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At least 1,153 records · Page 64

An Ocean-Atmosphere Simulation for Studying Air-Sea Interactions

During the past few years the Goddard Earth Observing System (GEOS) and Massachusetts Institute of Technology (MIT) modeling groups have produced, respectively, global atmosphere-only and ocean-only simulations with km-scale grid spacing. These simulations have proved invaluable for process studies and for the development of satellite and in-situ sampling strategies. Nevertheless, a key limitation of these "nature" simulations is the lack of interactivity between the ocean and the atmosphere, which limits their usefulness for studying air-sea interactions and for designing observing missions to study these interactions. To remove this limitation, we aim to couple the km-scale GEOS atmosphere simulation to the km-scale MIT ocean simulation.

Strobach, Ehud↗

The NASA Applied Sciences Program: Volcanic Ash Observations and Applications

Since 2000, the NASA Applied Sciences Program has been actively transitioning observations and research to operations. Particular success has been achieved in developing applications for NASA Earth Observing Satellite (EOS) sensors, integrated observing systems, and operational models for volcanic ash detection, characterization, and transport. While other observations and applications remain to be developed for the current constellation of NASA EOS sensors and integrated with observing and forecast systems, future requirements and capabilities for volcanic ash observations and applications are also being developed. Many of these are based on technologies currently being tested on NASA aircraft, Unmanned Aerial Systems (UAS) and balloons. All of these efforts and the potential advances that will be realized by integrating them are shared in this presentation.

John J Murray↗

Enabling Cloud Services and Enhanced Data Discovery With Earthdata-Varinfo

NASA’s Earth Observing System Data and Information System (EOSDIS) contains thousands of Earth science datasets from satellites, models, and field campaigns. Each of these collections can contain hundreds of variables that describe each measurement within the dataset, therefore an automated method for generating UMM-Var records is necessary. The Unified Metadata Model for Variables (UMM-Var) provides a framework for variable metadata records in NASA’s Common Metadata Repository (CMR). The Python tool, earthdata-varinfo, was developed to solve this problem of automating the curation of UMM-Var records. Given either a collection DMR file or a netCDF-4 file, earthdata-varinfo can scrape variable metadata and return a CMR compliant UMM-Var record. Earthdata-varinfo can generate thousands of UMM-Var records in a matter of seconds, thus enabling subsetting capabilities and enhancing data discovery.

Eni Awowale↗

The Transition of Satellite Observations Assimilated in GEOS to JEDI

The Goddard Earth Observing System (GEOS) is used by NASA’s Global Modeling and Assimilation Office (GMAO) to produce weather, climate, and air quality forecasts and reanalysis datasets. In order to incorporate the Joint Effort for Data assimilation Integration (JEDI) system into GEOS it is necessary to provide a validated set of input observations in JEDI. The GMAO, in collaboration with the Joint Center for Satellite Data Assimilation (JCSDA), is developing the Unified Forward Operator (UFO) in JEDI and adding all the necessary features to replicate the existing capability of the Gridpoint Statistical Interpolation (GSI)–based GEOS atmospheric data assimilations system. GMAO has been adding, validating, and updating procedures to assimilate the vast array of satellite and conventional observations assimilated in GEOS, including the GEOS all-sky microwave radiance assimilation framework to assimilate those observations in the UFO. Robust tests have been conducted to ensure correct configurations of observational data bias correction, quality control, and observation error in UFO and good agreements between UFO and GSI results. Our work on satellite observations will be reported in this presentation.

Jianjun Jin↗

Evaluation of Radiometric Performance of CERES Instruments Aboard Terra

The Terra satellite platform carries the first two flight models of the Clouds and the Earth’s Radiant Energy System, which make radiometric measurements of the Earth to examine the roles of cloud feedback and radiation balance in the Earth System. The Terra-borne instruments use three channels: the shortwave (0.2 - 5 µm), total (0.2 – 100 µm) and window (8 – 12 µm), which are calibrated using an onboard internal calibration module to track the long-term stability of each channel. Observed measurements are converted to top-of-atmosphere radiances by accounting for the instrument optics and detector sensitivity coefficients determined from prelaunch calibrations. Trends in the instrument’s radiometric performance determined through on-orbit calibrations and vicarious studies were applied, and these corrections have shown to produce a stable data record of radiative fluxes over the lifetime of the mission. Changes in instrument observations and new methods to account for them as a result of the discontinuation of station keeping for Terra will be discussed.

