Guimond, S. R. (2007).
A diagnostic study of the effects of trough interactions on tropical cyclone QPF. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: A composite study is presented analyzing the influence of upper-tropospheric troughs on the evolution of precipitation in twelve Atlantic tropical cyclones (TCs) between the years 2000 � 2005. The TRMM Multi-Satellite Precipitation Analysis (TMPA) is used to examine the enhancement of precipitation within a 24 h window centered on trough interaction (TI) time in a shear-vector relative coordinate system. Eddy angular momentum flux convergence (EFC) computed from European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses is employed to objectively determine the initiation of a TI while adding insight, along with vertical wind shear, into the intensification of TC vortices. The relative roles of the dynamics (EFC and vertical wind shear) and thermodynamics (moist static energy potential) in TIs are outlined in the context of precipitation enhancement that provides quantitative insight into the “good trough”/“bad trough” paradigm. The largest precipitation rates and enhancements are found in the down-shear left quadrant of the storm, consistent with previous studies of convective asymmetries. Maximum mean enhancement values of 1.4 mm/h are found at the 200 km radius in the down-shear left quadrant. Results indicate that the largest precipitation enhancements occur with “medium” TIs; comprised of EFC values between 17 � 22 (m/s)/day and vertical wind shear Sensitivity tests on the upper vertical wind shear boundary reveal the importance of using the tropopause for wind shear computations when a TC enters mid-latitude regions. Changes in radial mean precipitation ranging from 29 � 40 % across all storm quadrants are found when using the tropopause as the upper boundary on the shear vector. Tests on the lower boundary using QuikSCAT ocean surface wind vectors expose large sensitivities on the precipitation ranging from 42 � 60 % indicating that the standard level of 850 hPa, outside of the boundary layer in most storms, is more physically reliable for computing vertical wind shear. These results should help to improve TC quantitative precipitation forecasting (QPF) as operational forecasters routinely rely on crude statistical methods and rules of thumb for forecasting TC precipitation.
Guimond, S. (2010).
Tropical Cyclone Inner-Core Dynamics: A Latent Heat Retrieval and Its Effects on Intensity and Structure Change; and the Impacts of Effective Diffusion on the Axisymmetrization Process. Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: Despite the fact that latent heating in cloud systems drives many atmospheric circulations, including tropical cyclones, little is known of its magnitude and structure due in large part to inadequate observations. In this work, a reasonably high-resolution (2 km), four-dimensional airborne Doppler radar retrieval of the latent heat of condensation is presented for rapidly intensifying Hurricane Guillermo (1997). Several advancements in the retrieval algorithm are shown including: (1) analyzing the scheme within the dynamically consistent framework of a numerical model, (2) identifying algorithm sensitivities through the use of ancillary data sources and (3) developing a precipitation budget storage term parameterization. The determination of the saturation state is shown to be an important part of the algorithm for updrafts of ~ 5 m s-1 or less. The uncertainties in the magnitude of the retrieved heating are dominated by errors in the vertical velocity. Using a combination of error propagation and Monte Carlo uncertainty techniques, biases were found to be small, and randomly distributed errors in the heating magnitude were ~16 % for updrafts greater than 5 m s-1 and ~156 % for updrafts of 1 m s- 1. The impact of the retrievals is assessed by inserting the heating into realistic numerical simulations at 2 km resolution and comparing the generated wind structure to the Doppler radar observations of Guillermo. Results show that using the latent heat retrievals outperforms a simulation that relies on a state-of-the-art microphysics scheme (Reisner and Jeffery 2009), in terms of wind speed root-mean-square errors, explained variance and eye/eyewall structure. The incorrect transport of water vapor (a function of the sub-grid model and the numerical approximations to advection) and the restrictions on the magnitude of heat release that ensure the present model's stability are suggested as sources of error in the simulation without the retrievals. Motivated by the latent heat retrievals, the dynamics of vortex axisymmetrization from the perspective of thermal anomalies is investigated using an idealized, non-linear atmospheric model (HIGRAD). Attempts at reproducing the results of previous work (Nolan and Grasso 2003; NG03) revealed