Evaluation of the Bias in the Use of Clear-Sky Compared with All-Sky Observations of Monthly and Annual Daytime Land Surface Temperature

Author:

Gallo Kevin1,Krishnan Praveena23

Affiliation:

1. a NOAA/NESDIS Center for Satellite Applications and Research, College Park, Maryland

2. b NOAA/Air Resources Laboratory Atmospheric Turbulence and Diffusion Division, Oak Ridge, Tennessee

3. c Oak Ridge Associated Universities, Oak Ridge, Tennessee

Abstract

Abstract Satellite-derived observations of land surface temperature (LST) are being utilized in a growing number of land surface studies; however, these observations are generally obtained from optical sensors that exclude cloudy observations of the land surface. The impact of using only clear-sky observations of land surfaces on monthly and annual estimates of daytime LST over two U.S. Climate Reference Network (USCRN) sites was evaluated over five years with daily in situ LST observations available for all-sky (clear and cloudy) conditions. The in situ LST observations were obtained for the nominal daytime observations associated with the MODIS sensors on board the Terra and Aqua satellites and were identified as all-sky or clear-sky conditions by utilizing cloud information provided with the MODIS LST product. Both monthly/annual mean and monthly/annual maximum values of daytime LST were significantly different when only clear-sky values were utilized, in comparison with all-sky values. Monthly averaged differences between the mean clear- and all-sky daytime LST (dLST) values ranged from −0.1° ± 1.5°C for January to 5.6° ± 1.8°C for May. Annually averaged dLST values, over the five years of the study, were 2.58°C, and differences between the maximum values of clear- and all-sky daytime LST values were −1.03°C. Although significant differences between mean annual clear-sky and all-sky daytime LST values were more frequent than differences observed for the annual maximum daytime LST values, the results suggest that the exclusive use of either mean or maximum clear-sky daytime LST values is not advisable for applications in which the use of daytime all-sky LST values would be more applicable.

Funder

NOAA USCRN Program

NESDIS/STAR GOES-R Program

NESDIS/STAR JPSS Program

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference60 articles.

1. Abera, T. A., J. Heiskanen, E. E. Maeda, and P. K. E. Pellikka, 2020: Land surface temperature trend and its drivers in East Africa. J. Geophys. Res. Atmos., 125, e2020JD033446, https://doi.org/10.1029/2020JD033446.

2. Discriminating clear sky from clouds with MODIS;Ackerman, S. A.,1998

3. Cloud detection with MODIS: Part II. Validation;Ackerman, S. A.,2008

4. AppEEARS Team, 2020: Application for extracting and exploring analysis ready samples (AppEEARS), version. 2.30. NASA EOSDIS LP DAAC, USGS/EROS Center, accessed 17 November 2021, https://lpdaacsvc.cr.usgs.gov/appeears.

5. Quantifying uncertainty in satellite-retrieved land surface temperature from cloud detection errors;Bulgin, C. E.,2018

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