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NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge, reduce risk, and support safe, productive human space missions. Through the powerful emerging computer science approaches of artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in biomedical science and engineered astronaut health systems, to enable Earth-independence and autonomy of mission operations. We present a decadal view of AI/ML architecture to support deep space mission goals, developed in concert with leaders in the field. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing hardware, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated real-time mission biomonitoring, and 8) a Precision Space Health system. Cutting-edge AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics data to phenotypic data using an ensemble model to infer causality of spaceflight rodent liver health disruption, 2) usage of explainable ML to interrogate the muscular underpinnings of spaceflight muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human space health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interaction networks, and 5) a suite of benchmarked open science datasets (spaceflight mouse liver; radiation DNA damage) enabling programmers to identify the best ML algorithms to answer space biological science questions.

space biology↗
NASA NTRS2021

Compact Thermal Imager (CTI) for Atmospheric Remote Sensing

The demonstration of a newly developed compact thermal imager (CTI) on the International Space Station (ISS) has provided not only a technology advancement but a rich high-resolution dataset on global clouds, atmospheric and land emissions. This study showed that the free-running CTI instrument could be calibrated to produce scientifically useful radiance imagery of the atmosphere, clouds, and surfaces with a vertical resolution of ~460 m at limb and a horizontal resolution of ~80 m at nadir. The new detector demonstrated an excellent sensitivity to detect the weak limb radiance perturbations modulated by small-scale atmospheric gravity waves. The CTI’s high-resolution imaging was used to infer vertical cloud temperature profiles from a side-viewing geometry. For nadir imaging, the combined high-resolution and high-sensitivity capabilities allowed the CTI to better separate cloud and surface emissions, including those in the planetary boundary layer (PBL) that had small contrast against the background surface. Finally, based on the ISS’s orbit, the stable detector performance and robust calibration algorithm produced valuable diurnal observations of cloud and surface emissions with respect to solar local time during May–October 2019, when the CTI had nearly continuous operation.

thermal imager↗
NASA NTRSDate not supplied

A Process Model of Interpersonal Relationship Formation in Isolated and Confined Environments

Future space crews will face several challenges such as living and working in a confined environment, isolated from others. These circumstances increase the importance of interpersonal compatibility, teamwork, and team performance. The interpersonal compatibility of space crews has been and continues to be of interest to both NASA and the Institute of Biomedical Problems (IBMP), whose research informs operations for Roscosmos. In NASA-sponsored research, interpersonal compatibility has been examined in terms of how the combination of team members’ personality traits, values, and demographics shape team member relationships and team performance overtime. IBMP-sponsored research mostly has moved away from trait-based approaches toward an idiographic (in-depth, heavily descriptive) approach to researching crew interpersonal relations. This research uses software such as Personal Self-Perception and Attitudes (PSPA), network approaches to team member relations, and content analysis of interactions to assess interpersonal compatibility, and infer states and team dynamics. Our research program integrated these ideas. Our primary research aim was to develop and empirically test a process model of interpersonal relationship formation in isolated and confinement environments. We created a model, collected data from teams in an isolated and confined environment, and applied a novel analytical strategy that combines trait, state, and interaction data (i.e., relational events). We focused specifically on the formation of strained relationships in isolation and confinement—or with whom fellow crewmembers find it difficult to work.

