Gerald L. Potter

Evaluating Parameterizations in General Circulation Models: Climate Simulation Meets Weather Prediction

To significantly improve the simulation of climate by general circulation models (GCMs), systematic errors in representations of relevant processes must first be identified, and then reduced. This endeavor demands that the GCM parameterizations of unresolved processes, in particular, should be tested over a wide range of time scales, not just in climate simulations. Thus, a numerical weather prediction (NWP) methodology for evaluating model parameterizations and gaining insights into their behavior may prove useful, provided that suitable adaptations are made for implementation in climate GCMs. This method entails the generation of short-range weather forecasts by a realistically initialized climate GCM, and the application of six hourly NWP analyses and observations of parameterized variables to evaluate these forecasts. The behavior of the parameterizations in such a weather-forecasting framework can provide insights on how these schemes might be improved, and modified parameterizations then can be test...

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.

Simulation of the northern summer monsoon in the ECMWF model: Sensitivity to horizontal resolution

Abstract The ability of the ECMWF model (cycle 33) to simulate the Indian and East Asian summer monsoons is evaluated at four different horizontal resolutions: T21, T42, T63, and T1O6. Generally, with respect to the large-scale features of the circulation, the largest differences among the simulations occur at T42 relative to T21. However, on regional scales, important differences among the high-frequency temporal variability serve as a further critical rest of the models ability to simulate the monsoon. T106 best captures both the spatial and temporal characteristics of the Indian and East Asian monsoons, whereas T42 fails to correctly simulate the sequence and development of synoptic-scale milestones that characterize the monsoon flow. In particular, T106 is superior at simulating the development and migration of the monsoon trough over the Bay of Bengal. In the T42 simulation, the development of the monsoon occurs one month earlier than typically observed. At this time the trough is incorrectly locate...

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.

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.

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

Satellite Observations for CMIP5: The Genesis of Obs4MIPs

The objective of the Observations for Model Intercomparison Projects (Obs4MIPs) is to provide observational data to the climate science community, which is analogous (in terms of variables, temporal and spatial frequency, and periods) to output from the 5th phase of the World Climate Research Programmes (WCRP) Coupled Model Intercomparison Project (CMIP5) climate model simulations. The essential aspect of the Obs4MIPs methodology is that it strictly follows the CMIP5 protocol document when selecting the observational datasets. Obs4MIPs also provides documentation that describes aspects of the observational data (e.g., data origin, instrument overview, uncertainty estimates) that are of particular relevance to scientists involved in climate model evaluation and analysis. In this paper, we focus on the activities related to the initial set of satellite observations, which are being carried out in close coordination with CMIP5 and directly engage NASAs observational (e.g., mission and instrument) science t...

Comparison of general circulation models to Earth Radiation Budget Experiment data - Computation of clear-sky fluxes

The recent availability of top-of-the-atmosphere radiometric measurements from the Earth Radiation Budget Experiment provides important opportunities for testing and improving numerical climate models. What is unique about these satellite data is that they provide monthly mean clear-sky measurements. There is, however, considerable confusion as to evaluating clear-sky radiative fluxes in climate models in a manner that is consistent with the satellite data processing system. This study provides a clear-sky flux computation method that serves as an analog to the data processing procedure and so provides a model diagnostic that is consistent with the processed satellite data. 11 refs., 4 figs., 5 tabs.

A Modeling Perspective on Cloud Radiative Forcing

Radiation fields from a perpetual July integration of a T106 version of the ECMWF operational model are used to identify the most appropriate way to diagnose cloud radiative forcing in a general circulation model, for the purposes of intercomparison between models. Differences between the methods 1 and 2 of Cess and Potter (1987) and a variant method are addressed. Method 1 is shown to be the least robust of all methods, due to the potential uncertainties related to persistent cloudiness, length of the sampling period, and biases in retrieved clear sky quantities due to insufficient sampling of the diurnal cycle. Method 2 is proposed as an unambiguous way to produce consistent radiative diagnostics for intercomparing model results. The impact of the three methods on the derived sensitivites and cloud feedbacks following an imposed change in sea surface temperature is discussed. The sensitivity of the results to horizontal resolution is considered by using the diagnostics from parallel integrations with T21 version of the model. 20 refs., 2 figs., 1 tab.