Geostationary Earth Radiation Budget Project: Status and Results

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1 Geostationary Earth Radiation Budget Project: Status and Results J. A. Hanafin, J. E. Harries, J. E. Russell, J. M. Futyan, H. Brindley, S. Kellock, S. Dewitte1, P. M. Allan2 Space and Atmospheric Physics, Imperial College, London, SW7 2BZ, UK 1 Royal Meteorological Institute of Belgium, 3 Ave. Circulaire, B-1180 Brussels, Belgium 2 Space Science and Technology Dept, Rutherford Appleton Laboratory, Didcot, OX11 0QX, UK Abstract The Geostationary Earth Radiation Budget experiment (GERB) is an absolute radiometer measuring the reflected shortwave (SW) and emitted longwave (LW) radiation from the Earth, from the Meteosat-8 spacecraft. From these measurements, the radiative energy balance of the part of the Earth seen from this geosynchronous vantage point are derived every 15 minutes, with a sub-satellite spatial resolution of 48km. The paper will report on the operation of the instrument, the accuracy of the radiances and fluxes obtained, the status of the instrument calibration, and results of research into convective cloud radiative forcing, and aerosol-radiation interactions over Africa and the Atlantic. Introduction The Geostationary Earth Radiation Budget (GERB) sensor is an instrument of opportunity on the Meteosat-8 spacecraft. It is a broadband radiometer, measuring the reflected shortwave (SW) and emitted longwave (LW) radiation at the top of the atmosphere (TOA). The instrument and operations are described in detail in Harries et al. (2005) and a brief summary is given here. At the heart of the instrument is a 256-element detector array, aligned in the north-south direction, and a primary mirror rotating counter to the spacecraft spin direction. The detectors are sensitive to radiation from 0.32µm to ~100µm (TOTAL channel), and a quartz filter cuts out wavelengths above 4µm when measuring the SW channel. As the Earth comes into the field of view (FOV) of the sensor, the mirror directs a frozen beam of radiation to the detectors. A scan begins by observing the area of space adjacent to the earth and the location observed by the north-south detector array is moved by one pixel width in the east-west direction on subsequent rotations until space is viewed again on the other side of the Earth s disk. A complete scan consists of 256x282 pixels in the SW and TOTAL channels, with a nadir resolution of ~50km2. A combination of the space viewed and the internal blackbody observations are used to convert the instrument voltages to filtered TOTAL and SW radiances. The radiances are geolocated and rectified to a 256x256 pixel grid. These are then unfiltered to remove effects of the sensor spectral and spatial responses and the LW radiance field is produced by removing the SW signal from the TOTAL channel. To convert the radiances to fluxes, a scene identification process retrieves surface type and cloud properties from the SEVIRI narrowband channels. Angular dependency models derived from CERES-TRMM are used in the radiance to flux conversion process. The radiance and flux data products are then resolution-enhanced using the higherresolution SEVIRI data to a ~9km2 nadir resolution.

2 Figure 1. TOTAL and SW scans prior to level 1.5 processing. Each scan consists of approximately 280 lines of 256 detector observations. The GERB instrument on board Meteosat-8 has been providing almost continuous data since The validation of these data is ongoing and the current results from validation are presented below. The official release of data for science users will take place following a reprocessing of the data collected to date, and remaining data issues are indicated. Also presented are results from ongoing research at Imperial College into cloud and aerosol radiative forcing using GERB, GERB-like and SEVIRI data. Validation Results The primary means of validation of GERB radiances and fluxes is through intercomparison with the Cloud and Earth s Radiant Energy System (CERES) instruments on board the Terra and Aqua instruments. A special scanning mode is implemented for CERES data collection on a regular basis to maximise the number of coangular, co-located data points for this purpose. The results shown below use Edition 8 (Instantaneous ERBE-like TOA estimates) from CERES FM-2 on the Terra spacecraft. The CERES sensors have higher spatial resolution than GERB, to which some of the variance in the comparisons can be attributed. Figure 2. Comparison of GERB and CERES FM2 ES8 LW (left) and SW (right) radiances. The colours correspond to scene type: ocean (blue); cloud (purple); bright vegetation (green); and bright desert (red). The agreement between the sensors in the LW is excellent, with a CERES/GERB mean ratio of / at the 95% confidence limit. Compensating differences have

