The state of knowledge regarding trends and an understanding of their causes is presented for a specific subset of extreme weather and climate types. For severe convective storms (tornadoes, hailstorms, and severe thunderstorms), differences in time and space of practices of collecting reports of events make using the reporting database to detect trends extremely difficult. Overall, changes in the frequency of environments favorable for severe thunderstorms have not been statistically significant. For extreme precipitation, there is strong evidence for a nationally averaged upward trend in the frequency and intensity of events. The causes of the observed trends have not been determined with certainty, although there is evidence that increasing atmospheric water vapor may be one factor. For hurricanes and typhoons, robust detection of trends in Atlantic and western North Pacific tropical cyclone (TC) activity is significantly constrained by data heterogeneity and deficient quantification of internal variability. Attribution of past TC changes is further challenged by a lack of consensus on the physical link- ages between climate forcing and TC activity. As a result, attribution of trends to anthropogenic forcing remains controversial. For severe snowstorms and ice storms, the number of severe regional snowstorms that occurred since 1960 was more than twice that of the preceding 60 years. There are no significant multidecadal trends in the areal percentage of the contiguous United States impacted by extreme seasonal snowfall amounts since 1900. There is no distinguishable trend in the frequency of ice storms for the United States as a whole since 1950.

Abstract. A hierarchy of E1 Nifio-Southern Oscillation (ENSO) prediction schemes has been developed during the Tropical Ocean-Global Atmosphere (TOGA) program which includes statistical schemes and physical models. The statistical models are, in general, based on linear statistical techniques and can be classified into models which use atmospheric (sea level pressure or surface wind) or oceanic (sea surface temperature or a measure of upper ocean heat content) quantities or a combination of oceanic and atmospheric quantities as predictors. The physical models consist of coupled oceanatmosphere models of varying degrees of complexity, ranging from simplified coupled models of the "shallow water" type to coupled general circulation models. All models, statistical and physical, perform considerably better than the persistence forecast in predicting typical indices of ENSO on lead times of 6 to 12 months. The TOGA program can be regarded as a success from this perspective. However, despite the demonstrated predictability, little is known about ENSO predictability limits and the predictability of phenomena outside the tropical Pacific. Furthermore, the predictability of anomalous features known to be associated with ENSO (e.g., Indian monsoon and Sahel rainfall, southern African drought, and off-equatorial sea surface temperature) needs to be addressed in more detail. As well, the relative importance of different physical mechanisms (in the ocean or atmosphere) has yet to be established. A seasonal dependence in predictability is seen in many models, but the processes responsible for it are not fully understood, and its meaning is still a matter of scientific discussion. Likewise, a marked decadal variation in skill is observed, and the reasons for this are still under investigation. Finally, the different prediction models yield similar skills, although they are initialized quite differently. The reasons for these differences are also unclear.

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Changes in the frequency of U.S. landfalling hurricanes with respect to the El Nino-Southern Oscillation (ENSO) cycle are assessed. Ninety-eight years (1900-97) of U.S. landfalling hurricanes are classified, using sea surface temperature anomaly data from the equatorial Pacific Ocean, as occurring during an El Nino (anomalously warm tropical Pacific waters), La Nina (anomalously cold tropical Pacific waters), or neither (neutral). The mean and variance of U.S. landfalling hurricanes are determined for each ENSO phase. Each grouping is then tested for Poisson distribution using a chi-squared test. Resampling using a "bootstrap" technique is then used to determine the 5% and 95% confidence limits of the results. Last, the frequency of major U.S. landfalling hurricanes (sus-tained winds of 96 kt or more) with respect to ENSO phase is assessed empirically. The results indicated that El Nino events show a reduction in the probability of a U.S. landfalling hurricane, while La Nina shows an increase in the chance of a U.S. hurricane strike. Quantitatively, the probability of two or more landfalling U.S. hurricanes during an El Nino is 28%, of two or more landfalls during neutral conditions is 48%, and of two or more landfalls during La Nina is 66%. The frequencies of landfalling major hurricanes show similar results. The probability of one or more major hurricane landfall during El Nino is 23% but is 58% during neutral conditions and 63% during La Nina.

[1] The seasonal circulation on the western shelf of the Gulf of Mexico is studied using a high-resolution numerical simulation, historical hydrographic data, sea level data, and satellite images. Three regions are distinguished, the Tamaulipas-Veracruz (TAVE) shelf, the Louisiana-Texas (LATEX) shelf, and the western Campeche Bank. On the TAVE shelf there is a swift reversal of the along-shelf current, downcoast from September to March and upcoast from May to August when there is upwelling due to offshore Ekman transport. Circulation on the western Campeche Bank is upcoast throughout the year. The LATEX shelf has a cyclonic circulation, except during summer months when the flow is eastward. During spring-summer the upcoast current on the TAVE shelf reaches the southern Texas shelf where it encounters a downcoast coastal current favoring offshore transports. In the fall-winter, the downcoast current reaches the southern Bay of Campeche where it meets an opposing along-shelf current, generating seasonal offshore transports. During fall and winter, cool low-salinity water from the Mississippi and Atchafalaya Rivers is advected westward along the LATEX shelf onto the TAVE shelf, developing along-shelf fronts and temperature inversions commonly observed over the outer shelf and shelf break. The main forcing over the western shelf of the gulf is the along-coast wind stress component. The existence of the cross-shelf transports in the confluence regions is supported by chlorophyll a data. Up to 80% of the seasonal sea level variability is explained by the along shelf currents and the low-frequency variability of the atmospheric sea level pressure.INDEX TERMS: 4227 Oceanography: General: Diurnal, seasonal, and annual cycles; 4219 Oceanography: General: Continental shelf processes; 4223 Oceanography: General: Descriptive and regional oceanography; KEYWORDS: shelf circulation, western Gulf of Mexico Citation: Zavala-Hidalgo, J., S. L. Morey, and J. J. O'Brien, Seasonal circulation on the western shelf of the Gulf of Mexico using a high-resolution numerical model,

