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Measurement of precipitation Doppler velocity by spaceborne radar is complicated by the large velocity of the satellite platform. Even if successive pulses are well correlated, the velocity measurement may be biased if the precipitation target does not uniformly fill the radar footprint. It has been previously shown that the bias in such situations can be reduced if full spectral processing is used. The authors present a processor based on field-programmable gate array (FPGA) technology that can be used for spectral processing of data acquired by future spaceborne precipitation radars. The requirements for and design of the Doppler processor are addressed. Simulation and laboratory test results show that the processor can meet real-time constraints while easily fitting in a single FPGA.

The authors use satellite data to examine the relationship between lightning and upper-level radar reflectivity. They find correlations between average flash rates and upper-level reflectivities over both land and ocean, although both flash rates and reflectivities are much lower over ocean than land. Analysis of the data using Empirical Orthogonal Functions (EOFs) shows similar EOFs for averaged lightning and reflectivity. In contrast, the EOFs of the anomalies of lightning and reflectivity have different spatial patterns; however, both have principal component time series that are correlated with the Southern Oscillation Index and, hence, El Nino. Differences in behavior of the lightning and reflectivity anomaly EOFs and principal components suggest that El Nino plays a smaller role in lightning anomaly than precipitation anomaly.

A compact, dual-frequency, dual-polarization, wide-angle scanning antenna system has been developed as part of an airborne instrument for measuring rainfal.

A sampling strategy and a signal processing technique are proposed to overcome Non Uniform Beam Filling (NUBF) errors on mean Doppler velocity measurements made by spaceborne weather radars.

The Global Precipitation Mission (GPM)is currently being developed as a follow-on to the Tropical Ranifall Measuring Mission (TRMM).

In this paper, the characteristics of the Doppler power spectrum observed by a spaceborne precipitation radar, under on Uniform Beam Filling (NUBF) condion will be presented, and the expected performance of some standard Doppler estimators and that of a new inversion technique will be investigated and compared.

This paper studies the performance of a spaceborne precipitation radar in measuring vertical Doppler velocity of rainfall.

A spaceborne radar for atmospheric observation must be able to detect atmospheric backscatter in the presence of clutter from the surface, due to antenna sidelobes.

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We compare two deterministic and two stochastic rain retrieval algorithms by applying them to 14 GHz reflectivity profiles acquired during TOGA COARE.

Teh SIR-C/X-sar radar observations of rain storms are the first multi-polarization and multi-frequency observations of percipitation from space. In addition to numerous, often dramatic images of severe weather systems obtained by forming a synthetic aperture in the usual side-looking attitude, several data takes were performed while the radar antennas were parallel to the ground and the radar beams were pointing at nadir. These oppoprtunities coincided with the passage of the Shuttle over Tropical Cyclone Odille in the southern Indian Ocean during the first flight, and over Typhoon Seth in the Western Pacific during the second flight. The resulting observations, or more apropriately, the resulting measurements, demonstrate for the first time the capability of a spaceborne multi-frequency multi-polarization microwave radar system to quantify precipitation rates, to detect hydrometer phase, and to classify rain type.

Several algorithms to calculate a rain-rate profile from a single-frequency air-or spaceborne radar backscatter profile and a given path-integrated attenuation have been proposed. The accuracy of any such algorithm is limited by the ambiguities between the (multiple) exact solutions, which depend on the variability of the parameters in the Z-R and k-R relations used. In this study, coupled Z-R and k-R relations are derived based on the drop size distribution. It is then shown that, because of the coupling, the relative difference between the multiple mutually ambiguous rain-rate profiles solving the problem must remain acceptably low, provided the available path-integrated attenuation value is known to within 0.5 dB.

It is well-documented (Hitschfeld and Bordan 1954, Meneghini 1978, Haddad et al 1993) that there are significant ambiguites inherent in the determination of a particular vertical rain intensity profile from a given time profile of radar echo powers measured by a downward-looking (spaceborne or airborne) radar at a single attenuating frequency.

A new airborne rain-mapping radar (ARMAR) has been developed by NASA and the Jet Propulsion Laboratory for operation on the NASA Ames DC-8 aircraft. The radar operates at 13.8 GHz, the frequency to be used by the radar on the Tropical Rainfall Measuring Mission (TRMM). ARMAR simulates the TRMM radar geometry by looking downward and scanning its antenna in the cross-track direction. This basic compatibility between ARMAR and TRMM allows ARMAR to provide information useful for the TRMM radar design, for rain retrieval algorithm development, and for postlaunch calibration. ARMAR has additional capabilities, including multiple polarization, Doppler velocity measurement, and a radiometer channel for brightness temperature measurement. The system has been tested in both ground-based and airborne configurations. This paper describes the design of the system and shows results of field tests.

Significant sources of uncertainty in global trace gas budgets are due to lack of knowledge concerning the areal and temporal extent of source and sink areas. Synthetic aperture radar (SAR) is particularly suited to studies of northern ecosystems because of its all-weather operating capability which enables the acquisition of seasonal data. As key controls on methane exchange, the ability to differentiate major vegetation communities, inundation, and leaf area index (LAI) with satellite and airborne SAR data would increase the accuracy and precision of regional and seasonal estimates of methane exchange. The utility of SAR data for monitoring key controls on methane emissions from Arctic and boreal ecosystems is examined.