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NASA NTRS2018

The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 Aerosol Extinction Retrieval Algorithm: Theoretical Basis

The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

Loughman, Robert↗
NASA NTRS2020

Polarimetric Radar Characteristics of Simulated and Observed Intense Convective Cores for a Midlatitude Continental and Tropical Maritime Environment

This study contrasts midlatitude continental and tropical maritime deep convective cores using polarimetric radar observables and retrievals from selected deep convection episodes during the MC3E and TWPICE field campaigns. The continental convective cores produce stronger radar reflectivities throughout the profiles, while maritime convective cores produce more positive differential reflectivity Z(dr) and larger specific differential phase K(dp) above the melting level. Hydrometeor identification retrievals revealed the presence of large fractions of rimed ice particles (snow aggregates) in the continental (maritime) convective cores, consistent with the Z(dr) and K(dp) observations. The regional cloud-resolving model simulations with bulk and size-resolved bin microphysics are conducted for the selected cases, and the simulation outputs are converted into polarimetric radar signals and retrievals identical to the observational composites. Both the bulk and the bin microphysics reproduce realistic land and ocean (L-O) contrasts in reflectivity, polarimetric variables of rain drops, and hydrometeor profiles, but there are still large uncertainties in describing Zdr and Kdp of ice crystals associated with the ice particle shapes/orientation assumptions. Sensitivity experiments are conducted by swapping background aerosols between the continental and maritime environments, revealing that background aerosols play a role in shaping the distinct L-O contrasts in radar reflectivity associated with raindrop sizes, in addition to the dominant role of background thermodynamics.

Toshihisa Matsui↗
NASA NTRS2000

MODIS Retrievals of Cloud Optical Thickness and Particle Radius

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity for global cloud studies with 36 spectral bands from the visible through the infrared, and spatial resolution from 250 m to 1 km at nadir. In particular, all solar window bands useful for simultaneous retrievals of cloud optical thickness and particle size (0.67, 0.86, 1.2, 1.6, 2.1, and 3.7 micron bands) are now available on a single satellite instrument/platform for the first time. An operational algorithm for the retrieval of these optical and cloud physical properties (including water path) have been developed for both liquid and ice phase clouds. The product is archived into two categories: pixel-level retrievals at 1 km spatial resolution (referred to as a Level-2 product) and global gridded statistics (Level-3 product). An overview of the MODIS cloud retrieval algorithm and early level-2 and -3 results will be presented. A number of MODIS cloud validation activities are being planned, including the recent Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign conducted in August/September 2000. The later part of the experiment concentrated on MODIS validation in the Namibian stratocumulus regime off the southwest coast of Africa. Early retrieval results from this regime will be discussed.

Platnick, S.↗
NASA NTRS2019

SPARROW: Steam Propelled Autonomous Retrieval Robot for Ocean Worlds

The Steam Propelled Autonomous Retrieval Robot (SPARROW) for Ocean Worlds was a Phase I mission concept study funded under the NASA NIAC program. This report represents the findings of that study and recommendations for future work. SPARROW, envisioned as a soccer ball-sized payload to a primary lander mission, is a propulsively hopping robot for the exploration of Europa's rugged, icy surface. A multi-thruster, passively gimballed robot within a protective, spherical shell, SPARROW is able to freely rotate, self-right, and tumble over chaotic terrains. Europa's abundant surface ice would be harvested as an in situ propellant source. The principal objective of SPARROW is to increase the science return of a Europa landed asset by enabling access to distal, spatially distributed geologic units. The design of mobility systems for Europa is challenging, due in part to its almost entirely unconstrained surface topography and strength. Images returned by Voyager and Galileo yielded resolutions on the order of hundreds of meters per pixel, with localized regions reaching 6 meters per pixel—still far larger than a typical rover. A key benefit of SPARROW's hopping, impact-tolerant design, is that it eliminates the need for a priori information regarding terrain topography and surface strength; no surface reaction forces are required for motion. In this context, SPARROW is believed to be entirely terrain agnostic. In this report we detail the results of three study objectives: i) to quantify the energy required to collect surface ice, change its phase, and maintain propellant temperature, ii) to identify control and estimation strategies that enable SPARROW to successfully reach, and return from, regions of scientific interest, and iii) to characterize the impact of SPARROW's range on likely science return. Five water-based propellant architectures are presented alongside their mass, power, and volume requirements. Monte Carlo simulations of SPARROW hopping and tumbling over 1 km of glacial ice are summarized, characterizing SPARROW's sensitivity to uncertainty in: initial pose, thrust profile, and vehicle-terrain interaction. A science traceability matrix is presented, which details the effect of sortie range on three science goals: constraining Europa's evolutionary morphology, assessing sub-surface ocean habitability, and searching for life and/or biosignatures.

