The Second Aerosol Characterization Experiment (ACE-2) data set along with ECMWF reanalysis meteorological fields provided the basis for the single column model (SCM) simulations, performed as part of the PACE (Parameterization of the Aerosol Indirect Climatic Effect) project. Six different SCMs were used to simulate ACE-2 case
studies of clean and polluted cloudy boundary layers, with the objective being to identify limitations of the aerosol/cloud/radiation interaction schemes within the range of uncertainty in in situ, reanalysis and satellite retrieved data. The exercise proceeds in three
steps. First, SCMs are configured with the same fine vertical resolution as the ACE-2 in situ data base to evaluate the numerical schemes for prediction of aerosol activation, radiative transfer and precipitation formation. Second, the same test is performed at the coarser vertical resolution of GCMs to evaluate its impact on the performance of the
parameterizations. Finally, SCMs are run for a 24–48 hr period to examine predictions of boundary layer clouds when initialized with large-scale meteorological fields. Several schemes were tested for the prediction of cloud droplet number concentration (N). Physically based activation schemes using vertical velocity show noticeable discrepancies compared to empirical schemes due to biases in the diagnosed cloud base vertical velocity. Prognostic schemes exhibit a larger variability than the diagnostic ones, due to a coupling between aerosol activation and drizzle scavenging in the calculation of N. When
SCMs are initialized at a fine vertical resolution with locally observed vertical profiles of liquid water, predicted optical properties are comparable to observations. Predictions however degrade at coarser vertical resolution and are more sensitive to the mean liquid
water path than to its spatial heterogeneity. Predicted precipitation fluxes are severely underestimated and improve when accounting for sub-grid liquid water variability. Results from the 24–48 hr runs suggest that most models have problems in simulating boundary
layer cloud morphology, since the large-scale initialization fields do not accurately reproduce observed meteorological conditions. As a result, models significantly overestimate optical properties. Improved cloud morphologies were obtained for models with subgrid inversions and subgrid cloud thickness schemes. This may be a result of
representing subgrid scale effects though we do not rule out the possibility that better large-forcing data may also improve cloud morphology predictions.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:13455 |
| Date | January 2003 |
| Creators | Menon, Surabo, Brenguier, Jean-Louis, Boucher, Olivier, Davison, Paul, Del Genio, Anthony D., Feichter, Johann, Ghan, Steven, Guibert, Sarah, Xiaohong, Liu, Lohmann, Ulrike, Pawlowska, Hanna, Penner, Joyce E., Quaas, Johannes, Roberts, David L., Schüller, Lothar, Snider, Jefferson |
| Contributors | NASA Goddard Institute for Space Studies, Columbia University, Lawrence Berkeley National Laboratory, Météo-France-CNRS, Universitédes Sciences et Technologies de Lille, Hadley Centre, Environment Systems Group, Max-Planck-Institut für Meteorologie, Pacific Northwest National Laboratory, University of Michigan, Dalhousie University, Warsaw University, Laboratoire de Météorologie Dynamique, Freie Universität Berlin, University of Wyoming |
| Publisher | Wiley |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Source | Journal of Geophysical Research : Atmospheres (2003), 108, D24, 4762 |
| Rights | info:eu-repo/semantics/openAccess |
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