R. A. Colman

Interpretation of Snow-Climate Feedback as Produced by 17 General Circulation Models

Snow feedback is expected to amplify global warming caused by increasing concentrations of atmospheric greenhouse gases. The conventional explanation is that a warmer Earth will have less snow cover, resulting in a darker planet that absorbs more solar radiation. An intercomparison of 17 general circulation models, for which perturbations of sea surface temperature were used as a surrogate climate change, suggests that this explanation is overly simplistic. The results instead indicate that additional amplification or moderation may be caused both by cloud interactions and longwave radiation. One measure of this net effect of snow feedback was found to differ markedly among the 17 climate models, ranging from weak negative feedback in some models to strong positive feedback in others.

Uncertainties in Carbon Dioxide Radiative Forcing in Atmospheric General Circulation Models

Global warming caused by an increase in the concentrations of greenhouse gases, is the direct result of greenhouse gas—induced radiative forcing. When a doubling of atmospheric carbon dioxide is considered, this forcing differed substantially among 15 atmospheric general circulation models. Although there are several potential causes, the largest contributor was the carbon dioxide radiation parameterizations of the models.

Cloud-radiative effects on implied oceanic energy transports as simulated by atmospheric general circulation models

This paper summarizes the ocean surface net energy flux simulated by fifteen atmospheric general circulation models constrained by realistically-varying sea surface temperatures and sea ice as part of the Atmospheric Model Intercomparison Project. In general, the simulated energy fluxes are within the very large observational uncertainties. However, the annual mean oceanic meridional heat transport that would be required to balance the simulated surface fluxes is shown to be critically sensitive to the radiative effects of clouds, to the extent that even the sign of the Southern Hemisphere ocean heat transport can be affected by the errors in simulated cloud-radiation interactions. It is suggested that improved treatment of cloud radiative effects should help in the development of coupled atmosphere-ocean general circulation models.

Evaluation of the South Pacific Convergence Zone in IPCC AR4 Climate Model Simulations of the Twentieth Century

Abstract Understanding how the South Pacific convergence zone (SPCZ) may change in the future requires the use of global coupled atmosphere–ocean models. It is therefore important to evaluate the ability of such models to realistically simulate the SPCZ. The simulation of the SPCZ in 24 coupled model simulations of the twentieth century is examined. The models and simulations are those used for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The seasonal climatology and interannual variability of the SPCZ is evaluated using observed and model precipitation. Twenty models simulate a distinct SPCZ, while four models merge intertropical convergence zone and SPCZ precipitation. The majority of models simulate an SPCZ with an overly zonal orientation, rather than extending in a diagonal band into the southeast Pacific as observed. Two-thirds of models capture the observed meridional displacement of the SPCZ during El Nino and La Nina events. The four models that use ...

Analysis of snow feedbacks in 14 general circulation models

Snow feedbacks produced by 14 atmospheric general circulation models have been analyzed through idealized numerical experiments. Included in the analysis is an investigation of the surface energy budgets of the models. Negative or weak positive snow feedbacks occurred in some of the models, while others produced strong positive snow feedbacks. These feedbacks are due not only to melting snow, but also to increases in boundary temperature, changes in air temperature, changes in water vapor, and changes in cloudiness. As a result, the net response of each model is quite complex. We analyze in detail the responses of one model with a strong positive snow feedback and another with a weak negative snow feedback. Some of the models include a temperature dependence of the snow albedo, and this has significantly affected the results.

Consensus on Twenty-First-Century Rainfall Projections in Climate Models More Widespread than Previously Thought

AbstractUnder global warming, increases in precipitation are expected at high latitudes and near major tropical convergence zones in some seasons, while decreases are expected in many subtropical and midlatitude areas in between. In many other areas there is no consensus among models on the sign of the projected change. This is often assumed to indicate that precipitation projections in these regions are highly uncertain.Here, twenty-first century precipitation projections under the Special Report on Emissions Scenarios (SRES) A1B scenario using 24 World Climate Research Programme (WCRP)/Coupled Model Intercomparison Project phase 3 (CMIP3) climate models are examined. In areas with no consensus on the sign of projected change there are extensive subregions where the projected change is “very likely” (i.e., probability > 0.90) to be small (relative to, e.g., the size of interannual variability during the late twentieth century) or zero. The statistical significance of and interrelationships between method...

A study of general circulation model climate feedbacks determined from perturbed sea surface temperature experiments

The response of a general circulation model (GCM) to global perturbations in sea surface temperatures (SSTs) is examined. The feedback strengths in the model are diagnosed by the response of top of atmosphere (TOA) radiative fluxes determined after substitution of fields from the “perturbed” climate into the “control.” Total feedback is divided into terms due to water vapour, lapse rate, surface temperature, and clouds (in turn analysed in terms of cloud amount, height and types). The “standard experiment” prescribes a globally uniform SST perturbation with fixed soil moisture. Four additional experiments vary the number of model vertical levels, the pattern of SST changes, the convection scheme, and the soil moisture. The SST pattern change chosen follows that of an equilibrium 2×CO2 experiment, which shows polar amplification of the surface warming. Variations in the clear sky sensitivity of the model are shown to depend primarily on changes in the long wave response due to competing (positive) water vapor and (generally negative) lapse rate feedbacks. Results here indicate that these feedbacks may be very different for differing experimental boundary conditions. The long wave feedback due to cloud amount changes is negative in all experiments, due to a very consistent decrease in high and middle cloud fractions. Conversely, cloud height feedback is positive due to a general increase in the altitude of (particularly high) cloud. Cloud height feedback is very sensitive to the choice of the convection scheme and to the change in vertical resolution. Greatest changes in the strength of the short wave cloud feedback results from modifications to the soil moisture specification and the convection scheme. The results here indicate that large differences in cloud feedback may be diagnosed from a single model, even without changes being made to the cloud parametrization. The value of the sensitivity can thus be expected to be a function not only of the physical parametrizations chosen for the model (e.g. the penetrative convection scheme), but also of the details of the manner in which the experiment was performed (e.g. SST and soil moisture specifications). The TOA radiation perturbation analysis method proves to be a powerful technique for diagnosing and understanding the physical processes responsible for the range in climate sensitivity found between the experiments.

