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  • 1
    Publication Date: 2009-01-01
    Description: The tropical cyclone (TC) track forecasts of the Navy Operational Global Atmospheric Prediction System (NOGAPS) were evaluated for a number of data assimilation experiments conducted using observational data from two periods: 4 July–31 October 2005 and 1 August–30 September 2006. The experiments were designed to illustrate the impact of different types of satellite observations on the NOGAPS TC track forecasts. The satellite observations assimilated in these experiments consisted of feature-track winds from geostationary and polar-orbiting satellites, Special Sensor Microwave Imager (SSM/I) total column precipitable water and wind speeds, Advanced Microwave Sounding Unit-A (AMSU-A) radiances, and Quick Scatterometer (QuikSCAT) and European Remote Sensing Satellite-2 (ERS-2) scatterometer winds. There were some differences between the results from basin to basin and from year to year, but the combined results for the 2005 and 2006 test periods for the North Pacific and Atlantic Ocean basins indicated that the assimilation of the feature-track winds from the geostationary satellites had the most impact, ranging from 7% to 24% improvement in NOGAPS TC track forecasts. This impact was statistically significant at all forecast lengths. The impact of the assimilation of SSM/I precipitable water was consistently positive and statistically significant at all forecast lengths. The improvements resulting from the assimilation of AMSU-A radiances were also consistently positive and significant at most forecast lengths. There were no significant improvements/degradations from the assimilation of the other satellite observation types [e.g., Moderate Resolution Imaging Spectroradiometer (MODIS) winds, SSM/I wind speeds, and scatterometer winds]. The assimilation of all satellite observations resulted in a gain in skill of roughly 12 h for the NOGAPS 48- and 72-h TC track forecasts and a gain in skill of roughly 24 h for the 96- and 120-h forecasts. The percent improvement in these forecasts ranged from almost 20% at 24 h to over 40% at 120 h.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 2
    Publication Date: 2006-08-01
    Description: The Weber barotropic model (WBAR) was originally developed using predefined 850–200-hPa analyses and forecasts from the NCEP Global Forecasting System. The WBAR tropical cyclone (TC) track forecast performance was found to be competitive with that of more complex numerical weather prediction models in the North Atlantic. As a result, WBAR was revised to incorporate the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecasts for use at the Joint Typhoon Warning Center (JTWC). The model was also modified to analyze its own storm-dependent deep-layer mean fields from standard NOGAPS pressure levels. Since its operational installation at the JTWC in May 2003, WBAR TC track forecast performance has been competitive with the performance of other more complex NWP models in the western North Pacific. Its TC track forecast performance combined with its high availability rate (93%–95%) has warranted its inclusion in the JTWC operational consensus. The impact of WBAR on consensus TC track forecast performance has been positive and WBAR has added to the consensus forecast availability (i.e., having at least two models to provide a consensus forecast).
    Print ISSN: 0882-8156
    Electronic ISSN: 1520-0434
    Topics: Geography , Physics
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  • 3
    Publication Date: 2009-02-01
    Description: In this study, new estimates of monthly freshwater discharge from continents, drainage regions, and global land for the period of 2003–05 are presented. The method uses observed terrestrial water storage change estimates from the Gravity Recovery and Climate Experiment (GRACE) and reanalysis-based atmospheric moisture divergence and precipitable water tendency in a coupled land–atmosphere water mass balance. The estimates of freshwater discharge are analyzed within the context of global climate and compared with previously published estimates. Annual cycles of observed streamflow exhibit stronger correlations with the computed discharge compared to those with precipitation minus evapotranspiration (P − E) in several of the world’s largest river basins. The estimate presented herein of the mean monthly discharge from South America (∼846 km3 month−1) is the highest among the continents and that flowing into the Atlantic Ocean (∼1382 km3 month−1) is the highest among the drainage regions. The volume of global freshwater discharge estimated here is 30 354 ± 1212 km3 yr−1. Monthly variations of global freshwater discharge peak between August and September and reach a minimum in February. Global freshwater discharge is also computed using a global ocean–atmosphere mass balance in order to validate the land–atmosphere water balance estimates and as a measure of global water budget closure. Results show close proximity between the two estimates of global discharge at monthly (RMSE = 329 km3 month−1) and annual time scales (358 km3 yr−1). Results and comparisons to observations indicate that the method shows important potential for global-scale monitoring of combined surface water and submarine groundwater discharge at near-real time, as well as for contributing to contemporary global water balance studies and for constraining global hydrologic model simulations.
