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At least 361 records · Page 20

Rainfall observations by an airbourne dual-fequency precipitation radar during CAMEX-4

The 2d Generation Precipitation Radar is a new design for a dual-frequency (13.4 and 35.6 GHz) spaceborne precipitation radar. An airborne PR-2 simulator has been developed to demonstrate key technologies. This airborne system was flown on the NASA DC-8 aircraft during the 4th Convection and Moisture Experiment in 2001. Data were acquired in Tropical Storms Chantal and Gabrielle, Hurricane Humberto, and in several more localized convective systems. The authors discuss the design of thePR-2 airborne radar and show observations from CAMEX-4. Overall, the observations validated the design of PR-2 and provide an extensive data set for scientific analysis.

precipitation radar TRMM GPM CAMEX-4↗

Analyses of the Integration of Carbon Dioxide Removal Assembly, Compressor, Accumulator and Sabatier Carbon Dioxide Reduction Assembly

A tool has been developed by the Sabatier Team for analyzing/optimizing CO2 removal assembly, CO2 compressor size, its operation logic, water generation from Sabatier, utilization of CO2 from crew metabolic output, and Hz from oxygen generation assembly. Tests had been conducted using CDRA/Simulation compressor set-up at MSFC in 2003. Analysis of test data has validated CO2 desorption rate profile, CO2 compressor performance, CO2 recovery and CO2 vacuum vent in CDRA desorption. Optimizing the compressor size and compressor operation logic for an integrated closed air revitalization system Is being conducted by the Sabatier Team.

Jeng, Frank F.↗

The Algorithm Theoretical Basis Document for the GLAS Atmospheric Data Products

The purpose of this document is to present a detailed description of the algorithm theoretical basis for each of the GLAS data products. This will be the final version of this document. The algorithms were initially designed and written based on the authors prior experience with high altitude lidar data on systems such as the Cloud and Aerosol Lidar System (CALS) and the Cloud Physics Lidar (CPL), both of which fly on the NASA ER-2 high altitude aircraft. These lidar systems have been employed in many field experiments around the world and algorithms have been developed to analyze these data for a number of atmospheric parameters. CALS data have been analyzed for cloud top height, thin cloud optical depth, cirrus cloud emittance (Spinhirne and Hart, 1990) and boundary layer depth (Palm and Spinhirne, 1987, 1998). The successor to CALS, the CPL, has also been extensively deployed in field missions since 2000 including the validation of GLAS and CALIPSO. The CALS and early CPL data sets also served as the basis for the construction of simulated GLAS data sets which were then used to develop and test the GLAS analysis algorithms.

Palm, Stephen P.↗

Demonstration of Hybrid Multilayer Insulation for Fixed Thickness Applications

Once on orbit, high performing insulation systems for cryogenic systems need just as good radiation (optical) properties as conduction properties. This requires the use of radiation shields with low conductivity spacers in between. By varying the height and cross-sectional area of the spacers between the radiation shields, the relative radiation and conduction heat transfers can be manipulated. However, in most systems, there is a fixed thickness or volume allocated to the insulation. In order to understand how various combinations of different multilayer insulation (MLI) systems work together and further validate thermal models of such a hybrid MLI set up, test data is needed. The MLI systems include combinations of Load Bearing MLI (LB-MLI) and traditional MLI. To further simulate the space launch vehicle case wherein both ambient pressure and vacuum environments are addressed, different cold-side thermal insulation substrates were included for select tests.

Cryogenic Fluid Management↗

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

In this work, we propose a hybrid model for Li-ion battery discharge and aging prediction that leverages fleet-wide data to predict future capacity drops.The model is built upon an hybrid approach merging physics-based and empirical equations, as well as neural network models in a recurrent neural network cell. The hybrid physics-informed neural network can predict voltage discharge cycles given the loading profile, and estimate the used capacity of the battery under random-loading conditions by tracking aging parameters connected to the residual capacity of the battery. By merging information on the battery aging parameters with existing fleet-wide aging data, the model can predict the future residual capacity of the battery that is being monitored, and therefore enable predictions of voltage discharge curves far ahead in the battery life cycle. We validated the approach using the NASA Prognostics Data Repository Battery data-set, which contains experimental data on Li-ion batteries discharged at random loading conditions in a controlled environment. The approach also allows the identification of discrepancies between the battery aging trend and the trend observed at the fleet level, so that batteries behaving differently from the rest of the fleet can be subject to closer monitoring and further testing to refine predictions.