Autonomous↗
NASA NTRS2004

Robust Requirements Tracing via Internet Search Technology: Improving an IV and V Technique

There are three major objectives to this phase of the work. (1) Improvement of Information Retrieval (IR) methods for Independent Verification and Validation (IV&V) requirements tracing. Information Retrieval methods are typically developed for very large (order of millions - tens of millions and more documents) document collections and therefore, most successfully used methods somewhat sacrifice precision and recall in order to achieve efficiency. At the same time typical IR systems treat all user queries as independent of each other and assume that relevance of documents to queries is subjective for each user. The IV&V requirements tracing problem has a much smaller data set to operate on, even for large software development projects; the set of queries is predetermined by the high-level specification document and individual requirements considered as query input to IR methods are not necessarily independent from each other. Namely, knowledge about the links for one requirement may be helpful in determining the links of another requirement. Finally, while the final decision on the exact form of the traceability matrix still belongs to the IV&V analyst, his/her decisions are much less arbitrary than those of an Internet search engine user. All this suggests that the information available to us in the framework of the IV&V tracing problem can be successfully leveraged to enhance standard IR techniques, which in turn would lead to increased recall and precision. We developed several new methods during Phase II; (2) IV&V requirements tracing IR toolkit. Based on the methods developed in Phase I and their improvements developed in Phase II, we built a toolkit of IR methods for IV&V requirements tracing. The toolkit has been integrated, at the data level, with SAIC's SuperTracePlus (STP) tool; (3) Toolkit testing. We tested the methods included in the IV&V requirements tracing IR toolkit on a number of projects.

Hayes, Jane↗
NASA NTRS2002

Non-Spherical Aerosol Phase Functions Derived from MODIS and AERONET Observations

We compare MODIS (Moderate Resolution Imaging Spectroradiometer) satellite aerosol retrievals of spectral optical thickness and size parameters over ocean with the same quantities derived from AERONET (Aerosol Robotic Network) observations made at island and coastal sites. Over much of the globe, the satellite-derived quantities agree well with the AERONET quantities. However, in regimes dominated by desert dust aerosol, the agreement is less robust. In the dust regimes, the MODIS retrievals show greater spectral dependence and report smaller particle sizes than do the AERONET derivations. We suggest that the reason for this discrepancy is the nonspherical nature of desert dust particles, which the initial MODIS algorithm is not able to handle. Using the discrepancy between MODIS and AERONET derived spectral optical thickness as an asset, instead of a detriment, we reconstruct the aerosol phase functions that the MODIS algorithm would have needed in order to match the AERONET retrievals. No assumptions of particle shape are used in the derivation of these functions and the results are empirical total column, ambient phase functions. We compare the empirically derived phase functions with phase functions calculated from spheres and spheroids, both situations in which assumptions about particle shape must be made. The resulting empirical nonspherical phase functions will be included in future updates of the MODIS algorithm.

Remer, L. A.↗
NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗
NASA NTRS2010

Detecting Thin Cirrus in Multiangle Imaging Spectroradiometer Aerosol Retrievals

Thin cirrus clouds (optical depth (OD) < 03) are often undetected by standard cloud masking in satellite aerosol retrieval algorithms. However, the Mu]tiangle Imaging Spectroradiometer (MISR) aerosol retrieval has the potential to discriminate between the scattering phase functions of cirrus and aerosols, thus separating these components. Theoretical tests show that MISR is sensitive to cirrus OD within Max{0.05 1 20%l, similar to MISR's sensitivity to aerosol OD, and MISR can distinguish between small and large crystals, even at low latitudes, where the range of scattering angles observed by MISR is smallest. Including just two cirrus components in the aerosol retrieval algorithm would capture typical MISR sensitivity to the natural range of cinus properties; in situations where cirrus is present but the retrieval comparison space lacks these components, the retrieval tends to underestimate OD. Generally, MISR can also distinguish between cirrus and common aerosol types when the proper cirrus and aerosol optical models are included in the retrieval comparison space and total column OD is >-0.2. However, in some cases, especially at low latitudes, cirrus can be mistaken for some combinations of dust and large nonabsorbing spherical aerosols, raising a caution about retrievals in dusty marine regions when cirrus is present. Comparisons of MISR with lidar and Aerosol Robotic Network show good agreement in a majority of the cases, but situations where cirrus clouds have optical depths >0.15 and are horizontally inhomogeneous on spatial scales shorter than 50 km pose difficulties for cirrus retrieval using the MISR standard aerosol algorithm..

