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Jeffrey Hawkins and Christopher Velden

Atmospheric and oceanographic field experiments are an important part of research programs aimed at enhancing observational analyses of meteorological and oceanic phenomena, validating new datasets, and/or supporting hypotheses. The Bulletin of the American Meteorological Society (BAMS) has chronicled many field programs, with a primary focus on the enhanced observational assets that were assembled to enable the projects' investigations. However, these field program summaries often overlook the multiple roles that satellite digital data, multispectral imagery, and derived products can play in premission planning, real-time forecasting and mission guidance, and extensive post–field phase analysis. In turn, these intensive observing periods often serve as crucial validation datasets for remotely sensed products and derived fields.

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A Study of the Mesoscale Wind Circulation in a Land-Sea Breeze Regime

Student Paper—First Place Winner of the Father James B. Macelwane Annual Award in Meteorology

Jeffrey D. Hawkins

The mesoscale wind circulation along the central Oregon coast is investigated by use of surface data gathered during the Coastal Upwelling Experiment 2 (CUE-2). A case with prevailing NNW winds, typical of the general pattern, was studied intensely and was compared with results from a similar study for a SE flow.

Buoy and coastal land station data provide time series and diurnal plots of: 1) the air and sea surface temperature; 2) the horizontal wind components; and 3) the wind speed.

The case with prevailing NNW winds (26–28 July 1973) had the following important characteristics: 1) a well-defined sea breeze event with supporting coastal temperature differential and less significant land breeze; 2) the formation of an eddy south of Cape Lookout; and 3) strong upwelling and sea surface temperatures affected by surface winds. In contrast, the case with SE winds (23–24 August 1973) showed only a noticeable sea breeze event with half the coastal temperature differential of the previous case.

It is strongly suggested that the mesoscale surface winds and the factors that influence them in this region be studied further if sea surface temperature forecasts are to be made.

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Douglas A. May, Jeffrey0 Hawkins, and Robert L. Pickett

Abstract

Efforts to monitor the Gulf of Mexico Loop Current and mesoscale ocean features using IR satellite imagery in the summertime have been significantly hindered by 1) strong surface heating that masks surface frontal gradients and 2) extremely high atmospheric water vapor attenuation that lowers effective satellite brightness-temperature values. These problems can now be addressed, provided high-quality multichannel infrared data are available during nighttime satellite passes. The National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) consists of three IR channels that include channels 3 (3.55–3.93 µm), 4 (10.3–11.3 µm), and 5 (11.5–12.5 µm). Of these, channel 3 is least affected by water vapor attenuation, making it better suited for viewing the ocean through a humid atmosphere. All satellites prior to NOAA-11, however, experienced substantial noise in channel 3 soon after launch, rendering the channel relatively useless for long-term oceanographic monitoring. NOAA-11, with a high-quality 3.7-µm channel, has enabled us to detect Loop Current and eddy features throughout the typical worst summertime conditions. A three-channel cross-product sea surface temperature (CPSST) algorithm was applied to nighttime images in August and September 1990 to monitor the Loop Current a major warm-core eddy (Quiet Eddy), and a minor warm-core eddy (Quiet Eddy II). Feature locations are verified using drifting data buoys. This capability demonstrates the importance of a low-noise AVHRR channel 3, and will increase our knowledge about Loop Current dynamics and ring periodicity during periods previously unfavorable for IR images.

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James S. Goerss, Christopher S. Velden, and Jeffrey D. Hawkins

