scholarly journals Predicting Atlantic Tropical Cyclone Seasonal Activity in April

2009 ◽  
Vol 24 (2) ◽  
pp. 436-455 ◽  
Author(s):  
Elinor Keith ◽  
Lian Xie
Keyword(s):  
Tropical Cyclone ◽  
Gulf Of Mexico ◽  
Confidence Level ◽  
Complex Problem ◽  
Empirical Orthogonal Functions ◽  
Orthogonal Functions ◽  
Random Chance ◽  
Major Hurricane ◽  
Hurricane Activity ◽  
The U.S

Abstract Seasonal hurricane forecasts are continuing to develop skill, although they are still subject to large uncertainties. This study uses a new methodology of cross-correlating variables against empirical orthogonal functions (EOFs) of the hurricane track density function (HTDF) to select predictors. These predictors are used in a regression model for forecasting seasonal named storm, hurricane, and major hurricane activity in the entire Atlantic, the Caribbean Sea, and the Gulf of Mexico. In addition, a scheme for predicting landfalling tropical systems along the U.S. Gulf of Mexico, southeastern, and northeastern coastlines is developed, but predicting landfalling storms adds an extra layer of uncertainty to an already complex problem, and on the whole these predictions do not perform as well. The model performs well in the basin-wide predictions over the entire Atlantic and Caribbean, with the predictions showing an improvement over climatology and random chance at a 95% confidence level. Over the Gulf of Mexico, only named storms showed that level of predictability. Predicting landfalls proves more difficult, and only the prediction of named storms along the U.S. southeastern and Gulf coasts shows an improvement over random chance at the 95% confidence level. Tropical cyclone activity along the U.S. northeastern coast is found to be unpredictable in this model; with the rarity of events, the model is unstable.

Hurricane “Amanda”: Rediscovery of a Forgotten U.S. Civil War Florida Hurricane

2013 ◽  
Vol 94 (11) ◽  
pp. 1735-1742 ◽  
Author(s):  
M. Chenoweth ◽  
C. J. Mock
Keyword(s):  
United States ◽  
Civil War ◽  
Tropical Cyclone ◽  
Natural Disaster ◽  
Tropical Cyclones ◽  
Tropical Cyclone Activity ◽  
Cyclone Activity ◽  
Major Hurricane ◽  
The U.S ◽  
States History

Among the most unusual and unexpected hurricanes in United States history is the only hurricane to make landfall in the month of May. This recently rediscovered storm that struck northwest Florida on 28 May 1863 created a natural disaster in the area that became lost to history because it was embedded in a much larger and important manmade event—in this case, the U.S. Civil War. The authors document the arrival of this storm both historically and meteorologically and anachronistically name it “Hurricane Amanda” in honor of the Union ship driven ashore by the hurricane. The hurricane revealed deficiencies and strengths in combat readiness by both sides. Meteorologically, the storm nearly achieved major hurricane status at landfall and its absence from modern databases of tropical cyclone activity is a useful reminder to users of important gaps in our knowledge of tropical cyclones even in the best-sampled storm basins.

scholarly journals Moisture Pathways into the U.S. Intermountain West Associated with Heavy Winter Precipitation Events*

2015 ◽  
Vol 16 (3) ◽  
pp. 1184-1206 ◽  
Author(s):  
Michael A. Alexander ◽  
James D. Scott ◽  
Dustin Swales ◽  
Mimi Hughes ◽  
Kelly Mahoney ◽  
...  
Keyword(s):  
Sierra Nevada ◽  
Heavy Precipitation ◽  
Empirical Orthogonal Functions ◽  
Water Vapor Transport ◽  
Intermountain West ◽  
Orthogonal Functions ◽  
Back Trajectories ◽  
Synoptic Conditions ◽  
The U.S ◽  
Precipitation Events

Abstract Two methods were used to identify the paths of moisture transport that reach the U.S. Intermountain West (IMW) during heavy precipitation events in winter. In the first, the top 150 precipitation events at stations located within six regions in the IMW were identified, and then back trajectories were initiated at 6-h intervals on those days at the four Climate Forecast System Reanalysis grid points nearest the stations. The second method identified the leading patterns of integrated water vapor transport (IVT) using the three leading empirical orthogonal functions of IVT over land that were first normalized by the local standard deviation. The top 1% of the associated 6-hourly time series was used to construct composites of IVT, atmospheric circulation, and precipitation. The results from both methods indicate that moisture originating from the Pacific that leads to extreme precipitation in the IMW during winter takes distinct pathways and is influenced by gaps in the Cascades (Oregon–Washington), the Sierra Nevada (California), and Peninsular Ranges (from Southern California through Baja California). The moisture transported along these routes appears to be the primary source for heavy precipitation for the mountain ranges in the IMW. The synoptic conditions associated with the dominant IVT patterns include a trough–ridge couplet at 500 hPa, with the trough located northwest of the ridge where the associated circulation funnels moisture from the west-southwest through the mountain gaps and into the IMW.

Empirical Methods in Short-Term Climate Prediction

2006 ◽  
Author(s):  
Huug van den Dool
Keyword(s):  
Climate Prediction ◽  
Empirical Orthogonal Functions ◽  
Data Sets ◽  
Seasonal Forecasts ◽  
Short Term ◽  
Orthogonal Functions ◽  
Ocean Atmosphere Interaction ◽  
Global Coverage ◽  
Atmosphere Interaction ◽  
Global Data

This clear and accessible text describes the methods underlying short-term climate prediction at time scales of 2 weeks to a year. Although a difficult range to forecast accurately, there have been several important advances in the last ten years, most notably in understanding ocean-atmosphere interaction (El Nino for example), the release of global coverage data sets, and in prediction methods themselves. With an emphasis on the empirical approach, the text covers in detail empirical wave propagation, teleconnections, empirical orthogonal functions, and constructed analogue. It also provides a detailed description of nearly all methods used operationally in long-lead seasonal forecasts, with new examples and illustrations. The challenges of making a real time forecast are discussed, including protocol, format, and perceptions about users. Based where possible on global data sets, illustrations are not limited to the Northern Hemisphere, but include several examples from the Southern Hemisphere.

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