Simulations of a Cold Front by Cloud-Resolving, Limited-Area, and Large-Scale Models, and a Model Evaluation Using In Situ and Satellite Observations

Abstract

The Global Energy and Water Cycle Experiment has identified the poor representation of clouds in atmospheric general circulation models as one of the major impediments for the use of these models in reliably predicting future climate change. One of the most commonly encountered types of cloud system in midlatitudes is that associated with cyclones. The purpose of this study is to investigate the representation of frontal cloud systems in a hierarchy of models in order to identify their relative weaknesses. The hierarchy of models was classified according to the horizontal resolution: cloud-resolving models (5-km resolution), limited-area models (20-km resolution), coarse-grid single-column models (300 km), and an atmospheric general circulation model (Ͼ100 km). The models were evaluated using both in situ and satellite data. The study shows, as expected, that the higher-resolution models give a more complete description of the front and capture many of the observed nonlinear features of the front. At the low resolution, the simulations are unable to capture the front accurately due to the lack of the nonlinear features seen in the high-resolution simulations. The model intercomparison identified problems in applying single-column models to rapidly advecting baroclinic systems. Mesoscale circulations driven by subgrid-scale dynamical, thermodynamical, and microphysical processes are identified as an important feedback mechanism linking the frontal circulations and the cloud field. Finally it is shown that the same techniques used to validate climatological studies with International Satellite Cloud Climatology Project data are also valid for case studies, thereby providing a methodology to generalize the single case studies to climatological studies.

Simulations of midlatitude frontal clouds by single‐column and cloud‐resolving models during the Atmospheric Radiation Measurement March 2000 cloud intensive operational period

“…However, the model largely overestimated optically thin cirrus clouds and optically thick low clouds and grossly underestimated the middle-level clouds in the cold sector of the storm in comparison with the ISCCP data. Similar model deficiencies in simulating cirrus clouds and middle-level clouds were also found in the work of Ryan et al [2000], which investigated the representation of frontal cloud systems in a hierarchy of models (SCMs, CRMs, LAMs, and GCMs) in simulating a typical cold front case observed over Australia. In their study, SCMs and CRMs were driven with the boundary forcing data produced from a 20-km LAM.…”

“…The reasons for these model errors are still not completely understood. Owing to the lack of detailed measurements of clouds and related microphysical fields, Ryan et al [2000] could not compare quantitatively the model simulations directly with observations.…”

Numerical Simulations of the Impacts of Land-Cover Change on Cold Fronts in South-West Western Australia

“…RAMS is a highly versatile three-dimensional mesoscale meteorological model (Pielke et al 1992;Cotton et al 2003) that has been extensively used for a wide variety of applications including modelling sea breezes (e.g., Ma and Lyons 2000;Cai and Steyn 2000;Miao et al 2003;Kala et al 2010) and storm events (e.g., Nair et al 1997;Kotroni et al 1998;Ryan et al 2000;. The latest 6.0 version was utilised and operated as a non-hydrostatic, compressible, primitive equation model with a σ z terrain-following vertical coordinate system with polar stereographic coordinates.…”

Confronting Models with Data: The GEWEX Cloud Systems Study

“…The Southern Ocean is blanketed by multilayer cloud systems associated with baroclinic weather systems, while the Northern Hemisphere storm tracks produce the brightest cloud albedos anywhere. In four major case studies, WG3 has made extensive use of regional or "limited area" models (LAMs), which can represent the four-dimensional structure of an extratropical synoptic system (e.g., Ryan et al 2000). Also, WG3 has made extensive use of satellite data, including data from the International Satellite Cloud Climatology Project (ISCCP; Rossow and Schiffer 1999).…”