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Katherine E. Lukens, Ernesto Hugo Berbery, and Kevin I. Hodges

Abstract

Northern Hemisphere winter storm tracks and their relation to winter weather are investigated using NCEP CFSR data. Storm tracks are described by isentropic PV maxima within a Lagrangian framework; these correspond well with those described in previous studies. The current diagnostics focus on strong-storm tracks, which comprise storms that achieve a maximum PV exceeding the mean value by one standard deviation. Large increases in diabatic heating related to deep convection occur where the storm tracks are most intense. The cyclogenesis pattern shows that strong storms generally develop on the upstream sectors of the tracks. Intensification happens toward the eastern North Pacific and all across the North Atlantic Ocean, where enhanced storm-track-related weather is found. In this study, the relation of storm tracks to near-surface winds and precipitation is evaluated. The largest increases in storm-track-related winds are found where strong storms tend to develop and intensify, while storm precipitation is enhanced in areas where the storm tracks have their highest intensity. Strong storms represent about 16% of all storms but contribute 30%–50% of the storm precipitation in the storm-track regions. Both strong-storm-related winds and precipitation are prone to cause storm-related losses in the eastern U.S. and North American coasts. Over the oceans, maritime operations are expected to be most vulnerable to damage offshore of the U.S. coasts. Despite making up a small fraction of all storms, the strong-storm tracks have a significant imprint on winter weather in North America potentially leading to structural and economic loss.

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Carolina S. Vera, Paula K. Vigliarolo, and Ernesto Hugo Berbery

Abstract

The most active winter synoptic-scale wave patterns over South America are identified using an extended empirical orthogonal function (EEOF) technique and are physically diagnosed using composite methods. Results show that the leading modes of short timescale variability propagate along two main paths: over the subtropical jet latitudes (∼30°S) and over the subpolar jet latitudes (∼60°S). This research focuses on the subtropical mode and its evolution over South America.

The observed structure of the systems associated with the subtropical mode resembles that of midlatitude baroclinic waves. Both cyclonic and anticyclonic perturbations display significant modifications in their three-dimensional structure as they evolve over extratropical and subtropical South America. While the upper-level perturbations are mostly unaffected when moving eastward, the lower-level perturbations advance following the shape of the Andes Mountains and exhibit an abrupt equatorward migration at the lee side of the mountains. As a result of such detachment, smaller eddy heat fluxes are observed in the vicinity of the orography and consequently a weaker eddy baroclinic growth is observed. Once the upper-level system is on the lee side, the perturbations acquire a more typical baroclinic wave structure and low-level intensification of the system occurs. The latter is largest around 1000 km east of the orography, where enhanced moisture transports from tropical latitudes along the eastern portion of the low-level cyclone favor precipitation occurrence over southeastern South America. Those precipitation processes seem to provide a diabatic source of energy that further contributes to the strengthening of the low-level cyclone. In addition, an intensification of the cyclone once over the ocean was found in 60% of the situations considered, which is consistent with previous research suggesting an additional source of moisture and heat flux due to the warm waters of the Brazil Current.

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Michael S. Fox-Rabinovitz, Ernesto Hugo Berbery, Lawrence L. Takacs, and Ravi C. Govindaraju

Abstract

Multiyear (1987–97) limited ensemble integrations using a stretched-grid GCM, previously developed and experimented with by the authors, are employed for U.S. regional climate simulations. The ensemble members (six in total) are produced at two different regional resolutions: three members with 60-km and the other three members with 10-km regional resolution. The use of these two finer and coarser regional resolution ensemble members allows one to examine the impact of resolution on the overall quality of the simulated regional fields. For the multiyear ensemble simulations, an efficient regional downscaling to realistic mesoscales has been obtained. The ensemble means of the midtroposphere prognostic variables (height and meridional wind) show an overall good resemblance to the global reanalysis, especially for summer. Low-level features like the warm season Great Plains low-level jet are well represented in the simulations. During winter the 100-km simulations develop a southward wind east of the Rockies that is present neither in the reanalyses nor in the 60-km simulations. The analysis of the annual mean precipitation and its variance reveals that the ensemble simulations reproduce many of the observed features of a high-resolution rain gauge dataset analyzed on a 0.5° × 0.5° grid. Signal-to-noise ratios are larger than 1.5 s over a major part of the United States, especially over the Midwest and also over the mountainous regions like the Rockies and the Appalachians, suggesting that the orographic forcing is contributing to a larger signal. The ratios are smaller toward the eastern and western U.S. coastlines. This result could be attributed, at least in part, to limits in the representation of the land–sea contrasts.