PINN↗

Solar FTIR Measurements of NOx Vertical Distributions – Part 2: Experiment-Based Scaling Factors Describing the Daytime Variation in Stratospheric NOx

Long-term experimental stratospheric NO2 and NO partial columns measured by means of solar Fourier-transform infrared (FTIR) spectrometry at Zugspitze (47.42° N, 10.98° E; 2964 m a.s.l.), Germany, were used to create a set of experiment-based monthly scaling factors (SFexp). The underlying data set is published in a companion paper (Nürnberg et al., 2024) and comprises over 25 years of measurements depicting the daytime variability of stratospheric NO2 and NO partial columns with respect to local solar time (LST). In accordance with simulation-based scaling factors recently published by Strode et al. (2022), we created SFexp normalized to SZA =72° for NO2 and NO for every month of the year as a function of solar zenith angle (SZA). Apart from a boundary value problem at minimum SZA values originating from averaging over different times of the month, the obtained scaling factors SFexp(NO2) and SFexp(NO) as a function of SZA represent the daytime behavior already shown in model simulations and experiments in the literature very well. This shows a well-pronounced increase in the NO2 and NO stratospheric partial column with the time of the day and a flattening of this increase after noon. In addition to the discussion of SFexp, we validate the simulation-based scaling factors SFsim(NO2) (Strode et al., 2022) and present simulation-based scaling factors for NO SFsim(NO). The simulation-based scaling factors show excellent agreement with the experiment-based ones; i.e., for NO2 and NO the mean value of the modulus between the experiment and simulation over all SZAs and months is only 0.02 %. We show that recently used model simulations can describe the real behavior of nitrogen oxide (NOx) variability in the stratosphere very well. Furthermore, we conclude that ground-based FTIR measurements can be used for validation of the output of photochemistry models and for creating experiment-based data sets describing the daytime stratospheric NOx variability as a function of SZA. This is a contribution to improved satellite validation and a better understanding of stratospheric photochemistry.

FTIR, nitrogen oxides, diurnal variability↗

The Salinity Pilot-Mission Exploitation Platform (Pi-MEP): A Hub for Validation and Exploitation of Satellite Sea Surface Salinity Data

The Pilot-Mission Exploitation Platform (Pi-MEP) for salinity is an ESA initiative originally meant to support and widen the uptake of Soil Moisture and Ocean Salinity (SMOS) mission data over the ocean. Starting in 2017, the project aims at setting up a computational web-based platform focusing on satellite sea surface salinity data, supporting studies on enhanced validation and scientific process over the ocean. It has been designed in close collaboration with a dedicated science advisory group in order to achieve three main objectives: gathering all the data required to exploit satellite sea surface salinity data, systematically producing a wide range of metrics for comparing and monitoring sea surface salinity products’ quality, and providing user-friendly tools to explore, visualize and exploit both the collected products and the results of the automated analyses. The Salinity Pi-MEP is becoming a reference hub for the validation of satellite sea surface salinity missions by providing valuable information on satellite products (SMOS, Aquarius, SMAP), an extensive in situ database (e.g., Argo, thermosalinographs, moorings, drifters) and additional thematic datasets (precipitation, evaporation, currents, sea level anomalies, sea surface temperature, etc.). Co-localized databases between satellite products and in situ datasets are systematically generated together with validation analysis reports for 30 predefined regions. The data and reports are made fully accessible through the web interface of the platform. The datasets, validation metrics and tools (automatic, user-driven) of the platform are described in detail in this paper. Several dedicated scientific case studies involving satellite SSS data are also systematically monitored by the platform, including major river plumes, mesoscale signatures in boundary currents, high latitudes, semi-enclosed seas, and the high-precipitation region of the eastern tropical Pacific. Since 2019, a partnership in the Salinity Pi-MEP project has been agreed between ESA and NASA to enlarge focus to encompass the entire set of satellite salinity sensors. The two agencies are now working together to widen the platform features on several technical aspects, such as triple-collocation software implementation, additional match-up collocation criteria and sustained exploitation of data from the SPURS campaigns

ocean↗

Scientific and engineering analyses of Jupiter's energetic electrons and protons

Details of magnetic field conclusions, UHF radio data sets, and the theoretical synchrotron radiation descriptions are summarized for several published and unpublished analyses. The relatively compact set of electron models inspires some confidence in their validity, particularly as they have been derived from numerous data and analysis techniques. Although the models have serious consequences for spacecraft design, the problems they imply are probably soluble with technologies anticipated for spacecraft to be designed for Jupiter encounter. By contrast, the proton models are very diverse, fluxes and energies spanning several orders of magnitude even for those models based on physical considerations; this results from the absence of applicable data. However, even in the midrange of these models, the proton energies and fluxes would be severely hazardous to several spacecraft subsystems. It is therefore desirable to apply further technical consideration to the modeling of Jupiter's energetic proton population.