Comparison of the Seasonal Change in Cloud-Radiative Forcing from Atmospheric General Circulation Models and Satellite Observations

We compare seasonal changes in cloud-radiative forcing (CRF) at the top of the atmosphere from 18 atmospheric general circulation models, and observations from the Earth Radiation Budget Experiment (ERBE). To enhance the CRF signal and suppress interannual variability, we consider only zonal mean quantities for which the extreme months (January and July), as well as the northern and southern hemispheres, have been differenced. Since seasonal variations of the shortwave component of CRF are caused by seasonal changes in both cloudiness and solar irradiance, the latter was removed. In the ERBE data, seasonal changes in CRF are driven primarily by changes in cloud amount. The same conclusion applies to the models. The shortwave component of seasonal CRF is a measure of changes in cloud amount at all altitudes, while the longwave component is more a measure of upper level clouds. Thus important insights into seasonal cloud amount variations of the models have been obtained by comparing both components, as generated by the models, with the satellite data. For example, in 10 of the 18 models the seasonal oscillations of zonal cloud patterns extend too far poleward by one latitudinal grid. •Institute for Terrestrial and Planetary Atmospheres, Marine Sciences Research Center, State University of New York at Stony Brook. 2program for Climate Model Diagnosis and Intercomparison, Lawrence Livermore National Laboratory, Livermore, California. 3Department of Numerical Mathematics, Russian Academy of Sciences, Moscow. 4Canadian Climate Centre, Downsview, Ontario. SLaboratoire de Mdtdorologie Dynamique, Paris. 6Bureau of Meteorology Research Centre, Melbourne, Victoria, Australia. 7Department of Atmospheric Science, Colorado State University, Fort Collins. 8NASA Goddard Institute for Space Studies, New York. 9Maltrio-France, Centre National de Recherches Mdtdorologiques, Toulouse, France. •oDivision of Atmospheric Research, Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria, Australia. •Max Planck Institute for Meteorology, Hamburg, Germany. •2National Center for Atmospheric Research, Boulder, Colorado. •3Hadley Centre for Climate Prediction and Research, U. K. Meteorological Office, Bracknell, England. •4Atmospheric Sciences Research Center, State University of New York at Albany. •SVoeikov Main Geophysical Obseratory, St. Petersburg, Russia. •6European Centre for Medium-Range Weather Forecasts, Reading, England. •7Department ofAtmospheric Sciences, University of Illinois, Urbana. 18Geophysical Fluid Dynamics Laboratory, National Oceanic and Atmospheric Administration, Princeton University, Princeton, New Jersey. Copyright 1997 by the American Geophysical Union. Paper number 97JD00927. 01480227/97/97JD-00927509.00

The South Pacific Convergence Zone in CMIP5 simulations of historical and future climate

The South Pacific Convergence Zone (SPCZ) is evaluated in historical simulations from 26 Coupled Model Intercomparison Project Phase 5 (CMIP5) models, and compared with previous generation CMIP3 models. A subset of 24 CMIP5 models are able to simulate a distinct SPCZ in the December to February (DJF) austral summer, although the position of the SPCZ in these models is too zonal compared with observations. The spatial pattern of SPCZ precipitation is improved in CMIP5 models relative to CMIP3 models, although the spurious double ITCZ precipitation band in the eastern Pacific is intensified in many CMIP5 models. All CMIP5 models examined capture some interannual variability of SPCZ latitude, and 19 models simulate a realistic correlation with El Niño–Southern Oscillation. In simulations of the twenty-first century under the RCP8.5 emission scenario, no consistent shift in the mean position of the DJF SPCZ is identified. Several models simulate significant shifts northward, and a similar number of models simulate significant southward shifts. The majority of CMIP5 models simulate an increase in mean DJF SPCZ precipitation, and there is an intensification of the eastern Pacific double ITCZ precipitation band in many models. Most models simulate regions of increased precipitation in the western part of the SPCZ and near the equator, and regions of decreased precipitation at the eastern edge of the SPCZ. Decomposition of SPCZ precipitation changes into dynamic and thermodynamic components reveals predominantly increased precipitation due to thermodynamic changes, while dynamic changes lead to regions of both positive and negative precipitation anomalies.

Does Soil Moisture Influence Climate Variability and Predictability over Australia

Abstract Interannual variations of Australian climate are strongly linked to the El Nino–Southern Oscillation (ENSO) phenomenon. However, the impact of other mechanisms on prediction, such as atmosphere–land surface interactions, has been less frequently investigated. Here, the impact of soil moisture variability on interannual climate variability and predictability is examined using the Bureau of Meteorology Research Centre atmospheric general circulation model. Two sets of experiments are run, each with five different initial conditions. In the first set of experiments, soil moisture is free to vary in response to atmospheric forcing in each experiment according to a set of simple prognostic equations. A potential predictability index is computed as the ratio of the models internal variability to its external forced variability. This estimates the level of predictability obtained assuming perfect knowledge of future ocean surface temperatures. A second set of five experiments with prescribed soil moist...