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James R. Jordan and Richard J. Lataitis

Abstract

Clear-air Doppler wind profilers perform poorly in dry, calm conditions when reflectivities are low. One solution to this problem is to use acoustic waves, generated by a collocated acoustic source, as the scattering target instead of clear-air turbulence. The idea for such an acoustically enhanced profiler was proposed more than 10 years ago. In a recent Antarctic experimental campaign, a vertically pointing acoustic source was used to extend the coverage of a standard four-beam 915-MHz wind profiler. Preliminary testing of the system revealed large biases in the retrieved wind profiles. A simple theory and a limited dataset suggest that the observed biases are consistent with a nonuniform acoustic illumination of the radar beams caused by the different acoustic and radar beam pointing angles. Our results suggest that this bias can be eliminated by aligning the acoustic and radar beams.

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J. A. Schroeder, J. R. Jordan, and M. T. Decker

Abstract

A modular design for a ground-based thermodynamic profiler is presented, based on experience with a six-channel microwave radiometer that has provided temperature, pressure, and moisture measurements continuously, unattended, since 1981. Each module consists of one pair of microwave channels, whose frequencies are chosen to facilitate the joint use of radio-frequency (RF) components, thus reducing hardware costs by nearly half. The number of modules included in a given system can be chosen to suit the altitude and accuracy requirements for that particular application. The accuracy of temperatures and pressure heights retrieved from simulated profilers with 4 to 18 channels is presented to illustrate the tradeoff between cost and accuracy.

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James R. Jordan, Richard J. Lataitis, and David A. Carter

Abstract

New algorithms for removing ground and intermittent clutter contamination from wind profiler data are presented. The techniques use wavelet transforms to “filter” the contribution of clutter to the wind profiler signals. Examples of typical clutter contamination using simulated and actual signals are presented. The corresponding Doppler spectra before and after wavelet filtering are compared. The authors find that wavelet filtering can reduce the clutter-to-clear-air signal power by as much as 40 dB, even when the clutter and clear-air peaks cannot be resolved in the Doppler spectrum. The enhancement in clear-air signal detectability in the presence of clutter is due to the more efficient separation of clutter and clear-air energy in the wavelet domain.

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Jordan R. Bell, Esayas Gebremichael, Andrew L. Molthan, Lori A. Schultz, Franz J. Meyer, Christopher R. Hain, Suravi Shrestha, and K. Cole Payne

Abstract

The normalized difference vegetation index (NDVI) has been frequently used to map hail damage to vegetation, especially in agricultural areas, but observations can be blocked by cloud cover during the growing season. Here, the European Space Agency’s Sentinel-1A/1B C-band synthetic aperture radar (SAR) imagery in co- and cross polarization is used to identify changes in backscatter of corn and soybeans damaged by hail during intense thunderstorm events in the early and late growing season. Following a June event, hail-damaged areas produced a lower mean backscatter when compared with surrounding, unaffected pixels [vertical–vertical (VV): −1.1 dB; vertical–horizontal (VH): −1.5 dB]. Later, another event in August produced an increase in co- and cross-polarized backscatter (VV: 0.7 dB; VH: 1.7 dB) that is hypothesized to result from the combined effects of crop growth, change in structure of damaged crops, and soil moisture conditions. Hail damage regions inferred from changes in backscatter were further assessed through coherence change detections to support changes in the structure of crops damaged within the hail swath. While studies using NDVI have routinely concluded a decrease in NDVI is associated with damage, the cause of change with respect to the damaged areas in SAR backscatter values is more complex. Influences of environmental variables, such as vegetation structure, vegetation maturity, and soil moisture conditions, need to be considered when interpreting SAR backscatter and will vary throughout the growing season.

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Andrew L. Molthan, Lori A. Schultz, Kevin M. McGrath, Jason E. Burks, J. Parks Camp, Kelsey Angle, Jordan R. Bell, and Gary J. Jedlovec

Abstract

Severe weather events including tornadoes, damaging winds, hail, and their combination produce changes in land surface vegetation and urban settings that are frequently observed through remote sensing. Capabilities continue to improve through a growing constellation of governmental and commercial assets, increasing the spatial resolution of visible, near to shortwave infrared, and thermal infrared remote sensing. Here, we highlight cases where visual interpretation of imagery benefitted severe weather damage assessments made within the NOAA/NWS Damage Assessment Toolkit. Examples demonstrate utility of imagery in assessing tracks and changes in remote areas where staffing limitations or access prevent a ground-based assessment.

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Andrew L. Molthan, Lori A. Schultz, Kevin M. McGrath, Jason E. Burks, J. Parks Camp, Kelsey Angle, Jordan R. Bell, and Gary J. Jedlovec
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W. L. Smith, H. E. Rvercomb, H. B. Howell, H. M. Woolf, R. O. Knuteson, R G. Decker, M. J. Lynch, E. R. Westwater, R. G. Strauch, K. P. Moran, B. Stankov, M. J. Falls, J. Jordan, M. Jacobsen, W. F. Dabberdt, R. McBeth, G. Albright, C. Paneitz, G. Wright, P. T. May, and M. T. Decker

During the week 29 October–4 November 1988, a Ground-based Atmospheric Profiling Experiment (GAPEX) was conducted at Denver Stapleton International Airport. The objective of GAPEX was to acquire and analyze atomspheric-temperature and moisture-profile data from state-of-the-art remote sensors. The sensors included a six-spectral-channel, passive Microwave Profiler (MWP), a passive, infrared High-Resolution Interferometer Sounder (HIS) that provides more than 1500 spectral channels, and an active Radio Acoustic Sounding System (RASS). A Cross-Chain Loran Atmospheric Sounding System (CLASS) was used to provide research-quality in situ thermodynamic observations to verify the accuracy and resolution characteristics of each of the three remote sensors. The first results of the project are presented here to inform the meteorological community of the progress achieved during the GAPEX field phase. These results also serve to demonstrate the excellent prospects for an accurate, continuous thermodynamic profiling system to complement NOAA's forthcoming operational wind profiler.

