Trajectory analysis using a weather prediction model is performed for five cases to interpret the formation of enhanced bands of vertically integrated water vapor (IWV) in the central and eastern Pacific that are frequently seen in satellite images from the Special Sensor Microwave Imager. The connection of these enhanced bands with poleward water vapor transport from the Tropics is also examined. It is shown that the leading end of the enhanced IWV bands (defined as the most eastward and poleward end) is the manifestation of moisture convergence in the warm conveyor belt associated with extratropical cyclones, while the bands away from the leading end result mainly from moisture convergence along the trailing cold fronts. There is evidence that some enhanced IWV bands may be associated with a direct poleward transport of tropical moisture along the IWV bands from the Tropics all the way to the extratropics. The trajectory analysis, together with the seasonal mean sea level pressure analysis, indicates that a favorable condition for the occurrence of a direct, along-IWV band transport of tropical (defined as south of 23.5°N) moisture to the U.S. West Coast in the eastern Pacific is a weakened subtropical ridge in the central Pacific with an enhanced southwesterly low-level flow. The authors hypothesize that the direct poleward transport of tropical moisture within an enhanced IWV band in the eastern Pacific is most possible in the neutral El Niño–Southern Oscillation (ENSO) phase and is least possible in the El Niño phase.

In this study, a coupled atmosphere-ocean wave modeling system is used to simulate air-sea interaction under high wind conditions. This coupled modeling system is made of three well-tested model components: The Pennsylvania State University-National Center for Atmospheric Research regional atmospheric Mesoscale Model, the University of Colorado version of the Princeton Ocean Model, and the ocean surface gravity wave model developed by the Wave Model Development and Implementation Group. The ocean model is initialized using a 9-month spinup simulation forced by 6-hourly wind stresses and with assimilation of satellite sea surface temperature (SST) and altimetric data into the model. The wave model is initialized using a zero wave state. The scenario in which the study is carried out is the intensification of a simulated hurricane passing over the Gulf of Mexico. The focus of the study is to evaluate the impact of sea spray, mixing in the upper ocean, warm-core oceanic eddies shed by the Gulf Loop Current, and the sea surface wave field on hurricane development, especially the intensity. The results from the experiments with and without sea spray show that the inclusion of sea spray evaporation can significantly increase hurricane intensity in a coupled air-sea model when the part of the spray that evaporates is only a small fraction of the total spray mass. In this case the heat required for spray evaporation comes from the ocean. When the fraction of sea spray that evaporates increases, so that the evaporation extracts heat from the atmosphere and cools the lower atmospheric boundary layer, the impact of sea spray evaporation on increasing hurricane intensity diminishes. It is shown that the development of the simulated hurricane is dependent on the location and size of a warm-core anticyclonic eddy shed by the Loop Current. The eddy affects the timing, rate, and duration of hurricane intensification. This dependence occurs in part due to changes in the translation speed of the hurricane, with a slower-moving hurricane being more sensitive to a warm-core eddy. The feedback from the SST change in the wake of the simulated hurricane is negative so that a reduction of SST results in a weaker-simulated hurricane than that produced when SST is held unchanged during the simulation. The degree of surface cooling is strongly dependent on the initial oceanic mixed layer (OML) depth. It is also found in this study that in order to obtain a realistic thermodynamic state of the upper ocean and not distort the evolution of the OML structure during data assimilation, care must be taken in the data assimilation procedure so as not to interfere with the turbulent dynamics of the OML. Compared with the sensitivity to the initial OML depth and the location and intensity of the warm eddy associated with the loop current, the model is found to be less sensitive to the wave-age-dependent roughness length.

The primary goal of the Second Wind Forecast Improvement Project (WFIP2) is to advance the state-of-the-art of wind energy forecasting in complex terrain. To achieve this goal, a comprehensive 18-month field measurement campaign was conducted in the region of the Columbia River basin. The observations were used to diagnose and quantify systematic forecast errors in the operational High-Resolution Rapid Refresh (HRRR) model during weather events of particular concern to wind energy forecasting. Examples of such events are cold pools, gap flows, thermal troughs/marine pushes, mountain waves, and topographic wakes. WFIP2 model development has focused on the boundary layer and surface-layer schemes, cloud–radiation interaction, the representation of drag associated with subgrid-scale topography, and the representation of wind farms in the HRRR. Additionally, refinements to numerical methods have helped to improve some of the common forecast error modes, especially the high wind speed biases associated with early erosion of mountain–valley cold pools. This study describes the model development and testing undertaken during WFIP2 and demonstrates forecast improvements. Specifically, WFIP2 found that mean absolute errors in rotor-layer wind speed forecasts could be reduced by 5%–20% in winter by improving the turbulent mixing lengths, horizontal diffusion, and gravity wave drag. The model improvements made in WFIP2 are also shown to be applicable to regions outside of complex terrain. Ongoing and future challenges in model development will also be discussed.

Improved weather forecasts help system operators know with greater accuracy how much variable renewable energy can be generated and how much other electric power they will need.