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FSU ETD Template Florida State University Libraries Electronic Theses, Treatises and Dissertations The Graduate School 2017 Predictability and Dynamics of the Genoa Low: Case Study and Operational Considerations Michael Snyder Follow this and additional works at the DigiNole: FSU's Digital Repository. For more information, please contact [email protected] FLORIDA STATE UNIVERSITY COLLEGE OF ARTS AND SCIENCES PREDICTABILITY AND DYNAMICS OF THE GENOA LOW: CASE STUDY AND OPERATIONAL CONSIDERATIONS By MICHAEL SNYDER A Thesis submitted to the Department of Earth, Ocean, & Atmospheric Science in partial fulfillment of the requirements for the degree of Master of Science 2017 Michael Snyder defended this thesis on March 30, 2017. The members of the supervisory committee were: Jeffrey Chagnon Professor Directing Thesis Robert Hart Committee Member Vasu Misra Committee Member The Graduate School has verified and approved the above-named committee members, and certifies that the thesis has been approved in accordance with university requirements. ii TABLE OF CONTENTS List of Figures ................................................................................................................................ iv Abstract .......................................................................................................................................... vi 1. INTRODUCTION ......................................................................................................................1 2. METHODOLOGY ......................................................................................................................9 3. RESULTS AND DISCUSSION ...............................................................................................16 3.1. PREDICTABILITY OF THE GENOA LOW ...................................................................16 3.2. GENOA LOW FORMATION AND THE MISTRAL WIND ..........................................25 4. CONCLUSIONS .......................................................................................................................34 References ......................................................................................................................................38 Biographical Sketch .......................................................................................................................40 iii LIST OF FIGURES 1 Figure 1. Manual analysis of surface potential temperature (C) (dashed) and MSLP (mb) with surface observations of sky cover, wind (kts), temperature (C), and dew point temperature (C) from 12Z 15 Nov 2007 (Figure 4 from McTaggart-Cowan, et al. 2009) ............................2 2 Figure 2. Terrain map of southwestern Europe and the Mediterranean Sea. .............................3 3 Figure 3. Time versus the natural logarithm of pressure in the center of the Genoa low broken into three developmental stages (Figure 12 from Buzzi and Tibaldi, 1977) .............................4 4 Figure 4. The spatial domain of COSMO-LEPS as indicated by the green box. The contours indicate the elevation in meters that was simulated in the numerical simulations (COSMO, 2008). .......................................................................................................................................10 5 Figure 5. A schematic of the ensemble method to assessing the likelihood of a weather event and the spread of numerical solutions which arise from small perturbations in the initial conditions. The ensemble spread is analogous to the forecast uncertainty of the specific weather phenomenon shaded in grey. The ensemble spread then can be projected to a set probabilities that the particular phenomenon will occur represented by the map on the right. (Figure 3, Bauer et al. 2015) ...................................................................................................11 6 Figure 6. Example MSLP (mb) field (top) and 10 meter speed (kts) (bottom) demonstrating the locations of the subdomains (boxed regions) used to isolate the Genoa low (top) and the mistral winds (bottom)... ..........................................................................................................14 7 Figure 7. Surface analysis (Crown copyright ©) for case 1 (top) and case 2 (bottom) (UKMET) .................................................................................................................................17 8 Figure 8. Synoptic evolution for Case 1 (top) and case 2 (bot). 500mb geopotential height contours with 850mb isotachs (kts) (top) and shaded MSLP (mb) (bot) for each case. ..........18 9 Figure 9. MSLP (mb) (shaded) for each ensemble initializations of case 1 at 1, 2, 3, and 4 days prior to cyclogenesis with time fixed at the cyclogenesis time. Individual ensemble members are numbered. Missing members were not archived. ...............................................20 10 Figure 10. Spaghetti plots of the minimum MSLP (mb) through the forecast period for case 1 ensemble simulations with event lead times of 1-4 days. The red line is the mean of all ensemble members, and the black dashed line marks the time of cyclogenesis. .....................22 11 Figure 11. Maps of the time evolution of the ensemble mean MSLP (mb) for the 3 day forecast in case 1 with time progressing from the 69-hour forecast time to the 81 hour forecast time from left to right. ................................................................................................23 iv 12 Figure 12. Shaded is the ensemble variance in MSLP (mb) for case 1 at the cyclogenesis time for each ensemble forecast lead time. Note: The scale for the 1 and 2 day lead times ranges from 0 to 4, and the scale for the 3 and 4 day lead times ranges from 0 to 12. Values below .5 mb are white. ............................................................................................................................24 13 Figure 13 Ensemble standard deviation in minimum MSLP (mb) (top) and 10m maximum mistral wind (bot) for simulations initialized 1-4 days prior to Genoa low development. The black dashed line marks the time of cyclogenesis. ..................................................................26 14 Figure 14. Maps of MSLP (mb) (left) and 10 m wind speed (kts) (right) for case 1 for all ensemble members. This ensemble run was initialized 3 days prior to the event. Time is fixed at the cyclogenesis time... ........................................................................................................28 15 Figure 15. Ensemble spaghetti plots of minimum MSLP (mb) (top) and maximum 10m mistral winds (kts) (bot) for case 1 (top) and case 2 (bot) for lead times at 3 days (left) and 4 days (right). The solid black line is the ensemble mean for each EPS run, and the vertical dashed black line marks the start of cyclogenesis. The green lines are the ensemble members chosen because they produced deep Genoa lows. The red lines are ensemble members chosen because they did not generate a Genoa low. The same 4 ensemble members in each case are highlighted in the same colors in the spaghetti plots of the maximum mistral wind field. .....29 16 Figure 16. Correlation of minimum MSLP and maximum mistral winds at a 3 day event lead time for case 1 (top) and at a 4 day event lead time for case 2 (bot). The correlation plots on the left side are at the time of cyclogenesis, and the plots on the right are correlations between the minimum MSLP and the time-lagged maximum wind speed. The time lad is 6 hours for case 1 and 12 hours for case 2. The line is the least squares regression line, and the correlation coefficient is labeled on each plot. ........................................................................31 17 Figure17. Time evolution of vorticity (shaded) ( 10 ^(-4) )(s^(-1)) and MSLP (contours) with 10m wind (vectors) from case 2, ensemble member 9. Time proceeds from left to right at 3-hourly segments. ...............................................................................................................33 v ABSTRACT The rapid development and sub-synoptic scale nature of the Genoa low in the Mediterranean Sea poses a forecasting challenge for United States Air Force (USAF). The Genoa low is a high-impact event for several Department of Defense (DOD) locations located in southern Europe, especially in the Po River Valley of northern Italy. This study evaluates the predictability and dynamics of the Genoa low extending to a 4-day event lead time as is required by the mission protocols at the affected locations. Two Genoa low case studies are analyzed: 16 Feb 2015 (case 1), and 13 July 2016 (case 2), using the COnsortium for Small-scale MOdeling Limited-area Ensemble Prediction System (COSMO-LEPS). Ensemble prediction systems provide a range of possible forecast outcomes given the uncertainty in initial conditions, boundary conditions, as well as model physics. As such, ensembles are used to assess and analyze the predictability of the Genoa low. The analysis demonstrates several key findings concerning the Genoa low. The Genoa low is only weakly predictable at a lead time of 4 days. It is shown that only a small fraction of ensemble members (approximately 25%) met the Genoa low verification thresholds at this lead time. Ensemble spaghetti plots and maps of the ensemble variance show that the possibility of low formation at longer lead times is most effectively visualized using maps of ensemble variance. Traditional postage-stamp plots and minimum MSLP plots contain too much noise and variability to permit a forecaster
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