The Impact of Satellite‐Derived Land Surface Temperatures on Numerical Weather Prediction Analyses and Forecasts

• Published in: Journal of geophysical research. Atmospheres 2017-09, Vol.122 (18), p.9783-9802
• Main Authors: Candy, B., Saunders, R. W., Ghent, D., Bulgin, C. E.
• Format: Article
• Language: English
• Subjects: Air temperature; data assimilation; Earth; Earth surface; Geophysics; Instruments; Kalman filters; land surface analysis; Land surface temperature; Land use; Moisture content; Night; Night-time; Nighttime; Prediction models; Radiometers; Remote sensing; Satellite instruments; Satellite observation; Satellite-borne instruments; Satellites; Soil; Soil analysis; Soil conditions; Soil improvement; Soil moisture; Soil temperature; Soils; Stations; Surface analysis (chemical); Surface temperature; Surface-air temperature relationships; Temperature; Temperature effects; Weather; Weather forecasting; Weather stations
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1002/2016JD026417

Land surface temperature (LST) observations from a variety of satellite instruments operating in the infrared have been compared to estimates of surface temperature from the Met Office operational numerical weather prediction (NWP) model. The comparisons show that during the day the NWP model can underpredict the surface temperature by up to 10 K in certain regions such as the Sahel and southern Africa. By contrast at night the differences are generally smaller. Matchups have also been performed between satellite LSTs and observations from an in situ radiometer located in Southern England within a region of mixed land use. These matchups demonstrate good agreement at night and suggest that the satellite uncertainties in LST are less than 2 K. The Met Office surface analysis scheme has been adapted to utilize nighttime LST observations. Experiments using these analyses in an NWP model have shown a benefit to the resulting forecasts of near‐surface air temperature, particularly over Africa. Key Points Satellite measurements of land surface temperature from the GlobTemperature project are compared to estimates from the Met Office numerical weather prediction model and to an in situ radiometer from a site in the UK A Kalman filter for land surface analysis has been adapted to ingest these satellite land surface temperature observations, initially for those made during nighttime Satellite nighttime observations of land surface temperature are found to improve near‐surface air temperature forecasts, particularly over Africa Plain Language Summary An accurate analysis of the state of the land surface, particularly the temperature and moisture content of the soil has been shown to improve forecasts from weather models. The temperature within the soil can be analysed using conventional observations from meteorological stations. However, the stations are not distributed uniformly across the earth's surface. In this work we investigate what happens if we use remote sensing measurements of surface temperature to estimate the soil conditions. The resulting soil conditions are then used to initialize a weather forecast model and we find that the air temperature forecasts are improved, especially over Africa.