Stephen L. Durden

THE CLOUDSAT MISSION AND THE A-TRAIN A New Dimension of Space-Based Observations of Clouds and Precipitation

CloudSat is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASAs Aqua and Aura satellites, a NASA–CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the CALIPSO lidar footprint and the other measurements of the constellation. The precision and near simultaneity of this overlap creates a unique multisatellite observing system for studying the atmospheric processes essential to the hydrological cycle. The vertical profiles of cloud properties provided by CloudSat on the global scale fill a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring these profi...

A three-component scattering model for polarimetric SAR data

An approach has been developed that involves the fit of a combination of three simple scattering mechanisms to polarimetric SAR observations. The mechanisms are canopy scatter from a cloud of randomly oriented dipoles, evenor double-bounce scatter from a pair of orthogonal surfaces with different dielectric constants and Bragg scatter from a moderately rough surface. This composite scattering model is used to describe the polarimetric backscatter from naturally occurring scatterers. The model is shown to describe the behavior of polarimetric backscatter from tropical rain forests quite well by applying it to data from NASA/Jet Propulsion Laboratorys (JPLs) airborne polarimetric synthetic aperture radar (AIRSAR) system. The model fit allows clear discrimination between flooded and nonflooded forest and between forested and deforested areas, for example. The model is also shown to be usable as a predictive tool to estimate the effects of forest inundation and disturbance on the fully polarimetric radar signature. An advantage of this model fit approach is that the scattering contributions from the three basic scattering mechanisms can be estimated for clusters of pixels in polarimetric SAR images. Furthermore, it is shown that the contributions of the three scattering mechanisms to the HH, HV, and VV backscatter can be calculated from the model fit. Finally, this model fit approach is justified as a simplification of more complicated scattering models, which require many inputs to solve the forward scattering problem.

Observations and Parameterizations of Particle Size Distributions in Deep Tropical Cirrus and Stratiform Precipitating Clouds: Results from In Situ Observations in TRMM Field Campaigns

Abstract This study reports on the evolution of particle size distributions (PSDs) and habits as measured during slow, Lagrangian-type spiral descents through deep subtropical and tropical cloud layers in Florida, Brazil, and Kwajalein, Marshall Islands, most of which were precipitating. The objective of the flight patterns was to learn more about how the PSDs evolved in the vertical and to obtain information of the vertical structure of microphysical properties. New instrumentation yielding better information on the concentrations of particles in the size (D) range between 0.2 and 2 cm, as well as improved particle imagery, produced more comprehensive observations for tropical stratiform precipitation regions and anvils than have been available previously. Collocated radar observations provided additional information on the vertical structure of the cloud layers sampled. Most of the spirals began at cloud top, with temperatures (T) as low as −50°C, and ended at cloud base or below the melting layer (ML)....

Modeling and observation of the radar polarization signature of forested areas

To understand radar measurements of forested areas, the authors have developed a model of L-band (25-cm) microwave scattering from a forest. The forest floor is layer of nearly vertical dielectric cylinders representing tree trunks Above this layer is a second layer consisting of randomly oriented cylinders which represent branches. The authors identify several scattering mechanisms and calculate the corresponding Stokes matrices, which combine to give the total Stokes matrix and resulting polarization signature. It is found that this simple model permits accurate prediction of the polarization of the scattered waves and that additional mechanisms, including the effects of leaves and twigs, are not required for the 25-cm observation of the forests studied. The authors present measurements of the polarization signature acquired over a forested area and show comparisons with model calculations. >

CloudSat's Cloud Profiling Radar After Two Years in Orbit: Performance, Calibration, and Processing

The Cloud Profiling Radar, the sole science instrument of the CloudSat Mission, is a 94-GHz nadir-looking radar that measures the power backscattered by hydrometeors (clouds and precipitation) as a function of distance from the radar. This instrument has been acquiring global time series of vertical cloud structures since June 2, 2006. In this paper, an overview of the radar performance and status, to date, is provided together with a description of the basic data products and the surface clutter rejection algorithm introduced for the Release 04 data product release.

