Huang, N. E., Wu, Z., Pinzón, J. E., Parkinson, C. L., Long, S. R., Blank, K., et al. (2009). Reductions Of Noise And Uncertainty In Annual Global Surface Temperature Anomaly Data.
Adv. Adapt. Data Anal., 01(03), 447–460.
Huang, N. E., Wu, Z., Long, S. R., Arnold, K. C., Chen, X., & Blank, K. (2009). On Instantaneous Frequency.
Adv. Adapt. Data Anal., 01(02), 177–229.
Wu, Z., & Huang, N. E. (2009). Ensemble Empirical Mode Decomposition: A Noise-Assisted Data Analysis Method.
Adv. Adapt. Data Anal., 01(01), 1–41.
Arbic, B. K., Karsten, R. H., & Garrett, C. (2009). On tidal resonance in the global ocean and the back-effect of coastal tides upon open-ocean tides.
Atmosphere-Ocean, 47(4), 239–266.
Shin, D. W., G. A. Baigorria, Y.-K. Lim, S. Cocke, T. E. LaRow, J. J. O'Brien, and J. W. Jones. (2009). Assessing Crop Yield Simulations with Various Seasonal Climate Data.
Science and Technology Infusion Climate Bulletin, .
Zeng, H., Chambers, J. Q., Negron-Juarez, R. I., Hurtt, G. C., Baker, D. B., & Powell, M. D. (2009). Impacts of tropical cyclones on U.S. forest tree mortality and carbon flux from 1851 to 2000.
Proc Natl Acad Sci U S A, 106(19), 7888–7892.
Abstract: Tropical cyclones cause extensive tree mortality and damage to forested ecosystems. A number of patterns in tropical cyclone frequency and intensity have been identified. There exist, however, few studies on the dynamic impacts of historical tropical cyclones at a continental scale. Here, we synthesized field measurements, satellite image analyses, and empirical models to evaluate forest and carbon cycle impacts for historical tropical cyclones from 1851 to 2000 over the continental U.S. Results demonstrated an average of 97 million trees affected each year over the entire United States, with a 53-Tg annual biomass loss, and an average carbon release of 25 Tg y(-1). Over the period 1980-1990, released CO(2) potentially offset the carbon sink in forest trees by 9-18% over the entire United States. U.S. forests also experienced twice the impact before 1900 than after 1900 because of more active tropical cyclones and a larger extent of forested areas. Forest impacts were primarily located in Gulf Coast areas, particularly southern Texas and Louisiana and south Florida, while significant impacts also occurred in eastern North Carolina. Results serve as an important baseline for evaluating how potential future changes in hurricane frequency and intensity will impact forest tree mortality and carbon balance.
Yin, J., Schlesinger, M. E., & Stouffer, R. J. (2009). Model projections of rapid sea-level rise on the northeast coast of the United States.
Nature Geosci, 2(4), 262–266.
Griffin, J. (2009).
Characterization of Errors in Various Moisture Roughness Length Parameterizations. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: Often the parameterization of the moisture roughness length is not seen as being important, as long as the parameterization seems reasonable; that is, it is within the rather considerable bounds of error for the data sets used to determine the parameterization. However, the choice of parameterization does influence height adjustments of humidity and calculations of turbulent heat fluxes. This paper focuses on the calculation of the turbulent heat fluxes using different parameterizations of roughness length. Five roughness length parameterizations are examined herein. These parameterizations include wall theory; the Clayson, Fairall, Curry parameterization; the Liu, Katsaros, Businger parameterization; Zilitinkevich et al. parameterization; and the COARE3.0 parameterization. Turbulent heat fluxes are calculated from each parameterization of the roughness length and are compared to observed turbulent heat flux values. The bulk latent heat flux estimates have a much better signal to noise ratio than the sensible heat fluxes, and are therefore the focus of the comparison to observations. This comparison indicates how to improve the proportionality in the above roughness length parameterizations, which are causing modeled turbulent heat flux magnitudes to be too large in four of the five parameterizations. The modeled turbulent heat fluxes are evaluated again after the modification of the parameterizations. Significant improvements in both the bias and the root mean square error (RMSE) are seen. Three parameterizations see roughly the same improvements of around 17Wm^-2 in the bias and roughly 10Wm^-2 in the RMSE. The largest improvements are in the Liu, Katsaros, Businger parameterization with bias improvements of over 45Wm^-2 and a RMSE reduction of nearly 32Wm^-2.
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.
Lowry, M. R. (2009).
Developing a Unified Superset in Quantifying Ambiguities Among Tropical Cyclone Best Track Data for the Western North Pacific. Master's thesis, Florida State University, Tallahassee, FL.
Abstract: In the western North Pacific basin, several agencies archive “best track” data of tropical cyclones. The Joint Typhoon Warning Center (JTWC) in Hawaii is responsible for the issuance of tropical cyclone warnings for United States Department of Defense interests and has a record of tropical cyclones extending back to 1945. The Japanese Meteorological Agency (JMA) is the World Meteorological Organization (WMO) official Regional Specialized Meteorological Center (RSMC) for the western North Pacific basin and has best track tropical cyclone data extending back to 1951. The Shanghai Typhoon Institute (STI) of the Chinese Meteorological Administration and the Hong Kong Observatory (HKO) of the Government of the Hong Kong Special Administrative Region also have 6-hourly tropical cyclone data records from 1949 and 1961, respectively. Western North Pacific (WNP) data sets are investigated in order to quantify ambiguities in position and intensity estimates among the forecast institutions through the development of a unified Superset. Ambiguities among the two primary warning centers (JMA and JTWC) are presented in the context of a changing observation network, observational tools, and analysis techniques since the beginning of tropical cyclone records. Mean differences in position estimates are found between the two centers on the order of 60 km prior to the introduction of meteorological satellites in 1961 and near 50 km following the deactivation of aircraft reconnaissance in 1987. Results show a step function change among intensity in JTWC and JMA best track data from 1989 to 1990 due to varying applications of the Dvorak intensity estimation technique. Parsing best track data into landfall subsets does not ameliorate interagency differences in position or intensity estimates. Additionally, analyses from Superset data call into question the veracity of JTWC best track data during the period from 1995-1999. The applicability of adopting an individual data set in discerning long term climate trends is examined in light of these differences. Past efforts to analyze, assemble, and maintain a complete, reliable best track tropical cyclone data set for the WNP are discussed among topical methods of incorporating the Superset within a basin-wide re-analysis.