El Niño-Southern Oscillation (ENSO) is a natural, coupled atmospheric-oceanic cycle that occurs in the tropical Pacific Ocean on an approximate time scale of 2-7 years. ENSO events have been shown in previous studies to be related to regional extremes in weather (e.g., hurricane occurrences, frequency and severity of tornadoes, droughts, and floods). The teleconnection of ENSO events to extreme weather events means the ability to classify an event as El Niño or La Niña is of interest in scientific and other applications. ENSO is most often classified using indices that indicate the warmth and coolness of equatorial tropical Pacific Ocean sea-surface temperatures (SSTs). Another commonly used index is based on sea-level pressure differences measured across the tropical Pacific Ocean. More recently, other indices have been proposed and have been shown to be effective in describing ENSO events. There is currently no consensus within the scientific community as to which of many indices best captures ENSO phases. The goal of this study is to compare several commonly used ENSO indices and to determine whether or not one index is superior in defining ENSO events; or alternatively, to determine which indices are best for various applications. The response and sensitivity of the SST-based indices and pressure-based indices are compared. The Niño 4 index has a relatively weak response to El Niño; the Niño 1+2 index has a relatively strong response to La Niña. Analysis of the sensitivity of the indices relative to one another suggests that the choice of index to use in ENSO studies is dependent upon the phase of ENSO that is to be studied. The JMA index is found to be more sensitive to La Niña events than all other indices. The SOI, Niño 3.4, and Niño 4 indices are almost equally sensitive to El Niño events and are more sensitive than the JMA, Niño 1+2, and Niño 3 indices.

[1] A numerical simulation of the Gulf of Mexico (GoM) using the Navy Coastal Ocean Model (NCOM) is used to identify the pathways by which fresh water discharged by major rivers in the northern Gulf is exported away from the region. The NCOM, a new primitive equation ocean model with a hybrid sigma/geopotential level vertical coordinate, is described along with its application to the GoM region. Trajectories from surface drifters are analyzed to show evidence of the seasonally shifting alongshore and crossshelf transport in the region. The model results are used to determine the preferred locations and times of year for cross-shelf and along-shelf export of low-salinity water from the northern GoM. The annual cycle of local wind stress plays an important role in shifting the export pathway of the fresh water discharged from the major rivers (primarily the Mississippi River) toward the east in the spring/summer, where it can be transported offshore by the currents associated with deep ocean mesoscale eddies, and toward the west in the fall/winter, where it is transported southward along the Mexican coastline as a coastally trapped current.

The dynamics of the flow field surrounding New Zealand are investigated using a series of global ocean models. The physical mechanisms governing the direction, magnitude, and location of the East Australian Current (EAC), the Tasman Front, the East Auckland Current (EAUC), and the East Cape Current (ECC) are studied using numerical simulations whose complexity is systematically increased. As new dynamics are added to each successive simulation, their direct and indirect effects on the flow field are examined. The simulations have horizontal resolutions of 1/8Њ, 1/16Њ, or 1/32Њ for each variable, and vertical resolutions ranging from 1.5-layer reduced gravity to 6-layer finite depth with realistic bottom topography. All simulations are forced by the Hellerman and Rosenstein monthly wind stress climatology. Analysis of these simulations shows that several factors play a critical role in governing the behavior of the examined currents. These factors include 1) mass balance of water pathways through the region, 2) gradients in the wind stress curl, 3) nonlinear flow instabilities, and 4) upper-ocean-topographic coupling due to mixed baroclinic and barotropic instabilities. Transport streamfunctions of a linear reduced gravity model reproduce the large-scale features well but produce an EAUC that flows counter to the observed direction. The residual of the mass balance of the transport through the Tasman Sea, the basinwide transport at 32ЊS, and the transport of the South Pacific subtropical gyre east of New Zealand determines the direction of the EAUC. The 6-layer nonlinear model allows isopycnal outcropping, which changes the transport through the Tasman Sea and produces an EAUC flowing in the observed direction. Gradients in the zonally integrated wind stress curl field determine the coastal separation points of the EAC, the EAUC, and the ECC, while a combination of nonlinear flow instabilities and upper-ocean-topographic coupling contribute to the formation of meanders in the Tasman Front. Increased resolution results in greater mixed baroclinicbarotropic instabilities and thus more upper-ocean-topographic coupling and surface variability, giving a more accurate simulation of topographically controlled mean meanders in the Tasman Front.