Pierce, Jeffrey R.↗
NASA NTRS1972

ERISTAR: Earth Resources Information Storage, Transformation, Analysis, and Retrieval administrative report

The 1972 Systems Engineering program at Marshall Space Flight Center where 15 participants representing 15 U.S. universities, 1 NASA/MSFC employee, and another specially assigned faculty member, participated in an 11-week program is discussed. The Fellows became acquainted with the philosophy of systems engineering, and as a training exercise, used this approach to produce a conceptional design for an Earth Resources Information Storage, Transformation, Analysis, and Retrieval System. The program was conducted in three phases; approximately 3 weeks were devoted to seminars, tours, and other presentations to subject the participants to technical and other aspects of the information management problem. The second phase, 5 weeks in length, consisted of evaluating alternative solutions to problems, effecting initial trade-offs and performing preliminary design studies and analyses. The last 3 weeks were occupied with final trade-off sessions, final design analyses and preparation of a final report and oral presentation.

Vachon, R. I.↗
NASA NTRS1988

An algorithm to derive precipitation profiles from a downward viewing radar and a multifrequency passive radiometer

An algorithm that yields a robust solution of the radar equation subjected to constraints imposed by measurements of dual polarized, multifrequency microwave radiances is developed. Using simulated data, it is shown that this algorithm generates retrieved hydrometeor profiles that overcome limitations of the radar retrievals introduced by noise and ambiguities in the phase of the hydrometeors.

Weinman, J. A.↗
NASA NTRS2017

An ISRU Propellant Production System to Fully Fuel a Mars Ascent Vehicle

ISRU of Mars resources was base lined in 2009 Design Reference Architecture (DRA) 5.0, but only for Oxygen production using atmospheric CO2The Methane (LCH4) needed for ascent propulsion of the Mars Ascent Vehicle (MAV) would need to be brought from Earth. HOWEVER: Extracting water from the Martian Regolith enables the production of both Oxygen and Methane from Mars resources Water resources could also be used for other applications including: Life support, radiation shielding, plant growth, etc. Water extraction was not base lined in DRA5.0 due to perceived difficulties and complexity in processing regolith. The NASA Evolvable Mars Campaign (EMC) requested studies to look at the quantitative benefits and trades of using Mars water ISRU Phase 1: Examined architecture scenarios for regolith water retrieval. Completed October 2015Phase 2: Deep dive of one architecture concept to look at end-to-end system size, mass, power of a LCH4LO2 ISRU production system.Evolvable Mars CampaignPre-deployed Mars ascent vehicle (MAV)4 crew membersPropellants: Oxygen MethaneGenerate a system model to roll up mass power of a full ISRU system and enable parametric trade studies. Leverage models from previous studies and technology development programs Anchor with mass power performance from existing hardware. Whenever possible used reference-able (published) numbers for traceability.Modular approach to allow subsystem trades and parametric studies. Propellant mass needs taken from most recently published MAV study:Polsgrove, T. et al. (2015), AIAA2015-4416MAV engines operate at mixture ratios (oxygen: methane) between 3:1 and 3.5:1, whereas the Sabatier reactor produces at a 4:1 ratio. Therefore:Methane production is the driving requirement-Excess Oxygen will be produced.

Mars surface↗
NASA NTRS2005

Sporadic E Morphology from GPS-CHAMP Radio Occultation

The scintillations of phase and amplitude in terms of signal-to-noise ratio (SNR) of the GPS radio occultation signal are caused by thin ionization layers. These thin irregular electron density layers in the E region ionosphere are often called sporadic E (Es). For a monthly retrieval of Es morphology we use the variances of the phase and SNR fluctuations of worldwide ~6000 GPS/CHAMP occultations in the E region. The Es climatology is studied globally with the SNR and phase variances in terms of monthly zonal means, seasonal maps, and diurnal and long-term variations. The zonal mean variances reveal strong, extended Es activities at summertime midlatitudes but weak, confined activities in wintertime high latitudes, peaking at ~105 km. Global maps at 105-km altitude show clear dependence of Es activities on the geomagnetic dip angle, where the summertime midlatitude Es occurs mostly at dip angles of 30 deg. - 60 deg. and the wintertime high-latitude enhancement occurs mostly at dip angles greater than 80 deg. The midlatitude Es variances exhibit a strong semidiurnal variation with peak hours near 0800 1000 and 2000 local solar time, respectively. The peak hours are delayed slightly with decreasing height, suggesting influences from the semidiurnal tide. To provide more insights on the observed SNR and phase variances, we model radio wave propagation for the CHAMP observing geometry under several perturbed cases in the E region ionosphere. The model simulations indicate that the SNR variance has the maximum response to Es perturbations at vertical wavelengths of 1.2 km, whereas the phase response maximizes at ~2 km (for the 1-s variance analysis). The characteristic scale depends little on the truncation time used in the SNR variance analysis, but it increases with the truncation time for the phase variances. Initial studies show that reasonable global Es morphology can be produced on a monthly and seasonal basis with the CHAMP one-antenna occultations. Better results from other existing and upcoming GPS occultation missions are anticipated in future studies, and they will significantly improve our understanding of this important phenomenon.

