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Kenneth S. Gage and Earl E. Gossard

Abstract

This review begins with a brief look at the early perspectives on turbulence and the role of Dave Atlas in the unfolding of mysteries concerning waves and turbulence as seen by powerful radars. The remainder of the review is concerned with recent developments that have resulted in part from several decades of radar and Doppler radar profiler research that have been built upon the earlier foundation.

A substantial part of this review is concerned with evaluating the intensity of atmospheric turbulence. The refractivity turbulence structure-function parameter C 2 n , where n is radio refractive index, is a common metric for evaluating the intensity of refractivity turbulence and progress has been made in evaluating its climatology. The eddy dissipation rate is a common measure of the intensity of turbulence and a key parameter in the Kolmogorov theory for locally homogeneous isotropic turbulence. Much progress has been made in the measurement of the eddy dissipation rate under a variety of meteorological conditions including within clouds and in the presence of precipitation. Recently, a new approach using dual frequencies has been utilized with improved results.

It has long been recognized that atmospheric turbulence especially under hydrostatically stable conditions is nonhomogeneous and layered. The layering means that the eddy dissipation and eddy diffusivity is highly variable especially in the vertical. There is ample observational evidence that layered fine structure is responsible for the aspect sensitive echoes observed by vertically directed very high frequency VHF profilers. In situ observations by several groups have verified that coherent submeter-scale structure is present in the refractivity field sufficient to account for the “clear air” radar echoes. However, despite some progress there is still no consensus on how these coherent structures are produced and maintained.

Advances in numerical modeling have led to new insights by simulating the structures observed by radars. This has been done utilizing direct numerical simulation (DNS) and large eddy simulation (LES). While DNS is especially powerful for examining the breaking of internal waves and the transition to turbulence, LES had been especially valuable in modeling the atmospheric boundary layer.

Internal gravity waves occupy the band of intrinsic frequencies bounded above by the Brunt–Väisälä frequency and below by the inertial frequency. These waves have many sources and several studies in the past decade have improved our understanding of their origin. Observational studies have shown that the amplitude of the mesoscale spectrum of motions is greater over mountainous regions than over flat terrain or oceans. Thus, it would appear that flow over nonuniform terrain is an important source for waves. Several numerical studies have successfully simulated the generation of internal waves from convection. Most of these are believed to result from deep convection with substantial wave motion extending into the upper troposphere, stratosphere, and mesosphere. Gravity waves known as convection waves are often seen in the stable free atmosphere that overlay convective boundary layers.

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Kenneth S. Gage and William H. Jasperson

The METRAC positioning system is a ground-based radio location system that makes use of the Doppler principle in order to track an inexpensive, expendable transmitter. A prototype system has recently been built and evaluated for the Environmental Protection Agency for possible use in the Regional Air Pollution Study Program. This paper presents a brief description of the METRAC system and some of the results of a field test of the prototype system conducted in Minneapolis. The field test consisted of a comparison of wind profiles derived from the METRAC system with wind profiles derived from simultaneous rawinsonde and theodolite tracking. The results of this test demonstrate the great accuracy and high-resolution of winds measured by the prototype system.

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George C. Reid and Kenneth S. Gage

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The existence of an annual variation in height and temperature of the tropopause over tropical regions has long been recognized, but has not been fully explained. In this paper it is proposed that the variation is a fairly direct response to the annual variation in average tropical surface insolation. The variation in insolation causes a corresponding annual cycle in average tropical sea surface temperature with a total range of order 1 K. The consequent variation in absolute humidity in turn produces an annual variation in upper tropospheric potential temperatures, and hence in the height and temperature of the tropopause.

The physical link between the surface and the tropopause is provided by convection in the cores of the giant cumulonimbus clouds (hot towers) of the tropical oceanic regions, in which air parcels can achieve the maximum possible heating by release of latent heat. The process is modeled quantitatively in a simplified way, and excellent agreement is found between the predicted and observed phase and amplitude of the annual variation in tropopause potential temperature.

Since the regular seasonal variation in insolation is relatively small in the tropics, the annual variation in sun-earth distance is an important factor in the variation of surface insolation. The annual cycle in the properties of the tropical tropopause thus provides the first identifiable effect of the earth's orbital eccentricity on climate parameters.

