Climate Models

Fields from two experiments performed with 18-level versions of the Commonwealth Scientific and Industrial Organization (CSIRO) global climate model (GCM) are compared with observed fields, focusing on quantities related to clouds and precipitation. The first experiment (denoted by PROG) employed a new prognostic treatment of stratiform clouds and precipitation, while the second experiment (denoted by DIAG18) employed a diagnostic treatment, similar to that used in the standard 9-level CSIRO GCM. The main findings are as follows.Global-mean quantities agree well with observations, although the global cloudiness in both runs is a little lower than observed values.Zonal-mean fields generally show good to very good agreement with observations, particularly in the PROG run, where marked improvements in the cloudiness and long-wave cloud radiative forcing (LWCF) at high latitudes are noted. The PROG run has cloud-liquid-water paths (LWPs) that are larger over mid-latitude oceans than those from satellite retrievals.Geographical distributions of precipitation, cloudiness, LWCF and SWCF (short-wave cloud radiative forcing) from both runs are generally in reasonable agreement with observations. Overall, the cloudiness and LWCF are somewhat more realistic in the PROG run, the SWCF is slightly more realistic in the DIAG18 run, and the precipitation is not greatly affected by the change of cloud scheme.Problems affecting both runs to some degree are:Global-mean quantities agree well with observations, although the global cloudiness in both runs is a little lower than observed values.Zonal-mean fields generally show good to very good agreement with observations, particularly in the PROG run, where marked improvements in the cloudiness and long-wave cloud radiative forcing (LWCF) at high latitudes are noted. The PROG run has cloud-liquid-water paths (LWPs) that are larger over mid-latitude oceans than those from satellite retrievals.Geographical distributions of precipitation, cloudiness, LWCF and SWCF (short-wave cloud radiative forcing) from both runs are generally in reasonable agreement with observations. Overall, the cloudiness and LWCF are somewhat more realistic in the PROG run, the SWCF is slightly more realistic in the DIAG18 run, and the precipitation is not greatly affected by the change of cloud scheme.Problems affecting both runs to some degree are:deficient cloudiness in the subtropics, and to a lesser extent in mid-latitudes;deficient SWCF in mid-latitudes, with a tendency towards excessive SWCF at low latitudes;deficient LWCF over land, mainly in the tropics and northern mid-latitudes;excessive precipitation, cloudiness and cloud radiative forcing in the tropical western Pacific Ocean in July.The reasons for the above findings are investigated, in part, via the use of sensitivity tests. The improved high-latitude cloudiness in the PROG run results from (a) replacement of a cloudiness parametrization based on relative humidity with one based on a generalized relative humidity that includes the contribution from cloud water, and (b) inclusion of the effect of frozen precipitation processes on the cloud fraction. The improved LWCF is primarily the result of more realistic treatment of cloud emissivity in the prognostic cloud scheme. The excessive LWPs over mid-latitude oceans in the PROG run can be corrected by a modest reduction in the critical cloud droplet radius that controls the onset of autoconversion. The deficient cloudiness in the subtropics and mid-latitudes (typical of current GCMs) can be improved by simple changes to the critical relative humidities used to control the onset of cloud formation or by an increase of vertical resolution, but this improvement comes at the cost of excessive cloudiness in the tropics. The errors in the modelled SWCF (also typical of current GCMs) suggest that there is a systematic latitudinal bias in the calculation of cloud–radiation interactions, such as the effect of solar zenith angle. The deficient LWCF over land is related to a deficiency of high cloud. The vigorous circulation in July over the tropical western Pacific is much more prominent in these 18-level simulations than in the standard 9-level version of the model, and is related to aspects of the model other than the cloud treatment.

The participation of different vegetation types within the physical climate system is investigated using a coupled atmosphere-biosphere model, CCM3-IBIS. We analyze the effects that six different vegetation biomes (tropical, boreal, and temperate forests, savanna, grassland and steppe, and shrubland/tundra) have on the climate through their role in modulating the biophysical exchanges of energy, water, and momentum between the land-surface and the atmosphere. Using CCM3-IBIS we completely remove the vegetation cover of a particular biome and compare it to a control simulation where the biome is present, thereby isolating the climatic effects of each biome. Results from the tropical and boreal forest removal simulations are in agreement with previous studies while the other simulations provide new evidence as to their contribution in forcing the climate. Removal of the temperate forest vegetation exhibits behavior characteristic of both the tropical and boreal simulations with cooling during winter and spring due to an increase in the surface albedo and warming during the summer caused by a reduction in latent cooling. Removal of the savanna vegetation exhibits behavior much like the tropical forest simulation while removal of the grassland and steppe vegetation has the largest effect over the central United States with warming and drying of the atmosphere in summer. The largest climatic effect of shrubland and tundra vegetation removal occurs in DJF in Australia and central Siberia and is due to reduced latent cooling and enhanced cold air advection, respectively. Our results show that removal of the boreal forest yields the largest temperature signal globally when either including or excluding the areas of forest removal. Globally, precipitation is most affected by removal of the savanna vegetation when including the areas of vegetation removal, while removal of the tropical forest most influences the global precipitation excluding the areas of vegetation removal.

A stochastic parameterization scheme for deep convection is described, suitable for use in both climate and NWP models. Theoretical arguments and the results of cloud-resolving models are discussed in order to motivate the form of the scheme. In the deterministic limit, it tends to a spectrum of entraining/detraining plumes and is similar to other current parameterizations. The stochastic variability describes the local fluctuations about a large-scale equilibrium state. Plumes are drawn at random from a probability distribution function (PDF) that defines the chance of finding a plume of given cloud-base mass flux within each model grid box. The normalization of the PDF is given by the ensemble-mean mass flux, and this is computed with a CAPE closure method. The characteristics of each plume produced are determined using an adaptation of the plume model from the Kain–Fritsch parameterization. Initial tests in the single-column version of the Unified Model verify that the scheme is ...

Abstract[1] A subset of climate simulations of the 20th century from the IPCC-AR4 is analyzed to assess the ability of these models to reproduce the observed climatological seasonal precipitation in South America during the period 1970–1999. Changes of the model climatology in a climate change scenario (SRESA1b) for the period 2070–2099 are also discussed. Results show that models are able to reproduce the main features of the precipitation seasonal cycle over South America, although the precipitation in the SACZ region and the precipitation maximum over southeastern South America observed during the cold season are not well- represented. There is a general consensus among models that the precipitation changes projected are mainly: i) an increase of summer precipitation over southeastern subtropical South America; ii) a reduction of winter precipitation over most of the continent; and iii) reduction of precipitation in all seasons along the southern Andes.