TRMM microwave imager rain estimates are used to quantify the spatial distribution of rainfall in tropical cyclones (TCs) over the global oceans. A total of 260 TCs were observed worldwide from 1 January 1998-31 December 2000, providing 2121 instantaneous TC precipitation observations. To examine the relationship between the storm intensity, its geographical location, and the rainfall distribution, the dataset is stratified into three intensity groups and six oceanic basins. The three intensity classes used in this study are tropical storms (TSs) with winds Ͻ33 m s Ϫ1 , category 1-2 hurricane-strength systems (CAT12) with winds from 34-48 m s Ϫ1 , and category 3-5 systems (CAT35) with winds Ͼ49 m s Ϫ1. The axisymmetric component of the TC rainfall is represented by the radial distribution of the azimuthal mean rainfall rates (R). The mean rainfall distribution is computed using 10-km annuli from the storm center to a 500-km radius. The azimuthal mean rain rates vary with storm intensity and from basin to basin. The maximum R is about 12 mm h Ϫ1 for CAT35, but decreases to 7 mm h Ϫ1 for CAT12, and to 3 mm h Ϫ1 for TS. The radius from the storm center of the maximum rainfall decreases with increasing storm intensity, from 50 km for TS to 35 km for CAT35 systems. The asymmetric component is determined by the first-order Fourier decomposition in a coordinate system relative to the storm motion. The asymmetry in TC rainfall varies significantly with both storm intensity and geographic locations. For the global average of all TCs, the maximum rainfall is located in the front quadrants. The location of the maximum rainfall shifts from the front-left quadrant for TS to the front-right for CAT35. The amplitude of the asymmetry varies with intensity as well; TS shows a larger asymmetry than CAT12 and CAT35. These global TC rainfall distributions and variability observed in various ocean basins should help to improve TC rainfall forecasting worldwide.

Real-time forecasts of five landfalling Atlantic hurricanes during 2005 using the Advanced Research Weather Research and Forecasting (WRF) (ARW) Model at grid spacings of 12 and 4 km revealed performance generally competitive with, and occasionally superior to, other operational forecasts for storm position and intensity. Recurring errors include 1) excessive intensification prior to landfall, 2) insufficient momentum exchange with the surface, and 3) inability to capture rapid intensification when observed. To address these errors several augmentations of the basic community model have been designed and tested as part of what is termed the Advanced Hurricane WRF (AHW) model. Based on sensitivity simulations of Katrina, the inner-core structure, particularly the size of the eye, was found to be sensitive to model resolution and surface momentum exchange. The forecast of rapid intensification and the structure of convective bands in Katrina were not significantly improved until the grid spacing approached 1 km. Coupling the atmospheric model to a columnar, mixed layer ocean model eliminated much of the erroneous intensification of Katrina prior to landfall noted in the real-time forecast.

Vertical wind shear and storm motion are two of the most important factors contributing to rainfall asymmetries in tropical cyclones (TCs). Global TC rainfall structure, in terms of azimuthal distribution and asymmetries relative to storm motion, has been previously described using the Tropical Rainfall Measuring Mission Microwave Imager rainfall estimates. The mean TC rainfall distribution and the wavenumber-1 asymmetry vary with storm intensity and geographical location among the six oceanic basins. This study uses a similar approach to investigate the relationship between the structure of TC rainfall and the environmental flow by computing the rainfall asymmetry relative to the vertical wind shear. The environmental vertical wind shear is defined as the difference between the mean wind vectors of the 200-and 850-hPa levels over an outer region extending from the radius of 200-800 km around the storm center. The wavenumber-1 maximum rainfall asymmetry is downshear left (right) in the Northern (Southern) Hemisphere. The rainfall asymmetry decreases (increases) with storm intensity (shear strength). The rainfall asymmetry maximum is predominantly downshear left for shear values Ͼ 7.5 m s Ϫ1. Large asymmetries are usually observed away from the TC centers. As TC intensity increases, the asymmetry maximum shifts upwind to the left. The analysis is further extended to examine the storm motion and the vertical wind shear and their collective effects on TC rainfall asymmetries. It is found that the vertical wind shear is a dominant factor for the rainfall asymmetry when shear is Ͼ5 m s Ϫ1. The storm motion-relative rainfall asymmetry in the outer rainband region is comparable to that of shear relative when the shear is Ͻ5 m s Ϫ1, suggesting that TC translation speed becomes an important factor in the low shear environment. The overall TC rainfall asymmetry depends on the juxtaposition and relative magnitude of the storm motion and environmental shear vectors in all oceanic basins.

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Reliable forecasts for the dispersion of oceanic contamination are important for coastal ecosystems, society, and the economy as evidenced by the Deepwater Horizon oil spill in the Gulf of Mexico in 2010 and the Fukushima nuclear plant incident in the Pacific Ocean in 2011. Accurate prediction of pollutant pathways and concentrations at the ocean surface requires understanding ocean dynamics over a broad range of spatial scales. Fundamental questions concerning the structure of the velocity field at the submesoscales (100 m to tens of kilometers, hours to days) remain unresolved due to a lack of synoptic measurements at these scales. Using high-frequency position data provided by the near-simultaneous release of hundreds of accurately tracked surface drifters, we study the structure of submesoscale surface velocity fluctuations in the Northern Gulf of Mexico. Observed two-point statistics confirm the accuracy of classic turbulence scaling laws at 200-m to 50-km scales and clearly indicate that dispersion at the submesoscales is local, driven predominantly by energetic submesoscale fluctuations. The results demonstrate the feasibility and utility of deploying large clusters of drifting instruments to provide synoptic observations of spatial variability of the ocean surface velocity field. Our findings allow quantification of the submesoscale-driven dispersion missing in current operational circulation models and satellite altimeter-derived velocity fields.T he Deepwater Horizon (DwH) incident was the largest accidental oil spill into marine waters in history with some 4.4 million barrels released into the DeSoto Canyon of the northern Gulf of Mexico (GoM) from a subsurface pipe over ∼84 d in the spring and summer of 2010 (1). Primary scientific questions, with immediate practical implications, arising from such catastrophic pollutant injection events are the path, speed, and spreading rate of the pollutant patch. Accurate prediction requires knowledge of the ocean flow field at all relevant temporal and spatial scales. Whereas ocean general circulation models were widely used during and after the DwH incident (2-6), such models only capture the main mesoscale processes (spatial scale larger than 10 km) in the GoM. The main factors controlling surface dispersion in the DeSoto Canyon region remain unclear. The region lies between the mesoscale eddy-driven deep water GoM (7) and the winddriven shelf (8) while also being subject to the buoyancy input of the Mississippi River plume during the spring and summer months (9). Images provided by the large amounts of surface oil produced in the DwH incident revealed a rich array of flow patterns (10) showing organization of surface oil not only by mesoscale straining into the loop current "Eddy Franklin," but also by submesoscale processes. Such processes operate at spatial scales and involve physics not currently captured in operational circulation models. Submesoscale motions, where they exist, can directly influence the local transport of biogeochemical tracers (11, 12) ...