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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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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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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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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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Mark A. Bourassa
,
Ernesto Rodriguez
, and
Rob Gaston
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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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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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Mark A. Bourassa
,
Dayton G. Vincent
, and
W. L. Wood

Abstract

An air–sea interaction model that includes turbulent transport due to capillary waves (surface ripples) is developed. The model differs from others in that the physical premises are applicable to low wind speeds (10-m wind speed, U 10 < 5 m s−1) as well as higher wind speeds. Another new feature of the model is an anisotropic roughness length, which allows a crosswind component of the stress to be modeled. The influence of the angle between the mean wind direction and the mean direction of wave propagation is included in the anisotropic roughness length.

Most models are not accurate at low wind speeds and tend to underestimate fluxes in low wind speed regions such as the tropical oceans. Improvements over previous models are incorporated in the momentum roughness length parameterization. In addition, the dimensionless constant in the relationship between the capillary wave component of momentum roughness length and friction velocity is reevaluated using both wave tank data and field data. The new value is found to be 0.06, a factor of 3 smaller than the original estimate of 0.18. Modeling the influence of capillary waves is shown to improve the accuracy of modeled surface fluxes and drag coefficients. Several sets of tropical observations are used to examine mean increases in modeled fluxes due to capillary waves. The changes in latent heat fluxes are compared to proposed increases due to convective overturning (sometimes called gustiness) and are found to be larger by a factor of 4. For U 10 < 7 m s−1, the mean estimates for tropical fluxes of momentum and latent heat are found to increase by 0.004 N m−2 and 6 W m−2.

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Stephen R. Guimond
,
Mark A. Bourassa
, and
Paul D. Reasor

Abstract

Despite the fact that latent heating in cloud systems drives many atmospheric circulations, including tropical cyclones, little is known of its magnitude and structure, largely because of inadequate observations. In this work, a reasonably high-resolution (2 km), four-dimensional airborne Doppler radar retrieval of the latent heat of condensation/evaporation is presented for rapidly intensifying Hurricane Guillermo (1997). Several advancements in the basic retrieval algorithm are shown, including 1) analyzing the scheme within the dynamically consistent framework of a numerical model, 2) identifying algorithm sensitivities through the use of ancillary data sources, and 3) developing a precipitation budget storage term parameterization. The determination of the saturation state is shown to be an important part of the algorithm for updrafts of ~5 m s−1 or less.

The uncertainties in the magnitude of the retrieved heating are dominated by errors in the vertical velocity. Using a combination of error propagation and Monte Carlo uncertainty techniques, biases are found to be small, and randomly distributed errors in the heating magnitude are ~16% for updrafts greater than 5 m s−1 and ~156% for updrafts of 1 m s−1. Even though errors in the vertical velocity can lead to large uncertainties in the latent heating field for small updrafts/downdrafts, in an integrated sense the errors are not as drastic.

In Part II, the impact of the retrievals is assessed by inserting the heating into realistic numerical simulations at 2-km resolution and comparing the generated wind structure to the Doppler radar observations of Guillermo.

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David E. Weissman
,
Mark A. Bourassa
, and
Jeffrey Tongue

Abstract

Rain within the footprint of the SeaWinds scatterometer on the QuikSCAT satellite causes more significant errors than existed with its predecessor, the NASA scatterometer (NSCAT) on Advanced Earth Observing Satellite-I (ADEOS-I). Empirical relations are developed that show how the rain-induced errors in the scatterometer wind magnitude depend on both the rain rate and on the wind magnitude. These relations are developed with collocated National Data Buoy Center (NDBC) buoy measurements (to provide accurate sea surface winds) and simultaneous Next Generation Weather Radar (NEXRAD) observations of rain reflectivity. An analysis, based on electromagnetic scattering theory, interprets the dependence of the scatterometer wind errors on volumetric rain rate over a range of wind and rain conditions. These results demonstrate that the satellite scatterometer responds to rain in a manner similar to that of meteorological radars, with a ZR relationship. These observations and results indicate that the combined (wind and rain) normalized radar cross section will lead to erroneously large wind estimates when the rain-related radar cross section exceeds a particular level that depends on the rain rate and surface wind speed.

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