Models of temperature structure and general circulation

Titan has a warm upper atmosphere. Whether it has a warm lower atmosphere and hot surface is an open question. This question is important not only from a purely scientific point of view, but also for assessing the viability of a Titan entry probe

The general circulation of the atmosphere

Theories of how Earth's surface climate may change in the future, of how it may have been in the past, and of how it is related to climates of other planets must build upon a theory of the general circulation of the atmosphere. The view of the atmospheric general circulation presented here focuses not on Earth's general circulation as such but on a continuum of idealized circulations with axisymmetric flow statistics. Analyses of observational data for Earth's atmosphere, simulations with idealized general circulation models, and theoretical considerations suggest how characteristics of the tropical Hadley circulation, of the extratropical circulation, and of atmospheric macroturbulence may depend on parameters such as the planet radius and rotation rate and the strength of the differential heating at the surface

An intercomparison of intraseasonal variability in general circulation models and observations

Low frequency oscillations appearing in three GCM seasonal cycle integrations are compared with the analyses of the European Center for Medium Range Weather Forecasting (ECMWF). All three models have the same resolution: 4 deg latitude by 5 deg longitude, with 9 levels. The dominant phase speeds and the differential vertical structure of the heating profiles in the GCMs are in general agreement with current theory involving the positive feedback between latent heating and moist static stability. All three GCMs fail to capture the detailed evolution in the different stages of the development and decay of the oscillation. The results suggest that an improvement in the boundary layer moisture processes may be crucial for a better simulation of the oscillation

A comparative analysis of Simplified General Circulation Models of the atmosphere of Venus

Within the context of a working group supported by ISSI (Bern, Switzerland), we have made an intercomparison work between Global Circulation Models using simpli?ed parameterizations for radiative forcing and other physical processes. Even with similar schemes and parameters, the different GCMs produce different circulations, illustrating interesting differences between dynamical model cores

A Statistical Evaluation of Atmosphere-Ocean General Circulation Models: Complexity vs. Simplicity

The principal tools used to model future climate change are General Circulation Models which are deterministic high resolution bottom-up models of the global atmosphere-ocean system that require large amounts of supercomputer time to generate results. But are these models a cost-effective way of predicting future climate change at the global level? In this paper we use modern econometric techniques to evaluate the statistical adequacy of three general circulation models (GCMs) by testing three aspects of a GCM's ability to reconstruct the historical record for global surface temperature: (1) how well the GCMs track observed temperature; (2) are the residuals from GCM simulations random (white noise) or are they systematic (red noise or a stochastic trend); (3) what is the explanatory power of the GCMs compared to a simple alternative time series model, which assumes that temperature is a linear function of radiative forcing. The results indicate that three of the eight experiments considered fail to reconstruct temperature accurately; the GCM errors are either red noise processes or contain a systematic error, and the radiative forcing variable used to simulate the GCM's have considerable explanatory power relative to GCM simulations of global temperature. The GFDL model is superior to the other models considered. Three out of four Hadley Centre experiments also pass all the tests but show a poorer goodness of fit. The Max Planck model appears to perform poorly relative to the other two models. It does appear that there is a trade-off between the greater spatial detail and number of variables provided by the GCMs and more accurate predictions generated by simple time series models. This is similar to the debate in economics regarding the forecasting accuracy of large macro-economic models versus simple time series models.

A scheme for parameterizing cirrus cloud ice water content in general circulation models

Clouds strongly influence th earth's energy budget. They control th amount of solar radiative energy absorbed by the climate system, partitioning the energy between the atmosphere and the earth's surface. They also control the loss of energy to space by their effect on thermal emission. Cirrus and altostratus are the most frequent cloud types, having an annual average global coverage of 35 and 40 percent, respectively. Cirrus is composed almost entirely of ice crystals and the same is frequently true of the upper portions of altostratus since they are often formed by the thickening of cirrostratus and by the spreading of the middle or upper portions of thunderstorms. Thus, since ice clouds cover such a large portion of the earth's surface, they almost certainly have an important effect on climate. With this recognition, researchers developing climate models are seeking largely unavailable methods for specifying the conditions for ice cloud formation, and quantifying the spatial distribution of ice water content, IWC, a necessary step in deriving their radiative characteristics since radiative properties are apparently related to IWC. A method is developed for specifying IWC in climate models, based on theory and measurements in cirrus during FIRE and other experiments

Stratospheric dynamics and transport studies

A three dimensional General Circulation Model/Transport Model is used to simulate stratospheric circulation and constituent distributions. Model simulations are analyzed to interpret radiative, chemical, and dynamical processes and their mutual interactions. Concurrent complementary studies are conducted using both global satellite data and other appropriate data. Comparisons of model simulations and data analysis studies are used to aid in understanding stratospheric dynamics and transport processes and to assess the validity of current theory and models

Tropical air-sea interaction in general circulation models

An intercomparison is undertaken of the tropical behavior of 17 coupled ocean-atmosphere models in which at least one component may be termed a general circulation model (GCM). The aim is to provide a taxonomy—a description and rough classification—of behavior across the ensemble of models, focusing on interannual variability. The temporal behavior of the sea surface temperature (SST) field along the equator is presented for each model, SST being chosen as the primary variable for intercomparison due to its crucial role in mediating the coupling and because it is a sensitive indicator of climate drift. A wide variety of possible types of behavior are noted among the models. Models with substantial interannual tropical variability may be roughly classified into cases with propagating SST anomalies and cases in which the SST anomalies develop in place. A number of the models also exhibit significant drift with respect to SST climatology. However, there is not a clear relationship between climate drift and the presence or absence of interannual oscillations. In several cases, the mode of climate drift within the tropical Pacific appears to involve coupled feedback mechanisms similar to those responsible for El Niño variability. Implications for coupled-model development and for climate prediction on seasonal to interannual time scales are discussed. Overall, the results indicate considerable sensitivity of the tropical coupled ocean-atmosphere system and suggest that the simulation of the warm-pool/cold-tongue configuration in the equatorial Pacific represents a challenging test for climate model parameterizations

Efficient dynamical downscaling of general circulation models using continuous data assimilation

Continuous data assimilation (CDA) is successfully implemented for the first time for efficient dynamical downscaling of a global atmospheric reanalysis. A comparison of the performance of CDA with the standard grid and spectral nudging techniques for representing long- and short-scale features in the downscaled fields using the Weather Research and Forecast (WRF) model is further presented and analyzed. The WRF model is configured at 25km horizontal resolution and is driven by 250km initial and boundary conditions from NCEP/NCAR reanalysis fields. Downscaling experiments are performed over a one-month period in January, 2016. The similarity metric is used to evaluate the performance of the downscaling methods for large and small scales. Similarity results are compared for the outputs of the WRF model with different downscaling techniques, NCEP reanalysis, and Final Analysis. Both spectral nudging and CDA describe better the small-scale features compared to grid nudging. The choice of the wave number is critical in spectral nudging; increasing the number of retained frequencies generally produced better small-scale features, but only up to a certain threshold after which its solution gradually became closer to grid nudging. CDA maintains the balance of the large- and small-scale features similar to that of the best simulation achieved by the best spectral nudging configuration, without the need of a spectral decomposition. The different downscaled atmospheric variables, including rainfall distribution, with CDA is most consistent with the observations. The Brier skill score values further indicate that the added value of CDA is distributed over the entire model domain. The overall results clearly suggest that CDA provides an efficient new approach for dynamical downscaling by maintaining better balance between the global model and the downscaled fields