Arrocha, G. (2006). Variability of Intraseasonal Precipitation Extremes Associated with ENSO in Panama . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Extensive analysis has been conducted over past decades showing the impacts of El Niño-Southern Oscillation (ENSO) on various regions throughout the world. However, these studies have not analyzed data from many stations in Panama, or they have not analyzed long periods of observations. For these reasons, they often miss climatological differences within the region induced by topography, or they do not possess enough observations to adequately study its climatology. Accordingly, the current study focuses on ENSO impacts on precipitation specific to the Isthmus of Panama. Results will be useful for agricultural and water resources planning and Panama Canal operations. Monthly total precipitation data were provided by Empresa de Transmisión Eléctrica S.A., which includes 32 stations with records from 1960 to 2004. The year is split into three seasons: two wet seasons (Early and Late Wet), one dry season (Dry). The country is also divided into regions according to similarities in the stations' climatology and geographic locations. Upper and lower precipitation extremes are associated with one of the three ENSO phases (warm, cold or neutral) to estimate their percentages of occurrences. The differences between each ENSO phases' seasonal precipitation distributions are statistically examined. Statistical analyses show effects of ENSO phases that vary by season and geographical region. Cold and warm ENSO years affect the southwestern half of the country considerably during the Late Wet season. Cold ENSO phases tend to increase rainfall, and the warm phase tends to decrease it. The opposite is true for the Caribbean coast. The Dry season experiences drier conditions in warm ENSO years, and the Early Wet season does not show any statistically significant difference between ENSO years' rainfall distributions.
DiNapoli, S. (2010). Determining the Error Characteristics of H*WIND . Master's thesis, Florida State University, Tallahassee, FL.
Abstract: The HRD Real-time Hurricane Wind Analysis System (H*Wind) is a software application used by NOAA's Hurricane Research Division to create a gridded tropical cyclone wind analysis based on a wide range of observations. One application of H*Wind fields is calibration of scatterometers for high wind speed environments. Unfortunately, the accuracy of the H*Wind product has not been studied extensively, and therefore the accuracy of scatterometer calibrations in these environments is also unknown. This investigation seeks to determine the uncertainty in the H*Wind product and estimate the contributions of several potential error sources. These error sources include random observation errors, relative bias between different data types, temporal drift resulting from combining non-simultaneous measurements, and smoothing and interpolation errors in the H*Wind software. The effects of relative bias between different data types and random observation errors are determined by performing statistical calculations on the observed wind speeds. We show that in the absence of large biases, the total contribution of all error sources results in an uncertainty of approximately 7% near the storm center, which increases to nearly 15% near the tropical storm force wind radius. The H*Wind analysis algorithm is found to introduce a positive bias to the wind speeds near the storm center, where the analyzed wind speeds are enhanced to match the highest observations. In addition, spectral analyses are performed to ensure that the filter wavelength of the final analysis product matches user specifications. With increased knowledge of these error sources and their effects, researchers will have a better understanding of the uncertainty in the H*Wind product, and can then judge the suitability of H*Wind for various research applications
Boisserie, M. (2010). Generation of an empirical soil moisture initialization and its potential impact on subseasonal forecasting skill of continental precipitation and air temperature . Ph.D. thesis, Florida State University, Tallahassee, FL, FL.
Abstract: The effect of the PAR technique on the model soil moisture estimates is evaluated using the Global Soil Wetness Project Phase 2 (GSWP-2) multimodel analysis product (used as a proxy for global soil moisture observations) and actual in-situ observations from the state of Illinois. The results show that overall the PAR technique is effective; across most of the globe, the seasonal and anomaly variability of the model soil moisture estimates well reproduce the values of GSWP-2 in the top 1.5 m soil layer; by comparing to in-situ observations in Illinois, we find that the seasonal and anomaly soil moisture variability is also well represented deep into the soil. Therefore, in this study, we produce a new global soil moisture analysis dataset that can be used for many land surface studies (crop modeling, water resource management, soil erosion, etc.). Then, the contribution of the resulting soil moisture analysis (used as initial conditions) on air temperature and precipitation forecasts are investigated. For this, we follow the experimental set up of a model intercomparison study over the time period 1986-1995, the Global Land-Atmosphere Coupling Experiment second phase (GLACE-2), in which the FSU/COAPS climate model has participated. The results of the summertime air temperature forecasts show a significant increase in skill across most of the U.S. at short-term to subseasonal time scales. No increase in summertime precipitation forecasting skill is found at short-term to subseasonal time scales between 1986 and 1995, except for the anomalous drought year of 1988. We also analyze the forecasts of two extreme hydrological events, the 1988 U.S. Drought and the 1993 U.S. flood. In general, the comparison of these two extreme hydrological event forecasts shows greater improvement for the summertime of 1988 than that of 1993, suggesting that soil moisture contributes more to the development of a drought than a flood. This result is consistent with Dirmeyer and Brubaker [1999] and Weaver et al. [2009]. By analyzing the evaporative sources of these two extreme events using the back-trajectory methodology of Dirmeyer and Brubaker [1999], we find similar results as this latter paper; the soil moisture-precipitation feedback mechanism seems to play a greater role during the drought year of 1988 than the flood year of 1993. Finally, the accuracy of this soil moisture initialization depends upon the quality of the precipitation dataset that is assimilated. Because of the lack of observed precipitation at a high temporal resolution (3-hourly) for the study period (1986-1995), a reanalysis product is used for precipitation assimilation in this study. It is important to keep in mind that precipitation data in reanalysis sometimes differ significantly from observations since precipitation is often not assimilated into the reanalysis model. In order to investigate that aspect, a similar analysis to that we performed in this study could be done using the 3-hourly Tropical Rainfall Measuring Mission (TRMM) dataset available for a the time period 1998-present. Then, since the TRMM dataset is a fully observational dataset, we expect the soil moisture initialization to be improved over that obtained in this study, which, in turn, may further increase the forecast skill.
Stauffer, C. L. (2018). Air-sea coupling dependency on sea surface temperature fronts as observed by research vessel data . Bachelor's thesis, Florida State University, Tallahassee, FL.
Morey, S., Koch, M., Liu, Y., & Lee, S. - K. (2017). Florida's oceans and marine habitats in a changing climate. In E. P. Chassignet, J. W. Jones, V. Misra, & J. Obeysekera (Eds.), Florida's climate: Changes, variations, & impacts (pp. 391–425). Gainesville, FL: Florida Climate Institute.
Bourassa, M. A. (2000). Shear stress model for the aqueous boundary layer near the air-sea interface. Journal of Geophysical Research – Oceans , 105 (C1), 1167–1176.
Tartaglione, C. S., Hanley, D. E., O'Brien, J. J., & Smith, S. R. (2002). Regional Effects of ENSO on U.S Hurricane Landfalls . COAPS Technical Report 02-5. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Bove, M. C., & O'Brien, J. J. PDO Modification of U.S ENSO Climate Impacts . COAPS Technical Report 00-3, 103 pp., Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, 32306-2840.
Arguez, A., Smith, S. R., & O'Brien, J. J. (2002). The relationship between low-frequency North Atlantic sea surface temperatures and Eastern North American climate . COAPS Technical Report 02-6. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
Salapata, D., Higgins, W., Schemn, J., & O'Brien, J. J. (2002). Winter Temperature and Precipitation Verification of the NCEP Operational Climate Model . COAPS Technical Report 02-04b. Tallahassee, FL: Center for Ocean-Atmospheric Prediction Studies, Florida State University.
