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Robert Rabin
and
Dusan Zrnic

Abstract

The VAD technique is applied to unevenly spaced data obtained with two nearby Doppler weather radars in the optically clear atmosphere. Assuming that the power of higher order harmonies can be neglected, a least-squares fit method obtains the zeroth and first harmonies. The VAD results are compared with a detailed dual Doppler-radar analysis of a nearby area. The divergence found by both methods is explained in terms of the synoptic weather situation. The value of single Doppler weather radar is demonstrated in determining subsynoptic vertical winds in clear air. Inherent errors are briefly discussed.

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Robert M. Rabin
and
Richard J. Doviak

Abstract

Observations are presented of time-varying radar reflectivity during a partial solar eclipse in Oklahoma. The measurements from a radar of 10-cm wavelength, were obtained in the clear-air boundary layer. The reflectivity changes closely follow the variation in solar radiation associated with the eclipse. Possible mechanisms for the change in reflectivity are reviewed, in particular the effect of surface fluxes of heat and mositure. A formula is derived that relates radar reflectivity to surface fluxes of sensible and latent heat. Other evidence of a relationship between these fluxes and sensible and latent heat. Other evidence of a relationship between these fluxes and radar reflectivity is presented, namely the effect of local cloud cover on reduced insolation and variations in surface wetness.

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Edward A. Brandes
and
Robert M. Rabin

Abstract

The utility of Doppler radar to study boundary-layer kinematics of a weak nonprecipitating cold front in Oklahoma on 16 October 1987 was examined with measurements from two radars. Diagnosis was impeded by operation at low antenna elevation angles, short radar ranges, and low signal-to-noise ratios. Further, kinematic parameters computed by single-radar velocity-azimuth-display (VAD) technique for meteorological wavelengths <125 km were significantly smoothed (more than 50% attenuated). Meteorological scales ≥5 km were well resolved (less than 50% attenuated) in wind fields synthesized from dual-Doppler radar observations, but derived parameters were particularly sensitive to the vertical extrapolation of radial velocity measurements in the presence of strong vertical wind shear.

Nonetheless, radar-derived wind flows depicted a sequence of events consistent with other instrumentation. In the vicinity of the front, mean-flow divergence, vertical velocity, and deformation, computed from single-radar measurements for an analysis domain of 30-km radius, were −4×10−5 s−1, 3 cm s−1, and 16×10−5 s−1, respectively. Agreement between the radars attested to the accuracy of the measurements. Local peak absolute values of divergence, deformation, and vertical vorticity, determined from dual-Doppler analysis, were 200–300 (×10−5) s−1. Extrema were concentrated along the frontal zone where signals were strong, and had dimensions of ∼10 km.

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Steven D. Smith
and
Robert M. Rabin

Abstract

Applications of Doppler weather radar data to the analysis of wind fields are reviewed. Radial velocity measurements from a single radar are used to estimate horizontal wind vectors within small azimuthal sectors using two different models. One assumes a uniform wind, the other a linear wind within the sector. Errors in wind estimates owing to gradients of wind are derived using harmonic analysis. The radar data analysis techniques are tested on complex wind patterns which were reconstructed from dual-Doppler radar measurements.

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Steven D. Smith
and
Robert M. Rabin

Abstract

An analysis technique to derive wind field parameters from single-Doppler velocity measurements, known as Modified Velocity-Volume Processing (MVVP) is examined from both theoretical and operational perspectives. For this technique, radar data within limited spatial volumes are fit to a model which usually assumes linearity of the Cartesian wind components. The accuracies and limitations of this technique are illustrated with examples from a case study of a severe storm outbreak in central Oklahoma on 17 May 1981. Implications for use of the MVVP in convective storm forecasting are considered.

