Starting from the assumption that the atmosphere is the primary source of variability internal to the midlatitude atmosphere-ocean system on intraseasonal to interannual timescales, the authors construct a simple stochastically forced, one-dimensional, linear, coupled energy balance model. The coupled system is then dissected into partially coupled and uncoupled systems in order to quantify the effects of coupling. The simplicity of the model allows for analytic evaluation of many quantities of interest, including power spectra, total variance, lag covariance between atmosphere and ocean, and surface flux spectra. The model predicts that coupling between the atmosphere and ocean in the midlatitudes will enhance the variance in both media and will decrease the energy flux between the atmosphere and the ocean. The model also demonstrates that specification of historical midlatitude sea surface temperature anomalies as a boundary condition for an atmospheric model will not generally lead to a correct simulation of low-frequency atmospheric thermal variance. This model provides a simple conceptual framework for understanding the basic aspects of midlatitude coupled variability. Given the simplicity of the model, it agrees well with numerical simulations using a two-level atmospheric general circulation model coupled to a slab mixed layer ocean. The simple model results are also qualitatively consistent with the results obtained in several other studies in which investigators coupled realistic atmospheric general circulation models to ocean models of varying complexity. This suggests that the experimental design of an atmospheric model coupled to a mixed layer ocean model would provide a reasonable null hypothesis against which to test for the presence of distinctive decadal variability. * Joint Institute for the Study of the Atmosphere and Ocean Contribution Number 382.

The sensitivity of the global atmospheric response to sea surface temperature (SST) anomalies throughout the tropical Indian and Pacific Ocean basins is investigated using the NCEP MRF9 general circulation model (GCM). Model responses in January are first determined for a uniform array of 42 localized SST anomaly patches over the domain. Results from the individual forcing experiments are then linearly combined using a statistically based smoothing procedure to produce sensitivity maps for many target quantities of interest, including the geopotential height response over the Pacific-North American (PNA) region and regional precipitation responses over North America, South America, Africa, Australia, and Indonesia.Perhaps the most striking result from this analysis is that many important targets for seasonal forecasting, including the PNA response, are most sensitive to SST anomalies in the Niño-4 region (5ЊN-5ЊS, 150ЊW-160ЊE) of the central tropical Pacific, with lesser and sometimes opposite sensitivities to SST anomalies in the Niño-3 region (5ЊN-5ЊS, 90Њ-150ЊW) of the eastern tropical Pacific. However, certain important targets, such as Indonesian rainfall, are most sensitive to SST anomalies outside both the Niño-4 and -3 regions.These results are also relevant in assessing atmospheric sensitivity to changes in tropical SSTs on decadal to centennial scales associated with natural as well as anthropogenic forcing. In this context it is interesting to note the surprising result that warm SST anomalies in one-third of the Indo-Pacific domain lead to a decrease of global mean precipitation.

Population growth and a changing climate will tax the future reliability of the Colorado River water supply. Using a heuristic model, we assess the annual risk to the Colorado River water supply for 2008–2057. Projected demand growth superimposed upon historical climate variability results in only a small probability of annual reservoir depletion through 2057. In contrast, a scenario of 20% reduction in the annual Colorado River flow due to climate change by 2057 results in a near tenfold increase in the probability of annual reservoir depletion by 2057. However, our analysis suggests that flexibility in current management practices could mitigate some of the increased risk due to climate change–induced reductions in flows.

The authors examine the sensitivity of the Battisti coupled atmosphere-ocean model-considered as a forecast model for the El Niño-Southern Oscillation (ENSO)-to perturbations in the sea surface temperature (SST) field applied at the beginning of a model integration. The spatial structures of the fastest growing SST perturbations are determined by singular vector analysis of an approximation to the propagator for the linearized system. Perturbation growth about the following four reference trajectories is considered: (i) the annual cycle, (ii) a freely evolving model ENSO cycle with an annual cycle in the basic state, (iii) the annual mean basic state, and (iv) a freely evolving model ENSO cycle with an annual mean basic state. Singular vectors with optimal growth over periods of 3, 6, and 9 months are computed.The magnitude of maximum perturbation growth is highly dependent on both the phase of the seasonal cycle and the phase of the ENSO cycle at which the perturbation is applied and on the duration over which perturbations are allowed to evolve. However, the spatial structure of the optimal perturbation is remarkably insensitive to these factors. The structure of the optimal perturbation consists of an east-west dipole spanning the entire tropical Pacific basin superimposed on a north-south dipole in the eastern tropical Pacific. A simple physical interpretation for the optimal pattern is provided. In most cases investigated, there is only one structure that exhibits growth.Maximum perturbation growth takes place for integrations that include the period June-August, and the minimum growth for integrations that include the period January-April. Maxima in potential growth also occur for forecasts of ENSO onset and decay, while minima occur for forecasts initialized during the beginning of a warm event, after the transition from a warm to a cold event, and continuing through the cold event. The physical processes responsible for the large variation in the amplitude of the optimal perturbation growth are identified. The implications of these results for the predictability of short-term climate in the tropical Pacific are discussed.

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Suppose you are a city planner, regional water manager, or wildlife conservation specialist who is asked to include the potential impacts of climate variability and change in your risk management and planning efforts. What climate information would you use? The choice is often regional or local climate projections downscaled from global climate models (GCMs; also known as general circulation models) to include detail at spatial and temporal scales that align with those of the decision problem. A few years ago this information was hard to come by. Now there is Web‐based access to a proliferation of high‐resolution climate projections derived with differing downscaling methods.

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