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Robert Schafer, Susan K. Avery, and Kenneth S. Gage

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VHF wind profiler measurements of zonal and meridional winds are compared with the NCEP–NCAR reanalysis at sites in the tropical Pacific. By December 1999 the profilers at Darwin, Australia, and Biak, Indonesia, in the western Pacific; Christmas Island, Kiribati, in the central Pacific; and Piura Peru, in the eastern Pacific had collected between 8 and 13 yr of nearly continuous data. While these profilers routinely observe winds up to about 20 km, only winds at Christmas Island are assimilated into the reanalysis. The long period of profiler operation provides an opportunity to study differences between the profiler and reanalysis winds in the equatorial Pacific, a region with geographically sparse observations. Mean and seasonal mean zonal and meridional winds are used to identify differences in the profiler and reanalysis winds. Two potential causes for the discrepancy between profiler and reanalysis winds are identified. The first of these is related to different spatial and temporal characteristics of the reanalysis and profiler data. The second cause is the geographical sparseness of rawinsonde data, and not assimilating wind profiler observations. The closest agreement between the mean and seasonal mean zonal winds was found at Christmas Island, a site at which profiler winds are assimilated. A good agreement between reanalysis and profiler meridional and zonal winds is also shown at Darwin, where nearby rawinsonde observations are available. The poorest agreement was found at Piura (where profiler winds are not assimilated), the closest rawinsonde is almost 2000 km from the profiler site, and topography is not adequately resolved in the reanalysis.

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Christopher R. Williams, Warner L. Ecklund, and Kenneth S. Gage

Abstract

An algorithm has been developed that classifies precipitating clouds into either stratiform, mixed stratiform/convective, deep convective, or shallow convective clouds by analyzing the vertical structure of reflectivity, velocity, and spectral width derived from measurements made with the vertical beam of a 915-MHz Doppler wind profiler. The precipitating clouds classified as stratiform and convective clouds match the physical and radar properties deduced by Doppler weather radars in the GATE and EMEX programs. The mixed stratiform/convective cloud category is a hybrid regime containing a melting-layer signature associated with stratiform clouds yet is turbulent above the melting level similar to convective clouds. Shallow convective clouds have hydrometeors confined entirely below the melting level implying that warm rain processes are occurring exclusively. The algorithm is illustrated by classifying precipitating clouds from 10 months of observations at Manus Island (2°S, 147°E) in the western Pacific. The sensitivity of the algorithm to threshold criteria is investigated using the Manus Island data.

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Christopher R. Williams, Kenneth S. Gage, Wallace Clark, and Paul Kucera

Abstract

This paper describes a method of absolutely calibrating and routinely monitoring the reflectivity calibration from a scanning weather radar using a vertically profiling radar that has been absolutely calibrated using a collocated surface disdrometer. The three instruments have different temporal and spatial resolutions, and the concept of upscaling is used to relate the small resolution volume disdrometer observations with the large resolution volume scanning radar observations. This study uses observations collected from a surface disdrometer, two profiling radars, and the National Weather Service (NWS) Weather Surveillance Radar-1988 Doppler (WSR-88D) scanning weather radar during the Texas–Florida Underflight-phase B (TEFLUN-B) ground validation field campaign held in central Florida during August and September 1998.

The statistics from the 2062 matched profiling and scanning radar observations during this 2-month period indicate that the WSR-88D radar had a reflectivity 0.7 dBZ higher than the disdrometer-calibrated profiler, the standard deviation was 2.4 dBZ, and the 95% confidence interval was 0.1 dBZ. This study implies that although there is large variability between individual matched observations, the precision of a series of observations is good, allowing meaningful comparisons useful for calibration and monitoring.

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Kenneth S. Gage, Christopher R. Williams, Wallace L. Clark, Paul E. Johnston, and David A. Carter

Abstract

Doppler radar profilers are widely used for routine measurement of wind, especially in the lower troposphere. The same profilers with minor modifications are useful tools for precipitation research. Specifically, the profilers are now increasingly being used to explore the structure of precipitating cloud systems and to provide calibration and validation of other instruments used in precipitation research, including scanning radars and active and passive satellite-borne sensors. A vertically directed profiler is capable of resolving the vertical structure of precipitating cloud systems that pass overhead. Standard profiler measurements include reflectivity, reflectivity-weighted Doppler velocity, and spectral width. This paper presents profiler observations of precipitating cloud systems observed during Tropical Rainfall Measuring Mission (TRMM) Ground Validation field campaigns. The observations show similarities and differences between convective systems observed in Florida; Brazil; and Kwajalein, Republic of the Marshall Islands. In addition, it is shown how a profiler can be calibrated using a collocated Joss–Waldvogel disdrometer, how the profiler can then be used to calibrate a scanning radar, and how the profiler may be used to retrieve drop size distributions.

