Using NOGAPS Singular Vectors to Diagnose Large-Scale Influences on Tropical Cyclogenesis

2013 ◽  
Author(s):  
Sharanya J. Majumdar ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds ◽  
James D. Doyle ◽  
Chun-Chieh Wu ◽  
...  
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Singular Vectors

Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis

2011 ◽  
Author(s):  
Sharanya J. Majumdar ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds ◽  
James D. Doyle ◽  
Chun-Chieh Wu ◽  
...  
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Singular Vectors

Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis

2012 ◽  
Author(s):  
Sharanya J. Majumdar ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds ◽  
James D. Doyle ◽  
Chun-Chieh Wu ◽  
...  
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Singular Vectors

Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis

2012 ◽  
Author(s):  
Sharanya J. Majumdar ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds ◽  
James D. Doyle ◽  
Chun-Chieh Wu ◽  
...  
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Singular Vectors

Using NOGAPS Singular Vectors To Diagnose Large-scale Influences On Tropical Cyclogenesis

2008 ◽  
Author(s):  
Sharanya J. Majumdar ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds ◽  
Chun-Chieh Wu
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Singular Vectors

Using NOGAPS Singular Vectors to Diagnose Large-scale Influences on Tropical Cyclogenesis

2010 ◽  
Author(s):  
Sharanya J. Majumdar ◽  
Melinda S. Peng ◽  
Carolyn A. Reynolds ◽  
James D. Doyle ◽  
Chun-Chieh Wu ◽  
...  
Keyword(s):  
Large Scale ◽  
Tropical Cyclogenesis ◽  
Singular Vectors

The Role of Equatorial Rossby Waves in Tropical Cyclogenesis. Part I: Idealized Numerical Simulations in an Initially Quiescent Background Environment

2010 ◽  
Vol 138 (4) ◽  
pp. 1368-1382 ◽  
Author(s):  
Jeffrey S. Gall ◽  
William M. Frank ◽  
Matthew C. Wheeler
Keyword(s):  
Tropical Cyclone ◽  
Large Scale ◽  
Phase Speed ◽  
Tropical Cyclogenesis ◽  
Initial Amplitude ◽  
Low Level ◽  
Wave Simulation ◽  
Horizontal Momentum ◽  
Good Agreement

Abstract This two-part series of papers examines the role of equatorial Rossby (ER) waves in tropical cyclone (TC) genesis. To do this, a unique initialization procedure is utilized to insert n = 1 ER waves into a numerical model that is able to faithfully produce TCs. In this first paper, experiments are carried out under the idealized condition of an initially quiescent background environment. Experiments are performed with varying initial wave amplitudes and with and without diabatic effects. This is done to both investigate how the properties of the simulated ER waves compare to the properties of observed ER waves and explore the role of the initial perturbation strength of the ER wave on genesis. In the dry, frictionless ER wave simulation the phase speed is slightly slower than the phase speed predicted from linear theory. Large-scale ascent develops in the region of low-level poleward flow, which is in good agreement with the theoretical structure of an n = 1 ER wave. The structures and phase speeds of the simulated full-physics ER waves are in good agreement with recent observational studies of ER waves that utilize wavenumber–frequency filtering techniques. Convection occurs primarily in the eastern half of the cyclonic gyre, as do the most favorable conditions for TC genesis. This region features sufficient midlevel moisture, anomalously strong low-level cyclonic vorticity, enhanced convection, and minimal vertical shear. Tropical cyclogenesis occurs only in the largest initial-amplitude ER wave simulation. The formation of the initial tropical disturbance that ultimately develops into a tropical cyclone is shown to be sensitive to the nonlinear horizontal momentum advection terms. When the largest initial-amplitude simulation is rerun with the nonlinear horizontal momentum advection terms turned off, tropical cyclogenesis does not occur, but the convectively coupled ER wave retains the properties of the ER wave observed in the smaller initial-amplitude simulations. It is shown that this isolated wave-only genesis process only occurs for strong ER waves in which the nonlinear advection is large. Part II will look at the more realistic case of ER wave–related genesis in which a sufficiently intense ER wave interacts with favorable large-scale flow features.

scholarly journals Tropical Cyclone Genesis Factors in Simulations of the Last Glacial Maximum