For comparison purposes, an additional simulation has been performed using a global uniform 2° × 2.5° grid with the same number of global grid points as those of the above stretched grids. The stretched-grid GCM ensemble means show, overall, a better regional depiction of features than those of the uniform-grid GCM.

The results of the study show that even using limited ensemble integrations with a state-of-the-art stretched-grid GCM is beneficial for reducing the uncertainty of the multiyear regional climate simulation, especially when using finer 60-km regional resolution.

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Omar V. Müller, Ernesto Hugo Berbery, Domingo Alcaraz-Segura, and Michael B. Ek

Abstract

This work discusses the land surface–atmosphere interactions during the severe drought of 2008 in southern South America, which was among the most severe in the last 50 years in terms of both intensity and extent. Once precipitation returned to normal values, it took about two months for the soil moisture content and vegetation to recover. The land surface effects were examined by contrasting long-term simulations using a consistent set of satellite-derived annually varying land surface biophysical properties against simulations using the conventional land-cover types in the Weather Research and Forecasting Model–Noah land surface model (WRF–Noah). The new land-cover dataset is based on ecosystem functional properties that capture changes in vegetation status due to climate anomalies and land-use changes.

The results show that the use of realistic information of vegetation states enhances the model performance, reducing the precipitation biases over the drought region and over areas of excessive precipitation. The precipitation bias reductions are attributed to the corresponding changes in greenness fraction, leaf area index, stomatal resistance, and surface roughness. The temperature simulation shows a generalized increase, which is attributable to a lower vegetation greenness and a doubling of the stomatal resistance that reduces the evapotranspiration rate. The increase of temperature has a beneficial effect toward the eastern part of the domain with a notable reduction of the bias, but not over the central region where the bias is increased. The overall results suggest that an improved representation of the surface processes may contribute to improving the predictive skill of the model system.

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Omar V. Müller, Ernesto Hugo Berbery, Domingo Alcaraz-Segura, and Michael B. Ek
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Wayne Higgins, Dave Ahijevych, Jorge Amador, Ana Barros, E. Hugo Berbery, Ernesto Caetano, Richard Carbone, Paul Ciesielski, Rob Cifelli, Miguel Cortez-Vazquez, Art Douglas, Michael Douglas, Gus Emmanuel, Chris Fairall, David Gochis, David Gutzler, Thomas Jackson, Richard Johnson, Clark King, Timothy Lang, Myong-In Lee, Dennis Lettenmaier, Rene Lobato, Victor Magaña, Jose Meiten, Kingtse Mo, Stephen Nesbitt, Francisco Ocampo-Torres, Erik Pytlak, Peter Rogers, Steven Rutledge, Jae Schemm, Siegfried Schubert, Allen White, Christopher Williams, Andrew Wood, Robert Zamora, and Chidong Zhang

The North American Monsoon Experiment (NAME) is an internationally coordinated process study aimed at determining the sources and limits of predictability of warm-season precipitation over North America. The scientific objectives of NAME are to promote a better understanding and more realistic simulation of warm-season convective processes in complex terrain, intraseasonal variability of the monsoon, and the response of the warm-season atmospheric circulation and precipitation patterns to slowly varying, potentially predictable surface boundary conditions.

During the summer of 2004, the NAME community implemented an international (United States, Mexico, Central America), multiagency (NOAA, NASA, NSF, USDA) field experiment called NAME 2004. This article presents early results from the NAME 2004 campaign and describes how the NAME modeling community will leverage the NAME 2004 data to accelerate improvements in warm-season precipitation forecasts for North America.

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