1. Combining satellite and surface observations to determine the radiative divergence across the atmosphere Tony Slingo Environmental Systems Science Centre University of Reading Background GERB on Meteosat-8 and the SINERGEE project The ARM Mobile Facility detachment to Niamey Combining the GERB, ARM and AMMA data AMMA-UK, CEH Wallingford, 20-21 January 2005

3. One motivation for our work is the large uncertainty in some of these radiative fluxes For example, in this diagram, the absorption of solar radiation in the atmosphere is 67 Wm -2, or 20% of the incoming flux from the sun Most of this absorption comes from water vapour and ozone, with a small contribution from clouds But some estimates are as high as 92 Wm -2 and require a significant contribution from aerosols (wind-blown dust, combustion products) and cloud absorption which is several times that predicted by current models We therefore need better observations of all of these fluxes, to improve our understanding of radiative processes and to develop better models

4. Meteosat Second Generation the latest operational European weather satellite, the first of which was launched in August 2002 as Meteosat 8

5. Internal black- body Front End Electronics Scan Mirror Telescope Calibration Monitor Quartz Filter Earth View Fold mirror and detector The GERB instrument GERB is the first such instrument to be flown in geostationary orbit and provides unprecedented temporal resolution, with images every 15 minutes Measures the two components of the Earth’s radiation balance; the broad-band reflected solar and emitted thermal radiative fluxes, with an absolute accuracy of 1%

6. Overview of SINERGEE project We obtain GERB data in “near-real time” –usually, well within 24 hours of data acquisition We obtain simulations for the same time performed by the Met Office, from 6-hourly NWP model analyses –0000, 0600, 1200 and 1800 UTC Results displayed on the SINERGEE web page; –www.nerc-essc.ac.uk/~rpa/GERB/gerb.html Objectives –evaluation of NWP model, validation of GERB and various other science applications

7. Recent comparison 15 November 2004 1200 UT OLRALBEDOOLRALBEDO GERBNWP model Model cloud errors can easily be distinguished. Near-real time comparisons are valuable for a wide range of other studies (e.g. outbreaks of Saharan dust)

8. Cloud screened data Work led by Jim Haywood shows that the large differences between GERB and the model over the western Sahara are most likely due to desert dust aerosols Data from 12Z, July 2003

9. Combining the GERB data with surface sites to obtain the atmospheric radiative divergence GERB provides the first measurements of the top of atmosphere radiation balance with the excellent temporal sampling required to make progress in estimating the radiative divergence across the atmosphere SINERGEE provides a framework for comparing GERB data with models We need complementary data at the surface The most comprehensive surface radiation data come from the Atmospheric Radiation Measurement program (ARM) Peter Henderson (PhD student) has been comparing surface radiative fluxes from the Met Office NWP model with data from ARM

10. Comparisons with data from ARM: Atmospheric Radiation Measurement program.

11. A small sample of the wide range of active and passive instruments available at the ARM sites 94GHz cloud profiling radar Fourier transform spectrometer Raman Lidar (water vapour) Radio acoustic sounding system

12. SGP April 2003 Darwin May 2003

13. Unfortunately, there are no ARM sites visible from GERB

14. However, there is an exciting new development; The ARM Mobile Facility (AMF)

15. Combining ARM, SINERGEE & AMMA RADAGAST –Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –A proposal led by Tony Slingo to deploy the new ARM Mobile Facility in Niamey, Niger to coordinate with AMMA 2006 and link to GERB –Approved in October by the ARM project –This is a substantial commitment and a valuable resource for AMMA –Sampling in space and time is still a major issue need additional satellite data, plus data from AMMA