A new East African satellite data validation station: Performance of the LSA-SAF all-weather land surface temperature product over a savannah biome

Abstract

We describe a new satellite data validation facility located in a savannah biome at the International Livestock Research Institute (ILRI) Kapiti Research Station (Kenya). The facility is focused on satellite land surface temperature (LST) and is equipped with multiple ground-viewing infrared radiometers across four sites. The in-situ LST observations are upscaled to match satellite LST products using a geometric illumination model. The in-situ sensor network represents a step-forward in LST validation in East Africa and savannah biomes. To our knowledge this is the first time that such an extensive network of LST radiometers and supporting measurements has been installed in sub-Saharan Africa, or a savannah. With this network we capture surface heterogeneity in a manner that has not previously been possible. The LST ground data from this station collected between October 2018 and March 2019 is used to evaluate the new Land Surface Analysis Satellite Application Facility (LSA-SAF) all-sky LST product (MLST-AS) that blends clear-sky infrared-retrieved LSTs with LSTs derived from a land surface energy balance model to fill gaps due to cloudy conditions. Comparison against the in-situ LSTs indicates overall accuracy, precision, and root-mean-square error (RMSE) of MLST-AS to be 2.02 K, 1.38 K and 3.64 K respectively. The infrared-retrieved LST component of MLST-AS under clear skies has an accuracy, precision and RMSE of 1.16 K, 0.8 K and 3.16 K respectively. The energy balance model-based component of MLST-AS has performance statistics of 3.02 K, 1.38 K and 4.16 K. The MLST-AS energy balance model component is observed to perform worse when surface moisture is present, underestimating night-time and daily maximum temperatures by between 2 and 4 K in the 24 h following surface water deposition as precipitation or dew.