Alexander Jarnot↗

Simplifying Analysis of Hierarchical HDF5 and NetCDF4 Files with Xarray-Datatree

NASA’s Earth Observing System Data and Information System (EOSDIS) contains thousands of Earth science datasets from satellites, models, and field campaigns. EOSDIS data are stored in formats that are well supported by the Earth Science community. These formats include the Hierarchical Data Format (HDF), with derivative flavors such as HDF-5 and the Network Common Data Format (NetCDF-4). The HDF specification allows for a directory-like hierarchy within a single file, known as "groups". Observational data and associated metadata within a single file can be distributed amongst multiple internal groups, which can also be nested to multiple levels. Working with datasets that have a group hierarchical structure can be difficult because of the nested structure of groups. Widely used packages, such as xarray, have data models that do not accommodate the hierarchical structure within HDF files, requiring users to traverse the file and open different HDF groups as separate, unrelated objects. Xarray-datatree is a Python package developed to solve the difficulty of traversing HDFs with a hierarchical group structure by creating a tree-like hierarchical data structure in xarray. The tree-like structure allows each group to be accessed once a DataTree object is instantiated. The migration of xarray-datatree into the xarray core library will reduce barriers to accessing Earth science data by eliminating the need to understand and traverse the specific hierarchy of a grouped HDF file.

Eni Awowale↗

The Computational Complexity, Parallel Scalability, and Performance of Atmospheric Data Assimilation Algorithms

The computational complexity of algorithms for Four Dimensional Data Assimilation (4DDA) at NASA's Data Assimilation Office (DAO) is discussed. In 4DDA, observations are assimilated with the output of a dynamical model to generate best-estimates of the states of the system. It is thus a mapping problem, whereby scattered observations are converted into regular accurate maps of wind, temperature, moisture and other variables. The DAO is developing and using 4DDA algorithms that provide these datasets, or analyses, in support of Earth System Science research. Two large-scale algorithms are discussed. The first approach, the Goddard Earth Observing System Data Assimilation System (GEOS DAS), uses an atmospheric general circulation model (GCM) and an observation-space based analysis system, the Physical-space Statistical Analysis System (PSAS). GEOS DAS is very similar to global meteorological weather forecasting data assimilation systems, but is used at NASA for climate research. Systems of this size typically run at between 1 and 20 gigaflop/s. The second approach, the Kalman filter, uses a more consistent algorithm to determine the forecast error covariance matrix than does GEOS DAS. For atmospheric assimilation, the gridded dynamical fields typically have More than 10(exp 6) variables, therefore the full error covariance matrix may be in excess of a teraword. For the Kalman filter this problem can easily scale to petaflop/s proportions. We discuss the computational complexity of GEOS DAS and our implementation of the Kalman filter. We also discuss and quantify some of the technical issues and limitations in developing efficient, in terms of wall clock time, and scalable parallel implementations of the algorithms.

Lyster, Peter M.↗

Assessment of the Orion-SLS Interface Management Process in Achieving the EIA 731.1 Systems Engineering Capability Model Generic Practices Level 3 Criteria

NASA is currently developing the next generation crewed spacecraft and launch vehicle for exploration beyond earth orbit including returning to the Moon and making the transit to Mars. Managing the design integration of major hardware elements of a space transportation system is critical for overcoming both the technical and programmatic challenges in taking a complex system from concept to space operations. An established method of accomplishing this is formal interface management. In this paper we set forth an argument that the interface management process implemented by NASA between the Orion Multi-Purpose Crew Vehicle (MPCV) and the Space Launch System (SLS) achieves the Level 3 tier of the EIA 731.1 System Engineering Capability Model (SECM) for Generic Practices. We describe the relevant NASA systems and associated organizations, and define the EIA SECM Level 3 Generic Practices. We then provide evidence for our compliance with those practices. This evidence includes discussions of: NASA Systems Engineering Interface (SE) Management standard process and best practices; the tailoring of that process for implementation on the Orion to SLS interface; changes made over time to improve the tailored process, and; the opportunities to take the resulting lessons learned and propose improvements to our institutional processes and best practices. We compare this evidence against the practices to form the rationale for the declared SECM maturity level.

Jellicorse, John J.↗

Observations Suggest That North African Dust Absorbs Less Solar Radiation Than Models Estimate

Desert dust accounts for a large fraction of shortwave radiation absorbed by aerosols, which adds to the climate warming produced by greenhouse gases. However, it remains uncertain exactly how much shortwave radiation dust absorbs. Here, we leverage in-situ measurements of dust single-scattering albedo to constrain absorption at mid-visible wavelength by North African dust, which accounts for approximately half of the global dust. We find that climate and chemical transport models overestimate North African dust absorption aerosol optical depth (AAOD) by up to a factor of two. This occurs primarily because models overestimate the dust imaginary refractive index, the effect of which is partially masked by an underestimation of large dust particles. Similar factors might contribute to an overestimation of AAOD retrieved by the Aerosol Robotic Network, which is commonly used to evaluate climate and chemical transport models. The overestimation of dust absorption by models could lead to substantial biases in simulated dust impacts on the Earth system, including warm biases in dust radiative effects.