Divine, N.↗

Simulating Underexpanded Plumes in Martian and Lunar Environments

While the Loci/Chem Computational fluid dynamics (CFD) application has been validated and used extensively for simulating launch environments in atmospheric conditions, use of this tool for simulating supersonic plumes at much lower ambient pressure requires further validation. Simulations of underexpanded plumes have been performed using Loci/Chem at Martian pressure to predict several metrics for laminar, turbulent, and impinging plumes. The CFD results are compared with an experimental data set for low Reynolds number plumes at these conditions in order to evaluate the current capability of the Loci/Chem tool for these types of environments. The CFD validation results to date show reasonable agreement with the experimental data across all the metrics of interest for the configurations considered. The Loci/Chem-Boltzmann tool is a hybrid continuum/rarefied flow solver which extends modeling capabilities to very low-pressure environments such as those on the Moon. The Loci/Chem-Boltzmann solver uses a gradient-based continuum breakdown criterion to restrict solution of the computationally expensive Boltzmann equation to only a subset of the domain, while using the Navier-Stokes equations elsewhere. This CFD application is under active development, and current efforts toward establishing production ready capability for evaluating Lunar plume surface interactions are well under way. Initial simulations of an Apollo Lunar excursion module indicate that several regions of the flow require solving the Boltzmann equations due to extreme rarefaction. Early simulations are promising, indicating reasonable overall computational time for a full 3D human scale lander simulation.

Plume Surface Interaction↗

Validation of Long-Term Global Aerosol Climatology Project Optical Thickness Retrievals Using AERONET and MODIS Data

A comprehensive set of monthly mean aerosol optical thickness (AOT) data from coastal and island AErosol RObotic NETwork (AERONET) stations is used to evaluate Global Aerosol Climatology Project (GACP) retrievals for the period 1995-2009 during which contemporaneous GACP and AERONET data were available. To put the GACP performance in broader perspective, we also compare AERONET and MODerate resolution Imaging Spectroradiometer (MODIS) Aqua level-2 data for 2003-2009 using the same methodology. We find that a large mismatch in geographic coverage exists between the satellite and ground-based datasets, with very limited AERONET coverage of open-ocean areas. This is especially true of GACP because of the smaller number of AERONET stations at the early stages of the network development. Monthly mean AOTs from the two over-the-ocean satellite datasets are well-correlated with the ground-based values, the correlation coefficients being 0.81-0.85 for GACP and 0.74-0.79 for MODIS. Regression analyses demonstrate that the GACP mean AOTs are approximately 17%-27% lower than the AERONET values on average, while the MODIS mean AOTs are 5%-25% higher. The regression coefficients are highly dependent on the weighting assumptions (e.g., on the measure of aerosol variability) as well as on the set of AERONET stations used for comparison. Comparison of over-the-land and over-the-ocean MODIS monthly mean AOTs in the vicinity of coastal AERONET stations reveals a significant bias. This may indicate that aerosol amounts in coastal locations can differ significantly from those in adjacent open-ocean areas. Furthermore, the color of coastal waters and peculiarities of coastline meteorological conditions may introduce biases in the GACP AOT retrievals. We conclude that the GACP and MODIS over-the-ocean retrieval algorithms show similar ranges of discrepancy when compared to available coastal and island AERONET stations. The factors mentioned above may limit the performance of the validation procedure and cause us to caution against a direct extrapolation of the presented validation results to the entirety of the GACP dataset.

MODIS (radiometry)↗

NASA sea ice validation program for the Defense Meteorological Satellite Program special sensor microwave imager

Attention is given to the prime objective of the NASA validation program, namely, to establish quantitative relationships between the sea ice parameters derived from the special sensor microwave imager (SSM/I) using an algorithm originally developed for the Nimbus 7 SMMR. The underlying philosophy of the validation program is that confidence in the SSM/I algorithm products is achieved not so much by detailed comparison with localized surface observations as by consistency with independent spatially and temporally coincident data sets. The results of the satellite and aircraft comparisons that serve as the basis for the validation of the NASA SSMI/I sea ice algorithm are presented. High-resolution radiometer and C-band SAR imagery from the March 1988 NASA and Navy SSM/I underflights are used to verify the location of the ice edge and to validate the sea ice concentrations as determined by the SSM/I algorithm. These studies are argued to provide the most comprehensive measure to date of the accuracy of sea ice products derived from a spaceborne multichannel microwave imager.