a discrepancy with the impacts of purely asymmetric forcing. While NG03 found that purely asymmetric heating led to a negligible, largely negative impact on the vortex intensification, in the present study the impacts of asymmetries are found to have an important, largely positive role. Absolute angular momentum budgets revealed that the essential difference between the present work and that of NG03 was the existence of a significant, axisymmetric secondary circulation in the basic-state vortex used in the HIGRAD simulations. This secondary circulation was larger than that present in NG03's simulations. The spin-up of the vortex caused by the asymmetric thermal anomalies was dominated by the axisymmetric fluxes of angular momentum at all times, indicating fundamentally different evolution of asymmetries in the presence of radial flow. Radial momentum budgets were performed to elucidate the mechanisms responsible for the formation of the physically significant secondary circulation. Results show that explicit (sub-grid) diffusion in the model was producing a gradient wind imbalance, which drives a radial inflow and associated secondary circulation in an attempt to re-gain balance. In addition, the production of vorticity anomalies from the asymmetric heating was found to be sensitive to the eddy diffusivity, with large differences between HIGRAD and the widely used WRF model for the exact same value of this uncertain parameter.
Hughes, P. J. (2006).
North Atlantic Decadal Variability of Ocean Surface Fluxes. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: The spatial and temporal variability of the surface turbulent heat fluxes over the North Atlantic is examined using the new objectively produced FSU3 monthly mean 1°x1° gridded wind and surface flux product for 1978-2003. The FSU3 product is constructed from in situ ship and buoy observations via a variational technique. A cost function based on weighted constraints is minimized in the process of determining the surface fluxes. The analysis focuses on a low frequency (basin wide) mode of variability where the latent and sensible heat flux anomalies transition from mainly positive to negative values around 1998. It is hypothesized that the longer time scale variability is linked to changes in the large scale circulation patterns possibly associated with the Atlantic Multidecadal Oscillation (AMO; Schlesinger and Ramankutty 1994, Kerr 2000). The changes in the surface heat fluxes are forced by fluctuations in the mean wind speed. Zonal averages show a clear dissimilarity between the turbulent heat fluxes and wind speed for 1982-1997 and 1998-2003 over the region extending from the equator to roughly 40°N. Larger values are associated with the earlier time period, coinciding with a cool phase of the AMO. The separation between the two time periods is much less evident for the humidity and air/sea temperature differences. The largest differences in the latent heat fluxes, between the two time periods, occur over the tropical, Gulf Stream, and higher latitude regions of the North Atlantic, with magnitudes exceeding 15 Wm-2. The largest sensible heat flux differences are limited to areas along the New England coast and poleward of 40°N.
Jones, B. (2004).
Influence of Panamanian Wind Jets on the Southeast Intertropical Convergence Zone. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Gridded QuikSCAT data has been used to show that a strong confluence zone of the Southeast Pacific Intertropical Convergence Zone (SITCZ) existed in 2000 � 2002 during boreal spring, and the Panama wind jet contributes to its variability. Time series analysis of winds off the Gulf of Panama and convergence advection into the Southern Hemisphere (from 80W to 95W) show these winds kept the SE Trades out of the Northern Hemisphere and created a confluent zone in the Southern Hemisphere. A monthly averaged SITCZ is maintained by the deceleration of the SE Trades that flow from warm water toward the equatorial cold tongue, creating a speed convergent zone south of the equator. Images of wind trajectories show zonally orientated SE Trade winds that were deflected from a divergent zone parallel to the coast of South America converge with more meridional Trades over warm waters. Panamanian winds crossed into the Southern Hemisphere to contribute to this convergence. It is hypothesized that this confluent zone can be intensified by the Panamanian winds. In 2002, the SITCZ confluent zone occurred with more intense Panamanian gap flow than the previous two years. Cross equatorial SE Trades wrapped anti-cyclonically around a divergent pocket in the Northern Hemisphere and became southward winds, which allowed the Panamanian winds to enter the Southern Hemisphere and intensify the SITCZ. Variability in the Panamanian winds makes a substantial contribution to the evolution of the SITCZ.
