The first Geostationary Earth Radiation Budget (GERB) instrument was launched during the 2002 summer
together with the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board of the Meteosat-8 satellite.
This broadband radiometer aims to deliver near real-time estimates of the top of the atmosphere solar and thermal
radiative fluxes at high temporal resolution thanks to the geostationary orbit. Such goal is achieved with the
L20 GERB processing which generates these fluxes at several spatial resolutions from the directional filtered
radiance measurements of the instrument. This processing consists of successive components, one of them being
a radiance-to-flux conversion. Such conversion is carried out in the solar region by using the shortwave angular
dependency models (ADMs) developed from the Tropical Rainfall Measuring Mission (TRMM) Clouds and the
Earth's Radiant Energy System (CERES) experiment. As these ADMs are stratisfed according to specific scene
properties, the GERB ground segment will have to rely on a scene identification of SEVIRI data which allows
us to select the proper ADM.
In this paper, we will briefly justify and describe the implementation of a specific GERB scene identification
for the offcial Edition 1 release of the L2 products. Preliminary comparisons between GERB and CERES scene
identifications both applied to SEVIRI data will follow. Finally, we will suggest possible improvements based on
limitations which could be found.
The synergy between the Geostationary Earth Radiation Budget (GERB) broadband radiometer and the Spinning
Enhanced Visible and Infra Red Imager (SEVIRI) on board the European meteorological satellite Meteosat-8
is exploited to estimate the diurnal variation of the direct short wave aerosols radiative forcing (DSWARF) from
biomass burning over Africa at sub-GERB footprint scale. Biomass burning are first identified at the SEVIRI
resolution (3 km at nadir) by applying a multispectral thresholding algorithm to the SEVIRI spectral measurements.
Reflected SW fluxes at the top-of-atmosphere for smoke aerosols are obtained by converting the measured
GERB radiances at the 3×3 SEVIRI pixel window in term of flux using a theoretically derived smoke angular
distribution model (ADM) based on the average scene identification (SI) from the 3×3 SEVIRI pixel box. The
calculated smoke ADM is a function of aerosol optical depth, surface type and solar and viewing geometry. The
TOA DSWARF for smoke aerosols is then estimated as the difference between radiative fluxes in the absence
and presence of biomass burning aerosols.
On 29th January 2004 the first Meteosat Second Generation satellite MSG-1, renamed Meteosat-8 (MS-8), commenced routine operations. MS-8 carries the new Spinning Enhanced Visible and Infra Red Imager (SEVIRI) and a Geostationary Earth Radiation Budget (GERB) radiometer. GERB provides valuable short- and long wave broadband measurements of the Earth in order to estimate the top-of-atmosphere radiation budget accurately. The unique feature of GERB in comparison with previous measurements of the Earth's radiation budget is its very fast temporal sampling (15 minutes) afforded by geostationary orbit. On the other hand, the GERB instrument only accounts for a crude spatial resolution (about 50 km at the sub-satellite point).
Taking advantage of the synergy between the data from GERB and SEVIRI, we propose at the Royal Meteorological Institute of Belgium to merge the two data streams to produce near real-time estimates of the radiation budget for limited geographical regions at a 3x3 SEVIRI pixel resolution (the SEVIRI resolution is 3 km at satellite sub-point).
Such fluxes aim to be used by the climate and numerical weather prediction (NWP) scientific communities through climate studies and validation/evaluation of the performance of NWP models over the region covered by MS-8.
The first Meteosat Second Generation (MSG) satellite was launched in August 2002. This EUMETSAT satellite carries 2 new instruments on the geostationary orbit: the Spinning Enhanced Visible and InfraRed Imager, SEVIRI, and the Geostationary Earth Radiation Budget, GERB. The unique feature of GERB in comparison with previous measurement missions of the Earth's radiation budget (e.g. ERBE, ScaRab and CERES experiments) is the high temporal sampling afforded by the geostationary orbit, albeit for a limited region of the globe. The GERB instrument provides accurate broadband measurements of the radiant energy originating in the reflection of the incoming solar energy by the Earth-atmosphere system and in the thermal emission within this system. The synergetic use of the SEVIRI data is needed to convert these directional measurements (radiances) into radiative fluxes at the top-of-atmosphere. Additionally, the SEVIRI data allows the enhancement of the spatial resolution of the GERB measurement. This paper describes the near real-time GERB processing system that has been set up at the Royal Meteorological Institute of Belgium (RMIB). This includes the unfiltering of the instrument data, the radiance-to-flux conversions and the enhancement of the instrument spatial resolution. An early validation of the instrument data by comparison with CERES data is presented. Finally, the different data formats, the way to access them and their expected accuracy are presented.
The Geostationary Earth Radiation Budget (GERB) instrument has been launched this summer together with the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on board of the Meteosat Second Generation (MSG) satellite. This broadband radiometer will aim to deliver near real-time estimates of the top of the atmosphere (TOA) radiative fluxes at the high temporal resolution due to the geostationary orbit. In order to infer these fluxes, a radiance-to-flux conversion based on Clouds and the Earth's Radiant Energy System (CERES) angular dependency models (ADMs) need to be performed on measured radiances. Due to the stratification of these ADMs according to some CERES scene identification (SI) features such as cloud optical depth and cloud fraction, the GERB ground segment must include some SI on SEVIRI data which mimic as close as possible the one from CERES in order to select the proper ADM. In this paper, we briefly present the method we used to retrieve cloud optical depth and cloud fraction on footprints made of several imager pixels. We then compare the retrieval of both features on the same targets using nearly time-simultaneous Meteosat-7 imager and CERES Single Satellite Footprint (SSF) data. The targets are defined as CERES radiometer footprints. We investigate the possible discrepancies between the two datasets according to surface type and, if they exist, suggest some strategies to homogenize GERB retrievals based on CERES ones.
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