GEOS-5 Simulations of Aerosol Index and

Aerosol Absorption Optical Depth with Comparison to OMI retrievals.

V. Buchard, A. da Silva, P. Colarco, R. Spurr

GMAO meeting – 03/31/2011

GEOS-5 Aerosols and VLIDORT interface (1)

• Aerosol transport module GOCART implemented in the GEOS-5 climate model.

– Driven by assimilated meteorological fields, radiative feedbacks– Simulates 5 aerosol types :

(dust, sea salt, black and organic carbon and sulfate)– Horizontal resolution : 0.5°x 0.65°– 72 vertical levels from surface to 85 km

Aerosol Mass Concentration :• for each grid cell• for each layer

Assimilation of MODIS/ MISR aerosol data

1) AEROSOL MODEL :

Mie calculations

Aerosol Mass Concentration

AOD

Updates

GEOS-5 Aerosols and VLIDORT interface (2)2) Vertical profiles of optical properties at OMI lat/long:

AOD, SSA, g, P(θ)• at OMI lat/long and λ• for each layer

Mie calculations

354 nm388 nm471 nm

Vertical profiles of AOD, SSA and g at OMI λ

Aerosol Mass Concentration :• for each layer• geolocation at OMI lat/long

OMI (Ozone Monitoring Instrument)/ AURA

VLIDORT Radiative transfer code :– Discrete Ordinate Method– Scalar or Vector mode– Several options for surface specification (Lambertian surface used here)

AOD, SSA, g, P(θ)• at OMI lat/long and λ• for each layer

Input parameters from OMI file :- Geometry angles :

• Solar Zenith Angle• Relative Azimuth Angle• Sensor Zenith Angle

- Surface albedo at 3 λ

Model Pressure & Temperature

3) Radiative transfer calculation :

• TOA radiances• Aerosol Index

GEOS-5 Aerosols and VLIDORT interface (3)

Aerosol Index

• Qualitative indicator of the presence of absorbing aerosol ( AI > 0 ).

• AI is derived from the change in the spectral dependence of the back-scattered UV radiances induced by aerosols relative to the Rayleigh scattering between 354 and 388 nm (Torres et al., 2007) :

• AI depends on : - aerosol concentration - aerosol layer height - aerosol optical properties

⇒ Globally, good agreement but :

A 388 nm

Comparison of monthly mean TOA Radiances (1)

Overestimation of the modeled radiances over land,

Underestimation of the modeled radiances over ocean in the southern hemisphere.

388 nm 388 nm 388 nm

GEOS-5 Free running model OMI Difference OMI – GEOS-5

GEOS-5 with assimilation of MODIS/MISR AOD

388 nm

Comparison of the monthly mean TOA Radiances (2)

A 354 & 471 nm

⇒ Same conclusions as 388nm

354 nm 354 nm 354 nm

471 nm 471 nm471 nm

GEOS-5 Free running model

GEOS-5 Free running model

OMI

OMI

Difference OMI – GEOS-5

Difference OMI – GEOS-5

UV Aerosol Index (AI) Comparison

⇒ GEOS-5 simulated AI captures major features, but is not perfect… too much dust in Northwest Africa, not enough dust in Arabia Peninsula, not enough biomass burning (Southwest Africa).

=> Assimilation of AOD from MODIS/MISR have small impact on AI.

GEOS-5 Free running model OMI Difference OMI – GEOS-5

GEOS-5 with assimilation of MODIS/MISR AOD Difference OMI – GEOS-5

Absorption AOD Comparison

OMI and modeled - AAOD capture both :• African dust • Biomass plumes in

Southwest Africa• Dust in Arabia Peninsula

A 388 nm

AI – AAOD :• Biomass plume too low• In Africa : dust plume or

concentration too high in the model ?

• In Arabia Peninsula : the model places the dust plumes too low ?

OMI - AAOD

OMI - AI

GEOS-5 - AAOD

GEOS-5 - AI

Model has some absorption in China, not observed by OMI

GEOS-5 Dust Vertical Distribution

Aerosol layer altitude : Use of CALIPSO dataIn Africa

Modeled dust plume height seems to be well placed

Modeled Mass Mixing ratio for Dust

Aerosol layer altitude : Use of CALIPSO dataIn Arabia Peninsula

Modeled Mass Mixing ratio for Dust

Large amount of aerosol close to the surface

Conclusions :• VLIDORT simulated Radiances and AI agree well with OMI. • Altitude of the aerosol layer can explain differences in AI (ex : Arabia

Peninsula). Plume height in the model or Planetary Boundary Layer Process ?.

• MODIS/MISR AOD assimilation have marginal impact on the comparison between AI products (MISR/MODIS do not contain absorption information).

Future work :• Recompute the AI with the new model (New Biomass emissions, optical

tables)

• Include clouds in the radiative transfer calculation and assessing their impact on AI .

• Inclusion of water leaving radiances using MODIS assimilated chlorophyll dataset (from Watson Gregg).

Conclusions – Future work