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Standard vector calculus formulas of Cartesian three space are projected onto the surface of a sphere. This produces symmetric equations with three nonindependent horizontal velocity components. Each orthogonal axis has a velocity component that rotates around its axis (eastward velocity rotates around the north–south axis) and a specific angular momentum component that is the product of the velocity component multiplied by the cosine of axis’ latitude. Angular momentum components align with the fixed axes and simplify several formulas, whereas the rotating velocity components are not orthogonal and vary with location. Three symmetric coordinates allow vector resolution and calculus operations continuously over the whole spherical surface, which is not possible with only two coordinates. The symmetric equations are applied to one-layer shallow water models on cubed-sphere and icosahedral grids, the latter being computationally simple and applicable to an ocean domain. Model results are presented for three different initial conditions and five different resolutions.

An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño-Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño-namely, eastern Pacific (EP) and central Pacific (CP) El Niño-and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.

The authors describe the characteristics of tropical cyclone (TC) activity in the GISS general circulation ModelE2 with a horizontal resolution 1deg x 1deg. Four model simulations are analyzed. In the first, the model is forced with sea surface temperature (SST) from the recent historical climatology. The other three have different idealized climate change simulations, namely (1) a uniform increase of SST by 2 deg., (2) doubling of the CO2 concentration and (3) a combination of the two. These simulations were performed as part of the US Climate Variability and Predictability Program Hurricane Working Group. Diagnostics of standard measures of TC activity are computed from the recent historical climatological SST simulation and compared with the same measures computed from observations. The changes in TC activity in the three idealized climate change simulations, by comparison with that in the historical climatological SST simulation, are also described. Similar to previous results in the literature, the changes in TC frequency in the simulation with a doubling CO2 and an increase in SST are approximately the linear sum of the TC frequency in the other two simulations. However, in contrast with previous results, in these simulations the effects of CO2 and SST on TC frequency oppose each other. Large-scale environmental variables associated with TC activity are then analyzed for the present and future simulations. Model biases in the large-scale fields are identified through a comparison with ERA-Interim reanalysis. Changes in the environmental fields in the future climate simulations are shown and their association with changes in TC activity discussed.

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.

The adjustment of parameterized gravity waves associated with model convection and finer vertical resolution has made possible the generation of the quasi-biennial oscillation (QBO) in two Goddard Institute for Space Studies (GISS) models, GISS Middle Atmosphere Global Climate Model III and a climate/middle atmosphere version of Model E2. Both extend from the surface to 0.002 hPa, with 2deg × 2.5deg resolution and 102 layers. Many realistic features of the QBO are simulated, including magnitude and variability of its period and amplitude. The period itself is affected by the magnitude of parameterized convective gravity wave momentum fluxes and interactive ozone (which also affects the QBO amplitude and variability), among other forcings. Although varying sea surface temperatures affect the parameterized momentum fluxes, neither aspect is responsible for the modeled variation in QBO period. Both the parameterized and resolved waves act to produce the respective easterly and westerly wind descent, although their effect is offset in altitude at each level. The modeled and observed QBO influences on tracers in the stratosphere, such as ozone, methane, and water vapor are also discussed. Due to the link between the gravity wave parameterization and the models' convection, and the dependence on the ozone field, the models may also be used to investigate how the QBO may vary with climate change.

Simulations of the preindustrial and doubled CO2 climates are made with the GISS Global Climate Middle Atmosphere Model 3 using two different estimates of the absolute solar irradiance value: a higher value measured by solar radiometers in the 1990s and a lower value measured recently by the Solar Radiation and Climate Experiment. Each of the model simulations is adjusted to achieve global energy balance; without this adjustment the difference in irradiance produces a global temperature change of 0.48C, comparable to the cooling estimated for the Maunder Minimum. The results indicate that by altering cloud cover the model properly compensates for the different absolute solar irradiance values on a global level when simulating both preindustrial and doubled CO2 climates. On a regional level, the preindustrial climate simulations and the patterns of change with doubled CO2 concentrations are again remarkably similar, but there are some differences. Using a higher absolute solar irradiance value and the requisite cloud cover affects the model's depictions of high-latitude surface air temperature, sea level pressure, and stratospheric ozone, as well as tropical precipitation. In the climate change experiments it leads to an underestimation of North Atlantic warming, reduced precipitation in the tropical western Pacific, and smaller total ozone growth at high northern latitudes. Although significant, these differences are typically modest compared with the magnitude of the regional changes expected for doubled greenhouse gas concentrations. Nevertheless, the model simulations demonstrate that achieving the highest possible fidelity when simulating regional climate change requires that climate models use as input the most accurate (lower) solar irradiance value.

The climate system of the Earth is endowed with a moderately strong greenhouse effect that is characterized by non-condensing greenhouse gases (GHGs) that provide the core radiative forcing. Of these, the most important is atmospheric CO2. There is a strong feedback contribution to the greenhouse effect by water vapor and clouds that is unique in the solar system, exceeding the core radiative forcing due to the non-condensing GHGs by a factor of three. The significance of the non-condensing GHGs is that once they have been injected into the atmosphere, they remain there virtually indefinitely because they do not condense and precipitate from the atmosphere, their chemical removal time ranging from decades to millennia. Water vapor and clouds have only a short lifespan, with their distribution determined by the locally prevailing meteorological conditions, subject to Clausius-Clapeyron constraint. Although solar irradiance is the ultimate energy source that powers the terrestrial greenhouse effect, there has been no discernible long-term trend in solar irradiance since precise monitoring began in the late 1970s. This leaves atmospheric CO2 as the effective control knob driving the current global warming trend. Over geological time scales, volcanoes are the principal source of atmospheric CO2, and the weathering of rocks is the principal sink, with the biosphere participating as both a source and a sink. The problem at hand is that human industrial activity is causing atmospheric CO2, to increase by 2 ppm per year, whereas the interglacial rate has been 0.005 ppm per year. This is a geologically unprecedented rate to turn the CO2 climate control knob. This is causing the global warming that threatens the global environment.

The variability of Atlantic tropical cyclones (TCs) associated with El Nino-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. CLIVAR Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multi-model ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions in the TC activities during eastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region as in observations. The difference between the models and observations is likely due to the bias of vertical wind shear in response to the shift of tropical heating associated with CP El Nino, as well as the model bias in the mean circulation.