signal to noise ration (SNR)↗
NASA NTRSDate not supplied

Hyperspectral Radiatve Transfer Modeling and its Applications

We will describe a fast radiative transfer model that is specifically designed for hyperspectral remote sensing applications. The fast radiative transfer model is capable of performing efficient and accurate calculations under cloudy condition and in the presence of solar radiations. The model uses a Principal Component Analysis to speed up computational speed. The PCRTM model is capable of simulating top of atmospheric radiance or reflectance spectral from 50 wavenumber to 30000 wavenumber. The PCRTM has a very good accuracy relative to reference line-by-line radiative transfer models and it saves orders of magnitude computational time. We will show comparisons of the PCRTM model to AIRS, CrIS, IASI, NAST-I, and SCIAMACHY data. We will further show results of applying the PCRTM retrieval algorithm to these remote sensing data to retrieve atmospheric temperature and moisture profiles, CO2, CO, CH4, N2O, and O3 profiles, cloud optical depth, size, phase, and height. Surface properties such as surface emissivity spectra and surface skin temperatures are also retrieved simultaneously.

X Liu↗
NASA NTRS2011

MODIS Cloud Optical Property Retrieval Uncertainties Derived from Pixel-Level VNIR/SWIR Radiometric Uncertainties

Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of optical thickness and effective particle radius for liquid water and ice phase clouds employ a well-known VNIR/ SWIR solar reflectance technique. For this type of algorithm, we evaluate the quantitative uncertainty in simultaneous retrievals of these two cloud parameters to pixel-level radiometric calibration estimates and other fundamental (and tractable) error sources.

Platnick, S.↗
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Kawamoto, K.↗
NASA NTRS2001

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds

Kawamoto, Kazuaki↗
NASA NTRS2006

The Potential of Water Vapor & Precipitation Estimation with a Differential-frequency Radar

In the presence of rain, the radar return powers from a three-frequency radar, with center frequency at 22.235 GHz and upper and lower frequencies chosen with equal water vapor absorption coefficients, can be used to estimate water vapor density and parameters of the precipitation. A linear combination of differential measurements between the center and lower frequencies on one hand and the upper and lower frequencies on the other provide an estimate of differential water vapor absorption. Conversely, the difference in radar reflectivity factors (in dB) between the upper and lower frequencies is independent of water vapor absorption and can be used to estimate the median mass diameter of the hydrometeors. For a down-looking radar, path-integrated estimates of water vapor absorption may be possible under rain-free as well as raining conditions by using the surface returns at the three frequencies. Cross-talk or interference between the precipitation and water vapor estimates depends on the frequency separation of the channels as well as on the phase state and the median mass diameter of the hydrometeors. Simulations of the retrieval of water vapor absorption show that the largest source of variability arises from the variance in the measured radar return powers while the largest biases occur in the mixed-phase region. Use of high pulse repetition frequencies and signal whitening methods may be needed to obtain the large number of independent samples required. Measurements over a fractional bandwidth, defined as the ratio of the difference between the upper and lower frequencies to the center frequency, up to about 0.2 should be passible in a differential frequency mode, where a single transceiver and antenna are used. Difficulties in frequency allocation may require alternative choices of frequency where the water vapor absorptions at the low and high frequencies are unequal. We consider the degradation in the retrieval accuracy when the frequencies are not optimum.

Meneghini, Robert↗
NASA NTRS1999

Thermal Tides and Stationary Waves Revealed by MGS TES

Atmospheric temperature retrievals from TES observed radiances make possible the most complete separation of the constituent wave modes evident in Mars atmosphere to date. We use all of the data from the pre-mapping mission phase, which affords good sampling of the diurnal tides and stationary waves. TES retrievals of atmospheric temperature on a grid of pressure levels are the fundamental data set in this study. We then fit this data to selected fourier modes in longitude and time for latitude and L(sub s) bins. From this we have identified the amplitudes and phases of the diurnal and semi-diurnal tides, the first few (gravest) stationary waves and standing waves, as well as an estimate of the zonal and time mean temperature meridional cross sections. These results will be compared with existing models and theory. A possible critical layer for the sun-synchronous diurnal tide may indicate 40 m/s surface zonal wind near 50S for L(sub s) =255-285. Additional information is contained in the original extended abstract.

Banfield, D.↗