Abstract

Experimental wind datasets were derived for two time periods (13–20 July and 24 August–10 September 1995) from GOES-8 observations processed at the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW CIMSS). The first dataset was focused on Tropical Storm Chantal, and the second dataset was focused on the multiple-storm environment that included Hurricanes Humberto, Iris, and Luis. Both datasets feature a processing and quality control strategy designed to optimize the quantity and content of geostationary satellite-derived winds in the vicinity of tropical cyclones. Specifically, the winds were extracted from high-density targets obtained from multispectral imagery, which included three water vapor bands (6.7, 7.0, and 7.3 μm), infrared, and visible. The Navy Operational Global Atmospheric Prediction System (NOGAPS) was used as the vehicle to determine the impact of these winds upon tropical cyclone track forecasts. During the 1995 Atlantic hurricane season the NOGAPS forecasts were found to be quite skillful, displaying relative improvement of tropical cyclone position error with respect to CLIPER (climate and persistence) of 20% at 24 h, 35% at 48 h, and 33% at 72 h. The NOGAPS data assimilation system was run with and without the high-density GOES-8 winds for the two aforementioned time periods. The assimilation of these winds resulted in significant improvements in the NOGAPS forecasts for Tropical Storm Chantal and Hurricane Iris and mixed results for Hurricanes Humberto and Luis. Overall, for all four cyclones, the NOGAPS forecasts made with the use of the UW CIMSS winds displayed relative improvement of forecast position error with respect to those made without the use of the UW CIMSS winds of 14% at 24 h, and 12% at both 48 and 72 h.

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Thomas F. Lee, Francis J. Turk, Jeffrey Hawkins, and Kim Richardson

Abstract

Images of the 85-GHz frequency from the Special Sensor Microwave Imager (SSM/I) aboard the Defense Meteorological Satellite Program (DMSP) spacecraft are routinely viewed by forecasters for tropical cyclone analyses. These images are valued because of their ability to observe tropical cyclone structure and to locate center positions. Images of lower-frequency SSM/I channels, such as 37 GHz, have poor quality due to the coarse spatial resolution, and therefore 85 GHz has become the de facto analysis standard. However, the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), launched in 1997, has much better spatial resolution for all channels than the SSM/I. Although originally designed to investigate precipitation for climate research, real-time images are now sent into tropical cyclone forecast offices, and posted to Web pages of the Naval Research Laboratory and the Fleet Numerical Meteorology and Oceanography Center, both in Monterey, California. TMI images of 37 GHz have a number of properties that make them useful complements to images of 85 GHz. They have the capacity to detect low-level circulation centers, which are sometimes unseen at 85 GHz. Also, because the 37-GHz channel generally senses atmospheric layers much nearer to the surface than 85 GHz, parallax error is less, allowing more accurate fixes. This paper presents several case studies comparing the two TMI frequencies and offers some forecasting guidelines for when to use each.

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Cristian Mitrescu, Steven Miller, Jeffrey Hawkins, Tristan L’Ecuyer, Joseph Turk, Philip Partain, and Graeme Stephens

Abstract

Within 2 months of its launch in April 2006 as part of the Earth Observing System A-Train satellite constellation, the National Aeronautics and Space Administration Earth System Science Pathfinder (ESSP) CloudSat mission began making significant contributions toward broadening the understanding of detailed cloud vertical structures around the earth. Realizing the potential benefit of CloudSat to both the research objectives and operational requirements of the U.S. Navy, the Naval Research Laboratory coordinated early on with the CloudSat Data Processing Center to receive and process first-look 94-GHz Cloud Profiling Radar datasets in near–real time (4–8 h latency), thereby making the observations more relevant to the operational community. Applications leveraging these unique data, described herein, include 1) analysis/validation of cloud structure and properties derived from conventional passive radiometers, 2) tropical cyclone vertical structure analysis, 3) support of research field programs, 4) validation of numerical weather prediction model cloud fields, and 5) quantitative precipitation estimation in light rainfall regimes.

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Peter G. Black, Russell L. Elsberry, Lynn K. Shay, Ray P. Partridge, and Jeffrey D. Hawkins

Abstract

Three drifting buoys were successfully air-dropped ahead of Hurricane Josephine. This deployment resulted in detailed simultaneous measurements of surface wind speed, surface pressure and subsurface ocean temperature during and subsequent to storm passage. This represents the first time that such a self-consistent data set of surface conditions within a tropical cyclone has been collected. Subsequent NOAA research overflights of the buoys, as part of a hurricane planetary boundary-layer experiment, showed that aircraft wind speeds, extrapolated to the 20 m level, agreed to within ±2 m s−1, pressures agreed to within ±1 mb, and sea-surface temperatures agreed to within ±0.8°C of the buoy values. Ratios of buoy peak 1 min wind (sustained wind) to one-half h mean wind > 1.3 were found to coincide with eyewall and principal rainband features.

