Articles | Volume 17, issue 24
Research article
21 Dec 2017
Research article |  | 21 Dec 2017

Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour

Anna Mackie, Paul I. Palmer, and Helen Brindley

Abstract. We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of −12 and 18 W m−2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m−2 for the longwave downwelling (upwelling) radiation flux and −21(−13) W m−2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation–model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model–observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.

Short summary
We compare the balance of solar and thermal radiation at the surface and the top of the atmosphere from a forecasting model to observations at a site in Niamey, Niger, in the Sahel. To interpret the energy budgets we examine other factors, such as cloud properties, water vapour and aerosols, which we use to understand the differences between the observation and model. We find that some differences are linked to lack of ice in clouds, underestimated aerosol loading and surface temperatures.
Final-revised paper