ALBERT

Description: Current passive-microwave rain-retrieval methods are largely based on databases built off-line using cloud models. The vertical distribution of hydrometeors within the cloud has a large impact on upwelling brightness temperatures ([31,[5]). Thus, a forward radiative transfer model can predict off-line the radiance associated with different rain scenarios. To estimate the rain from measured brightness temperatures, one simply looks for the rain scenario whose associated radiances are closest to the measurements. To understand the uncertainties in this process, we first study the dependence of the simulated brightness temperatures on different hydrometeor size distribution (DSD) models. We then analyze the marginal and joint distributions of the radiances observed by the Tropical Rainfall Measuring Mission satellite and of those in the databases used in the TRMM rain retrievals. We finally calculate the covariances of the rain profiles and brightness temperatures in the TRMM passive-microwave database and derive a simple parametric model for the conditional uncertainty, given measured radiances. These results are used to characterize the uncertainty inherent in the passive-microwave retrieval.

Description: This paper addresses the problem of finding a parametric form for the raindrop size distribution (DSD) that(1) is an appropriate model for tropical rainfall, and (2) involves statistically independent parameters. Such a parameterization is derived in this paper. One of the resulting three "canonical" parameters turns out to vary relatively little, thus making the parameterization particularly useful for remote sensing applications. In fact, a new set of r drop-size-distribution-based Z-R and k-R relations is obtained. Only slightly more complex than power laws, they are very good approximations to the exact radar relations one would obtain using Mie scattering. The coefficients of the new relations are directly related to the shape parameters of the particular DSD that one starts with. Perhaps most important, since the coefficients are independent of the rain rate itself, the relations are ideally suited for rain retrieval algorithms.

Description: This paper describes a computationally efficient nearly optimal Bayesian algorithm to estimate rain (and drop size distribution) profiles, given a radar reflectivity profile at a single attenuating wavelength. In addition to estimating the averages of all the mutually ambiguous combinations of rain parameters that can produce the data observed, the approach also calculates the n-ns uncertainty in its estimates (this uncertainty thus quantifies "the amount of ambiguity" in the "solution"). The paper also describes a more general approach that can make estimates based on a radar reflectivity profile together with an approximate measurement of the path-integrated attenuation, or a radar reflectivity profile and a set of passive microwave brightness temperatures. This more general "combined" algorithm is currently being adapted for the Tropical Rainfall Measuring Mission.

Description: This paper presents some crucial design parameters and a strawman system design for a nadir-looking, 94-GHz spaceborne cloud profiling radar. This sensor is expected to provide cloud measurements at vertical resolution of 500 m and with a minimum detectable cloud reflectivity of slightly better than -30 dBZ. The radar design is intended to be accommodated by a spacecraft with limited resources. It uses a 2-m antenna and an extended interaction amplifier (EIA) that are readily available in either ground-based and airborne applications. For space application, improvements in the EIA lifetime and space qualification will be required. For various reasons, the spaceborne cloud radar system development is expected to be greatly benefited by the implementation of an aircraft cloud radar instrument.

Description: The significant ambiguities 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 are well-documented. Indeed, one already knows that by appropriately varying the parameters of the reflectivity-rain-rate (Z - R) and/or attenuation-rain-rate (k - R) relationships, one can produce several substantially different hypothetical rain rate profiles which would have the same radar power profile. Imposing the additional constraint that the path-averaged rain-rate be a given fixed number does reduce the ambiguities but falls far short of eliminating them. While we now know how to generate as many mutually ambiguous rain-rate profiles from a given profile of received radar reflectivities as we like, there remains to produce a quantitative measure to assess how likely each of these profiles is, what the appropriate 'average' profile should be, and what the 'variance' of these multiple solutions is. Of course, in order to do this, one needs to spell out the stochastic constraints that can allow us to make sense of the words 'average' and 'variance' in a mathematically rigorous way. Such a quantitative approach would be particularly well-suited for such systems as the proposed Precipitation Radar of the Tropical Rainfall Measuring Mission (TRMM). Indeed, one would then be able to use the radar reflectivities measured by the TRMM radar from one particular look in order to estimate the most likely rain-rate profile that would have produced the measurements, as well as the uncertainty in the estimated rain-rates as a function of range. Such an optimal approach is described in this paper.

Description: The Cassini Radar's synthetic aperture radar (SAR) ambiguity analysis is unique with respect to other spaceborne SAR ambiguity analyses owing to the non-orbiting spacecraft trajectory, asymmetric antenna pattern, and burst mode of data collection. By properly varying the pointing, burst mode timing, and radar parameters along the trajectory this study shows that the signal-to-ambiguity ratio of better than 15 dB can be achieved for all images obtained by the Cassini Radar.

Description: In this paper a sea surface radar echo spectral analysis technique to correct for the rainfall velocity error caused by radar-pointing uncertainty is presented. The correction procedure is quite straightforward when the radar is observing a homogeneous rainfall field. When nonuniform beam filling (NUBF) occurs and attenuating frequencies are used, however, additional steps are necessary in order to correctly estimate the antenna-pointing direction. This new technique relies on the application of the combined frequency-time (CFT) algorithm to correct for uneven attenuation effects on the observed sea surface Doppler spectrum. The performance of this correction technique was evaluated by a Monte Carlo simulation of the Doppler precipitation radar backscatter from high-resolution 3D rain fields (either generated by a cloud resolving numerical model or retrieved from airborne radar measurements). The results show that the antenna-pointing-induced error can, indeed, be reduced by the proposed technique in order to achieve 1 m s(exp -1) accuracy on rainfall vertical velocity estimates.

Description: The precipitation radar planned for the Tropical Rainfall Measuring Mission (TRMM) will be the first of its kind to measure vertical rainfall distributions from space. The TRMM radar will scan +/- 20 degrees across the nadir track. The range-gated backscattering powers over the entire scan swath will be measured, classified (rain versus no-rain), averaged, and processed to derive the rainfall rates. With this observation scheme, there are two major reasons why it is important to know the rain-perturbed backscattering coefficient of the surface background (tilde over sigma_0)...

Description: Cassini Radar is a multimode rada instrument designed to probe the optically inaccessible surface of Titan, Saturn's largest moon. The individual modes will allow surface imaging, surface emissivity measurements. Recently, the breadboard model of this instrument was built and has undergone a series of functional and perfomance tests. The results obtained from these tests indicate that the instrument design is satisfactory and that the various required performance parameters are suffieciently met.

Description: Numerous studies have documented the effect of El Nino-Southern Oscillation (ENSO) on rainfall in many regions of the globe. The question of whether ENSO is the single most important factor in interannual rainfall variability has received less attention, mostly because the kind of data that would be required to make such an assessment were simply not available. Until 1979 the evidence linking El Nino with changes in rainfall around the world came from rain gauges measuring precipitation over land masses and a handful of islands. From 1980 until the launch of the Tropical Rainfall Measuring Mission (TRMM) in November 1997 the remote sensing evidence was confined to ocean rainfall because of the very poor sensitivity of the instruments over land. In this paper we summarize the results of a principal component analysis of TRMM's 60-month (January 1998 to December 2002) global land and ocean remote-sensing record of monthly rainfall accumulations. Contrary to the first principal component of the rainfall itself, the first three indices of the anomaly are most sensitive to precipitation over the ocean rather than over the land. With the help of archived surface station data the first TRMM rain anomaly index is extended back several decades. Comparison of the extended index with the Southern Oscillation Index confirms that the first principal component of the rainfall anomaly is strongly correlated with the ENSO indices.