Buoy trajectories and subsurface temperature measurements revealed the existence of a series of mesoscale eddies in the subtropical front. Buoy data revealed storm-generated, inertia-gravity-wave motions superposed upon mean current fields, which reached a maximum surface speed > 1.2 m s−1 immediately following storm passage. A maximum mixed-layer-temperature decrease of 1.8°C was observed to the right of the storm path. A temperature increase of 3.5°C at 100 m and subsequent decrease of 4.8°C following storm passage indicated a combination of turbulent mixing, upwelling and horizontal advection processes.

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Jeffrey D. Hawkins, Thomas F. Lee, Joseph Turk, Charles Sampson, John Kent, and Kim Richardson

Tropical cyclone (TC) monitoring requires the use of multiple satellites and sensors to accurately assess TC location and intensity. Visible and infrared (vis/IR) data provide the bulk of TC information, but upper-level cloud obscurations inherently limit this important dataset during a storm's life cycle. Passive microwave digital data and imagery can provide key storm structural details and offset many of the vis/IR spectral problems. The ability to view storm rainbands, eyewalls, impacts of shear, and exposed low-level circulations, whether it is day or night, makes passive microwave data a significant tool for the satellite analyst. Passive microwave capabilities for TC reconnaissance are demonstrated via a near-real-time Web page created by the Naval Research Laboratory in Monterey, California. Examples are used to illustrate tropical cyclone monitoring. Collocated datasets are incorporated to enable the user to see many aspects of a storm's organization and development by quickly accessing one location.

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Steven D. Miller, John M. Forsythe, Philip T. Partain, John M. Haynes, Richard L. Bankert, Manajit Sengupta, Cristian Mitrescu, Jeffrey D. Hawkins, and Thomas H. Vonder Haar

Abstract

The launch of the NASA CloudSat in April 2006 enabled the first satellite-based global observation of vertically resolved cloud information. However, CloudSat’s nonscanning W-band (94 GHz) Cloud Profiling Radar (CPR) provides only a nadir cross section, or “curtain,” of the atmosphere along the satellite ground track, precluding a full three-dimensional (3D) characterization and thus limiting its utility for certain model verification and cloud-process studies. This paper details an algorithm for extending a limited set of vertically resolved cloud observations to form regional 3D cloud structure. Predicated on the assumption that clouds of the same type (e.g., cirrus, cumulus, and stratocumulus) often share geometric and microphysical properties as well, the algorithm identifies cloud-type-dependent correlations and uses them to estimate cloud-base height and liquid/ice water content vertical structure. These estimates, when combined with conventional retrievals of cloud-top height, result in a 3D structure for the topmost cloud layer. The technique was developed on multiyear CloudSat data and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) swath data from the NASA Aqua satellite. Data-exclusion experiments along the CloudSat ground track show improved predictive skill over both climatology and type-independent nearest-neighbor estimates. More important, the statistical methods, which employ a dynamic range-dependent weighting scheme, were also found to outperform type-dependent near-neighbor estimates. Application to the 3D cloud rendering of a tropical cyclone is demonstrated.

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James P. Kossin, John A. Knaff, Howard I. Berger, Derrick C. Herndon, Thomas A. Cram, Christopher S. Velden, Richard J. Murnane, and Jeffrey D. Hawkins

Abstract

New objective methods are introduced that use readily available data to estimate various aspects of the two-dimensional surface wind field structure in hurricanes. The methods correlate a variety of wind field metrics to combinations of storm intensity, storm position, storm age, and information derived from geostationary satellite infrared (IR) imagery. The first method estimates the radius of maximum wind (RMW) in special cases when a clear symmetric eye is identified in the IR imagery. The second method estimates RMW, and the additional critical wind radii of 34-, 50-, and 64-kt winds for the general case with no IR scene–type constraint. The third method estimates the entire two-dimensional surface wind field inside a storm-centered disk with a radius of 182 km. For each method, it is shown that the inclusion of infrared satellite data measurably reduces error. All of the methods can be transitioned to an operational setting or can be used as a postanalysis tool.

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