Reconstruction of Hourly All-Weather Land Surface Temperature by Integrating Reanalysis Data and Thermal Infrared Data From Geostationary Satellites (RTG)

Abstract

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de > REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) <

Near-Real-Time Estimation of Hourly All-Weather Land Surface Temperature by Fusing Reanalysis Data and Geostationary Satellite Thermal Infrared Data

“…The quality of the FY-4A LST has been evaluated several times in previous studies, and the results show that it has acceptable accuracy [47], [52]. The RMSE of the FY-4A LST used in this study ranged from 3.13 to 4.98 K at the six ground sites [52].…”

TRIMS LST: A daily 1-km all-weather land surface temperature dataset for the Chinese landmass and surrounding areas (2000–2021)

“…were generally better than the daytime results, with an average RMSE of 1.74 K. The R 2 of the TRIMS LST for the four groups of sites were higher than 0.95 under clear-sky conditions, indicating that the TRIMS LST was in good agreement with the insitu LST. The improved accuracy of the TRIMS LST may be due to the reduction of the systematic bias of the original MODIS LST in the E-RTM method by extracting the LFC and HFC (Ding et al, 2022).…”

“…In this stage, the LST-related multidimensional temporal parameters are selected from GLDAS and an expression such as Eq. ( 2) is established for estimating LSTM-G-Aqua-T1: As demonstrated in Section 3.2, a high-resolution LST can be represented as a linear/nonlinear mapping of coarse-resolution multidimensional temporal parameters, and similar mapping relationships can be obtained in adjacent moments and periods (Ding et al, 2022). Therefore, fM-G-Terra can be equally used to estimate the 1-km all-weather LST at the Aqua overpass time.…”

“…This method is based on the interrelationship of different LSTs: neighbouring HFCcld are correlated at the limited spatial domain. Previous studies have shown that the approaches analogous to the convolutional implementation of sliding windows have a good ability to improve both the accuracy and the image quality of the merged LSTs (Ding et al, 2022;Long et al, 2020;Zhang et al, 2019). Similar pixels (termed as S) need to meet the following criteria: (i) they are within the same sliding window as the target pixel, and (ii) their land cover type does not differ from the target pixel.…”

“…Third, the temperature information retrieved from PMW observations contains information from the subsurface, which is physically different from the TIR LST, which provides the skin temperature (Zhou et al, 2017). Compared with the PMW data, reanalysis data can provide spatially continuous LSTs and related surface parameters; thus, it can act as an alternative basis to obtain the all-weather LST (Long et al, 2020;Ding et al, 2022). A typical method is the Reanalysis and Thermal infrared remote sensing Merging (RTM) method proposed by Zhang et al (2021) for integrating the GLDAS and MODIS LSTs for the Tibetan Plateau.…”