizontal resolutions of 12 km (G12) and 3 km (G03). We investigated the utility of these profiles for the atmospheric correction of TIR data and LST estimation, using the moderate resolution atmospheric transmission (MODTRAN) model and the Landsat 8 TIRS10 band. The accuracy evaluation was performed using 27 clear-sky cases over a radiosonde station in Southern Brazil. We included in the comparative analysis NASA’s Atmospheric Correction Parameter Calculator (ACPC) web-tool and profiles obtained directly from the NCEP CFSv2 reanalysis. The atmospheric parameters from ACPC, followed by those from CFSv2, were in better agreement with parameters calculated using in situ radiosondes. When applied into the radiative transfer equation (RTE) to retrieve LST, the best results (RMSE) were, in descending order: CFSv2 (0.55 K), ACPC (0.56 K), WRF G12 (0.79 K), and WRF G03 (0.82 K). Our findings suggest that there is no special need to increase the horizontal resolution of reanalysis profiles aiming at RTE-based LST retrieval. However, the WRF results were still satisfactory and promising, encouraging further assessments. We endorse the use of the well-known ACPC and recommend the NCEP CFSv2 profiles for TIR atmospheric correction and LST single-channel retrieval. |
| first_indexed | 2024-03-10T05:42:13Z |
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| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-10T05:42:13Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-6be09c7e3fcf453caf12efab13498b242023-11-22T22:24:21ZengMDPI AGAtmosphere2073-44332021-10-011211143610.3390/atmos12111436Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF ModelLucas Ribeiro Diaz0Daniel Caetano Santos1Pâmela Suélen Käfer2Nájila Souza da Rocha3Savannah Tâmara Lemos da Costa4Eduardo Andre Kaiser5Silvia Beatriz Alves Rolim6State Research Center for Remote Sensing and Meteorology (CEPSRM), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, Porto Alegre 91501-970, RS, BrazilCenter for Natural and Exact Sciences, Department of Physics, Universidade Federal de Santa Maria (UFSM), Av. Roraima, Santa Maria 97105-900, RS, BrazilState Research Center for Remote Sensing and Meteorology (CEPSRM), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, Porto Alegre 91501-970, RS, BrazilState Research Center for Remote Sensing and Meteorology (CEPSRM), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, Porto Alegre 91501-970, RS, BrazilState Research Center for Remote Sensing and Meteorology (CEPSRM), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, Porto Alegre 91501-970, RS, BrazilState Research Center for Remote Sensing and Meteorology (CEPSRM), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, Porto Alegre 91501-970, RS, BrazilState Research Center for Remote Sensing and Meteorology (CEPSRM), Universidade Federal do Rio Grande do Sul (UFRGS), Av. Bento Gonçalves 9500, Porto Alegre 91501-970, RS, BrazilThis work gives a first insight into the potential of the Weather Research and Forecasting (WRF) model to provide high-resolution vertical profiles for land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing. WRF numerical simulations were conducted to downscale NCEP Climate Forecast System Version 2 (CFSv2) reanalysis profiles, using two nested grids with horizontal resolutions of 12 km (G12) and 3 km (G03). We investigated the utility of these profiles for the atmospheric correction of TIR data and LST estimation, using the moderate resolution atmospheric transmission (MODTRAN) model and the Landsat 8 TIRS10 band. The accuracy evaluation was performed using 27 clear-sky cases over a radiosonde station in Southern Brazil. We included in the comparative analysis NASA’s Atmospheric Correction Parameter Calculator (ACPC) web-tool and profiles obtained directly from the NCEP CFSv2 reanalysis. The atmospheric parameters from ACPC, followed by those from CFSv2, were in better agreement with parameters calculated using in situ radiosondes. When applied into the radiative transfer equation (RTE) to retrieve LST, the best results (RMSE) were, in descending order: CFSv2 (0.55 K), ACPC (0.56 K), WRF G12 (0.79 K), and WRF G03 (0.82 K). Our findings suggest that there is no special need to increase the horizontal resolution of reanalysis profiles aiming at RTE-based LST retrieval. However, the WRF results were still satisfactory and promising, encouraging further assessments. We endorse the use of the well-known ACPC and recommend the NCEP CFSv2 profiles for TIR atmospheric correction and LST single-channel retrieval.https://www.mdpi.com/2073-4433/12/11/1436thermal infrared (TIR)atmospheric correctionreanalysisLandsatradiative transfer equation (RTE)NCEP CFSv2 |
| spellingShingle | Lucas Ribeiro Diaz Daniel Caetano Santos Pâmela Suélen Käfer Nájila Souza da Rocha Savannah Tâmara Lemos da Costa Eduardo Andre Kaiser Silvia Beatriz Alves Rolim Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model Atmosphere thermal infrared (TIR) atmospheric correction reanalysis Landsat radiative transfer equation (RTE) NCEP CFSv2 |
| title | Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model |
| title_full | Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model |
| title_fullStr | Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model |
| title_full_unstemmed | Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model |
| title_short | Land Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model |
| title_sort | land surface temperature retrieval using high resolution vertical profiles simulated by wrf model |
| topic | thermal infrared (TIR) atmospheric correction reanalysis Landsat radiative transfer equation (RTE) NCEP CFSv2 |
| url | https://www.mdpi.com/2073-4433/12/11/1436 |
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