3 been identified, however, with warmer scenes having ratios >1 and colder scenes having ratios <1. These differences are due to different LW limits applied in the data processing and this disparity will be resolved during reprocessing. For SW radiances, the agreement is scene-dependent. The best results are over deserts, where the ratio is / As the scene being viewed becomes bluer, the ratio reduces, down to / for ocean observations. A revised spectral response to be used in reprocessing is expected to improve these discrepancies. A small detectorspecific dependence has also been identified, which may be due to inter-detector response CERES-GERB SW filtered radiance comparison differences. As each detector observes a very small latitude range due to the scanning procedure, this could also be due to differences in the mean scene viewed by each 1.04 detector. This issue is under investigation. CERES/GERB radiance ratio All Ocean Dark Veg Bright Veg Dark Desert Bright Desert Cloudy Figure 3. Separation of CERES/GERB SW radiance ratio according to scene type, showing agreement decreasing with blueness of scene. Radiance to flux conversion is the biggest source of error for radiation budget data. Due to GERB s fixed geometry, any viewing angle-dependent errors in the ADMs will result in systematic biases, so analysis of ADM performance and research into improvements is ongoing to minimise this. Theoretical ADMs based on SBDART calculations and scene identification from SEVIRI IR channels are used in processing of GERB LW fluxes. Comparisons with the CERES LW fluxes show a mean ratio of ± 0.002, with an indication of limb-darkening at the edge of the disk for the GERB fluxes and scene-dependent differences Validation studies of the GERB clear sky ocean fluxes seem to indicate diurnally varying errors in the application of the ADMs which result in a spurious diurnal signal in the fluxes (~ ±20Wm-2). Whether this is due to the CERES ADMs themselves, or to the way in which they are applied to the GERB data is under investigation. Data Release and Other Issues Large and time varying errors noted initially in the geolocation were due to inaccurate pointing information from Meteosat-8. The geolocation accuracy has been greatly improved by additional data made available by EUMETSAT to correct this information. Smaller systematic offsets (~1 pixel) can be corrected by tuning the instrument in-flight optical model used in processing. Planned improvements will allow

4 the 0.1 pixel geolocation accuracy specification to be met, however it is unlikely that this will be achieved for the edition 1 release. Periods around local midnight have been shown to be affected by stray solar illumination when the sun is close to the instrument FOV. Significant contamination of Earth radiances occurs for 6-8 weeks before and after equinoxes. A new gain calculation has been introduced to minimise time periods affected by using running averages. This also removes contamination on the occasions when the moon is present in the space views used for converting voltages to radiances. A study of the straylight problem will be carried out in the future, and data affected will be flagged for the first data released. Detector response has been very stable since launch, overall. Detector 192 has not performed to specification since launch and the response of detectors has been degraded since February 2005, due to a mechanical fault. Data affected from these detectors will also be flagged. Cloud Radiative Forcing Standard radiation budget monthly mean data products average over all cloud systems and weather regimes. This limits their application in regional scale studies of specific cloud regimes and in validation of numerical models. In order to study the effects of individual cloud types separately, previous methods include using daily averages of cloud and radiation data or radiative transfer modelling. Both cloud type and cloud radiative forcing (CRF) can vary strongly through the day, however, which can lead to incorrect attribution using diurnal mean quantities (fig. 4). Data which can resolve both day to day and diurnal variations is therefore required. The GERB-like data shown here was produced by applying a narrowband-broadband conversion to SEVIRI channels, but the results are similar when pre-release GERB data was analysed. The EUMETSAT CLA cloud analysis product was used to identify low, mid and high-level clouds in a 15 minute snapshot at 3 hour intervals. Figure 4. a) Occurrence of low, mid and high level clouds on 1st June 2004 from SEVIRI CLA product. b) Breakdown of cloud fraction, SW CRF and LW CRF separated into cloud type for that day, showing that the large SW CRF signal would be incorrectly attributed to the more prevalent high cloud if daily mean quantities were used. The problem being addressed is summarised in figure 4 (a) and (b). Over the African convective region on the day shown (01/06/2004), a typical diurnal variation in cloud type and fraction is observed in the CLA product (fig. 4 (a)). As high clouds dominate the cloud cover in terms of time, the SW CRF effect due to low clouds present on this day would be incorrectly attributed to high clouds using the method described by

