B. J. McAvaney

GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview

Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detai...

Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject

The ability of 15 atmospheric general circulation models (AGCM) to simulate the tropical intraseasonal oscillation has been studied as part of the Atmospheric Model Intercomparison Project (AMIP). Time series of the daily upper tropospheric velocity poential and zonal wind, averaged over the equatorial belt, were provided from each AGCM simulation. These data were analyzed using a variety of techniques such as time filtering and space-time spectral analysis to identify eastward and westward moving waves. The results have been compared with an identical assessment of the European Centre for Medium-range Weather Forecasts (ECMWF) analyses for the period 1982–1991. The models display a wide range of skill in simulating the intraseasonal oscillation. Most models show evidence of an eastward propagating anomaly in the velocity potential field, although in some models there is a greater tendency for a standing oscillation, and in one or two the field is rather chaotic with no preferred direction of propagation. Where a model has a clear eastward propagating signal, typical periodicities seem quite reasonable although there is a tendency for the models to simulate shorter periods than in the ECMWF analyses, where it is near 50 days. The results of the space-time spectral analysis have shown that no model has captured the dominance of the intraseasonal oscillation found in the analyses. Several models have peaks at intraseasonal time scales, but nearly all have relatively more power at higher frequencies (< 30 days) than the analyses. Most models underestimate the strength of the intraseasonal variability. The observed intraseasonal oscillation shows a marked seasonality in its occurrence with greatest activity during northern winter and spring. Most models failed to capture this seasonality. The interannual variability in the activity of the intraseasonal oscillation has also been assessed, although the AMIP decade is too short to provide any conclusive results. There is a suggestion that the observed oscillation was suppressed during the strong El Niño of 1982/83, and this relationship has also been reproduced by some models. The relationship between a models intraseasonal activity, its seasonal cycle and characteristics of its basic climate has been examined. It is clear that those models with weak intraseasonal activity tend also to have a weak seasonal cycle. It is becoming increasingly evident that an accurate description of the basic climate may be a prerequisite for producing a realistic intraseasonal oscillation. In particular, models with the most realistic intraseasonal oscillations appear to have precipitation distributions which are better correlated with warm sea surface temperatures. These models predominantly employ convective parameterizations which are closed on buoyancy rather than moisture convergence.

Monsoon changes for 6000 years ago: Results of 18 simulations from the Paleoclimate Modeling Intercomparison Project (PMIP)

Amplification of the northern hemisphere seasonal cycle of insolation during the mid-Holocene causes a northward shift of the main regions of monsoon precipitation over Africa and India in all 18 simulations conducted for the Paleoclimate Modeling Intercomparison Project (PMIP). Differences among simulations are related to differences in model formulation. Despite qualitative agreement with paleoecological estimates of biome shifts, the magnitude of the monsoon increases over northern Africa are underestimated by all the models.

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.

Intercomparison and interpretation of surface energy fluxes in atmospheric general circulation models

We have analyzed responses of the surface energy budgets and hydrologic cycles of 19 atmospheric general circulation models to an imposed, globally uniform sea surface temperature perturbation of 4 K. The responses of the simulated surface energy budgets are extremely diverse and are closely linked to the responses of the simulated hydrologic cycles. The response of the net surface energy flux is not controlled by cloud effects; instead, it is determined primarily by the response of the latent heat flux. The prescribed warming of the oceans leads to major increases in the atmospheric water vapor content and the rates of evaporation and precipitation. The increased water vapor amount drastically increases the downwelling infrared radiation at the Earths surface, but the amount of the change varies dramatically from one model to another.

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.

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.

A proposal for a general interface between land surface schemes and general circulation models

The aim of this paper is to propose a general interface for coupling general circulation models (GCMs) to land surface schemes (LSS) in order to achieve a plug compatibility between these complex models. As surface parameterizations include more processes, they have moved from being subroutines of GCMs to independent schemes which can also be applied for other purposes. This evolution has raised the problem within climate modeling groups of coupling these schemes to GCMs in a simple and flexible way. As LSS reaches a larger independence, a general interface is needed to enable exchange within the community. This paper discusses the tasks LSS have to fulfill when coupled to a GCM after a review of the current state of the art and the likely future evolutions of both components. The numerical schemes used for the processes which couple the land surfaces to the atmosphere are reviewed to ensure that the interface can be applied to all LSS and GCMs after only minor changes.

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.