Search

The authors have decomposed the anthropogenic aerosol radiative forcing into direct contributions from each aerosol species to the planetary energy balance through absorption and scattering of solar radiation, indirect effects of anthropogenic aerosol on solar and infrared radiation through droplet and crystal nucleation on aerosol, and semidirect effects through the influence of solar absorption on the distribution of clouds. A three-mode representation of the aerosol in version 5.1 of the Community Atmosphere Model (CAM5.1) yields global annual mean radiative forcing estimates for each of these forcing mechanisms that are within 0.1 W m−2 of estimates using a more complex seven-mode representation that distinguishes between fresh and aged black carbon and primary organic matter. Simulating fresh black carbon particles separately from internally mixed accumulation mode particles is found to be important only near fossil fuel sources. In addition to the usual large indirect effect on solar radiation, this study finds an unexpectedly large positive longwave indirect effect (because of enhanced cirrus produced by homogenous nucleation of ice crystals on anthropogenic sulfate), small shortwave and longwave semidirect effects, and a small direct effect (because of cancelation and interactions of direct effects of black carbon and sulfate). Differences between the three-mode and seven-mode versions are significantly larger (up to 0.2 W m−2) when the hygroscopicity of primary organic matter is decreased from 0.1 to 0 and transfer of the primary carbonaceous aerosol to the accumulation mode in the seven-mode version requires more hygroscopic material coating the primary particles. Radiative forcing by cloudborne anthropogenic black carbon is only −0.07 W m−2.

The global performance of a new two-moment cloud microphysics scheme for a general circulation model (GCM) is presented and evaluated relative to observations. The scheme produces reasonable representations of cloud particle size and number concentration when compared to observations, and it represents expected and observed spatial variations in cloud microphysical quantities. The scheme has smaller particles and higher number concentrations over land than the standard bulk microphysics in the GCM and is able to balance the top-of-atmosphere radiation budget with 60% the liquid water of the standard scheme, in better agreement with retrieved values. The new scheme diagnostically treats both the mixing ratio and number concentration of rain and snow, and it is therefore able to differentiate the two key regimes, consisting of drizzle in shallow, warm clouds and larger rain drops in deeper cloud systems. The modeled rain and snow size distributions are consistent with observations.

A global atmosphere–land model with an embedded subgrid orography scheme is used to simulate the period 1977–2100 using ocean surface conditions and radiative constituent concentrations for a climate change scenario. Climate variables simulated for multiple elevation classes are mapped according to a high-resolution elevation dataset in 10 regions with complex terrain. Analysis of changes in the simulated climate leads to the following conclusions. Changes in surface air temperature and precipitation differ from region to region in a manner similar to simulations without the subgrid scheme. Subgrid elevation contributes little to spatial variability of the change in temperature and the relative change in precipitation. In some regions somewhat greater warming occurs at higher elevations because of the same tendency in the free troposphere, but in others greater warming occurs near the melting level where snow albedo feedback amplifies the warming. Changes in snow water are highly dependent on altitude because of its nonlinear dependence on changes in the melting level. Absolute changes usually increase with altitude because more snow is currently available for depletion, but for extremely cold conditions the simulated warming is insufficient to increase melting. Relative changes in snow water always decrease with altitude as the likelihood that a warming will enhance melting or change the phase of precipitation decreases with decreasing temperature at higher altitudes. In places where snow accumulates, an artificial upper bound on snow water (which is required in any climate model that does not treat lateral snow transport) limits the sensitivity of snow water to climate change considerably. The simulated impact of climate change on regional mean snow water varies widely, with little impact in regions in which the upper bound on snow water is the dominant snow-water sink, moderate impact in regions with a mixture of seasonal and pemanent snow, and profound relative impacts on regions with little permanent snow.