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Robert M. Rabin
and
Timothy J. Schmit

Abstract

In this note, the relationship between the observed daytime rise in surface radiative temperature, derived from the Geostationary Operational Environmental Satellites (GOES) sounder clear-sky data, and modeled soil moisture is explored over the continental United States. The motivation is to provide an infrared (IR) satellite–based index for soil moisture, which has a higher resolution than possible with the microwave satellite data. The daytime temperature rise is negatively correlated with soil moisture in most areas. Anomalies in soil moisture and daytime temperature rise are also negatively correlated on monthly time scales. However, a number of exceptions to this correlation exist, particularly in the western states. In addition to soil moisture, the capacity of vegetation to generate evapotranspiration influences the amount of daytime temperature rise as sensed by the satellite. In general, regions of fair to poor vegetation health correspond to the relatively high temperature rise from the satellite. Regions of favorable vegetation match locations of lower-than-average temperature rise.

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Valliappa Lakshmanan
,
Kurt Hondl
, and
Robert Rabin

Abstract

Existing techniques for identifying, associating, and tracking storms rely on heuristics and are not transferrable between different types of geospatial images. Yet, with the multitude of remote sensing instruments and the number of channels and data types increasing, it is necessary to develop a principled and generally applicable technique. In this paper, an efficient, sequential, morphological technique called the watershed transform is adapted and extended so that it can be used for identifying storms. The parameters available in the technique and the effects of these parameters are also explained.

The method is demonstrated on different types of geospatial radar and satellite images. Pointers are provided on the effective choice of parameters to handle the resolutions, data quality constraints, and dynamic ranges found in observational datasets.

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Elen Cutrim
,
David W. Martin
, and
Robert Rabin

A survey of shallow (fair weather) cumulus clouds over part of Amazonia yields evidence of enhanced frequency where the forest had been cleared. The survey covers one dry-season month from 1988. It employs a threshold algorithm to construct an image of cumulus cloud cover from sets of geostationary satellite visible–infrared image pairs. Cumulus images were constructed for two times. The morning image shows no association of the cumulus index with cultural features. However, in the afternoon image a patch of high index values coincides with deforestation along highway BR-364 in the state of Rondonia.

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Valliappa Lakshmanan
,
Robert Rabin
,
Jason Otkin
,
John S. Kain
, and
Scott Dembek

Abstract

Visualizing model forecasts using simulated satellite imagery has proven very useful because the depiction of forecasts using cloud imagery can provide inferences about meteorological scenarios and physical processes that are not characterized well by depictions of those forecasts using radar reflectivity. A forward radiative transfer model is capable of providing such a visible-channel depiction of numerical weather prediction model output, but present-day forward models are too slow to run routinely on operational model forecasts.

It is demonstrated that it is possible to approximate the radiative transfer model using a universal approximator whose parameters can be determined by fitting the output of the forward model to inputs derived from the raw output from the prediction model. The resulting approximation is very close to the result derived from the complex radiative transfer model and has the advantage that it can be computed in a small fraction of the time required by the forward model. This approximation is carried out on model forecasts to demonstrate its utility as a visualization and forecasting tool.

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William H. Raymond
,
Robert M. Rabin
, and
Gary S. Wade

The Mississippi River floodplain in the states of Arkansas, Tennessee, Mississippi, and Louisiana presents a readily discernible feature in weather satellite images. This floodplain appears in the spring and early summer as a daytime warm anomaly at infrared (IR) wavelengths and as a bright reflective area at visible wavelengths. Remnants of this feature can occasionally be identified at nighttime in the IR satellite images. During June the normalized difference vegetation index identifies major contrasts between this intense agricultural region and the surrounding mixed-forest region. This distinction and the homogeneity of the floodplain, with its alluvial soil, contrast with the encircling region, creating an agricultural region containing heat island features. Thirty years of climatological surface station data for the month of June reveal that the surface air temperatures in the floodplain experience less diurnal variation than those in the surrounding regions. This is primarily because nighttime minimums are warmer in the Mississippi River floodplain.

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