This study analyzes passive and active microwave measurements during the 2003 Wakasa Bay field experiment for understanding of the electromagnetic characteristics of frozen hydrometeors at millimeter-wave frequencies. Based on these understandings, parameterizations of the electromagnetic scattering properties of snow at millimeter-wave frequencies are developed and applied to the hydrometeor profiles obtained by airborne radar measurements. Calculated brightness temperatures and radar reflectivity are compared with the millimeter-wave measurements.

Snowfall is an important component of the Earth's precipitation and hydrological cycle. Remote measurements of frozen hydrometeor properties have been limited because coincident measurements of microphysical and electromagnetic properties of snowfall have not been available. Snowfall measurement from space has been suggested as a solution to overcome this limitation. The precipitating clouds contain a sufficient density of ice water equivalent from snow crystals, graupel, or both, when brightness temperature is at 85 GHz. The NOAA Advanced Microwave Sounding Unit (AMSU) has been used to derive snowfall over land using millimeter-wave radiometry. This study analyzes the millimeter-wave radiometric measurements of frozen hydrometeors during the field experiment that was held in Wakasa bay of Japan in January 29, 2003. It was found that a lognormal distribution represents the snow PSD during the field experiments. The MM5 cloud simulation is employed to provide temperature and humidity profiles for the radiative transfer calculations. This study seeks to derive characteristics of snow whose electromagnetic properties are consistent with microwave brightness temperature at several frequencies provided by the MIR sensors and the radar reflectivity measured by PR-2 (Precipitation Radar) and ACR (Airborne Cloud Radar).

Results of concurrent airborne measurements of snowfalls with the Millimeter-wave Imaging Radiometer (MIR) and the Airborne Cloud Radar (ACR) are reported in this paper. The measurements were obtained during January-February 2003 in a field experiment in Wakasa Bay, Japan. The MIR is an imaging radiometer that measures radiation at seven channels between 89 GHz and 340 GHz. The ACR operates at 94 GHz and provides nadir-viewing radar reflectivity profiles with very good accuracy. Three days of snowfall events were observed during this field deployment. It was found that the MIR brightness temperature depressions at the frequencies of 183.3/spl plusmn/1, 183.3/spl plusmn/3, 183.3/spl plusmn/7, and 340 GHz strongly correlate with the ACR reflectivity profiles during these snow events. Radiometric signatures from the remaining less opaque channels of the MIR (89, 150 and 220 GHz) showed ambiguity in snowfall detection due to variation in surface emissivities. An attempt to retrieve the ice water path and the median mass equivalent sphere diameter of the snowfalls would be described and results discussed.

Previous research studies have used multifrequency radar Doppler spectra to study different aspects of precipitation, and have demonstrated its utility as an accurate profiling raingauge method (Firda, 1999). Recently this concept have been used to retrieve the drop size distribution (DSD) and vertical air motion in rain using a dual-frequency cloud profiling radar system, operating at 33GHz (Ka-band) and 95GHz (W-band), will provide measurements over a wider dynamic range of rain conditions, extending the active rain-gauge concept to heavier rain rates. The use of the W-bandsignal will provide accurate measurement of the vertical air motion in rain. Considering the conditions of heavy rain in which case large nonspherical raindrops exist, the actual drop's shapes will be corrected. Data will be processed as suggested by Firda et al., 1999. This research's goal is to develop software to retrieve several cloud characterization parameters, such as drop size distribution and vertical air motion from collected data during November 2001 at the Cloud and Radiation Testbed (CART) site in Lamont, Oklahoma. Rain rate estimates, drop size distribution and the vertical air motion retrieval used to study the inner processes of rain will be presented.

The Microwave Remote Sensing Laboratory (MIRSL) at the University of Massachusetts and the Cloud Microwave Measurements of Atmospheric Events (CLiMMATE) Laboratory at the University of Puerto Rico at Mayaguez are collaborating to modify a MK2 marine radar donated by Raytheon for use as meteorological radar nodes in a proposed weather radar network. This will be the first network to measure lower atmospheric phenomena in Puerto Rico. The radar consists of an antenna, a rotator, and a transceiver that will be placed at top of a tower or building, along with a data processing system. This paper derives two important equations describing the curved earth effect on beam propagation for radar range calculation. It also describes the method used to survey the MIRSL Tilson Farm field site, and the eleven campuses of the University of Puerto Rico backbone and justifies their fixed offset antennas' elevation angle and location.