5 Webb et al. (2001). In fact, the high clouds have a significant LW CRF, as they reduce LW TOA emission, but a smaller SW CRF than low cloud (fig. 4 (b)). Instantaneous CRF are attributed to a cloud type based on the CLA product. These are then averaged to produce a monthly time-step mean CRF corresponding to each cloud type which consists of 8 mean values at 3-hour intervals. These are then averaged to give the monthly mean CRF for each cloud type. The results are presented in figure 5, showing that all clouds can have a significant SW CRF effect. High clouds dominate in tropical convergence region and towards mid-latitudes, and low clouds dominate over sub-tropical oceans (Futyan et al., 2005). Figure 5. Monthly mean cloud fraction (top panels), LWCRF (middle panels) and SWCRF (bottom panels) for high (left), mid (middle) and low level (right) clouds for June The monthly mean was calculated using diurnally resolved time step mean values. Aerosol Radiative Forcing In order to study aerosol radiative forcing (ARF), the amount of aerosol must first be established. A retrieval based on the SEVIRI IR channels is being developed. The enhanced resolution GERB cloud flags are used to discriminate between clear and cloudy conditions. Aerosol optical depth (AOD) and size information are then retrieved in

6 nominally clear regions, initially only over ocean. LUTs of simulated SEVIRI visible and near IR channel reflectances are then generated as a function of solar and viewing geometry and AOD for available dust representations. These retrievals are being validated against ground-based observations and additional satellite measurements. A comparison with MODIS AOD retrievals is shown in figure 5, showing very good spatial consistency between the 2 products. Figure 6. MODIS AOD retrievals (at 0.644µm) at 1200 UTC (a) and 1500 UTC (d) on 4th March Corresponding retrievals from SEVIRI are shown in (b) and (e). The aerosol model used in the LUT generation is identical to that used in the 3rd generation AVHRR algorithm (after Ignatov and Stowe). 2-D histograms of MODIS versus SEVIRI optical depths for each time slot are shown in (c) and (f), with a oneto one line shown for comparison. AERONET observations of optical depth at 0.67 µm at the Dakar and Cape Verde sites through the day of March 5th 2004 are shown in figure 7. The averages of retrievals from SEVIRI based on the AVHRR 3rd generation aerosol model (purely scattering) as well as retrievals obtained using the same model with a small absorbing component included are shown for comparison. Because the algorithm is designed to work over ocean only, points within an area of ~ 60 km2 off the coast of Cape Verde and Dakar are included in the averages the error bars on the white crosses indicate the spatial variation in the retrievals. Other, dedicated dust models, including a non-spherical model, have been tested and the AVHRR-like model gives the best agreement with both MODIS and AERONET observations for the cases studied so far.

7 Figure 7. Comparison of AERONET with AOD retrieved from SEVIRI using the AVHRR 3rd generation aerosol model with (white crosses) and without (green crosses) a small absorption component. In figure 8, the time-series of GERB-like SW radiances and fluxes for the same locations and times as the AOD retrievals described above (blue triangles) is shown. Broadband radiances and fluxes were calculated as a function of AOD using SBDART to investigate the likely impact of applying a cloud rather than aerosol ADM. The white stars are the broadband radiances and fluxes retrieved from the LUTs based on the SEVIRI AOD retrievals. While the radiances agree reasonably well in terms of magnitude and temporal evolution, the fluxes show a marked discrepancy, indicating that an incorrect ADM can have a large effect on the values obtained. Green stars show the simulated clear-sky fluxes, based on the given viewing geometry and under the assumption that no aerosol is present, which highlight the fact that the calculated ARF will also be in error.

8 Conclusions Results from the GERB project have been reported. The validation of the data is ongoing, but results to date are encouraging. Intercomparison with CERES has highlighted some areas for improvement in both the LW and SW radiances and fluxes. Where possible, these will be addressed in a planned reprocessing of the entire dataset collected to date. Remaining known issues will be flagged in the first edition of the data released. Release of data for use by the wider science community is expected in the near future, following the reprocessing exercise. Results of cloud and aerosol radiative forcing studies have also been presented, demonstrating the potential for application of GERB data to these areas of study. More accurate attribution of cloud radiative forcing to particular cloud types will improve our understanding of cloud-radiation feedbacks. Studies of the effects of aerosol on TOA radiation will help to achieve convergence between models and observations and reduce uncertainty in the regional-scale effects of aerosol. References Futyan, J. M., J.E. Russell, J.E. Harries Determining cloud forcing by cloud type from geostationary satellite data, Geophys.Res. Lett., 32, L08807, doi: /2004gl Harries J. E., J.E. Russell, J.A. Hanafin, et al The Geostationary Earth Radiation Budget Project, Bull. American Meteor. Soc. 86 (7) pp Webb, M., C. Senior, S. Bony, and J. J. Morcrette Combining ERBE and ISCCP data to assess cloud in the Hadley Centre, ECWMF and LMD atmospheric climate models, Clim. Dyn., 17, pp