Storm track

Abstract: A methodology is presented for the real-time automated identification, tracking, and short-term forecasting of thunderstorms based on volume-scan weather radar data. The emphasis is on the concepts upon which the methodology is based. A “storm” is defined as a contiguous region exceeding thresholds for reflectivity and size. Storms defined in this way are identified at discrete time intervals. An optimization scheme is employed to match the storms at one time with those at the following time, with some geometric logic to deal with mergers and splits. The short-term forecast of both position and size is based on a weighted linear fit to the storm track history data. The performance of the detection and forecast were evaluated for the summer 1991 season, and the results are presented.

Abstract: The aim of this paper is to explore the use of both an Eulerian and system-centered method of storm track diagnosis applied to a wide range of meteorological fields at multiple levels to provide a range of perspectives on the Northern Hemisphere winter transient motions and to give new insight into the storm track organization and behavior. The data used are primarily from the European Centre for Medium-Range Weather Forecasts reanalyses project extended with operational analyses to the period 1979–2000. This is supplemented by data from the National Centers for Environmental Prediction and Goddard Earth Observing System 1 reanalyses. The range of fields explored include the usual mean sea level pressure and the lower- and upper-tropospheric height, meridional wind, vorticity, and temperature, as well as the potential vorticity (PV) on a 330-K isentropic surface (PV330) and potential temperature on a PV = 2 PVU surface (θPV2). As well as reporting the primary analysis based on feature tracking, t...

Abstract: Bridging the traditional gap between the spatio-temporal scales of weather and climate is a significant challenge facing the atmospheric community. In particular, progress in both medium-range and seasonal-to-interannual climate prediction relies on our understanding of recurrent weather patterns and the identification of specific causes responsible for their favoured occurrence, persistence or transition. Within this framework, I here present evidence that the main climate intra-seasonal oscillation in the tropics-the Madden-Julian Oscillation (MJO)-controls part of the distribution and sequences of the four daily weather regimes defined over the North Atlantic-European region in winter. North Atlantic Oscillation (NAO) regimes are the most affected, allowing for medium-range predictability of their phase far exceeding the limit of around one week that is usually quoted. The tropical-extratropical lagged relationship is asymmetrical. Positive NAO events mostly respond to a mid-latitude low-frequency wave train initiated by the MJO in the western-central tropical Pacific and propagating eastwards. Precursors for negative NAO events are found in the eastern tropical Pacific-western Atlantic, leading to changes along the North Atlantic storm track. Wave-breaking diagnostics tend to support the MJO preconditioning and the role of transient eddies in setting the phase of the NAO. I present a simple statistical model to quantitatively assess the potential predictability of the daily NAO index or the sign of the NAO regimes when they occur. Forecasts are successful in approximately 70 per cent of the cases based on the knowledge of the previous approximately 12-day MJO phase used as a predictor. This promising skill could be of importance considering the tight link between weather regimes and both mean conditions and the chances of extreme events occurring over Europe. These findings are useful for further stressing the need to better simulate and forecast the tropical coupled ocean-atmosphere dynamics, which is a source of medium-to-long range predictability and is the Achilles' heel of the current seamless prediction suites.

Abstract: Summer climate in the North Atlantic‐European sector possesses a principal pattern of year-to-year variability that is the parallel to the well-known North Atlantic Oscillation in winter. This summer North Atlantic Oscillation (SNAO) is defined here as the first empirical orthogonal function (EOF) of observed summertime extratropical North Atlantic pressure at mean sea level. It is shown to be characterized by a more northerly location and smaller spatial scale than its winter counterpart. The SNAO is also detected by cluster analysis and has a near-equivalent barotropic structure on daily and monthly time scales. Although of lesser amplitude than its wintertime counterpart, the SNAO exerts a strong influence on northern European rainfall, temperature, and cloudiness through changes in the position of the North Atlantic storm track. It is, therefore, of key importance in generating summer climate extremes, including flooding, drought, and heat