Cavalieri, Donald J.↗

Validation of MODIS Aerosol Retrieval Over Ocean

The MODerate resolution Imaging Spectroradiometer (MODIS) algorithm for determining aerosol characteristics over ocean is performing with remarkable accuracy. A two-month data set of MODIS retrievals co-located with observations from the AErosol RObotic NETwork (AERONET) ground-based sunphotometer network provides the necessary validation. Spectral radiation measured by MODIS (in the range 550 - 2100 nm) is used to retrieve the aerosol optical thickness, effective particle radius and ratio between the submicron and micron size particles. MODIS-retrieved aerosol optical thickness at 660 nm and 870 nm fall within the expected uncertainty, with the ensemble average at 660 nm differing by only 2% from the AERONET observations and having virtually no offset. MODIS retrievals of aerosol effective radius agree with AERONET retrievals to within +/- 0.10 micrometers, while MODIS-derived ratios between large and small mode aerosol show definite correlation with ratios derived from AERONET data.

Remer, Lorraine A.↗

Global Energy and Water Exchanges Program Surface Radiation Budget Release 4 Integrated Product: Algorithm Theoretical Basis Document

This document represents the Algorithm Theoretical Basis Document (ATBD) describing the NASA Langley Research Center's Surface Radiation budget (SRB) developed in collaboration with the World Research Climate Programme's Global Energy and Water Exchanges Program. The top of atmosphere and surface fluxes span from July 1, 1983 through June 30, 2017. The shortwave or solar wavelengths span the entire record. The thermal infrared or longwave fluxes span globally from January 1, 1988 to December 30, 2009. Before 1988, only the land-only fluxes are available. After 2009 only the ocean fluxes are available. This document describes all the inputs and radiative transfer algorithms used to generate the TOA and surface radiative fluxes. The fluxes include upward and downward, all-sky, clear-sky and pristine sky conditions. Surface net fluxes and cloud radiative effect are computed and presented as part of the analysis. Comparisons to other data products are made to assess the top-of-atmosphere and surface fluxes. Additionally, surface measurements are utilized to validation the surface fluxes. The surface validation analysis shows the the radiative fluxes are improved compared to the previous version. Data set cautions are also presented.

surface radiation budget↗

Worldwide Historical Estimates of Leaf Area Index, 1932-2000

Approximately 1000 published estimates of leaf area index (LAI) from nearly 400 unique field sites, covering the period 1932-2000, have been compiled into a single data set. LA1 is a key parameter for global and regional models of biosphere/atmosphere exchange of carbon dioxide, water vapor, and other materials. It also plays an integral role in determining the energy balance of the land surface. This data set provides a benchmark of typical values and ranges of LA1 for a variety of biomes and land cover types, in support of model development and validation of satellite-derived remote sensing estimates of LA1 and other vegetation parameters. The LA1 data are linked to a bibliography of over 300 originalsource references.This report documents the development of this data set, its contents, and its availability on the Internet from the Oak Ridge National Laboratory Distributed Active Archive Center for Biogeochemical Dynamics. Caution is advised in using these data, which were collected using a wide range of methodologies and assumptions that may not allow comparisons among sites.

Scurlock, J. M. O.↗

Simulating Underexpanded Jets in Martian and Lunar Environments

As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The GCD PSI Project, planned to be accomplished over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the PSI Project also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the activities and accomplishments in the past year for the Prediction of Plume Flow in low pressure environments component of the PSI Project. While the Loci/Chem Computational fluid dynamics (CFD) application has been validated and used extensively for simulating launch environments in atmospheric conditions, use of this tool for simulating supersonic plumes at Mars-like ambient pressure requires further validation. CFD simulations of underexpanded jets have been performed using Loci/Chem for Mars-like conditions to predict several metrics for steady laminar, turbulent, and impinging plumes. The CFD results are compared with an experimental data set for low Reynolds number plumes at these conditions in order to evaluate the current capability of the Loci/Chem tool for these types of environments. The CFD validation results to date show reasonable agreement with the experimental data across all of the metrics of interest for the configurations considered. The Loci/Chem-Boltzmann CFD application is a hybrid continuum/rarefied flow solver which extends modeling capabilities to very low pressure environments such as those on the Moon. The Loci/Chem-Boltzmann solver uses a gradient-based continuum breakdown criterion to restrict solution of the computationally expensive Boltzmann equation to only a subset of the domain, while using the Navier-Stokes equations elsewhere. This CFD application is under active development, and current efforts toward establishing production ready capability for evaluating Lunar plume surface interactions are well under way. Initial simulations of an Apollo LEM indicate that several regions of the flow require solving the Boltzmann equations due to extreme rarefaction. Early simulations are promising, indicating reasonable overall computational time for a full 3D human scale lander simulation.

