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Jingyu Wang, Xiquan Dong, Aaron Kennedy, Brooke Hagenhoff, and Baike Xi

the Southern Great Plains (SGP) of the United States, this was offset by a nocturnal, negative bias, whereas biases were predominantly positive over the Northern Great Plains (NGP). The segregation of model performance by meteorological regimes has been commonly used in the climate modeling community where ample data allow for separation of model performance by prevailing conditions or synoptic patterns. In turn, this can provide insight into model behavior (e.g., forcing mechanisms responsible

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Andrew C. Winters, Daniel Keyser, and Lance F. Bosart

),(d) 1200 UTC 28 Jan 1991. As for the sample cases shown in Figs. 2 and 3 , the weighted PCs at all analysis times during 1979–2014 excluding the summer months are plotted on the NPJ phase diagram in order to classify each analysis time into one of the four NPJ regimes, or to identify analysis times during which the NPJ lies within the unit circle ( Fig. 4 ). For this classification scheme, the analysis times are classified based on, first, whether the position of the NPJ within the NPJ phase diagram

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Andrew C. Winters, Lance F. Bosart, and Daniel Keyser

. Nevertheless, given that the NPJ phase diagram is constructed from the two leading modes of 250-hPa zonal wind variability over the North Pacific, plotting the weighted PCs in the NPJ phase diagram and tracking their evolution over time encompasses many important aspects of the NPJ evolution. Fig . 5. Schematic illustrating the NPJ phase diagram and the classification scheme used to determine the NPJ regime prior to ETE initiation. The values plotted on the axes of the NPJ phase diagram correspond to the

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John T. Abatzoglou, Renaud Barbero, and Nicholas J. Nauslar

://nimbus.cos.uidaho.edu/JFSP/pages/publications.html ). REFERENCES Burrows, L. D. , 1987 : Development of forecast guidance for Santa Ana conditions . Natl. Wea. Dig. , 12 ( 1 ), 4 – 11 . Conil, S. , and Hall A. , 2006 : Local regimes of atmospheric variability: A case study of Southern California . J. Climate , 19 , 4308 – 4325 . Durran, D. R. , 1990 : Atmospheric Processes over Complex Terrain. Meteor. Monogr., No. 45, Amer. Meteor. Soc., 394 pp. Edinger, J. G. , Helvey R. A. , and Baumhefner D. , 1964 : Surface wind patterns in

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V. E. Kousky and R. W. Higgins

as “El Niño conditions” or “La Niña conditions” are used. 4. ENSO alert classification system The El Niño and La Niña phenomena, which are extremes in the ENSO cycle, are the most important sources for the predictable portion of interannual climate variability. Since the early 1980s, the CPC has routinely documented the state of the global climate system, with a focus on climate conditions in the tropical Pacific. As mentioned earlier, CPC established the monthly Climate Diagnostics Bulletin

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Philip N. Schumacher, Gregory Frosig, Jason L. Selzler, and Robert A. Weisman

Achtor, T. H. , and Horn L. , 1986 : Spring season Colorado cyclones. Part I: Use of composites to relate upper and lower tropospheric wind fields. J. Climate Appl. Meteor. , 25 , 732 – 743 . 10.1175/1520-0450(1986)025<0732:SSCCPI>2.0.CO;2 Barnes, S. L. , 1964 : A technique for maximizing details in numerical weather map analysis. J. Appl. Meteor. , 3 , 396 – 409 . 10.1175/1520-0450(1964)003<0396:ATFMDI>2.0.CO;2 Barnes, S. L. , 1973 : Mesoscale objective analysis using weighted

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Andrew W. Colman, Erika J. Palin, Michael G. Sanderson, Robert T. Harrison, and Ian M. Leggett

height forecasting system for the northern North Sea that predicts wave heights 8 months ahead is described. The forecasting system is based on the sign and magnitude of the winter North Atlantic Oscillation (NAO) index, which are forecast using sea surface temperatures (SSTs) in the North Atlantic for the preceding month of May. The skill of current climate models in predicting the NAO on seasonal time scales is low ( van Oldenborgh 2005 ; Arribas et al. 2010 ). Climate models that include a

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Gregory J. Connor and Frank Woodcock

flow type; and Reap (1994) for lightning activity forecasts objectively stratified by pattern classification of low-level flow]. The technique of synoptic regime stratification is conceptually appealing as this methodology simulates the thought processes of operational meteorologists when faced with a forecasting problem. The procedure is employed to establish the essence of a forecasting problem. Operational forecasters initially think in the broadscale to provide a context for a forecast

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Piero A. Chessa and François Lalaurette

. , 1999 : Mesoscale precipitation and temperature regimes in Sardinia (Italy) and the related synoptic circulations. Theor. Appl. Climatol , 63 , 195 – 222 . 10.1007/s007040050103 Eckert, P. , Cattani D. , and Ambhul J. , 1996 : Classification of ensemble forecasts by means of an artificial neural network. Meteor. Appl , 3 , 169 – 178 . Illari, L. , and Marshall C. J. , 1983 : On the interpretation of eddy fluxes during a blocking episode. J. Atmos. Sci , 40 , 2232 – 2242 . 10

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Frédéric Atger

forecasts onto a 8 × 8 chessboard. Other conditional classifications have been based on the existence of large-scale weather regimes, more likely to be predictable in the late medium range (Santurette et al. 1998, manuscript submitted to Quart. J. Roy. Meteor. Soc. ). The conditional classification methods have the advantage of resulting in a limited number of configurations. Therefore, meteorological interpretation may be coupled with objective postprocessing based on the distribution of ensemble

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