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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2021
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oai:doaj.org-article:6be09c7e3fcf453caf12efab13498b242021-11-25T16:44:45ZLand Surface Temperature Retrieval Using High-Resolution Vertical Profiles Simulated by WRF Model10.3390/atmos121114362073-4433https://doaj.org/article/6be09c7e3fcf453caf12efab13498b242021-10-01T00:00:00Zhttps://www.mdpi.com/2073-4433/12/11/1436https://doaj.org/toc/2073-4433This 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.Lucas Ribeiro DiazDaniel Caetano SantosPâmela Suélen KäferNájila Souza da RochaSavannah Tâmara Lemos da CostaEduardo Andre KaiserSilvia Beatriz Alves RolimMDPI AGarticlethermal infrared (TIR)atmospheric correctionreanalysisLandsatradiative transfer equation (RTE)NCEP CFSv2Meteorology. ClimatologyQC851-999ENAtmosphere, Vol 12, Iss 1436, p 1436 (2021) |
institution |
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DOAJ |
language |
EN |
topic |
thermal infrared (TIR) atmospheric correction reanalysis Landsat radiative transfer equation (RTE) NCEP CFSv2 Meteorology. Climatology QC851-999 |
spellingShingle |
thermal infrared (TIR) atmospheric correction reanalysis Landsat radiative transfer equation (RTE) NCEP CFSv2 Meteorology. Climatology QC851-999 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 |
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. |
format |
article |
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 |
title |
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_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_sort |
land surface temperature retrieval using high-resolution vertical profiles simulated by wrf model |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/6be09c7e3fcf453caf12efab13498b24 |
work_keys_str_mv |
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1718413024580075520 |