The minimum detectable radar reflectivity (dBZemin) is computed for the University of Massachusetts' 33 GHz/95 GHz Cloud Profiling Radar System (CPRS) under humid tropical conditions. Extinction by water vapor and oxygen are calculated for a horizontally stratified atmosphere as a function of range and scan angle for both radar frequencies. Combined radiosonde and dual-frequency microwave radiometer measurements are used to model radar signal extinction for the Maritime Continent Thunderstorm Experiment (MCTEX), which was conducted in northern Australia. These data are compared with CPRS radar measurements to evaluate the performance of both frequencies for sensing clouds and precipitation versus elevation angle.

The University of Massachusetts, Colorado State University and the National Center for Atmospheric Research are collaborating to develop an advanced Multi-Frequency Radar (MFR) system for studying clouds and precipitation, which should become operational in 2004. This highly portable radar consists of three polarimetric Doppler subsystems operating at Ku-band (13.8 GHz), Ka-band (33 GHz) and W-band (95 GHz), a programmable scanning pedestal, and a unique single aperture antenna that generates co-located matched beams at each wavelength. This combination of wavelengths allows measurement of a wide range of atmospheric targets including weakly reflecting clouds and precipitation.

The study of high altitude clouds has motivated the development of new airborne and space-borne millimeter-wave cloud radars. Airborne millimeter-wave radars can offer better spatial resolution and sensitivity than ground-based counterparts, by avoiding water vapor attenuation in the lower atmosphere and spatial resolution degradation due to beam spreading. Furthermore, aircraft can cover large geographic areas and simulate satellite geometry. A next generation 95 GHz Compact Millimeter-wave radar (CMR) is currently under development. Incorporation of pulse compression will provide sensitivity comparable to larger klystron tube-based transmitters traditionally used in ground based 95 GHz radars. The CPU-bases signal processor will be replaced with a stand alone processor bases on re-configurable Field Programmable Gate Array Logic (FPGA). The new processor digitizes the IF signal, performs digital-in phase and quadrature phase detection, and applies the pulse-pair algorithm.

This paper describes the identification of regions of ice, cloud droplets, rain, mixed-phase hydrometers, and insects in stratiform clouds using 33 and 95 GHz radar measurements of reflectivity, linear-depolarization ratio (LDR), dual-wavelength ratio, and velocity from a single-antenna radar system. First, the radar system, experiment, and data products are described. Then, regions are classified using a rule-based classifier derived primarily from LDR, velocity, and altitude. Next, a region-dependent attenuation-correction algorithm is developed to remove attenuation biases in the reflectivity estimate, and histograms of the corrected data are presented for each data product and class. The labeled regions and attenuation-corrected data are then used to train a neural net and maximum likelihood classifier. These agree with the rule-based classifier 96% and 94% of the time, respectively. Finally, the paper evaluates the importance of measuring dual-frequency parameters, velocity, and depolarization ratio.

Millimeter-wave radars have been used since the early 1950s to study clouds and precipitation, but until recently these early instruments were limited to simple backscatter power measurements and were plagued by hardware problems. However, development of solid-state millimeter-wave componentry and high-power klystron amplifiers has spurred the evolution of reliable, coherent radars operating up to 95 GHz. In addition, advances in digital signal processing technology have resulted in single-card processors that can simultaneously execute algorithms to compute reflectivity, Doppler, and polarimetric quantities in real time. A review of the current state of the art in millimeter-wave cloud radars is presented, including a discussion of transmitters, antennas, and receiver components. Two radar systems built by the University of Massachusetts are described, including a mobile, dual-frequency (33- and 95-GHz) polarimetric radar, and an airborne 95-GHz polarimetric radar that was recently flown in a cooperative experiment with the University of Wyoming. Spaceborne applications are also discussed, especially the use of satellite-based 95-GHz radars for measuring the vertical distribution of clouds.>