Kara, A. B. (2003).
A Fine Resolution Hybrid Coordinate Ocean Model (HYCOM) for the Black Sea with a New Solar Radiation Penetration Scheme. Ph.D. thesis, Florida State University, Tallahassee, FL.
Keeling, T. B. (2009).
Modified JMA ENSO Index and Its Improvements to ENSO Classification. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: El Nino-Southern Oscillation (ENSO) is a widely known phenomenon that affects many areas including the southeast United States. Over the southeast U.S. the Japan Meteorological Agency (JMA) ENSO index was modified to establish better classifications. In order to properly understand the effects of ENSO on this location a new approach was needed. Spatial resolution was improved by utilization of the PRISM dataset. PRISM provided monthly precipitation and temperature data over the contiguous US at 4 km resolution. Temporal resolution was improved by disregarding the traditional JMA definition of an ENSO year. The new definition requires six consecutive months of 0.5°C anomalies or larger to be listed as an ENSO event. By utilization of this definition, the ENSO index was modified to a monthly index from a yearly index. Many ENSO events begin in the summer months and end before the preceding September, therefore, an adoption of a monthly index is justified. Although several of the effects vary widely over the domain, there are a few prevalent patterns of ENSO effects. During warm phase, from November-April, wet conditions are seen in the coastal areas. July and August are both dry. From fall to spring, Florida and the Atlantic Coast are basically dry, however; the Mississippi River Valley doesn't appear wet as previous studies have indicted. Patterns of temperatures across the southeast are less variable than the precipitation. Differences between the ModJMA and JMA can be seen in several months, especially during late spring and early autumn. This result is not surprising based on the rigid definition of the JMA index. An interesting result presented itself throughout the study. Individual tropical storms can be identified with the increased resolution PRISM data provides. A state by state breakdown of the ModJMA conclusions provides regional summaries. The ModJMA better classifies ENSO periods and leads to a more precise impact of ENSO over the southeast United States.
Briggs, K. (2006).
ENSO Event Reproduction: A Comparison of an EOF vs. A Cyclostationary (CSEOF) Approach. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: In past studies, El Niño-Southern Oscillation (ENSO) events have been linked to devastating weather extremes. Climate modeling of ENSO is often dependent on limited records of the pertinent physical variables, thus longer records of these variables is desirable. Noisy signals, such as monthly sea surface temperature, are good candidates for reproduction by several existing auto-regression techniques. Through auto-regression, influential principal component modes are broken down into a series of time points that are each dependent upon an optimal weighting of the surrounding points. Using these unique numerical relationships, a noisy signal can be reproduced by thus processing the leading modes and adding an artificial record of properly distributed noise. Statistical measures of important ENSO regions suggest that the nature of oceanic and atmospheric anomalous events is cyclic with respect to certain timescales; for example, the monthly timescale. To detect ENSO signals in the presence of a varying background noise field, the detection method should take into account the signal's strong phase-locking with this nested variation. Cyclostationary Emperical Orthogonal Functions (CSEOFs) are built upon the idea of nested cycles, unlike traditional EOFs, which incorporate a design that is better detailed for stationary processes. In this study, both EOF and CSEOF modes of a 50-year Pacific SST record are processed using an auto-regression technique, and several sets of artificial SST records are constructed. Appropriate statistical indices are applied to these artificial time series to ensure an acceptable consistency with the real record, and then artificial data is produced using the artificial time series. In all cases, the cyclostationary approach produces more realistic warm ENSO events with respect to timing, strength, and other traits than does the stationary approach. However, both methods produce only a fair representation of cold events, suggesting that further study is necessary for improvement of La Niña modeling. Shorter records of variables such as sea level height and Pacific wind stress anomalies can hinder the usefulness of auto-regression, owing to time point dependence on surrounding points. Using a regression technique to find an evolutionary consistency (i.e. physically consistent patterns) between one of these variables and a variable with a longer record (such as SST) can eliminate this problem. Once a regression relationship is found between two variables, the variable with the shorter record can be re-written to match the time evolution of the variable with the longer record. Here regression, both EOF and CSEOF, is performed on both sea surface temperature and sea level height (a 20-year record), and sea surface temperature and wind stress (a 39-year record). Once the regression relationships are found, artificial SST time series are incorporated in place of the original time series to produce several artificial 50-year SLH and wind stress data sets. 5 Pacific regions are chosen, and statistics and behavior of the artificial sets within these regions are compared to those of the original data. Once again the cyclostationary approach fares better than the stationary. In particular the EOF assumption of cross correlational symmetry fails to capture the direction-dependence of ENSO evolution, causing inconsistent ENSO behavior. This renders an EOF method insufficient for climate modeling and prediction, and implies that a better aim is to incorporate physical cyclic features via a cyclostationary method.
