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A high-resolution regional atmospheric model is used to simulate present-day western North Pacific (WNP) tropical cyclone (TC) activity and to investigate the projected changes for the late twenty-first century. Compared to observations, the model can realistically simulate many basic features of the WNP TC activity climatology, such as the TC genesis location, track, and lifetime. A number of spatial and temporal features of observed TC interannual variability are captured, although observed variations in basinwide TC number are not. A relatively well-simulated feature is the contrast of years when the Asian summer monsoon trough extends eastward (retreats westward), more (fewer) TCs form within the southeastern quadrant of the WNP, and the corresponding TC activity is above (below) normal over most parts of the WNP east of 125°E. Future projections with the Coupled Model Intercomparison Project phase 3 (CMIP3) A1B scenario show a weak tendency for decreases in the number of WNP TCs, and for increases in the more intense TCs; these simulated changes are significant at the 80% level. The present-day simulation of intensity is limited to storms of intensity less than about 55 m s−1. There is also a weak (80% significance level) tendency for projected WNP TC activity to shift poleward under global warming. A regional-scale feature is a projected increase of the TC activity north of Taiwan, which would imply an increase in TCs making landfall in north China, the Korean Peninsula, and parts of Japan. However, given the weak statistical significance found for the simulated changes, an assessment of the robustness of such regional-scale projections will require further study.

A new methodology for assessing the impact of surface heat fluxes on precipitation is applied to data from the North American Regional Reanalysis (NARR) and to output from the Geophysical Fluid Dynamics Laboratory’s Atmospheric Model 2.1 (AM2.1). The method assesses the sensitivity of afternoon convective rainfall frequency and intensity to the late-morning partitioning of latent and sensible heating, quantified in terms of evaporative fraction (EF). Over North America, both NARR and AM2.1 indicate sensitivity of convective rainfall triggering to EF but no appreciable influence of EF on convective rainfall amounts. Functional relationships between the triggering feedback strength (TFS) metric and mean EF demonstrate the occurrence of stronger coupling for mean EF in the range of 0.6 to 0.8. To leading order, AM2.1 exhibits spatial distributions and seasonality of the EF impact on triggering resembling those seen in NARR: rainfall probability increases with higher EF over the eastern United States and Mexico and peaks in Northern Hemisphere summer. Over those regions, the impact of EF variability on afternoon rainfall triggering in summer can explain up to 50% of seasonal rainfall variability. However, the AM2.1 metrics also exhibit some features not present in NARR, for example, strong coupling extending northwestward from the central Great Plains into Canada. Sources of disagreement may include model hydroclimatic biases that affect the mean patterns and variability of surface flux partitioning, with EF variability typically much lower in NARR. Finally, the authors also discuss the consistency of their results with other assessments of land–precipitation coupling obtained from different methodologies.

Abstract-NERSC has partnered with 20 representative application teams to evaluate performance on the Xeon-Phi Knights Landing architecture and develop an application-optimization strategy for the greater NERSC workload on the recently installed Cori system. In this article, we present early case studies and summarized results from a subset of the 20 applications highlighting the impact of important architecture differences between the Xeon-Phi and traditional Xeon processors. We summarize the status of the applications and describe the greater optimization strategy that has formed.

Although land-atmosphere coupling is thought to play a role in shaping the mean climate and its variability, it remains difficult to quantify precisely. The present study aims to isolate relationships between early morning surface turbulent fluxes partitioning [i.e., evaporative fraction (EF)] and subsequent afternoon convective precipitation frequency and intensity. A general approach involving statistical relationships among input and output variables, known as sensitivity analysis (SA), is used to develop a reduced complexity metamodel of the linkage between EF and convective precipitation. Two additional quantities characterizing the early morning convective environment, convective triggering potential (CTP) and low-level humidity (HIlow) deficit, are included. The SA approach is applied to the North American Regional Reanalysis (NARR) for June-August (JJA) conditions over the entire continental United States, Mexico, and Central America domain. Five land-atmosphere coupling regimes are objectively characterized based on CTP, HIlow, and EF. Two western regimes are largely atmospherically controlled, with a positive link to CTP and a negative link to HIlow. The other three regimes occupy Mexico and the eastern half of the domain and show positive links to EF and negative links to HIlow, suggesting that both surface fluxes and atmospheric humidity play a role in the triggering of rainfall in these regions. The regimes associated with high mean EF also tend to have high sensitivity of rainfall frequency to variations in EF. While these results may be sensitive to the choice of dataset, the approach can be applied across observational, reanalysis, and model datasets and thus represents a potentially powerful tool for intercomparison and validation as well as for characterizing land-atmosphere interaction regimes.

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A model to forecast the motion of oil spilled on the surface of water was established by combining separate models for the motion of oil, the motion of water, and the motion of air. The model for the motion of oil is based upon the hydrodynamic equations as they apply to oil on water. This model requires information at both the lower and upper boundaries of oil. At the oil lower boundary, the information is obtained from a model for the motion of water. This model is formulated by combining Ekman dynamics and continuity for the upper mixed layer of the sea. At the oil upper boundary, a model for the motion of air provides the required information. This model is based upon an analysis of output obtained from one of the National Weather Service's multi-level atmospheric models. A number of case studies demonstrate the features of the separate models and the composite oil spill model.