S T Bell↗
NASA NTRS2012

GRAIL Refinements to Lunar Seismic Structure

The present ]day internal structure of the Moon provides insight not only into its own formation and evolution, but also that of all rocky planetary bodies. The most direct way to probe a planet fs interior structure is through seismology. As part of the Apollo lunar missions, four seismometers were deployed on the nearside surface of the Moon between the years 1969 and 1972. These instruments operated continuously until 1977, forming the only substantial extraterrestrial seismic data set in existence. These data have been used to constrain various aspects of the seismic velocity and density structure of the Moon. Typical 1-D models recognize a 30-60 km thick crust overlying a nearly constant ]velocity mantle, and extend to a depth of approximately 1000 km, below which the lack of penetrating moonquake ray ]paths precludes the seismic determination of deeper structure. Previously, the lack of observed moonquakes from the far side of the Moon has been used to infer the presence of a highly attenuating (possibly molten) core. Indirect geophysical measurements such as moment of inertia, magnetic induction, lunar laser ranging, and elemental abundances of mare basalts also place varying constraints on core size and state. In combination with seismic studies, these indirect measurements have been used to arrive at a commonly accepted model of the Moon's deepest interior that includes a solid inner and fluid outer core, overlain by a partial melt boundary layer. We recently applied modern array seismology techniques to the Apollo data and revealed detailed core structure, including the first direct confirmation of the presence of a solid inner core. Our study focused on the identification of core ]reflected phases in deep moonquake seismograms. The resulting model of the Moon fs innermost structure was found to be consistent with the commonly accepted model. However, the modeled layer radii may vary by tens of kilometers, as is expected when accounting for uncertainties such as moonquake location, timing errors, and potential seismic heterogeneities. In addition, the modeled velocities may vary with a 1-to-1 trade ]off with the modeled reflector depth. The GRAIL (Gravity Recovery and Interior Laboratory) mission, launched in Sept. 2011, placed two nearly identical spacecraft in lunar orbit. The two satellites make extremely high-resolution measurements of the lunar gravity field, which can be used to constrain the interior structure of the Moon using a "crust to core" approach. GRAIL fs constraints on crustal thickness, mantle structure, core radius and stratification, and core state (solid vs. molten) will complement seismic investigations in several ways. Here we present a progress report on our efforts to advance our knowledge of the Moon fs internal structure using joint gravity and seismic analyses. We will focus on methodology, including 1) refinements to the seismic core constraint accomplished through array processing of Apollo seismic data, made by applying a set of travel time corrections based on GRAIL structure estimates local to each Apollo seismic station; 2) modeling deep lunar structure through synthetic seismograms, to test whether the seismic core model can reproduce the core reflections observed in the Apollo seismograms; and 3) a joint seismic and gravity inversion in which we attempt to fit a family of seismic structure models with the gravity constraints from GRAIL, resulting in maps of seismic velocities and densities that vary from a nominal model both laterally and with depth.

Weber, Renee↗
NASA NTRS1975

Correlation of an optical system degradation with contamination on a critical surface

The loss of sensitivity of a radiantly cooled radiometer during space operation was investigated. A quartz crystal microbalance (QCM), mounted in the proximity of the instrument filter lens and held at its temperature, measured the contaminant at the location during a vacuum test. The temperature cycling of the lens and the QCM verified the contamination of the lens as the cause of the deterioration. Data on the instrument performance in space and in the chamber allowed estimation of the rate of contaminant accretion on the lens in space service. That rate was used to estimate the contaminant partial pressure. The nature of material was inferred by comparison of the partial pressures and the saturated vapor pressures of materials at the temperature of the contaminated surface. These data, in conjunction with data on fields of view of the lens, are used to identify the sources of contamination.

Scialdone, J. J.↗
NASA NTRS1991

Growth and characterization of high-performance photorefractive BaTiO3 crystals

Barium titanate has been used for many nonlinear optical applications primarily because it has high grain and high self-pumped phase conjugate reflectivities. However, barium titanate has had a relatively slow response time, and thus low sensitivity. Therefore, it has not been suited to real-time operations. In this report we will describe the modifications in crystal growth, doping, reduction, and poling that have produced barium titanate crystals with the fastest photorefractive response time reported to date, approximately 21 microseconds with a beam-coupling gain coefficient of 38.7 cm(exp -1) and the highest sensitivity reported to date of 3.44 cm(exp 3)/kJ. The sensitivity of these barium titanate crystals is comparable to or greater than other photorefractive oxides. We will show, for the first time, beam-coupling in barium titanate at video frame rates. We infer from response time measurements that barium titanate has a phonon limited mobility. Also, photorefractive response time measurements as a function of the crystallographic orientation and grating wave vector for our cobalt-doped oxygen reduced crystals indicate that their faster response time arise because of an increase in the free carrier lifetime.