The climate simulated by a global atmosphere–land model with a physically based subgrid orography scheme is evaluated in 10 selected regions. Climate variables simulated for each of multiple elevation classes within each grid cell are mapped according to a high-resolution distribution of surface elevation in each region. Comparison of the simulated annual mean climate with gridded observations leads to the following conclusions. At low to moderate elevations the downscaling scheme correctly simulates increasing precipitation, decreasing temperature, and increasing snow with increasing elevation across distances smaller than 100 km. At high elevations the downscaling scheme correctly simulates decreasing precipitation with increasing elevation. The rain shadow of many mountain ranges is poorly resolved, with too little precipitation simulated on the windward side of mountain ranges and too much on the lee side. The simulated sensitivity of surface air temperature to surface elevation is too strong, particularly in valleys influenced by drainage circulations. Observations show little evidence of a “snow shadow,” so the neglect of the subgrid rain shadow does not produce an unrealistic simulation of the snow distribution. Summertime snow area, which is a proxy for land ice, is much larger than observed, mostly because of excessive snowfall but in some places because of a cold bias. Summertime snow water equivalent is far less than the observed thickness of glaciers because a 1-m upper bound on snow water is applied to the simulations and because snow transport by slides is neglected. The 1-m upper bound on snow water equivalent also causes an underestimate of seasonal snow water during late winter, compared with gridded station measurements. Potential solutions to these problems are discussed.

Global climate change due to increasing concentrations of greenhouse gases has stimulated numerous studies and discussions about its possible impacts on water resources. Climate scenarios generated by climate models at spatial resolutions ranging from about 50 km to 400 km may not provide enough spatial specificity for use in impact assessment. In Parts I and II of this paper, the spatial specificity issue is addressed by examining what information on mesoscale and small-scale spatial features can be gained by using a regional climate model with a subgrid parameterization of orographic precipitation and land surface cover, driven by a general circulation model. Numerical experiments have been performed to simulate the present-day climatology and the climate conditions corresponding to a doubling of atmospheric CO 2 concentration. This paper describes and contrasts the large-scale and mesoscale features of the greenhouse warming climate signals simulated by the general circulation model and regional climate model over the Pacific Northwest. Results indicate that changes in the large-scale circulation exhibit strong seasonal variability. There is an average warming of about 28C, and precipitation generally increases over the Pacific Northwest and decreases over California. The precipitation signal over the Pacific Northwest is only statistically significant during spring, when both the change in the large-scale circulation and increase in water vapor enhance the moisture convergence toward the north Pacific coast. The combined effects of surface temperature and precipitation changes are such that snow cover is reduced by up to 50% on average, causing large changes in the seasonal runoff. This paper also describes the high spatial resolution (1.5 km) climate signals simulated by the regional climate model. Reductions in snow cover of 50%‐90% are found in areas near the snow line of the control simulation. Analyses of the variations of the climate signals with surface elevation ranging from sea level to 4000 m over two mountain ranges in the Pacific Northwest show that because of changes in the alitude of the freezing level, strong elevation dependency is found in the surface temperature, rainfall, snowfall, snow cover, and runoff signals.

A 6.25-km resolution dataset of meteorology, vegetation type, and soil type for a domain covering a typical global climate model grid cell is used to drive a land surface physics model for a period of 6 months. Additional simulations are performed driving the land surface physics model by spatially averaged meteorology, spatially averaged vegetation characteristics, spatially averaged soil properties, and spatially averaged meteorology, vegetation characteristics, and soil properties. By comparing the simulated water balance for the whole domain for each simulation, the relative influence of subgrid variability in meteorology, vegetation, and soil are assessed. Subgrid variability in summertime precipitation is found to have the largest effect on the surface hydrology, with a nearly twofold increase on surface runoff and a 15% increase in evapotranspiration. Subgrid variations in vegetation and soil properties also increase surface runoff and reduce evapotranspiration, so that surface runoff is 2.75 times as great with subgrid variability than without and evapotranspiration is 19% higher with subgrid variability than without.

A set of general circulation model simulations is analyzed to determine how cloud distribution and cloud radiative properties might change as climate warms and to isolate and quantify the various feedback effects of clouds on climate sensitivity. For this study the NCAR Community Climate Model (CCM1) was modified so that the cloud radiative properties (albodo, emissivity, and absorptivity) are no longer prescribed, but are functions of the cloud liquid water content. Following the Cess and Potter approach for estimating climate sensitivity, we consider results from two sets of simulations. In one set, cloud liquid water is diagnosed from the simulated condensation rate and thus is free to vary with condensation, while in the other set, the cloud liquid water content is a fixed field (dependent only on altitude and latitude) that is obtained by averaging the results of the first set of experiments. The experiments make it possible to isolate the effects of cloud liquid water feedback. We find that...