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Mark A. Bourassa and Kelly McBeth Ford

Abstract

A more versatile and robust technique is developed for determining area-averaged surface vorticity based on vector winds from swaths of remotely sensed wind vectors. This technique could also be applied to determine the curl of stress, and it could be applied to any gridded dataset of winds or stresses. The technique is discussed in detail and compared to two previous studies that focused on early development of tropical systems. Error characteristics of the technique are examined in detail. Specifically, three independent sources of error are explored: random observational error, truncation error, and representation error. Observational errors are due to random errors in the wind observations and determined as a worst-case estimate as a function of averaging spatial scale. The observational uncertainty in the Quick Scatterometer (QuikSCAT)-derived vorticity averaged for a roughly circular shape with a 100-km diameter, expressed as one standard deviation, is approximately 0.5 × 10−5 s−1 for the methodology described herein. Truncation error is associated with the assumption of linear changes between wind vectors. Uncertainty related to truncation has more spatial organization in QuikSCAT data than observational uncertainty. On 25- and 50-km scales, the truncation errors are very large. The third type of error, representation error, is due to the size of the area being averaged compared to values with 25-km length scales. This type of error is analogous to oversmoothing. Tropical and subtropical low pressure systems from three months of QuikSCAT observations are used to examine truncation and representation errors. Representation error results in a bias of approximately −1.5 × 10−5 s−1 for area-averaged vorticity calculated on a 100-km scale compared to vorticity calculated on a 25-km scale. The discussion of these errors will benefit future projects of this nature as well as future satellite missions.

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Mark A. Bourassa, Ernesto Rodriguez, and Rob Gaston
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Yangxing Zheng, Mark A. Bourassa, and Paul Hughes

Abstract

The authors' modeling shows that changes in sea surface temperature (SST) gradients and surface roughness between oil-free water and oil slicks influence the motion of the slick. Physically significant changes occur in surface wind speed, surface wind divergence, wind stress curl, and Ekman transport mostly because of SST gradients and changes in surface roughness between the water and the slick. These remarkable changes might affect the speed and direction of surface oil. For example, the strongest surface wind divergence (convergence) occurring in the transition zones owing to the presence of an oil slick will induce an atmospheric secondary circulation over the oil region, which in turn might affect the surface oil movement. SST-related changes to wind stress curl and Ekman transport in the transition zones appear to increase approximately linearly with the magnitude of SST gradients. Both surface roughness difference and SST gradients give rise to a net convergence of Ekman transport for oil cover. The SST gradient could play a more important role than surface roughness in changes of Ekman transport when SST gradients are large enough (e.g., several degrees per 10 km). The resulting changes in Ekman transport also induce the changes of surface oil movement. Sensitivity experiments show that appropriate selections of modeled parameters and geostrophic winds do not change the conclusions. The results from this idealized study indicate that the feedbacks from the surface oil presence to the oil motion itself are not trivial and should be further investigated for consideration in future oil-tracking modeling systems.

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Yangxing Zheng, Renhe Zhang, and Mark A. Bourassa

Abstract

Composite analysis from NCEP–NCAR reanalysis datasets over the period 1948–2007 indicates that stronger East Asian winter monsoons (EAWM) and stronger Australian summer monsoons (ASM) generally coexist in boreal winters preceding the onset of El Niño, although the EAWM tend to be weak after 1990, probably because of the decadal shift of EAWM and the change in El Niño events from cold-tongue type to warm-pool type. The anomalous EAWM and ASM enhance surface westerlies over the western tropical Pacific Ocean (WTP). It is proposed that the enhanced surface westerlies over the WTP prior to El Niño onset are generally associated with the concurrent anomalous EAWM and ASM. A simple analytical atmospheric model is constructed to test the hypothesis that the emergence of enhanced surface westerlies over the WTP can be linked to concurrent EAWM and ASM anomalies. Model results indicate that, when anomalous northerlies from the EAWM converge with anomalous southerlies from the ASM, westerly anomalies over the WTP are enhanced. This result provides a possible explanation of the co-impact of the EAWM and the ASM on the onset of El Niño through enhancing the surface westerly over the WTP.