Thomas Shurtz↗

SHADOZ (Southern Hemisphere ADditional OZonesondes): An Ozonesonde Network for Satellite Validation, Climatology and Modeling

In the past 5 years, new tropical ozone data products have been developed from TOMS and other satellites, During this period, global chemical-transport models have been used for ozone assessment studies. However, there has been a lack of independent ozone profiles in the tropics for evaluation of the data sets and models. In 1998, NASA's Goddard Space Flight Center, Wallops Flight Facility and NOAA's CMDL (Climate Monitoring and Diagnostics Lab), began a 2-year project to collect a consistent data set by augmenting ozonesonde launches at southern hemisphere tropical sites The measurements are available to the scientific community at a single electronic location - the SHADOZ website at NASA/Goddard: http://code9l6.gsfc.nasa.gov/Data services/Shadoz/shadoz hmpg2.html. Stations in SHADOZ include four islands in the Pacific: Fiji, Tahiti, San Cristobal (Galapagos) and American Samoa. Two sites are at and in the Atlantic: Natal (Brazil) and Ascension Island. Three other sites span Africa (Nairobi and Irene, South Africa) and the Indian Ocean (Reunion Island and Watukosek in Java, Indonesia). All SHADOZ sites are using ECC-type sondes, with the conversion from JMD sondes at Java in 1999, but there are variations in sonde preparation technique and data processing. During the 1998-1999 period, more than 550 sondes were incorporated into the SHADOZ data base. Examples from these measurements illustrate the tropical wave-one pattern in total ozone which is easily detectable by satellite. They also show that the wave-one pattern appears to be in the troposphere, as assumed in creating the modified-residual tropospheric ozone data product from TOMS. SHADOZ will add data from intensive field campaigns from time to time. Recent contributions to the SHADOZ archive are from the INDOEX (Indian Ocean Experiment January-March 1999)sondes at the Maldives (5N, 73E) and 27 sondes on the US NOAA oceanographic vessel, the FIN Ronald H Brown between Virginia (US) and Mauritius via CapeTown, during a cruise in January and February 1999. In 2000, as part of the SAFARI-2000 experiment and a validation project called Southern African Validation for EOS (SAVE), enhancement of ozonesonde launches at Irene (South Africa) will extend the data set from this site beyond the 1998-1999 period.

Thompson, Anne M.↗

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗

Assimilation of Stratospheric Meteorological and Constituent Observations: A Review

This talk reviews the assimilation of meteorological and constituent observations of the stratosphere. The first efforts to assimilate observations into stratospheric models were during the early 1980s, and a number of research studies followed during the next decade. Since the launch of the Upper Atmospheric Research Satellite (UARS) in 1991, model-assimilated data sets of the stratospheric meteorological state have been routinely available. These assimilated data sets were critical in bringing together observations from the different instruments on UARS as well as linking UARS observations to measurements from other platforms. Using trajectory-mapping techniques, meteorological assimilation analyses are, now, widely used in the analysis of constituent observations and have increased the level of quantitative study of stratospheric chemistry and transport. During the 1990s the use of winds and temperatures from assimilated data sets became standard for offline chemistry and transport modeling. variability in middle latitudes. The transport experiments, however, reveal a set of shortcomings that become obvious as systematic errors are integrated over time. Generally, the tropics are not well represented, mixing between the tropics and middle latitudes is overestimated, and the residual circulation is not accurate. These shortcomings reveal underlying fundamental challenges related to bias and noise. Current studies using model simulation and data assimilation in controlled experimentation are highlighting the issues that must be addressed if assimilated data sets are to be convincingly used to study interannual variability and decadal change. observations. The primary focus has been on stratospheric ozone, but there are efforts that investigate a suite of reactive chemical constituents. Recent progress in ozone assimilation shows the potential of assimilation to contribute to the validation of ozone observations and, ultimately, the retrieval of ozone profiles from space-based radiance measurements. Assimilated data sets provide accurate analyses of synoptic and planetary Scale At the same time, stratospheric assimilation is evolving to include constituent

Rood, Richard B.↗