Presentation is loading. Please wait.

Presentation is loading. Please wait.

Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –led by Tony Slingo, ESSC, Reading University, UK Links the ARM.

Published bySamantha Gray Modified over 9 years ago

Similar presentations

Presentation on theme: "Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –led by Tony Slingo, ESSC, Reading University, UK Links the ARM."— Presentation transcript:

1 Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –led by Tony Slingo, ESSC, Reading University, UK Links the ARM Mobile Facility with GERB (Geostationary Earth Radiation Budget instrument on Meteosat) & AMMA The objective is to derive the divergence of radiation across the atmosphere: –by combining the AMF measurements of the surface radiative fluxes and vertical structure of the atmosphere with GERB data from the top of the atmosphere and AMMA observations –study the radiative properties of aerosols (desert dust, biomass), water vapour and clouds –provide comprehensive observations for testing radiation codes The RADAGAST project

2 Red: Aerosol Optical Thickness at 675nm from the AERONET site at Banizoumbou Black: Angstrom exponent Downward Solar flux (daily averages Wm -2 ) Purple: Total Green: Diffuse Grey bands: clouds Downward solar fluxes are controlled by clouds and by aerosol Dust storm

3 Downward Thermal flux Wm -2 Black: Daily average Red: variability Grey bands: clouds Column water vapour (cm) Green: Radiometer Red: Sonde Downward thermal fluxes are controlled by clouds, column water vapor, atmospheric temperatures and aerosol (see later) Dust storm

4 GERB reflected solar Wm -2 ARG: Standard product (50km resolution) HR: High Resolution hybrid product using SEVIRI imager data (10km resolution) Downward Solar flux (daily averages Wm -2 ) Purple: Total Green: Diffuse Grey bands: clouds GERB and AMF fluxes will be combined to calculate atmospheric divergence

5 Downward Thermal flux Wm -2 Black: Daily average Red: variability Grey bands: clouds GERB OLR Wm -2 ARG: Standard product (50km resolution) HR: High Resolution hybrid product using SEVIRI imager data (10km resolution) GERB and AMF fluxes will be combined to calculate atmospheric divergence

6

7 Comparisons with the Edwards/Slingo radiation code One of the main RADAGAST objectives is to provide comprehensive observations for testing radiation codes We have compared longwave simulations by the Edwards and Slingo (1996) radiation code with observed fluxes from the AMF broad-band radiometers and (in radiance mode) with AERI radiances, for cloud-free conditions Unlike the NWP comparisons shown earlier, these are stand-alone tests, running the code with input from the observed thermodynamic profiles This has produced some very interesting differences The work has benefitted from collaboration with Eli Mlawer (AER), who carried out parallel calculations with LBLRTM

8 Comparisons with Edwards/Slingo radiation code The large reduction in column water vapour in October controls the downward longwave fluxes, as shown earlier, but not the differences. Could aerosol be causing the flux differences during the dry season? Downward thermal flux (Wm -2 ) Observed minus modelled (Wm -2 ) Red: observed Blue: modelled

9 Every peak in the Banizoumbou AOT time-series after September has a corresponding peak in the downward thermal flux difference. However, that doesn’t necessarily mean that the cause of the differences is aerosol; it could still be thin and/or high cloud that becomes relatively more important because of the dry atmosphere (and which also fools the aerosol retrieval).

10

11

12

13 MPL corrected backscatter MPL calculated extinction profile January 21

14 Calculated daily average SW and LW radiative effects at surface due to aerosol only (Jan-Apr 2006) Daily average effect of aerosol on surface fluxes during dry season is -36.5 Wm -2 on SW and +26.8 Wm -2 on LW Shortwave (Wm -2 )Longwave (Wm -2 )

15 Summary and future work Over a year of data from the AMF, GERB and SEVIRI –several articles and press releases: http://www.arm.govhttp://www.arm.gov –major dust storm in March 2006 (Slingo et al., Geophysical Research Letters, 30 December 2006) –overview paper by Miller and Slingo in Bulletin of the American Meteorological Society (scheduled for August 2007) Aerosol has a large influence on solar fluxes (expected) and appears to have a significant influence on thermal fluxes (unexpected) Ongoing work includes: –analysis of AMF and GERB fluxes throughout 2006, for clear and cloudy conditions, and comparisons with radiation and NWP models –developing the methodology to derive area-average surface fluxes, including exploiting the data from the second site at Banizoumbou –combining AMF and GERB data to derive atmospheric divergence –Radagast website; http://radagast.nerc-essc.ac.ukhttp://radagast.nerc-essc.ac.uk

Download ppt "Radiative Atmospheric Divergence using ARM Mobile Facility, GERB data and AMMA stations –led by Tony Slingo, ESSC, Reading University, UK Links the ARM."

Similar presentations

© University of Reading 2010 1 Richard Allan Department of Meteorology, University of Reading Thanks to: Jim Haywood and Malcolm.