Warde, C.↗
NASA NTRS2011

Volatile Analyzer for Lunar Polar Missions

One of the major questions remaining for the future exploration of the Moon by humans concerns the presence of volatiles on our nearest neighbor in space. Observational studies, and investigations involving returned lunar samples and using robotic spacecraft infer the existence of volatile compounds particularly water [1]. It seems very likely that a volatile component will be concentrated at the poles in circumstances where low-temperatures exist to provide cryogenic traps. However, the full inventory of species, their concentration and their origin and sources are unknown. Of particular importance is whether abundances are sufficient to act as a resource of consumables for future lunar expeditions especially if a long-term base involving humans is to be established. To address some of these issues requires a lander designed specifically for operation at a high-lunar latitude. A vital part of the payload needs to be a volatile analyzer such as the Gas Analysis Package specifically designed for identification quantification of volatile substances and collecting information which will allow the origin of these volatiles to be identified [1]. The equipment included, particularly the gas analyzer, must be capable of operation in the extreme environmental conditions to be encountered. No accurate information yet exists regarding volatile concentration even for sites closer to the lunar equator (because of contamination). In this respect it will be important to understand (and thus limit) contamination of the lunar surface by extraneous material contributed from a variety of sources. The only data for the concentrations of volatiles at the poles comes from orbiting spacecraft and whilst the levels at high latitudes may be greater than at the equator, the volatile analyzer package under consideration will be designed to operate at the highest specifications possible and in a way that does not compromise the data.

Gibons, Everett K.↗
NASA NTRS2011

Oxygen and Magnesium Isotopic Compositions of Asteroidal Materials Returned from Itokawa by the Hayabusa Mission

The Hayabusa spacecraft made two touchdowns on the surface of Asteroid 25143 Itokawa on November 20th and 26th, 2005. The Asteroid 25143 Itokawa is classified as an S-type asteroid and inferred to consist of materials similar to ordinary chondrites or primitive achondrites [1]. Near-infrared spectroscopy by the Hayabusa spacecraft proposed that the surface of this body has an olivine-rich mineral assemblage potentially similar to that of LL5 or LL6 chondrites with different degrees of space weathering [2]. The spacecraft made the reentry into the Earth s atmosphere on June 12th, 2010 and the sample capsule was successfully recovered in Australia on June 13th, 2010. Although the sample collection processes on the Itokawa surface had not been made by the designed operations, more than 1,500 grains were identified as rocky particles in the sample curation facility of JAXA, and most of them were judged to be of extraterrestrial origin, and definitely from Asteroid Itokawa on November 17th, 2010 [3]. Although their sizes are mostly less than 10 microns, some larger grains of about 100 microns or larger were also included. The mineral assembly is olivine, pyroxene, plagioclase, iron sulfide and iron metal. The mean mineral compositions are consistent with the results of near-infrared spectroscopy from Hayabusa spacecraft [2], but the variations suggest that the petrologic type may be smaller than the spectroscopic results. Several tens of grains of relatively large sizes among the 1,500 grains will be selected by the Hayabusa sample curation team for preliminary examination [4]. Each grain will be subjected to one set of preliminary examinations, i.e., micro-tomography, XRD, XRF, TEM, SEM, EPMA and SIMS in this sequence. The preliminary examination will start from the last week of January 2011. Therefore, samples for isotope analyses in this study will start from the last week of February 2011. By the time of the LPSC meeting we will have measured the oxygen and magnesium isotopic composition of several grains. We will present the first results from the isotope analyses that will have been performed.

