The ESA Land Surface Temperature (LST) Climate Change Initiative (LST_cci, https://climate.esa.int/en/projects/land-surface-temperature/) project aims to provide an accurate view of temperatures across land surfaces globally over the past 25 years. The main LST_cci data records are derived from inverting infrared observations from a variety of satellite sensors. This is the established technique to derive reasonably accurate and spatially resolved LST estimates. However, clouds obscure the radiation emanating from the surface, so infrared data records can only provide a clear-sky view of the surface. To have estimates for “all-weather” conditions, LST_cci is also providing a 25-year data record derived from microwave observations, which can see through most clouds, therefore providing a view of the surface independent of cloud coverage.
The microwave LST is derived from the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imagers (SSM/I) and the Special Sensor Microwave Imager Sounder (SSMIS) instruments. These sensors are operational weather satellites not originally designed with the instrumental and orbital stability constrains required to study decadal climate trends. To mitigate these limitations for climate studies, different aspects of data selection and algorithm development aspects have been considered, including:
1) Brightness temperatures. The Fundamental Climate Data Record (FCDR) of Microwave Imager Radiances from the Satellite Application Facility on Climate Monitoring (CM SAF) is selected to provide the observations. It corrects calibration anomalies and several known issues with the instruments to ensure the long-term stability of the FCDR, providing an inter-calibrated and homogenized data record of brightness temperatures.
2) Retrieval algorithm. To reduce the dependence on ancillary data, the processing is based around a neural network algorithm having only as inputs the observations at 18, 22, 36, and 85 GHz, together with pre-calculated emissivity values to account for the large variations in microwave emissivity. While most of the surface temperature information comes from the 18 and 36 GHz window channels, the 22 GHz, being close to a water vapor line, and the 85 GHz, more impacted by the atmosphere, allow to take into account atmospheric variations without the need to rely on related ancillary data.
3) Time correction. The orbital drift of the DMSP platforms results in variations of the overpass local time during the lifetime of the instrument. To facilitate climate studies, a temperature adjustment is available to have all LST estimates corrected to a fixed local time (6AM/PM).
The current processing is based around the inversion of the observations from SSM/I onboard the DMSP F13 satellite, and SSMIS onboard F17, covering respectively the periods 1996-2008 and 2009-2020. Twice per day LST estimates are available, coinciding with the descending (~6AM) and ascending (~6PM) overpasses of the instrument. The estimated uncertainty suggests precisions ranging between 2.0 and 3.5 K depending on the observing conditions. Comparing with the infrared retrievals, the uncertainties are larger, reflecting the stronger dependence of the microwave radiances in a more varying surface emissivity. Adding the time-correction offset permits to have the previous LST estimates adjusted to represent the LST at a fixed local time of 6 AM/PM. This correction improves the time stability of the data record, although adds a new component of uncertainty (~1.0-2.0 K) related to the errors of the time correction.
Current validation efforts are targeting comparisons with point measurements and larger scale estimates from atmospheric reanalysis. Comparing with in situ LST from a selection of ground stations, Root Means Square Differences take values between 2.0 and 5.0 K, but these figures need to be approached with caution due to the challenge of comparing the station point measurement with the ~25 km footprint of the microwave LST estimates. To analyze the stability of the long time series, the LST has been globally compared with skin temperature from ERA5. The first analyses suggests that the SSM/I and SMIS time-corrected LST data records are reasonably stable with time when considered as two independent time series, and that the discontinuities in the time-corrected data record associated with the change of instrument are greatly reduced when the data record is considered as a full time series.
The SSM/I and SSMIS LST data record is publicly available and can be downloaded from the ESA CCI Open Data Portal. Daily, monthly, and yearly LST estimates are provided, separated by descending and ascending orbits. The LST values are offered as a L3C product where the original swath L2 estimates have been remapped to a regular grid of 0.25 degrees to facilitate the use of the data record for global applications, but the original L2 values can also be provided if requested. The LST adjustment is included in the L3C files, and can be added by the user to have the time series at any location providing an LST estimate at a fixed 6AM/PM local time.