2012 ◽  
Vol 25 (12) ◽  
pp. 4348-4365 ◽  
Author(s):  
Robert L. Korty ◽  
Suzana J. Camargo ◽  
Joseph Galewsky
Keyword(s):  
Tropical Cyclone ◽  
Last Glacial Maximum ◽  
Large Scale ◽  
Glacial Maximum ◽  
Tropical Cyclogenesis ◽  
Tropical Cyclone Genesis ◽  
Surface Cooling ◽  
Last Glacial ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract Large-scale environmental factors that favor tropical cyclogenesis are calculated and examined in simulations of the Last Glacial Maximum (LGM) from the Paleoclimate Modelling Intercomparison Project Phase 2 (PMIP2). Despite universally colder conditions at the LGM, values of tropical cyclone potential intensity, which both serves as an upper bound on thermodynamically achievable intensity and indicates regions supportive of the deep convection required, are broadly similar in magnitude to those in preindustrial era control simulation. Some regions, including large areas of the central and western North Pacific, feature higher potential intensities at the LGM than they do in the control runs, while other regions including much of the Atlantic and Indian Oceans are lower. Changes in potential intensity are strongly correlated with the degree of surface cooling during the LGM. Additionally, two thermodynamic parameters—one that measures midtropospheric entropy deficits relevant for tropical cyclogenesis and another related to the time required for genesis—are broadly more favorable in the LGM simulation than in the preindustrial era control. A genesis potential index yields higher values for the LGM in much of the western Pacific, a feature common to nearly all of the individual models examined.

Four Years of Tropical ERA-40 Vorticity Maxima Tracks. Part II: Differences between Developing and Nondeveloping Disturbances

2009 ◽  
Vol 137 (8) ◽  
pp. 2576-2591 ◽  
Author(s):  
Brandon Kerns ◽  
Edward Zipser
Keyword(s):  
Large Scale ◽  
Deep Convection ◽  
Vertical Wind Shear ◽  
Skill Score ◽  
Relative Vorticity ◽  
Prediction Skill ◽  
Tropical Cyclogenesis ◽  
Linear Discriminant ◽  
Predictive Skill ◽  
Heidke Skill Score

Abstract Using a subset of the relative vorticity maxima (VM) tracks described in Part I, large-scale environmental fields, cold cloud area, and rainfall area are used to discriminate between developing and nondeveloping tropical disturbances in the eastern North Pacific (EPAC) and Atlantic Oceans. By using a minimum cold cloud coverage requirement, the nondeveloping VM are limited to disturbances with enhanced low-level relative vorticity and widespread deep convection. Linear discriminant analysis is used to determine the overall discrimination and the relative importance of each predictor for each basin separately. It is important to distinguish the two basins because, for many predictors, the differences between the basins are greater than the differences between developing and nondeveloping VM in each basin. Using the parametric forecast method, there is greater discrimination and prediction skill in the EPAC than in the Atlantic. There are also significant differences between the two basins in terms of the degree of discrimination provided by each of the predictors. Surprisingly, the mean vertical wind shear magnitude is greater for EPAC developing VM than for EPAC nondeveloping VM. Incorporating the satellite-derived predictors marginally improves the potential forecast skill in the EPAC but not in the Atlantic. The prediction skill (Heidke skill score) of tropical cyclogenesis in the Atlantic is similar to what has been obtained in previous studies using cloud cluster tracks. There is greater predictive skill in the EPAC.

scholarly journals Ensemble-Based Error and Predictability Metrics Associated with Tropical Cyclogenesis. Part I: Basinwide Perspective

2014 ◽  
Vol 142 (8) ◽  
pp. 2879-2898 ◽  
Author(s):  
William A. Komaromi ◽  
Sharanya J. Majumdar
Keyword(s):  
Standard Deviation ◽  
Wind Shear ◽  
Large Scale ◽  
Predictive Power ◽  
Forecast Error ◽  
Ensemble Prediction ◽  
Tropical Cyclogenesis ◽  
Small Scale ◽  
Ensemble Prediction System ◽  
Error Standard Deviation

Abstract Several metrics are employed to evaluate predictive skill and attempt to quantify predictability using the ECMWF Ensemble Prediction System during the 2010 Atlantic hurricane season, with an emphasis on large-scale variables relevant to tropical cyclogenesis. These metrics include the following: 1) growth and saturation of error, 2) errors versus climatology, 3) predicted forecast error standard deviation, and 4) predictive power. Overall, variables that are more directly related to large-scale, slowly varying phenomena are found to be much more predictable than variables that are inherently related to small-scale convective processes, regardless of the metric. For example, 850–200-hPa wind shear and 200-hPa velocity potential are found to be predictable beyond one week, while 200-hPa divergence and 850-hPa relative vorticity are only predictable to about one day. Similarly, area-averaged quantities such as circulation are much more predictable than nonaveraged quantities such as vorticity. Significant day-to-day and month-to-month variability of predictability for a given metric also exists, likely due to the flow regime. For wind shear, more amplified flow regimes are associated with lower predictive power (and thereby lower predictability) than less amplified regimes. Relative humidity is found to be less predictable in the early and late season when there exists greater uncertainty of the timing and location of dry air. Last, the ensemble demonstrates the potential to predict error standard deviation of variables averaged in 10° × 10° boxes, in that forecasts with greater ensemble standard deviation are on average associated with greater mean error. However, the ensemble tends to be underdispersive.

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