Yurimoto, H↗
NASA NTRS1995

Inductive Approaches to Improving Diagnosis and Design for Diagnosability

The first research area under this grant addresses the problem of classifying time series according to their morphological features in the time domain. A supervised learning system called CALCHAS, which induces a classification procedure for signatures from preclassified examples, was developed. For each of several signature classes, the system infers a model that captures the class's morphological features using Bayesian model induction and the minimum message length approach to assign priors. After induction, a time series (signature) is classified in one of the classes when there is enough evidence to support that decision. Time series with sufficiently novel features, belonging to classes not present in the training set, are recognized as such. A second area of research assumes two sources of information about a system: a model or domain theory that encodes aspects of the system under study and data from actual system operations over time. A model, when it exists, represents strong prior expectations about how a system will perform. Our work with a diagnostic model of the RCS (Reaction Control System) of the Space Shuttle motivated the development of SIG, a system which combines information from a model (or domain theory) and data. As it tracks RCS behavior, the model computes quantitative and qualitative values. Induction is then performed over the data represented by both the 'raw' features and the model-computed high-level features. Finally, work on clustering for operating mode discovery motivated some important extensions to the clustering strategy we had used. One modification appends an iterative optimization technique onto the clustering system; this optimization strategy appears to be novel in the clustering literature. A second modification improves the noise tolerance of the clustering system. In particular, we adapt resampling-based pruning strategies used by supervised learning systems to the task of simplifying hierarchical clusterings, thus making post-clustering analysis easier.

Fisher, Douglas H.↗
NASA NTRS2005

Overview of Results from the Cassini Magnetospheric Imaging Instrument (MIMI) During the First Year of Operations

The MIMI investigation comprises three sensors covering the indicated energy ranges: the Ion and Neutral Camera (INCA) -- 7 keV/nuc 3 Mev) and protons (1.6 < E < 160 Mev) from the back end of the dual field-of-view telescope. The Saturn observation sequences began in January, 2004 and culminated in Saturn Orbit Insertion on July 1, 2004. The MIMI sensors observed substantial activity in interplanetary space for several months prior to SOI, including several interplanetary shocks associated with corotating interaction regions, numerous increases most likely originating from particle streams in the vicinity of the Saturnian bow shock and energetic neutral atoms (ENA) emanating from Saturn s magnetosphere. Results following SOI revealed: a dynamical magnetosphere with a day-night asymmetry and an 11-hour periodicity; several water-product ions (O+, OH+, H2O+), but little N+; inferred quantities of neutral gas sufficient to cause major losses in the trapped ions and electrons in the middle and inner magnetosphere; a Titan exosphere that is a copious source of ENA; INCA imaging through ENA has also revealed a previously unknown radiation belt residing inward of the D-ring that is most likely the result of double charge-exchange between the main radiation belt and the upper layers of Saturn s exosphere. Finally, there is ample evidence for the presence of substorm-like injections of plasma that subsequently corotates for a number of days before dissipating on the night-side magnetotail. The observations will be presented and discussed in the context of current theoretical models.

Krimigis, S. M.↗
NASA NTRS1977

Flow characteristics in an expansion tunnel as inferred from velocity measurements

A photoionization technique was used to study flow characteristics in an expansion tunnel. Vertical surveys of the axial component of flow velocity just downstream from the nozzle exit were obtained, and estimates of freestream density were inferred from the velocity measurement technique. The pitot pressure was measured and compared to the average axial component of velocity as a function of time for the two cases when air and CO2 were used as test gases. Vertical velocity and static density profiles at the nozzle exit are presented for the case when CO2 was used as test gas. Experimental results were used to determine the diameter and uniformity of the test core at the nozzle exit and the duration of the quasi-steady flow period. These data are relevant to evaluation of the suitability of operating an expansion tube as an expansion tunnel. The expansion tunnel is an expansion tube with a conical nozzle positioned at the exit of the acceleration section, so that nozzle entrance flow conditions are hypersonic and characterized by hypervelocity.