Kvaleberg, E. (2004).
Generation of Cold Core Filaments and Eddies Through Baroclinic Instability on a Continental Shelf. Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: The formation of cold core filaments on an idealized continental shelf is investigated using a numerical model to simulate the ocean's response to surface cooling. A horizontal density gradient forms because of uneven buoyancy loss due to the sloping bottom, and this gradient induces an alongshelf current in thermal wind balance, that in time becomes unstable. As the instabilities grow, filaments, and later eddies, are generated so that dense water near the coast is mixed offshore. Scaling arguments of the filament wavelength indicate that the current is baroclinically unstable, and an analytical model of the frontal expansion with time is in very good agreement with the simulations. This study was inspired by satellite observations of sea surface temperature on the West Florida Shelf during the winter months, in which it is clearly seen that cold core filaments extend from a thermal front. Numerical experiments are therefore designed to allow for reliable comparisons with conditions in this region.
Brolley, J. M. (2004).
Experimental Forest Fire Threat Forecast. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Climate shifts due to El Niño (warmer than normal ocean temperatures in the tropical Pacific Ocean) and La Niña (cooler than normal) are well known and used to predict seasonal temperature and precipitation trends up to a year in advance. These climate shifts are particularly strong in the Southeastern United States. During the winter and spring months, El Niño brings plentiful rainfall and cooler temperatures to Florida. Recent los Niños occurred in 1997-1998, one of the strongest on record, with another mild El Niño in 2002-2003. Conversely, La Niña is associated with warm and dry winter and spring seasons in Florida. Temperature and precipitation affect wildfire activity; interannual drivers of climate, like ENSO, have an influence on wildfire activity. Studies have shown a strong connection between wildfires in Florida and La Niña, with the more than double the average number of acres burned (O'Brien et al 2002; Jones et al. 1999). While this relationship is important and lends a degree of predictability to the relative activity of future wildfire seasons, human activities such as effective suppression, prescribed burns, and ignition can play an equally important role in wildfire risks. This study forecasts wildfire potential rather than actual burn statistics to avoid complications due to human interactions. This wildfire threat potential is based upon the Keetch-Byram Drought Index (KBDI). The KBDI is well suited as a seasonal forecast medium. It is based on daily temperature and rainfall measurements and responds to changing climate and weather conditions on time scales of days to months, and this index is high during dry warm weather patterns and low during wet cool patterns. The KBDI has been widely used in forestry in the Southeastern United States since its development in the 1970's, with foresters and firefighters have a good level of familiarity with the index and its applications. The KBDI is calculated daily and used as an index by wildfire managers. This study calculates wildfire potential using a statistical method known as bootstrapping. Many datasets contain approximately a half-century of data, and the limited dataset will introduce biases. Bootstrapping can remedy bias by simulating thousands of years of data, which retain the climatology for the past half-century. Bootstrapping preserves the mean but not the variance. By incorporating this method, this study will improve long-term forest fire risks that will become useful for those living or working near forests and assist in managing forests and wildfires. The Southeast Climate Consortium will also be issuing wildfire risk forecast for Florida and parts of Alabama and Georgia based on ENSO phase and the KBDI. Climate information and ENSO predictions are better served by incorporating them with known climate indices that are routinely used in the forestry sector. Wildfire managers and foresters operationally use the KBDI to monitor and predict wildfire activity (O'Brien et al. 2002). Meteorologists at the Florida Division of Forestry have demonstrated the validity of the KBDI as an indicator of potential wildfire activity in Florida (Long 2004). They showed that the value of the KBDI is not as important as the deviation from the monthly average. The wildfire risk forecast is based on the probabilities of KBDI anomalies and will present the probabilities associated with large deviations from the seasonal normal.
