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|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.|
|Hurlburt, H., Brassington, G., Drillet, Y., Kamachi, M., Benkiran, M., Bourdallé-Badie, R., et al. (2009). High-Resolution Global and Basin-Scale Ocean Analyses and Forecasts. Oceanog., 22(3), 110–127.|
|Jardak, M., Navon, I. M., & Zupanski, M. (2009). Comparison of sequential data assimilation methods for the Kuramoto-Sivashinsky equation. Int. J. Numer. Meth. Fluids, .|
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.
|Legg, S., Briegleb, B., Chang, Y., Chassignet, E. P., Danabasoglu, G., Ezer, T., et al. (2009). Improving Oceanic Overflow Representation in Climate Models: The Gravity Current Entrainment Climate Process Team. Bull. Amer. Meteor. Soc., 90(5), 657–670.|
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.
|Maue, R. N. (2009). Northern Hemisphere tropical cyclone activity. Geophys. Res. Lett., 36(5).|
|Metzger, E. J., H.E. Hurlburt, A.J. Wallcraft, O.M. Smedstad, J.A. Cummings, and E.P. Chassignet. (2009). Predicting Ocean Weather using the HYbrid Coordinate Ocean Model (HYCOM). NRL Review, , submitted.|
|Misra, V. (2009). Harvesting model uncertainty for the simulation of interannual variability. J. Geophys. Res., 114(D16).|
|Misra, V. (2009). The Amplification of the ENSO Forcing over Equatorial Amazon. J. Hydrometeor, 10(6), 1561–1568.|