Observed differences between near-surface air and skin temperatures using satellite and ground-based data
Accurate estimates of long-term land surface temperature (Ts) and near-surface air temperature (Ta) at finer spatio-temporal resolutions are crucial for surface energy budget studies, for environmental applications, for land surface model data assimilation, and for climate change assessment and its associated impacts. The Atmospheric Infrared Sounder (AIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) sensors onboard the Aqua satellite provide a unique opportunity to estimate both temperatures twice daily at the global scale. In this study, differences between Ta and Ts were assessed locally over regions of North America from 2009 to 2013 using ground-based observations covering a wide range of geographical, topographical, and land cover types. The differences between Ta and Ts during non-precipitating conditions are generally 2–3 times larger than precipitating conditions. However, these differences show noticeable diurnal and seasonal variations. The differences between Ta and Ts were also investigated at the global scale using the AIRS estimates under clear-sky conditions for the period 2003–2015. The tropical regions showed about 5–20 °C warmer Ts than Ta during the day-time, whereas opposite characteristics (about 2–5 °C cooler Ts than Ta) are found over most parts of the globe during the night-time. Additionally, Ts estimates from the AIRS and the MODIS sensors were inter-compared. Although large-scale features of Ts were essentially similar for both sensors, considerable differences in magnitudes were observed (> 6 °C over mountainous regions). Finally, Ta and Ts estimates from the AIRS and MODIS sensors were validated against ground-based observations for the period of 2009–2013. The error characteristics notably varied with ground stations and no clear evidence of their dependency on land cover types or elevation was detected. However, the MODIS-derived Ts estimates generally showed larger biases and higher errors compared to the AIRS-derived estimates. The biases and errors increased steadily when the spatial resolution of the MODIS estimates changed from finer to coarser. These results suggest that representativeness error should be properly accounted for when validating satellite-based temperature estimates with point observations.
The authors would like to thank the editor and anonymous reviewers for their constructive comments. The statements contained within the manuscript are not the opinions of the funding agency or the US government; they reflect the authors’ opinions only. MODIS/Aqua land surface temperature data obtained from NASA EOSDID LP DAAC (https://lpdaac.usgs.gov/), Aqua/AIRS data products obtained from the GES DISC (https://disc.gsfc.nasa.gov/), USCRN observations obtained from the NOAA National Centers for Environmental Information (https://www.ncdc.noaa.gov/crn/), and MODIS-based 0.5 km global land cover climatology obtained from the USGS Land Cover Institute (https://landcover.usgs.gov/) are thankfully acknowledged.
This study was supported by the National Science Foundation (NSF) Research Experiences for Undergraduates (REU) under Grant 1560050 and by the Center for Remote Sensing and Earth System Sciences at the New York City College of Technology. This study was also partially supported by the Department of Defense Army Research Office under Grant W911NF–15–1–0070 and by NASA under Grant NNH15ZDA001N.
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