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Robert Schafer, Susan K. Avery, Kenneth S. Gage, and George N. Kiladis

Abstract

UHF (boundary layer) and VHF (troposphere–stratosphere) wind profilers have operated at Christmas Island (2°N, 157°W) in the central equatorial Pacific from 1986 to 2002. Observed profiles of winds are sparse over the tropical oceans, but these are critical for understanding convective organization and the interaction of convection and waves. While the zonal winds below about 10 km have previously shown good agreement with the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis (RI), significant differences were found above a height of 10 km that were attributed to the low detectability of the wind signal in the profiler observations. Meridional winds at all levels show less agreement, with differences attributed to errors of representativeness and the sparseness of observations in the region. This paper builds on previous work using the Christmas Island wind profilers and presents the results of reprocessing the 17-yr profiler record with techniques that enhance the detectability of the signal at upper heights. The results are compared with nearby rawinsonde soundings obtained during a special campaign at Christmas Island and the RI, NCEP–Department of Energy (DOE) reanalysis (RII), and the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40). The newly processed profiler zonal and meridional wind observations show good agreement with rawinsonde observations from 0.5 to 19 km above sea level, with difference statistics similar to other studies. There is also significant improvement in the agreement of RI and RII reanalysis and profiler upper-level zonal and meridional winds from previous studies. A comparison of RII and ERA-40 reanalysis shows that difference statistics between the reanalyses are similar in magnitude to differences between the profiler and the individual reanalyses.

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Paul E. Johnston, Leslie M. Hartten, Carl H. Love, David A. Carter, and Kenneth S. Gage

Abstract

Comparisons of data taken by collocated Doppler wind profilers using 100-, 500-, and 1000-m pulse lengths show that the velocity profiles obtained with the longer pulses are displaced in height from contemporaneous profiles measured with the shorter pulses. These differences are larger than can be expected from random measurement errors. In addition, there is evidence that the 500-m pulse may underestimate the wind speed when compared with the 100-m pulse.

The standard radar equation does not adequately account for the conditions under which observations are made. In particular, it assumes that atmospheric reflectivity is constant throughout the pulse volume and that observations can be assigned to the peak of the range-weighting function. However, observations from several tropical profilers show that reflectivity gradients with magnitudes greater than 10 dB km−1 are common. Here, a more general radar equation is used to simulate the radar response to the atmosphere. The simulation shows that atmospheric reflectivity gradients cause errors in the range placement. Observed reflectivity gradients can be used to calculate a correction to the range location of the observations that helps to reduce these errors.

Examples of these errors and the application of the correction to selected cases are shown. The evidence presented shows that reflectivity gradients are the main cause of the pervasive differences observed between the different radar observations.

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Stephen M. Sekelsky, Warner L. Ecklund, John M. Firda, Kenneth S. Gage, and Robert E. McIntosh

Abstract

Multifrequency radar measurements collected at 2.8 (S band), 33.12 (Ka band), and 94.92 GHz (W band) are processed using a neural network to estimate median particle size and peak number concentration in ice-phase clouds composed of dry crystals or aggregates. The model data used to train the neural network assume a gamma particle size distribution function and a size–density relationship having decreasing density with size. Results for the available frequency combinations show sensitivity to particle size for distributions with median volume diameters greater than approximately 0.2 mm.

Measurements are presented from the Maritime Continent Thunderstorm Experiment, which was held near Darwin, Australia, during November and December 1995. The University of Massachusetts—Amherst 33.12/94.92-GHz Cloud Profiling Radar System, the NOAA 2.8-GHz profiler, and other sensors were clustered near the village of Garden Point, Melville Island, where numerous convective storms were observed. Attenuation losses by the NOAA radar signal are small over the pathlengths considered so the cloud-top reflectivity values at 2.8 GHz are used to remove propagation path losses from the higher-frequency measurements. The 2.8-GHz measurements also permit estimation of larger particle diameters than is possible using only 33.12 and 94.92 GHz. The results suggest that the median particle size tends to decrease with height for stratiform cloud cases. However, this trend is not observed for convective cloud cases where measurements indicate that large particles can exist even near the cloud top.

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