Miller, C. G.↗
NASA NTRS2020

Apatites in Gale Crater

ChemCam is an active remote sensing instrument suite that has operated successfully on MSL since landing Aug. 6th, 2012. It uses laser pulses to remove dust and to analyze rocks up to 7 m away. Laser-induced breakdown spectroscopy (LIBS) obtains emission spectra of materials ablated from the samples in electronically excited states. The intensities of the emission lines scale with the abundances of the related element. ChemCam is sensitive to most major rock-forming elements as well as to a set of minor and trace elements such as F, Cl, Li, P, Sr, Ba, and Rb. The measured chemical composition can then be used to infer the mineralogical composition of the ablated material. Here, we report a summary of inferred apatite detections along the MSL traverse at Gale Crater. We present the geologic settings of these findings and derive some interpretations about the formation conditions of apatite in time and space.

Forni, O.↗
NASA NTRS1992

Chemical environments of submarine hydrothermal systems

Perhaps because black-smoker chimneys make tremendous subjects for magazine covers, the proposal that submarine hydrothermal systems were involved in the origin of life has caused many investigators to focus on the eye-catching hydrothermal vents. In much the same way that tourists rush to watch the spectacular eruptions of Old Faithful geyser with little regard for the hydrology of the Yellowstone basin, attention is focused on the spectacular, high-temperature hydrothermal vents to the near exclusion of the enormous underlying hydrothermal systems. Nevertheless, the magnitude and complexity of geologic structures, heat flow, and hydrologic parameters which characterize the geyser basins at Yellowstone also characterize submarine hydrothermal systems. However, in the submarine systems the scale can be considerably more vast. Like Old Faithful, submarine hydrothermal vents have a spectacular quality, but they are only one fascinating aspect of enormous geologic systems operating at seafloor spreading centers throughout all of the ocean basins. A critical study of the possible role of hydrothermal processes in the origin of life should include the full spectrum of probable environments. The goals of this chapter are to synthesize diverse information about the inorganic geochemistry of submarine hydrothermal systems, assemble a description of the fundamental physical and chemical attributes of these systems, and consider the implications of high-temperature, fluid-driven processes for organic synthesis. Information about submarine hydrothermal systems comes from many directions. Measurements made directly on venting fluids provide useful, but remarkably limited, clues about processes operating at depth. The oceanic crust has been drilled to approximately 2.0 km depth providing many other pieces of information, but drilling technology has not allowed the bore holes and core samples to reach the maximum depths to which aqueous fluids circulate in oceanic crust. Such determinations rely on studies of pieces of deep oceanic crust uplifted by tectonic forces such as along the Southwest Indian Ridge, or more complete sections of oceanic crust called ophiolite sequences which are presently exposed on continents owing to tectonic emplacement. Much of what is thought to happen in submarine hydrothermal systems is inferred from studies of ophiolite sequences, and especially from the better-exposed ophiolites in Oman, Cyprus and North America. The focus of much that follows is on a few general features: pressure, temperature, oxidation states, fluid composition and mineral alteration, because these features will control whether organic synthesis can occur in hydrothermal systems.

Shock, Everett L.↗
NASA NTRS1993

Synergistic use of optical and microwave data in agrometeorological applications

Remotely sensed optical and microwave data can be synergistically used to infer land surface properties. Optical data can be used to estimate surface albedo, radiation absorption by vegetation canopies and their photosynthetic efficiencies. Vegetation canopy reflectance at red and near-infrared wavelengths can be used to correct for vegetation effect on microwave emissivities at low frequencies for estimating soil moisture. Optical data can also provide information about surface and air temperatures, precipitable water vapor, cloud top temperature and its water content. This information can be utilized to correct microwave data for atmospheric effects. These points are illustrated with theoretical analyses and by application to satellite data. The basic physical mechanisms operative at the various wavelengths are also discussed.