Brolley, J. M. (2007).
Effects of ENSO, NAO (PVO), and PDO on Monthly Extreme Temperatures and Precipitation. Ph.D. thesis, Florida State University, Tallahassee, FL.
Abstract: The El Nino-Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), the Pacific Decadal Oscillation (PDO), and the Polar Vortex Oscillation (PVO) produce conditions favorable for monthly extreme temperatures and precipitation. These climate modes produce upper-level teleconnection patterns that favor regional droughts, floods, heat waves, and cold spells, and these extremes impact agriculture, energy, forestry, and transportation. The above sectors prefer the knowledge of the worst (and sometimes the best) case scenarios. This study examines the extreme scenarios for each phase and the combination of phases that produce the greatest monthly extremes. Data from Canada, Mexico, and the United States are gathered from the Historical Climatology Network (HCN). Monthly data are simulated by the utilization of a Monte Carlo model. This Monte Carlo method simulates monthly data by the stochastic selection of daily data with identical ENSO, PDO, and PVO (NAO) characteristics. In order to test the quality of the Monte Carlo simulation, the simulations are compared with the observations using only PDO and PVO. It has been found that temperatures and precipitation in the simulation are similar to the model. Statistics tests have favored similarities between simulations and observations in most cases. Daily data are selected in blocks of four to eight days in order to conserve temporal correlation. Because the polar vortex occurs only during the cold season, the PVO is used during January, and the NAO is used during other months. The simulated data are arranged, and the tenth and ninetieth percentiles are analyzed. The magnitudes of temperature and precipitation anomalies are the greatest in the western Canada and the southeastern United States during winter, and these anomalies are located near the Pacific North American (PNA) extrema. Western Canada has its coldest (warmest) Januaries when the PDO and PVO are low (high). The southeastern United States has its coldest Januaries with high PDO and low PVO and warmest Januaries with low PDO and high PVO. Although extremes occur during El Nino or La Nina, many stations have the highest or lowest temperatures during neutral ENSO. In California and the Gulf Coast, the driest (wettest) Januaries tend to occur during low (high) PDO, and the reverse occurs in Tennessee, Kentucky, Ohio, and Indiana. Summertime anomalies, on the other hand, are weak because temperature variance is low. Phase combinations that form the wettest (driest) Julies form spatially incoherent patterns. The magnitudes of the temperature and precipitation anomalies and the corresponding phase combinations vary regionally and seasonally. Composite maps of geopotential heights across North America are plot for low, median, and high temperatures at six selected sites and for low, median, and high precipitation at the same sites. The greatest fluctuations occur near the six sites and over some of the loci of the PNA pattern. Geopotential heights tend to decrease (increase) over the target stations during the cold (warm) cases, and the results for precipitation are variable.