Three-component scattering model to describe polarimetric SAR data

Classification, decomposition and modeling of polarimetric SAR data has received a great deal of attention in the recent literature. The objective behind these efforts is to better understand the scattering mechanisms which give rise to the polarimetric signatures seen in SAR image data. In this paper, a new approach is described, which involves the fit of a combination of three simple scattering mechanisms to the polarimetric SAR observations. The mechanisms are volume scatter from a cloud of randomly oriented dipoles, even-bounce scatter from a pair of orthogonal surfaces with different dielectric constants and Bragg scatter from a moderately rough surface. This composite scattering model is used to describe the polarimetric backscatter from naturally occurring scatterers. Results are presented of application of this new algorithm to different types of scene, including multi-frequency polarimetric SAR images of a tropical rain forest, a boreal forest, a pine forest, geologic targets, urban areas and agricultural fields. Fitting the model to polarimetric SAR data of the tropical rain forest for example, allows clear discrimination between flooded and non-flooded forest. The model can be used to estimate the overall contribution from each of the three basic scattering mechanisms for each SAR image pixel.

ARMAR: An airborne rain-mapping radar

Abstract 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.

On the role of “hot towers” in tropical cyclone formation

SummaryThe probabilistic approach to tropical cyclogenesis is advanced here by examining the role of convection in the early stages. The development of “hot towers”, that is tall cumulonimbus towers which reach or penetrate the tropopause, and their role in tropical cyclogenesis is investigated in two well-documented cases of formation. namely hurricane Daisy (1958) in the Atlantic and Tropical Cyclone Oliver (1993) in the Coral Sea. The hot towers in Daisy had been intensively studied by Malkus and Riehl three decades ago but remained mainly unpublished. The dynamics of Oliver genesis by merging mesoscale vortices has been recently reported, but much of the aircraft data remained. This paper adds the evolving contribution of cumulus-scale events and their associated electrification, which was made possible by the addition of an electric field mill, a numerical cloud model and other remote sensors.In their genesis stages, Daisy and Oliver appeared very different because Daisy resulted from a deepening tropical wave in the Atlantic and the pre-Oliver vortex emerged eastward from the Australian monsoon trough. However, the vertical profiles of θE in the rain areas were nearly identical, with the characteristic concave shape showing substantial midlevel minima. Therefore, both required increasing upflux of high θE subcloud air in order to accomplish the formation stage, with about two hot towers each in the nascent eyewall. In both cases, partial eyewalls developed at the edge of the convection, permitting subsidence in the forming eye, which was shown to contribute to the pressure fall. The probabilistic concept proposes that any contribution to early pressure fall raises the probability of success. When the incipient storm goes through those fragile phases more rapidly, the risk of death by the onset of unfavorable large-scale factors such as wind shear or upper-level subsidence is reduced. Daisy developed in an inactive, moist environment with light, variable winds throughout the troposphere while in Oliver, strong divergent upper outflow apparently outweighed strong wind shear, although the latter was responsible for a slow and messy development of a closed, circular eye.In both storms, the hot towers in the major rainband were taller and stronger than those in the early eyewall. Onedimensional time-dependent model runs were used to simulate both in Oliver with two important results: 1) the taller rainband clouds permitted greater high level heating, if it could be retained; and 2) greater electrification and more lighting occurred in the rainband although the partial eyewall clouds also showed strong electrification. Airborne radar, electrification measurements and models are fitted together to understand their relationship. An important result is the clear inference that fairly deep mixed phase regions existed in both eyewall and rainband, in which the DC-8 aircraft experienced liquid water at temperatures colder than −40°C below freezing. These results show that the claims of no supercooled liquid water in tropical cyclones require re-examination with the proper measurements of electricification that are now feasible.

NASA's Genesis and Rapid Intensification Processes (GRIP) Field Experiment

In August–September 2010, NASA, NOAA, and the National Science Foundation (NSF) conducted separate but closely coordinated hurricane field campaigns, bringing to bear a combined seven aircraft with both new and mature observing technologies. NASAs Genesis and Rapid Intensification Processes (GRIP) experiment, the subject of this article, along with NOAAs Intensity Forecasting Experiment (IFEX) and NSFs Pre-Depression Investigation of Cloud-Systems in the Tropics (PREDICT) experiment, obtained unprecedented observations of the formation and intensification of tropical cyclones. The major goal of GRIP was to better understand the physical processes that control hurricane formation and intensity change, specifically the relative roles of environmental and inner-core processes. A key focus of GRIP was the application of new technologies to address this important scientific goal, including the first ever use of the unmanned Global Hawk aircraft for hurricane science operations. NASA and NOAA conducted coord...

Parameterizing the Raindrop Size Distribution

Abstract 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 Γ 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.