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Heather M. Holbach and Mark A. Bourassa

Abstract

Tropical cyclogenesis in the eastern North Pacific (EPAC) basin is related to gap-wind-induced surface relative vorticity, the monsoon trough, and the intertropical convergence zone (ITCZ). There are several gaps in the Central American mountains, on the eastern edge of the EPAC basin, through which wind can be funneled to generate surface wind jets (gap winds). This study focuses on gap winds that occur over the Gulf of Papagayo and Gulf of Tehuantepec. Quick Scatterometer (QuikSCAT) 10-m equivalent neutral winds are used to identify gap wind events that occur during May through November of 2002–08. Dvorak fix locations, Gridded Satellite (GridSat) infrared (IR) data, and National Hurricane Center (NHC) tropical cyclone (TC) reports are used to track the disturbances during the study period. Surface vorticity is tracked using the QuikSCAT winds and the contribution of surface vorticity from the gap winds to the development of each disturbance is categorized as small, medium, or large. Cross-calibrated multiplatform surface wind data are used to verify the tracking of QuikSCAT-computed surface vorticity and to identify when the monsoon trough and the ITCZ are present. It is found that gap winds are present over the Gulf of Papagayo and Gulf of Tehuantepec for about 50% of the QuikSCAT coverage days and that these gap winds appear to contribute to the development of disturbances in the EPAC. Considerably more TCs form when the monsoon trough is present versus the ITCZ and the majority of the contributions from the gap winds also occur when the monsoon trough is present.

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Steven M. DiNapoli, Mark A. Bourassa, and Mark D. Powell

Abstract

The Hurricane Research Division (HRD) Real-time Hurricane Wind Analysis System (H*Wind) is a software application used by NOAA’s HRD to create a gridded tropical cyclone wind analysis based on a wide range of observations. These analyses are used in both forecasting and research applications. Although mean bias and RMS errors are listed, H*Wind lacks robust uncertainty information that considers the contributions of random observation errors, relative biases between observation types, temporal drift resulting from combining nonsimultaneous measurements into a single analysis, and smoothing and interpolation errors introduced by the H*Wind analysis. This investigation seeks to estimate the total contributions of these sources, and thereby provide an overall uncertainty estimate for the H*Wind product.

A series of statistical analyses show that in general, the total uncertainty in the H*Wind product in hurricanes is approximately 6% near the storm center, increasing to nearly 13% near the tropical storm force wind radius. The H*Wind analysis algorithm is found to introduce a positive bias to the wind speeds near the storm center, where the analyzed wind speeds are enhanced to match the highest observations. In addition, spectral analyses are performed to ensure that the filter wavelength of the final analysis product matches user specifications. With increased knowledge of bias and uncertainty sources and their effects, researchers will have a better understanding of the uncertainty in the H*Wind product and can then judge the suitability of H*Wind for various research applications.

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Mark A. Bourassa, Dayton G. Vincent, and W. L. Wood

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A simple coupled flux and sea state model is developed. It is applicable to low, moderate, and high wind speeds, with a nonarbitrary wave age. It is fully consistent with an atmospheric flux parameterization. The flux model includes the influence of capillary waves on surface stress, which dominate surface stress on a wave-perturbed surface for U10 < 7 m s−1. The coupled model is verified for conditions of local equilibrium and it is used to examine the influences of surface tension and capillary waves on the equilibrium sea state at low and moderate wind speeds (U10 < 7 m s−1). Capillary waves can directly influence characteristics of the airflow (roughness length and friction velocity), and surface tension can directly influence wave characteristics (period, phase speed, and wave age). The influences of capillary waves and surface tension on wave characteristics are found to be noticeable for U10 < 6 m s−1, and are likely to be significant in most applications when U10 < 5 m s−1. The conditions under which relations valid for higher wind speeds break down are discussed. The new sea state parameterization is an improvement over previous relations (which apply well for U10 > 7 m s−1) because it is also applicable for low and moderate winds. The mean wind speed over most of the world's oceans is less than 7 m s−1, so there is considerable need for such a parameterization. The nonarbitrary wave age is particularly important because of the influence of wave age on the shape and size of waves, as well as fluxes of momentum, heat, and moisture.

