Data Record for period 2004-2015
Downward Surface Longwave Flux (DSLF) is the result of atmospheric absorption, emission and scattering within the entire atmospheric column and may be defined as the thermal irradiance reaching the surface in the thermal infrared spectrum (4-100 µm). In clear sky situations DSLF depends on the vertical profiles of temperature and gaseous absorbers (primarily the water-vapour followed by CO2, and others of smaller importance like O3, CH4, N2O and CFCs). However, DSLF is determined by the radiation that originates from a shallow layer close to the surface (about one third being emitted by the lowest 10 meters and 80% by the 500-meter layer). The cloud contribution mainly occurs in the atmospheric window (8-13 µm) and mainly depends on cloud base properties (height, temperature and emissivity). DSLF is directly related to the greenhouse effect and its monitoring has an important role in climate change studies. Other applications include meteorology (land applications) and Hydrology.
The characteristics and file format of this demonstration Data Record are the same as its correspondent NRT product. It is documented in the following documents:
Please see Product Peer-Review publications in References.
The use of LSA SAF products in publications is kindly requested to be duly acknowledged:
DSLF and DIDSLF were provided by the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF; Trigo et al., 2011)
Trigo, I. F., C. C. DaCamara, P. Viterbo, J.-L. Roujean, F. Olesen, C. Barroso, F. Camacho-de Coca, D. Carrer, S. C. Freitas, J. García-Haro, B. Geiger, F. Gellens-Meulenberghs, N. Ghilain, J. Meliá, L. Pessanha, N. Siljamo, and A. Arboleda, 2011: The Satellite Application Facility on Land Surface Analysis. Int. J. Remote Sens., 32, 2725-2744, doi: 10.1080/01431161003743199
DSLF is a particularly difficult parameter to retrieve since satellites cannot directly measure it. However the hybrid methods that make a combined use of satellite and NWP data are particularly suitable for operational purposes. Different bulk parameterizations are currently applied for clear/cloudy sky conditions. The identification of cloudy pixels is based on the cloud mask generated by using the software provided by the Nowcasting and Very Short Range Forecasting Satellite Application Facility (NWC SAF).
The adopted algorithm to compute DSLF consists of an hybrid method based on two different bulk parameterisation schemes (e.g., Prata, 1996; Josey et al, 2003) using as input ECMWF forecasts of 2m temperature, 2m dew point temperature and total column water vapour as well as the two cloud products from NWC SAF (Cloud Mask and Effective Cloudiness).
The DSLF product is computed within the area covered by the MSG disk, over 4 specific geographical regions (Europe, Africa - Northern Africa and Southern Africa - and South America), every 30 minutes. For each time-slot and geographical region, the DSLF field and respective Quality Control (QC) data are disseminated in HDF5 format; the relevant information concerning the data fields is included in the HDF5 attributes.
The quality of the DLSF product depends on the accuracy of both cloudy pixel detection and atmospheric column characterisation (temperature and humidity). Accordingly the definition of the DSLF confidence levels is based on the following parameters: atmospheric characteristics (i.e. surface temperature and column water vapour) for clear sky conditions and total cloud fraction for cloudy sky conditions. Three confidence levels are defined (respectively above nominal, nominal and below nominal) that correspond to uncertainties estimated on DSLF values (respectively less than 5%, between 5 and 10% and above 10%).
Josey, S.A., Pascal, R.W., Taylor, P.K., Yelland, M.J., (2003), A New Formula For Determining the Atmospheric Longwave Flux at Ocean Surface at Mid-High Latitudes. Journal of Geophysical Research - Oceans, doi:10.1029/2002JC00141.
Prata, A.J. (1996): A new long-wave formula for estimating downward clear-sky radiation at the surface, Q. J. R. Meteorol. Soc., 122, 1121-1151