Evaluation of aerosol and cloud properties in three climate models using MODIS observations and its corresponding COSP simulator, as well as their application in aerosol–cloud interactions
-
Published:2020-02-10
Issue:3
Volume:20
Page:1607-1626
-
ISSN:1680-7324
-
Container-title:Atmospheric Chemistry and Physics
-
language:en
-
Short-container-title:Atmos. Chem. Phys.
Author:
Saponaro Giulia, Sporre Moa K.ORCID, Neubauer DavidORCID, Kokkola HarriORCID, Kolmonen Pekka, Sogacheva Larisa, Arola AnttiORCID, de Leeuw GerritORCID, Karset Inger H. H., Laaksonen AriORCID, Lohmann UlrikeORCID
Abstract
Abstract. The evaluation of modelling diagnostics with appropriate observations is an important task that establishes the capabilities and reliability of models.
In this study we compare aerosol and cloud properties obtained from three different climate models (ECHAM-HAM, ECHAM-HAM-SALSA, and NorESM) with satellite observations using Moderate Resolution Imaging Spectroradiometer (MODIS) data. The simulator MODIS-COSP version 1.4 was implemented into the climate models to obtain MODIS-like cloud diagnostics, thus enabling model-to-model and model-to-satellite comparisons. Cloud droplet number concentrations (CDNCs) are derived identically from MODIS-COSP-simulated and MODIS-retrieved values of cloud optical depth and effective radius. For CDNC, the models capture the observed spatial distribution of higher values typically found near the coasts, downwind of the major continents, and lower values over the remote ocean and land areas. However, the COSP-simulated CDNC values are higher than those observed, whilst the direct model CDNC output is significantly lower than the MODIS-COSP diagnostics. NorESM produces large spatial biases for ice cloud properties and thick clouds over land. Despite having identical cloud modules, ECHAM-HAM and ECHAM-HAM-SALSA diverge in their representation of spatial and vertical distributions of clouds.
From the spatial distributions of aerosol optical depth (AOD) and aerosol index (AI), we find that NorESM shows large biases for AOD over bright land surfaces, while discrepancies between ECHAM-HAM and ECHAM-HAM-SALSA can be observed mainly over oceans. Overall, the AIs from the different models are in good agreement globally, with higher negative biases in the Northern Hemisphere.
We evaluate the aerosol–cloud interactions by computing the sensitivity parameter ACICDNC=dln(CDNC)/dln(AI) on a global scale. However, 1 year of data may be considered not enough to assess the similarity or dissimilarities of the models due to large temporal variability in cloud properties.
This study shows how simulators facilitate the evaluation of cloud properties and expose model deficiencies, which are necessary steps to further improve the parameterisation in climate models.
Funder
Seventh Framework Programme
Publisher
Copernicus GmbH
Subject
Atmospheric Science
Reference104 articles.
1. Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation: 2.
Multiple aerosol types, J. Geophys. Res.-Atmos., 105,
6837–6844, https://doi.org/10.1029/1999JD901161,
2000. a, b, c, d 2. Abdul-Razzak, H. and Ghan, S. J.: A parameterization of aerosol activation 3.
Sectional representation, J. Geophys. Res., 107, D3,
https://doi.org/10.1029/2001JD000483, 2002. a, b 3. Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The
impact of humidity above stratiform clouds on indirect aerosol climate
forcing, Nature, 432, 1014–1017, https://doi.org/10.1038/nature03174, 2004. a 4. Ban-Weiss, G. A., Jin, L., Bauer, S. E., Bennartz, R., Liu, X., Zhang, K.,
Ming, Y., Guo, H., and Jiang, J. H.: Evaluating clouds, aerosols, and their
interactions in three global climate models using satellite simulators and
observations, J. Geophys. Res.-Atmos., 119,
10876–10901, https://doi.org/10.1002/2014JD021722,
2014. a, b, c, d, e 5. Bellouin, N., Quaas, J., Gryspeerdt, E., Kinne, S., Stier, P., Watson-Parris,
D., Boucher, O., Carslaw, K., Christensen, M., Daniau, A.-L., Dufresne,
J.-L., Feingold, G., Fiedler, S., Forster, P., Gettelman, A., Haywood, J.,
Lohmann, U., Malavelle, F., Mauritsen, T., McCoy, D., Myhre, G.,
Mülmenstädt, J., Neubauer, D., Possner, A., Rugenstein, M., Sato, Y.,
Schulz, M., Schwartz, S., Sourdeval, O., Storelvmo, T., Toll, V., Winker, D.,
and Stevens, B.: Bounding global aerosol radiative forcing of climate change,
Rev. Geophys., accepted, 2020. a, b
Cited by
13 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|