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J. M. Wilczak, R. G. Strauch, F. M. Ralph, B. L. Weber, D. A. Merritt, J. R. Jordan, D. E. Wolfe, L. K. Lewis, D. B. Wuertz, J. E. Gaynor, S. A. McLaughlin, R. R. Rogers, A. C. Riddle, and T. S. Dye

Abstract

Winds measured with 915- and 404-MHz wind profilers are frequently found to have nonrandom errors as large as 15 m s−1 when compared to simultaneously measured rawinsonde winds. Detailed studies of these errors which occur only at night below about 4 km in altitude and have a pronounced seasonal pattern, indicate that they are due to the wind profilers' detection of migrating songbirds (passerines). Characteristics of contaminated data at various stages of data processing are described, including raw time series, individual spectra, averaged spectra, 30- or 60-s moments, 3- or 6-min winds, and hourly averaged winds. An automated technique for the rejection of contaminated data in historical datasets, based on thresholding high values of rnoment-level reflectivity and spectral width, is shown to be effective. Techniques designed for future wind profiter data acquisition systems are described that show promise for rejecting bird echoes, with the additional capability of being able to retrieve the true wind velocity in many instances. Finally, characteristics of bird migration revealed by wind profilers are described, including statistics of the spring (March–May) 1993 migration season determined from the 404-MHz Wind Profiler Demonstration Network (WPDN). During that time, contamination of moment data occurred on 43% of the nights monitored.

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Steven J. Goodman, James Gurka, Mark DeMaria, Timothy J. Schmit, Anthony Mostek, Gary Jedlovec, Chris Siewert, Wayne Feltz, Jordan Gerth, Renate Brummer, Steven Miller, Bonnie Reed, and Richard R. Reynolds

The Geostationary Operational Environmental Satellite R series (GOES-R) Proving Ground engages the National Weather Service (NWS) forecast, watch, and warning community and other agency users in preoperational demonstrations of the new and advanced capabilities to be available from GOES-R compared to the current GOES constellation. GOES-R will provide significant advances in observing capabilities but will also offer a significant challenge to ensure that users are ready to exploit the new 16-channel imager that will provide 3 times more spectral information, 4 times the spatial coverage, and 5 times the temporal resolution compared to the current imager. In addition, a geostationary lightning mapper will provide continuous and near-uniform real-time surveillance of total lightning activity throughout the Americas and adjacent oceans encompassing much of the Western Hemisphere. To ensure user readiness, forecasters and other users must have access to prototype advanced products within their operational environment well before launch. Examples of the advanced products include improved volcanic ash detection, lightning detection, 1-min-interval rapid-scan imagery, dust and aerosol detection, and synthetic cloud and moisture imagery. A key component of the GOES-R Proving Ground is the two-way interaction between the researchers who introduce new products and techniques and the forecasters who then provide feedback and ideas for improvements that can best be incorporated into NOAA's integrated observing and analysis operations. In 2012 and beyond, the GOES-R Proving Ground will test and validate display and visualization techniques, decision aids, future capabilities, training materials, and the data processing and product distribution systems to enable greater use of these products in operational settings.

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J. Fishman, L. T. Iraci, J. Al-Saadi, K. Chance, F. Chavez, M. Chin, P. Coble, C. Davis, P. M. DiGiacomo, D. Edwards, A. Eldering, J. Goes, J. Herman, C. Hu, D. J. Jacob, C. Jordan, S. R. Kawa, R. Key, X. Liu, S. Lohrenz, A. Mannino, V. Natraj, D. Neil, J. Neu, M. Newchurch, K. Pickering, J. Salisbury, H. Sosik, A. Subramaniam, M. Tzortziou, J. Wang, and M. Wang

The Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission was recommended by the National Research Council's (NRC's) Earth Science Decadal Survey to measure tropospheric trace gases and aerosols and coastal ocean phytoplankton, water quality, and biogeochemistry from geostationary orbit, providing continuous observations within the field of view. To fulfill the mandate and address the challenge put forth by the NRC, two GEO-CAPE Science Working Groups (SWGs), representing the atmospheric composition and ocean color disciplines, have developed realistic science objectives using input drawn from several community workshops. The GEO-CAPE mission will take advantage of this revolutionary advance in temporal frequency for both of these disciplines. Multiple observations per day are required to explore the physical, chemical, and dynamical processes that determine tropospheric composition and air quality over spatial scales ranging from urban to continental, and over temporal scales ranging from diurnal to seasonal. Likewise, high-frequency satellite observations are critical to studying and quantifying biological, chemical, and physical processes within the coastal ocean. These observations are to be achieved from a vantage point near 95°–100°W, providing a complete view of North America as well as the adjacent oceans. The SWGs have also endorsed the concept of phased implementation using commercial satellites to reduce mission risk and cost. GEO-CAPE will join the global constellation of geostationary atmospheric chemistry and coastal ocean color sensors planned to be in orbit in the 2020 time frame.

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