The SLSTR Level-2 products are generated via several processors (processing overview at Level-2 Processing Overview) and divided into two branches :

• The Marine Branch operated by EUMETSAT and providing SST/L2P products, SLSTR NRT aerosol products and SLSTR NRT fire products
• The Land Branch operated by ESA and providing LST products and SLSTR NTC Fire products

Detailed description of Marine branch processing and products can be found on https://www.eumetsat.int/sea-surface-temperature-services, https://www.eumetsat.int/S3-NRT-FRP and https://www.eumetsat.int/S3-AOD  

The LST processing module includes a split-window method, using radiances from two channels whose band centres are close in wavelength, to determine the effective radiometric temperature of the Earth's surface "skin" in the instrument field of view ("skin" referring to the top surface in bare soil conditions and to the effective emitting temperature of vegetation "canopies" as determined from a view of the top of a canopy). This method assumes that the linearity of the relationship between LST and BT results from linearization of the Planck function and linearity of the variation of atmospheric transmittance with column water vapour amount. Several modules are also dedicated to contextual information, such as probabilistic cloud and snow mask. Computation of Uncertainties are also included in this SLSTR Level 2 processor.

The processor generating the FRP products, namely the FRP IPF, has been deployed in January 2020. The objective is to detect any fire over land and ocean and to provide Fire radiative power associated with this fire. In addition, several characteristics as the classification, the uncertainties and some radiometric measurements are also provided for each fire. Over land, this processing is performed over the 1km nadir view image grid and uses a combination of the thermal S7 and F1 measurements to detect fires. The fires are first detected using a spatial and a spectral filter, then confirmed by comparing individual pixel measurements with background characterization. Once a fire has been confirmed, it can be characterized through estimation of its fire radiative power.  This computation is based on a power law approximation to the Planck function and exploits the fact that for the temperature range of active fires the Planck function relationship between emitted spectral radiance and emitter temperature approaches a 4th order power law at MIR wavelengths.

A second fire detection method is also applied on the 500m grid and is using the SWIR measurements as the hotspot signals will be maximized at this smaller pixel area and the algorithm will be most sensitive to the smaller sub-pixel hotspots. This detection is applied only during night-time and over both Land and Ocean surface. A clustering approach is performed to find correspondence between fires detected using thermal channels and fires detected using SWIR channels.

Common to these core processing main modules, both processors include:

• one module dedicated to checking the input Level-1B files and auxiliary files to verify their presence and self-consistency,
• one module gathering general functions such as deriving pixel-by-pixel estimates of radiance, BT, radiance uncertainty and BT uncertainty for channels S2, S3, S6 to S9, F1 and F2,
• one module dedicated to product formatting, which populates and writes out the product metadata and data fields.