Myneni, R. B.↗
NASA NTRS1983

Plasma jet effects on the ionospheric plasma

Heavy ion beams were injected into the ionospheric plasma (experiments ARCS 1 and ARCS 2). In ARCS 1, operation of a 25eV argon ion source, mounted on a plasma diagnostic payload, produced an accelerated electron population; broadband electric field turbulence; large, spin synchronized electric field perturbations; and depletions of thermal ions. In ARCS 2, the ion source was deployed upward along the local magnetic field direction away from the diagnostic payload, and observed effects are contained within several meters of the ion source. However, enhanced wave levels near the LHR frequency are observed at distances up to 1 km, as are the injected ions themselves. A measurement of the dominant wavelength of the enhanced waves is consistent with an inference based upon the accelerated electron population seen in ARCS 1. This electron population is not evident during ARCS 2.

Moore, T. E.↗
NASA NTRS2006

Introduction to MODIS Cloud Products

The Earth's radiative energy balance and hydrological cycle are fundamentally coupled with the distribution and properties of clouds. Therefore, the ability to remotely infer cloud properties and their variation in space and time is crucial for establishing climatologies as a reference for validation of present-day climate models and in assessing future climate change. Remote cloud observations also provide data sets useful for testing and improving cloud model physics, and for assimilation into numerical weather prediction models. The MODerate Resolution Imaging Spectroradiometer (MODIS) imagers on the Terra and Aqua Earth Observing System (EOS) platforms provide the capability for globally retrieving these properties using passive solar reflectance and infrared techniques. In addition to providing measurements similar to those offered on a suite of historical operational weather platforms such as the Advanced Very High Resolution Radiometer (AVHRR), the High-resolution Infrared Radiation Sounder (HIRS), and the Geostationary Operational Environmental Satellite (GOES), MODIS provides additional spectral and/or spatial resolution in key atmospheric bands, along with on-board calibration, to expand the capability for global cloud property retrievals. The core MODIS operational cloud products include cloud top pressure, thermodynamic phase, optical thickness, particle size, and water path, and are derived globally at spatial resolutions of either 1- or 5-km (referred to as Level-2 or pixel-level products). In addition, the MODIS atmosphere team (collectively providing cloud, aerosol, and clear sky products) produces a combined gridded product (referred to as Level-3) aggregated to a 1 equal-angle grid, available for daily, eight-day, and monthly time periods. The wealth of information available from these products provides critical information for climate studies as well as the continuation and improved understanding of existing satellite-based cloud climatologies derived from heritage instruments. This chapter provides an overview of the MODIS Level-2 and -3 operational cloud products.

Baum, Bryan A.↗
NASA NTRS2004

On Study of Air/Space-borne Dual-Wavelength Radar for Estimates of Rain Profiles

In this study, a framework is discussed to apply air/space-borne dual-wavelength radar for the estimation of characteristic parameters of hydrometeors. The focus of our study is on the Global Precipitation Measurements (GPM) precipitation radar, a dual-wavelength radar that operates at Ku (13.8 GHz) and Ka (35 GHz) bands. As the droplet size distributions (DSD) of rain are expressed as the Gamma function, a procedure is described to derive the median volume diameter (D(sub 0)) and particle number concentration (N(sub T)) of rain. The correspondences of an important quantity of dual-wavelength radar, defined as deferential frequency ratio (DFR), to the D(sub 0) in the melting region are given as a function of the distance from the 0 C isotherm. A self-consistent iterative algorithm that shows a promising to account for rain attenuation of radar and infer the DSD without use of surface reference technique (SRT) is examined by applying it to the apparent radar reflectivity profiles simulated from the DSD model and then comparing the estimates with the model (true) results. For light to moderate rain the self-consistent rain profiling approach converges to unique and correct solutions only if the same shape factors of Gamma functions are used both to generate and retrieve the rain profiles, but does not converges to the true solutions if the DSD form is not chosen correctly. To further examine the dual-wavelength techniques, the self-consistent algorithm, along with forward and backward rain profiling algorithms, is then applied to the measurements taken from the 2nd generation Precipitation Radar (PR-2) built by Jet Propulsion Laboratory. It is found that rain profiles estimated from the forward and backward approaches are not sensitive to shape factor of DSD Gamma distribution, but the self-consistent method is.

Liao, Liang↗