IEEE
Geoscience and Remote Sensing Society

Abbreviation: GRSS, S Code 29

BEYOND NEXRAD

I. Introduction

II. NEXRAD Evolution

It goes without saying that robust front end processing alleviates a myriad of problems in subsequent feature extraction. Clean data, free humans from tiresome examination of suspicious signatures. Furthermore, correct data are much less likely to be misclassified by algorithms. Thus a more effective exploitation of remote sensing technology would be possible if a versatile processor is utilized in the WSR-88D. Significant system enhancements would be possible in algorithm development, hardware/software improvements, and upgrading of capabilities; these four topics are briefly discussed.

a) Algorithms

Detection of phenomena, determination of their strength or hazard potential, and quantitative measurements of precipitation are classified under the category of algorithms. Evolution of algorithms is an ongoing process and will continue to occupy practitioners and scientists for years to come. Presently much work remains to enhance the existing algorithms. Most of these use procedures that are based on decision trees. New more efficient methods must be devised. Modern pattern recognition and image processing techniques need to be explored together with hybrid approaches that blend numerical models with data.

b) Range and velocity ambiguities /software and hardware enhancements

Mitigation of range and velocity ambiguities is one of the highest priorities of the WSR-88D system. Whereas software improvements continue to be tested it is becoming increasingly clear that hardware solutions are needed. To test the most promising methods versatile signal processors should be employed. Much of the theoretical work in this area has been done, but tests and operational demonstrations are lacking.

c) Increase in capability

Discrimination of precipitation types and determination of water accumulation is a long standing problem. The WSR-88D is contributing much to its solution. But, even if pushed to the limits of sophistication, there will remain situations for which single polarized radars fall short from providing satisfactory estimates of amounts and types of precipitation. This is, for example, because hail size and presence is inferred from indirect measurements of storm structure, and problems of rainfall estimation are inherent to methods that use backscattered power. Recent breakthroughs in radar polarimetry have been made that address these deficiencies.

Measurements of hail with the polarimetric radar is direct and discrimination of sizes might be possible. The most robust measurement of heavy rainfall (larger than 15 mm/hr) can be made using specific differential phase which is a polarimetric variable. This measurement is not affected by radar calibration, nor by attenuation or partial beam blockages! There is also evidence that radar polarimetry can be used to determine snow types and transition zones between liquid and ice precipitation. Addition of the polarimetric capability to the WSR-88D is a realistic possibility, especially because there are schemes which would not compromise other measurements.

Although these and other advantages of polarimetric method have been documented in case studies, an operational demonstration similar to the Joint Doppler Operation Project is needed to test the practical utility. Assuming that the operational demonstration is successful, a cost benefit study would be conducted; if the results are positive appropriate action by NOAA/NWS could be made to initiate the enhancement.

d) New systems

There might be aspects of operations which could not be met with evolutionary changes in the WSR-88D. Timely detection of fast evolving phenomena is more likely at volume scan intervals of one or less minute, as opposed to the current 5 min. Examples are the weather at airport terminals that are presently observed with the Terminal Doppler Weather Radar (TDWR). A rapid scan phased array radar with polarization agility is the ultimate active sensor suitable for such applications. In combination with physical models data, from this sensor will allow one to infer tendencies of the phenomena under surveillance so that correct decisions concerning aircraft control can be made. Rapid scan should also lead to better estimates of wind components transverse to the radial.

III. Conclusion