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Ashton Robinson Cook
,
Lance M. Leslie
,
David B. Parsons
, and
Joseph T. Schaefer

Abstract

In recent years, the potential of seasonal outlooks for tornadoes has attracted the attention of researchers. Previous studies on this topic have focused mainly on the influence of global circulation patterns [e.g., El Niño–Southern Oscillation (ENSO), North Atlantic Oscillation, or Pacific decadal oscillation] on spring tornadoes. However, these studies have yielded conflicting results of the roles of these climate drivers on tornado intensity and frequency. The present study seeks to establish linkages between ENSO and tornado outbreaks over the United States during winter and early spring. These linkages are established in two ways: 1) statistically, by relating raw counts of tornadoes in outbreaks (defined as six or more tornadoes in a 24-h period in the United States east of the Rocky Mountains), and their destructive potential, to sea surface temperature anomalies observed in the Niño-3.4 region, and 2) qualitatively, by relating ENSO to shifts in synoptic-scale atmospheric phenomena that contribute to tornado outbreaks. The latter approach is critical for interpreting the statistical relationships, thereby avoiding the deficiencies in a few of the previous studies that did not provide physical explanations relating ENSO to shifts in tornado activity. The results suggest that shifts in tornado occurrence are clearly related to ENSO. In particular, La Niña conditions consistently foster more frequent and intense tornado activity in comparison with El Niño, particularly at higher latitudes. Furthermore, it is found that tornado activity changes are tied not only to the location and intensity of the subtropical jet during individual outbreaks but also to the positions of surface cyclones, low-level jet streams, and instability axes.

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Philippe Drobinski
,
Fatima Karbou
,
Peter Bauer
,
Philippe Cocquerez
,
Christophe Lavaysse
,
Terry Hock
,
David Parsons
,
Florence Rabier
,
Jean-Luc Redelsperger
, and
Stéphanie Vénel

Abstract

During the international African Monsoon Multidisciplinary Analysis (AMMA) project, stratospheric balloons carrying gondolas called driftsondes capable of dropping meteorological sondes were deployed over West Africa and the tropical Atlantic Ocean. The goals of the deployment were to test the technology and to study the African easterly waves, which are often the forerunners of hurricanes. Between 29 August and 22 September 2006, 124 sondes were dropped over the seven easterly waves that moved across Africa into the Atlantic between about 10° and 20°N, where almost no in situ vertical information exists. Conditions included waves that developed into Tropical Storm Florence and Hurricanes Gordon and Helene. In this study, a selection of numerical weather prediction model outputs has been compared with the dropsondes to assess the effect of some developments in data assimilation on the quality of analyses and forecasts. By comparing two different versions of the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) model of Météo-France with the dropsondes, first the benefits of the last data assimilation updates are quantified. Then comparisons are carried out using the ARPEGE model and the Integrated Forecast System (IFS) model of the European Centre for Medium-Range Weather Forecasts. It is shown that the two models represent very well the vertical structure of temperature and humidity over both land and sea, and particularly within the Saharan air layer, which displays humidity below 5%–10%. Conversely, the models are less able to represent the vertical structure of the meridional wind. This problem seems to be common to ARPEGE and IFS, and its understanding still requires further investigations.

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