Retrieval Consistency between LST CCI Satellite Data Products over Europe and Africa

Abstract

The assessment of satellite-derived land surface temperature (LST) data is essential to ensure their high quality for climate applications and research. This study intercompared seven LST products (i.e., ATSR_3, MODISA, MODIST, SLSTRA, SLSTRB, SEVIR2 and SEVIR4) of the European Space Agency’s (ESA) LST Climate Change Initiative (LST_cci) project, which are retrieved for polar and geostationary orbit satellites, and three operational LST products: NASA’s MODIS MOD11/MYD11 LST and ESA’s AATSR LST. All data were re-gridded on to a common spatial grid of 0.05° and matched for concurrent overpasses within 5 min. The matched data were analysed over Europe and Africa for monthly and seasonally aggregated median differences and studied for their dependence on land cover class and satellite viewing geometry. For most of the data sets, the results showed an overall agreement within ±2 K for median differences and robust standard deviation (RSD). A seasonal variation of median differences between polar and geostationary orbit sensor data was observed over Europe, which showed higher differences in summer and lower in winter. Over all land cover classes, NASA’s operational MODIS LST products were about 2 K colder than the LST_cci data sets. No seasonal differences were observed for the different land covers, but larger median differences between data sets were seen over bare soil land cover classes. Regarding the viewing geometry, an asymmetric increase of differences with respect to nadir view was observed for day-time data, which is mainly caused by shadow effects. For night-time data, these differences were symmetric and considerably smaller. Overall, despite the differences in the LST retrieval algorithms of the intercompared data sets, a good consistency between the LST_cci data sets was determined.

Solar zenith angle-based calibration of Himawari-8 land surface temperature based on MODIS spatiotemporal characteristics

“…Numerous studies have noted discrepancies between LST acquired at essentially the same time from both geostationary and polar-orbiting platforms (e.g., Pérez-Planells et al, 2023). Nighttime LST products exhibit good agreement across various viewing configurations, whereas daytime observations have discrepancies attributed to the influence of shadows and temperature gradients within the landscape cover .…”

“…demonstrated a difference of approximately ±1 K between LST products from the AVHRR sensor onboard Metop polar-orbiting satellites and the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the MSG geostationary platform. Pérez-Planells et al (2023) reported that Terra-and Aqua-MODIS LST products (i.e., MOD11 and MYD11, respectively) were around 2 K cooler than the LST datasets from the European Space Agency's Climate Change Initiative (ESA CCI) across all land cover classes. Similarly, found MYD11 LST generally showed lower values than their SW algorithm-retrieved Himawari-8 LST over southeast China and Australia.…”