Additional results include a criterion for the capillary cutoff, significant wave height, and dominant wave period (as functions of wind speed and wave age). Consistency with a flux parameterization is crucial because of the influence of atmospheric stability on surface stress, which influences wave characteristics. The modeled significant wave height for local equilibrium is shown to be consistent with several parameterizations. The modeled dominant period is a good match to that of the Pierson–Moskowitz spectrum when U10 > 13 m s−1; however, for lower wind speeds, the modeled period differs significantly from that of the Pierson–Moskowitz spectrum. The new model is validated with field observations. The differences are largely due to the capillary cutoff, which was not considered by Pierson and Moskowitz.

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Ryan J. Sharp, Mark A . Bourassa, and James J. O'Brien

A method for early detection of the systems that become tropical cyclones (TCs) in the Atlantic hurricane basin is developed using the SeaWinds scatterometer aboard the QuikSCAT satellite. The method is based on finding positive vorticity signals exceeding a threshold magnitude and horizontal extent within the swath of vector wind observations. The thresholds applied herein are subjectively derived from the TCs of the 1999 Atlantic hurricane season. The thresholds are applied to two sets of data for the 2000 season: research-quality data and near-real-time (< 3-h delay) data (available starting 18 August 2000). For the 2000 research-quality data, 7 of 18 TCs had signals that were detected an average of 27 h before the National Hurricane Center (NHC) classified them as tropical depressions. For the near-real-time data, 3 of 12 TCs had signals that were detected an average of 20 h before NHC classification. The SeaWinds scatterometer is a powerful new tool that, in addition to other conventional products (e.g., satellite images that determine if convection is organized and persistent), could help the NHC detect potential TCs earlier.

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Heather M. Holbach, Eric W. Uhlhorn, and Mark A. Bourassa

Abstract

Wind and wave-breaking directions are investigated as potential sources of an asymmetry identified in off-nadir remotely sensed measurements of ocean surface brightness temperatures obtained by the Stepped Frequency Microwave Radiometer (SFMR) in high-wind conditions, including in tropical cyclones. Surface wind speed, which dynamically couples the atmosphere and ocean, can be inferred from SFMR ocean surface brightness temperature measurements using a radiative transfer model and an inversion algorithm. The accuracy of the ocean surface brightness temperature to wind speed calibration relies on accurate knowledge of the surface variables that are influencing the ocean surface brightness temperature. Previous studies have identified wind direction signals in horizontally polarized radiometer measurements in low to moderate (0–20 m s−1) wind conditions over a wide range of incidence angles. This study finds that the azimuthal asymmetry in the off-nadir SFMR brightness temperature measurements is also likely a function of wind direction and extends the results of these previous studies to high-wind conditions. The off-nadir measurements from the SFMR provide critical data for improving the understanding of the relationships between brightness temperature, surface wave–breaking direction, and surface wind vectors at various incidence angles, which is extremely useful for the development of geophysical model functions for instruments like the Hurricane Imaging Radiometer (HIRAD).

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Anthony Arguez, Mark A. Bourassa, and James J. O’Brien

Abstract

Wind data from the SeaWinds instrument on NASA’s Quick Scatterometer (QuikSCAT) satellite are investigated to ascertain how well the surface manifestation of the Madden–Julian oscillation (MJO) can be resolved. The MJO signal is detected in nonfiltered gridded data using extended EOF analysis of the zonal wind field, overshadowed by annual, semiannual, and monsoon-related modes. After bandpass filtering with Lanczos weights, MJO signals are clearly detected in several kinematic quantities, including the zonal wind speed, the zonal pseudostress, and the velocity potential. Extraction of the MJO using QuikSCAT winds compares favorably with extraction using NCEP Reanalysis 2, except that the QuikSCAT signal appears to be more robust.

In addition, an alternative bandpass-filtering technique using variable filter weights near time series endpoints is presented. The method uses least squares minimization to match newly created frequency response functions in edge zones as closely as possible to the predetermined frequency response function of interior points. This method stands in contrast to the common practice of simply discarding those endpoints where a convolution cannot be computed.

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