Submitted as: model evaluation paper 07 Apr 2021

Submitted as: model evaluation paper | 07 Apr 2021

Review status: a revised version of this preprint is currently under review for the journal GMD.

Multi-sensor analyses of the skin temperature for the assimilation of satellite radiances in the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS, cycle 47R1)

Sebastien Massart, Niels Bormann, Massimo Bonavita, and Cristina Lupu Sebastien Massart et al.
  • ECMWF Shinfield Park Reading RG2 9AX United Kingdom

Abstract. The assimilation of clear-sky radiance in the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric analysis relies on the clear-sky radiances observation operator. Some of these radiances have frequencies that make them sensitive to both the surface and atmosphere. Because the atmospheric and surface analyses are currently not strongly coupled, a specific treatment of the surface is required. The observation operator expects in particular, a skin temperature value at the observation location and time, together with the profiles of the atmospheric variables along the viewing path. This skin temperature is added to the control variable and optimised simultaneously with all the atmospheric variables to produce optimal simulated radiances.

We present two approaches to add the skin temperature to the control variable. In the current TOVSCV approach, a series of skin temperature value per observation location is added to the control variable. Effectively, in the optimisation process, the skin temperature acts as a sink variable in observation space and is uncoupled from the skin temperature at other locations. In the novel SKTACV approach, two-dimensional skin temperature fields are added to the control variable. All clear-sky radiances then participate in the optimisation of these two-dimensional fields and the analysis produces temporally and spatially consistent skin temperature fields.

We compare the two approaches over two seasons of three months each. Overall, there is a neutral impact of the new approach on the analysis and forecast. Besides, there are some evidences that the contribution of the sub-surface layers should be represented in the new approach for the skin temperature associated with the microwave instruments.

Sebastien Massart et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-37', Anonymous Referee #1, 04 May 2021
    • AC1: 'Reply on RC1', Sebastien Massart, 13 May 2021
  • CEC1: 'Comment on gmd-2021-37', Astrid Kerkweg, 10 May 2021
    • AC2: 'Reply on CEC1', Sebastien Massart, 13 May 2021
  • RC2: 'Comment on gmd-2021-37', Anonymous Referee #2, 11 May 2021
    • AC3: 'Reply on RC2', Sebastien Massart, 13 May 2021

Sebastien Massart et al.

Sebastien Massart et al.


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Short summary
Numerical weather predictions combine data from satellites with atmospheric forecasts. Some satellites measure the radiance emitted by the Earth surface. To use them, one has to use the knowledge of the surface properties like the temperature of a thin layer on top of it. An error on this temperature leads to a misuse of the satellite data and affects the quality of the weather forecast. We developed a new approach to better estimate this temperature which should help improving the forecast.