AeroCom Prescribed

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Contents

Proposed "AeroCom Prescribed" Model/Satellite Intercomparison

Introduction

Aerosol radiative forcing estimates of global aerosol models and satellite retrievals show considerable diversity that can partly be attributed to differences in the aerosol radiative properties but partly also to processes and assumptions in the host models (e.g. surface albedos, clouds). The contribution of these host model processes to the total forcing uncertainty is entirely unclear. We propose a simple AeroCom model/satellite intercomparison study with prescribed aerosol fields that will facilitate their quantification.

Motivation

Even for the case of identical aerosol emissions, the simulated direct aerosol radiative forcings show significant diversity among the AeroCom models (Schulz et al., 2006). Our analysis of the absorption in the AeroCom models (Presentation at the 2006 AeroCom meeting , Poster at the AGU Fall Meeting 2006) indicates a larger diversity in the translation from given aerosol radiative properties (absorption optical depth) to actual atmospheric absorption than in the translation of a given atmospheric burden of black carbon to the radiative properties (absorption optical depth). The large diversity is caused by differences in the simulated cloud fields, radiative transfer, the relative vertical distribution of aerosols and clouds, and the effective surface albedo. This indicates that differences in the host model (GCM or CTM hosting the aerosol model) parameterizations contribute significantly to the simulated diversity of atmospheric absorption and consequently of the TOA forcing.

However, similar issues equally apply to models used to retrieve the total and anthropogenic aerosol radiative effects from satellite data. Recent retrieved forcing estimates, all based on the MODIS satellite data, show considerable diversity in the resulting aerosol radiative forcings. These diversities indicate that differences in host model (GCM or CTM hosting the aerosol modules or model to retrieve the aerosol effects from satellite data) parameterisations contribute significantly to the diversity of the simulated and retrieved aerosol radiative forcing. The magnitude of these effects cannot be estimated from the diagnostics of the first AeroCom forcing experiment.

To quantify the contribution of differences in host models (global aerosol models and satellite retrievals) to the estimated aerosol radiative forcing and absorption we propose a simple AeroCom experiment with prescribed aerosol fields. The simulated forcing variability among the models and satellite retrievals is then a direct measure of the host model contribution to the uncertainty in the assessment of the aerosol radiative effects.

Experimental Setup

To quantify the contribution of differences in the host model processes to the simulated aerosol radiative forcing and absorption estimates from global aerosol models and satellite retrievals, the AeroCom Prescribed experiment is performed with prescribed identical aerosol radiative properties. Global 3D aerosol distributions are provided to the participants as monthly-mean fields of aerosol extinction, single scattering albedo, and asymmetry factor, derived from the AeroCom median model. These aerosol radiative properties are made available on 24 SW bands that can be mapped to the bands of the individual host model radiation schemes. Quality checks, such as diagnostic output of the 3D aerosol fields as implemented in each model, ensure the comparability of the aerosol implementation in the participating models. Specifically:

  • Global 3D aerosol distributions are provided as monthly-mean field of aerosol extinction, single scattering albedo, and asymmetry factor derived from the AeroCom median model.
  • These aerosol radiative properties are provided on 24 SW bands that can be mapped to the bands of the individual host model radiation schemes.
  • The 3D fields of radiative properties are to be interpolated to the respective model/retrieval resolution. An interpolation tool will be provided (cdo tools).
  • Quality checks, such as diagnostic output of the 3D aerosol fields as implemented in each model, ensure the comparability of the aerosol implementation in the models.

Based on this identical aerosol input data, participating models and satellite retrievals calculate the aerosol radiative forcing that is submitted to the AeroCom database and analysed.

Diagnostics

(To be completed)

Aerosols

  • 3D aerosol radiative properties as implemented in the model (quality check)
  • Separate diagnostics for in-cloud and clear-sky radiative properties as applied also in the forcing experiment. If aerosol are neglected in clouds, submit fields as zero.
  •  ?

Clouds

  • 3D fractional cloud cover
  • 3D cloud optical depth
  •  ?

Radiation

  • Forcing protocol as in the AeroCom Forcing experiment - or better:
  • Upwelling and downwelling clear-sky and all-sky radiative fluxes at the top-of-atmosphere and surface for pre-industrial and present day periods
  • Explicit cloudy-sky and clear-sky aerosol radiative properties as applied in the model
  • Single column calculations for 1D aerosol profile, solar zenith angle, and surface albedo at few selected locations? (Benchmarking with reference radiation codes.)
  •  ?

General model parameters

  • Prescribed surface albedo
  • Effective surface albedo as applied in the model (including effects of snow cover, moisture, etc.)
  • Information on radiation scheme (bands, key assumptions)
  •  ?

Timeframe

The implementation of the experimental setup is simple and the results could guide future AeroCom experiments. Thus, we could propose a short timeframe of less than 6 months:

Date Task
- 10/2008 Interactive discussion and finalization of the diagnostic protocol
10/2008 - 11/2008 Beta-testing in ECHAM and HadGEM models
12/2009 - 04/2009 Implementation stage and submission of results
05/2009 - 11/2009 Publication stage
10/2009 Discussion at AeroCom workshop in Princeton

Intended Participation

  • University of Oxford / Max Planck Institute for Meteorology / Caltech:
    Model: ECHAM5-HAM
    PhilipStier
  • National Center for Atmospheric Research:
    Model: CCSM3
    William Collins
  • University of Oslo, Department of Geosciences
    Model: UiO_CTM
    Gunnar Myhre
  • RIAM, Kyushu University / CCSR, University of Tokyo
    Model: SPRINTARS
    Toshihiko Takemura
  • UK MetOffice Hadley Centre
    Model: HadGEM
    Olivier Boucher, Nicolas Bellouin
  • Laboratoire Science Climat et de l'Enivonnement
    Model: LMDzT-INCA
    Michael Schulz, Yves Balkanski
  • Your Group:
    Model: Your Model
    Your Signature

Discussion

Please add your thoughts here and sign with (~~~ = Username).

A leading ":" indents your comments so that they refer to the previous comment.
See http://meta.wikimedia.org/wiki/Help:Talk_page for more help. PhilipStier


--PhilipStier 13:57, 14 December 2006 (EST)

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