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|Deremble, B., Dewar, W. K., & Chassignet, E. P. (2016). Vorticity dynamics near sharp topographic features. J Mar Res, 74(6), 249–276.|
Ford, K. M. (2008). Uncertainty in Scatterometer-Derived Vorticity. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A more versatile and robust technique is developed for determining area averaged surface vorticity based on vector winds from the SeaWinds scatterometer on the QuikSCAT satellite. This improved technique is discussed in detail and compared to two previous studies by Sharp et al. (2002) and Gierach et al. (2007) that focused on early development of tropical systems. The error characteristics of the technique are examined in detail. Specifically, three independent sources of error are explored: random observational error, truncation error and representation error. Observational errors are due to random errors in the wind observations, and determined as a worst-case estimate as a function of averaging spatial scale. The observational uncertainty in vorticity averaged for a roughly circular shape with a 100 km diameter, expressed as one standard deviation, is approximately 0.5 x 10 -5 s-1 for the methodology described herein. Truncation error is associated with the assumption of linear changes between wind vectors. For accurate results, it must be estimated on a case-by-case basis. An attempt is made to determine a lower bound of truncation errors through the use of composites of tropical disturbances. This lower bound is calculated as 10-7 s-1 for the composites, which is relatively small compared to the tropical disturbance detection threshold set at 5 x 10-5 s-1, used in an earlier study. However, in more realistic conditions, uncertainty related to truncation errors is much larger than observational uncertainty. The third type of error discussed is due to the size of the area being averaged. If the wind vectors associated with a vorticity maximum are inside the perimeter of this area (away from the edges), it will be missed. This type of error is analogous to over-smoothing. Tropical and sub-tropical low pressure systems from three months of QuikSCAT observations are used to examine this error. This error results in a bias of approximately 1.5 x 10-5 s-1 for area averaged vorticity calculated on a 100 km scale compared to vorticity calculated on a 25 km scale. The discussion of these errors will benefit future projects of this nature as well as future satellite missions.
|Gierach, M. M., Bourassa, M. A., Cunningham, P., O'Brien, J. J., & Reasor, P. D. (2007). Vorticity-Based Detection of Tropical Cyclogenesis. J. Appl. Meteor. Climatol., 46(8), 1214–1229.|
Hite, M. M. (2006). Vorticity-Based Detection of Tropical Cyclogenesis. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Ocean wind vectors from the SeaWinds scatterometer on QuikSCAT and GOES imagery are used to develop an objective technique that can detect and monitor tropical disturbances associated with the early stages of tropical cyclogenesis in the Atlantic basin. The technique is based on identification of surface vorticity and wind speed signatures that exceed certain threshold magnitudes, with vorticity averaged over an appropriate spatial scale. The threshold values applied herein are determined from the precursors of 15 tropical cyclones during the 1999-2004 Atlantic hurricane seasons using research-quality QuikSCAT data. Tropical disturbances are found for these cases within a range of 19 hours to 101 hours before classification as tropical cyclones by the National Hurricane Center (NHC). The 15 cases are further subdivided based upon their origination source (i.e., easterly wave, upper-level cut-off low, stagnant frontal zone, etc). Primary focus centers on the cases associated with tropical waves, since these waves account for approximately 63% of all Atlantic tropical cyclones. The detection technique illustrates the ability to track these tropical disturbances from near the coast of Africa. Analysis of the pre-tropical cyclone (TC) tracks for these cases depict stages, related to wind speed and precipitation, in the evolution of an easterly wave to tropical cyclone.
|Holbach, H. M., & Bourassa, M. A. (2014). The Effects of Gap-Wind-Induced Vorticity, the Monsoon Trough, and the ITCZ on East Pacific Tropical Cyclogenesis. Mon. Wea. Rev., 142(3), 1312–1325.|
|Holbach, H. M., & Bourassa, M. A. (2017). Platform and Across-Swath Comparison of Vorticity Spectra From QuikSCAT, ASCAT-A, OSCAT, and ASCAT-B Scatterometers. IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing, 10(5), 2205–2213.|
|Kanamitsu, M., Yulaeva, E., Li, H., & Hong, S. - Y. (2013). Catalina Eddy as revealed by the historical downscaling of reanalysis. Asia-Pacific J Atmos Sci, 49(4), 467–481.|
Maue, R. N. (2004). Evolution of Frontal Structure Associated with Extratropical Transitioning Hurricanes. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Many tropical cyclones move poleward, encounter vertical shear associated with the midlatitude circulation, and undergo a process called extratropical transition (ET). One of the many factors affecting the post-transition extratropical storm in terms of reintensification, frontal structure, and overall evolution is the upper-level flow pattern. Schultz et al. (1998) categorized extratropical cyclones according to two of the many possible cyclone paradigms in terms of the upper-level trough configuration: The Norwegian cyclone model (Bjerknes and Solberg 1922) associated with high-amplitude diffluent trough flow and the Shapiro-Keyser cyclone lifecycle (1990) with low-amplitude confluent troughs. Broadly speaking, the former category is associated with a strong, meridionally oriented cold front with a weak warm front while the latter lifecycle usually entails a prominent, zonally oriented warm front. However, as will be shown, simple antipode lifecycle definitions fail to capture hybrid or cross-lifecycle evolution of transitioned tropical cyclones. To exemplify the importance upper-level features such as jet streaks and troughs, a potential vorticity framework is coupled with vector frontogenesis functions to diagnose the interaction between the poleward transitioning cyclone and the midlatitude circulation. Particular focus is concentrated upon the evolution and strength of frontal fracture from both a PV and frontogenesis viewpoint. The final outcome of extratropical transition is highly variable depending on characteristics of the tropical cyclone, SSTs, and environmental factors such as strength of vertical shear. Here, three storms (Irene 1999, Fabian 2003, and Kate 2003) typify the inherent variability of one such ET outcome, warm seclusion. Very strong winds are often observed in excess of 50 ms-1 along the southwestern flank of the storm down the bent-back warm front. The low-level wind field kinematics are examined using vector frontogenesis functions and QuikSCAT winds. A complex empirical orthogonal function (CEOF) technique is adapted to temporally interpolate ECMWF model fields (T, MSLP) to overpass times of the scatterometer, an improvement over simple linear interpolation. Overall, the above diagnosis is used to support a hypothesis concerning the prevalence of hurricane-force winds surrounding secluded systems.
Keywords: Extratropical Transition, Frontogenesis, Fronts, Quikscat, Cyclone Lifecycles, Warm Seclusion, Frontal Fracture, Potential Vorticity, Hurricane Kate, Hurricane Irene, Hurricane Fabian, Tropical Cyclones
|Moeller, L. (2011). Low-Frequency Variations of the Sea Breeze in Florida. Master's thesis, Florida State University, Tallahassee, FL.|
|Peng, M. S., Maue, R. N., Reynolds, C. A., & Langland, R. H. (2007). Hurricanes Ivan, Jeanne, Karl (2004) and mid-latitude trough interactions. Meteorol. Atmos. Phys., 97(1-4), 221–237.|