Advancing coupled land-atmosphere data assimilation through the integration of thermal infrared observations

Land-atmosphere interactions play a key role in the predictive skill of numerical weather prediction (NWP) models. The skin temperature is an important variable in this context, being at the interface between the land surface and the atmosphere, and modulating exchanges of heat, moisture, and momentum. Despite the abundance of high-resolution satellite data, assimilating infrared radiances over land has historically been challenging due to complex, heterogeneous surface emissivity and the highly dynamic diurnal variations of skin temperature.

This presentation highlights recent developments within the coupled data assimilation (DA) system at the European Centre for Medium-Range Weather Forecasts (ECMWF). For the first time, window channel (10.8 μm) infrared brightness temperatures from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) are activated in the four-dimensional variational analysis (4D-Var) system over land. To simulate the corresponding brightness temperatures in observation space, the forward operator - the RTTOV radiative transfer model – requires accurate representations of land surface emissivity, provided by the CAMEL Broadband Emissivity Climatology Version 3, and the land surface skin temperature. Up until now, this skin temperature acted as a sink variable in the 4D-Var.

Our new approach utilises an extended control vector, known as the TOVSCV, to explicitly assimilate the skin temperature in the Land Data Assimilation System (LDAS). Within each 12-hour DA window of the coupled land-atmosphere system, the analysed skin temperature from 4D-Var is included in the LDAS simplified extended Kalman filter (SEKF) observation vector as a pseudo-observation to constrain the soil temperature analysis.

This coupled DA approach bridges the gap between atmospheric radiance assimilation and the estimation of the land surface state. We will discuss the technical implementation of the TOVSCV extended control vector, the updated SEKF formulation, and the impact of this coupled methodology on the Earth system analysis. We will present results comparing the performance of these recent developments with a control experiment.

The work in this study is performed as part of the Data Assimilation and Numerical Testing for Copernicus Expansion Missions (DANTEX) project in collaboration with the European Space Agency (ESA).