© University of Reading Richard Allan Department of Meteorology, University of Reading Thanks to: Jim Haywood and Malcolm.
Figure 1: Using GERB and SEVIRI data to evaluate the Met Office NWP model in near-real time; example SINERGEE comparisons for 8 th March 2006 at 1200 UTC.

Figure 1: Using GERB and SEVIRI data to evaluate the Met Office NWP model in near-real time; example SINERGEE comparisons for 8 th March 2006 at 1200 UTC.
IRS2004, Busan, August 2004 Using Satellite Observations and Reanalyses to Evaluate Climate and Weather Models Richard Allan Environmental Systems Science.

IRS2004, Busan, August 2004 Using Satellite Observations and Reanalyses to Evaluate Climate and Weather Models Richard Allan Environmental Systems Science.
Robin Hogan, Richard Allan, Nicky Chalmers, Thorwald Stein, Julien Delanoë University of Reading How accurate are the radiative properties of ice clouds.

Robin Hogan, Richard Allan, Nicky Chalmers, Thorwald Stein, Julien Delanoë University of Reading How accurate are the radiative properties of ice clouds.
3) Empirical estimate of surface longwave radiation Use an empirical estimate of the clear-sky surface downward longwave radiation (SDLc) to estimate the.

3) Empirical estimate of surface longwave radiation Use an empirical estimate of the clear-sky surface downward longwave radiation (SDLc) to estimate the.
Evaluating the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data Richard Allan, Tony Slingo Environmental Systems.

Evaluating the Met Office global forecast model using Geostationary Earth Radiation Budget (GERB) data Richard Allan, Tony Slingo Environmental Systems.
Evaluating the Met Office global forecast model using GERB data Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading.

Evaluating the Met Office global forecast model using GERB data Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading.
EUMETSAT 2006 Helsinki Exploitation of GERB/SEVIRI data for evaluation of the Met Office global forecast model Richard Allan, Tony Slingo Environmental.

EUMETSAT 2006 Helsinki Exploitation of GERB/SEVIRI data for evaluation of the Met Office global forecast model Richard Allan, Tony Slingo Environmental.
Comparisons between GERB and the Met Office NWP model Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Sean Milton,

Comparisons between GERB and the Met Office NWP model Richard Allan, Tony Slingo Environmental Systems Science Centre, University of Reading Sean Milton,
SYSTEMATIC BIASES 3-hourly comparisons of top of atmosphere radiation from GERB and the Met Office global forecast model Systematic biases in model fluxes.

SYSTEMATIC BIASES 3-hourly comparisons of top of atmosphere radiation from GERB and the Met Office global forecast model Systematic biases in model fluxes.
GERB/CERES Meeting 2006 Exeter Evaluation of clouds and radiation in the Met Office global forecast model using GERB/SEVIRI data Richard Allan, Tony Slingo.

GERB/CERES Meeting 2006 Exeter Evaluation of clouds and radiation in the Met Office global forecast model using GERB/SEVIRI data Richard Allan, Tony Slingo.
Jean-Louis Roujean CNRM / Météo-France

Jean-Louis Roujean CNRM / Météo-France
Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.

Using a Radiative Transfer Model in Conjunction with UV-MFRSR Irradiance Data for Studying Aerosols in El Paso-Juarez Airshed by Richard Medina Calderón.
A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.

A thermodynamic model for estimating sea and lake ice thickness with optical satellite data Student presentation for GGS656 Sanmei Li April 17, 2012.
GIST 24/10/06 Jeff Settle, ESSC Reconciling Point and Area Data for RADAGAST GIST 24 October 2006.

GIST 24/10/06 Jeff Settle, ESSC Reconciling Point and Area Data for RADAGAST GIST 24 October 2006.
Climate change in 19-22 centuries in observational and model data Evgeny Volodin, Institute of Numerical Mathematics RAS, Moscow, Russia.

Climate change in centuries in observational and model data Evgeny Volodin, Institute of Numerical Mathematics RAS, Moscow, Russia.
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.

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.
Initial testing of longwave parameterizations for broken water cloud fields - accounting for transmission Ezra E. Takara and Robert G. Ellingson Department.

Initial testing of longwave parameterizations for broken water cloud fields - accounting for transmission Ezra E. Takara and Robert G. Ellingson Department.
Combining satellite and surface observations to determine the radiative divergence across the atmosphere Tony Slingo Environmental Systems Science Centre.

Combining satellite and surface observations to determine the radiative divergence across the atmosphere Tony Slingo Environmental Systems Science Centre.
Radiative forcing - measured at Earth‘s surface - corroborate the increasing greenhouse effect R.Philpona 1, B.Dürr 1, C.May 1, A.Ohmura 2 and M.Wild 2.

Radiative forcing - measured at Earth‘s surface - corroborate the increasing greenhouse effect R.Philpona 1, B.Dürr 1, C.May 1, A.Ohmura 2 and M.Wild 2.

Similar presentations

Ads by Google