    Print ISSN: 1525-755X
    Electronic ISSN: 1525-7541
    Topics: Geography , Geosciences , Physics
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  • 4
    Publication Date: 2007-05-01
    Description: The extent to which the tropical cyclone (TC) track forecast error of a consensus model (CONU) routinely used by the forecasters at the National Hurricane Center can be predicted is determined. A number of predictors of consensus forecast error, which must be quantities that are available prior to the official forecast deadline, were examined for the Atlantic basin in 2001–03. Leading predictors were found to be consensus model spread, defined to be the average distance of the member forecasts from the consensus forecast, and initial and forecast TC intensity. Using stepwise linear regression and the full pool of predictors, regression models were found for each forecast length to predict the CONU TC track forecast error. The percent variance of CONU TC track forecast error that could be explained by these regression models ranged from just over 15% at 48 h to nearly 50% at 120 h. Using the regression models, predicted radii were determined and were used to draw circular areas around the CONU forecasts that contained the verifying TC position 73%–76% of the time. Based on the size of these circular areas, a forecaster can determine the confidence that can be placed upon the CONU forecasts. Independent data testing yielded results only slightly degraded from those of dependent data testing, highlighting the capability of these methods in practical forecasting applications.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 5
    Publication Date: 2009-10-01
    Description: This work identifies and documents a suite of large-scale drivers of rainfall variability in the Australian region. The key driver in terms of broad influence and impact on rainfall is the El Niño–Southern Oscillation (ENSO). ENSO is related to rainfall over much of the continent at different times, particularly in the north and east, with the regions of influence shifting with the seasons. The Indian Ocean dipole (IOD) is particularly important in the June–October period, which spans much of the wet season in the southwest and southeast where IOD has an influence. ENSO interacts with the IOD in this period such that their separate regions of influence cover the entire continent. Atmospheric blocking also becomes most important during this period and has an influence on rainfall across the southern half of the continent. The Madden–Julian oscillation can influence rainfall in different parts of the continent in different seasons, but its impact is strongest on the monsoonal rains in the north. The influence of the southern annular mode is mostly confined to the southwest and southeast of the continent. The patterns of rainfall relationship to each of the drivers exhibit substantial decadal variability, though the characteristic regions described above do not change markedly. The relationships between large-scale drivers and rainfall are robust to the selection of typical indices used to represent the drivers. In most regions the individual drivers account for less than 20% of monthly rainfall variability, though the drivers relate to a predictable component of this variability. The amount of rainfall variance explained by individual drivers is highest in eastern Australia and in spring, where it approaches 50% in association with ENSO and blocking.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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  • 6
    Publication Date: 2009-11-01
    Description: The causes of rainfall variations in southeastern Australia associated with three key El Niño years (1982, 1997, and 2002) are explored. Whereas 1982 and 2002 were exceptionally dry years, 1997 had near-average rainfall. These variations in rainfall can be explained by changes in the behavior of cutoff low pressure systems. Although each year had a similar number of cutoff low events, 1997 had higher rainfall per cutoff low event when compared with the other years. In particular, rain in 1997 is attributable to five large wet events from cutoff low pressure systems. In each of these wet events, the moist air originated from the marine boundary layer off the coast of northeastern Australia. Cutoff lows in 1982 and 2002 were much drier and did not draw in moist air from the northeastern coast. In typical classifications, 1982 and 1997 are grouped together as “canonical” El Niños whereas 2002 is a Modoki El Niño. The results presented here imply that these groupings are not definitive in explaining variations in southeastern Australian rainfall.
    Print ISSN: 0027-0644
    Electronic ISSN: 1520-0493
    Topics: Geography , Geosciences , Physics
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