Atmospheric science↗

NASA GSFC CCMC Recent Model Validation Activities

The Community Coordinated Modeling Center (CCMC) holds the largest assembly of state-of-the-art physics-based space weather models developed by the international space physics community. In addition to providing the community easy access to these modern space research models to support science research, its another primary goal is to test and validate models for transition from research to operations. In this presentation, we provide an overview of the space science models available at CCMC. Then we will focus on the community-wide model validation efforts led by CCMC in all domains of the Sun-Earth system and the internal validation efforts at CCMC to support space weather servicesjoperations provided its sibling organization - NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov). We will also discuss our efforts in operational model validation in collaboration with NOAA/SWPC.

Rastaetter, L.↗

TOPEX/POSEIDON mission overview

TOPEX/POSEIDON is the first space mission specifically designed and conducted for studying the circulation of the world's oceans. A state-of-the-art radar altimetry system is used to measure the precise height of sea level, from which information on the ocean circulation is obtained. The satellite, launched on August 10, 1992, has been making observations of the global oceans with unprecedented accuracy since late September 1992. To meet the stringent measurement accuracy required for ocean circulation studies, a number of innovative improvements have been made to the mission design, including the first dual-frequency space-borne radar altimeter capable of retrieving the ionospheric delay of the radar signal, a three-frequency microwave radiometer for retrieving the signal delay caused by the water vapor in the troposphere, an optimal model of the Earth's gravity field and multiple satellite tracking systems for precision orbit determination. Additionally, the satellite also carries two experimental instruments to demonstrate new technologies: a single-frequency solid-state altimeter for the technology of low-power, low-weight altimeter and a Global Positioning System receiver for continuous,precise satellite tracking. The performance of the mission's measurement system has been tested by numerous verification studies. The results indicate that the root-sum-square accuracy of a single-pass sea level measurement is 4.7 cm for the TOPEX system and 5.1 cm for the POSEIDON system; both are more than a factor of 2 better than the requirement of 13.7 cm. This global data set is being analyzed to improve understanding of the global ocean circulation as well as the ocean tides, geodesy, and geodynamics, and ocean wind and waves. The mission is designed to last for at least 3 years with a possible extension to 6 years. The multiyear global data set will go a long way toward understanding the ocean circulation and its variability in relation to climate change. A summary of the mission's systems and their performance as well as the mission's science team is presented.

Fu, Lee-Lueng↗

On the Reprocessing and Reanalysis of Observations for Climate

The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Uncertainty↗

Development of a model of machine hand eye coordination and program specifications for a topological machine vision system

A unified approach to computer vision and manipulation is developed which is called choreographic vision. In the model, objects to be viewed by a projected robot in the Viking missions to Mars are seen as objects to be manipulated within choreographic contexts controlled by a multimoded remote, supervisory control system on Earth. A new theory of context relations is introduced as a basis for choreographic programming languages. A topological vision model is developed for recognizing objects by shape and contour. This model is integrated with a projected vision system consisting of a multiaperture image dissector TV camera and a ranging laser system. System program specifications integrate eye-hand coordination and topological vision functions and an aerospace multiprocessor implementation is described.

Source record↗

Accretion of Moon and Earth and the emergence of life

The discrepancy between the impact records on the Earth and Moon in the time period, 4.0-3.5 Ga calls for a re-evaluation of the cause and localization of the late lunar bombardment. As one possible explanation, we propose that the time coverage in the ancient rock record is sufficiently fragmentary, so that the effects of giant, sterilizing impacts throughout the inner solar system, caused by marauding asteroids, could have escaped detection in terrestrial and Martian records. Alternatively, the lunar impact record may reflect collisions of the receding Moon with a series of small, original satellites of the Earth and their debris in the time period about 4.0-3.5 Ga. The effects on Earth of such encounters could have been comparatively small. The location of these tellurian moonlets has been estimated to have been in the region around 40 Earth radii. Calculations presented here, indicate that this is the region that the Moon would traverse at 4.0-3.5 Ga, when the heavy and declining lunar bombardment took place. The ultimate time limit for the emergence of life on Earth is determined by the effects of planetary accretion--existing models offer a variety of scenarios, ranging from low average surface temperature at slow accretion of the mantle, to complete melting of the planet followed by protracted cooling. The choice of accretion model affects the habitability of the planet by dictating the early evolution of the atmosphere and hydrosphere. Further exploration of the sedimentary record on Earth and Mars, and of the chemical composition of impact-generated ejecta on the Moon, may determine the choice between the different interpretations of the late lunar bombardment and cast additional light on the time and conditions for the emergence of life.

NASA Discipline Exobiology↗

Application of the Shuttle Laser Altimeter in an Accuracy Assessment of Global 1-Kilometer Digital Elevation Data

Shuttle Laser Altimeter (SLA) data have been used to evaluate the accuracy of GTOPO30, the first comprehensive, 1 km resolution, global topographic data set. GTOPO30 was developed by the USGS Eros Data Center (EDC), in part, to address NASA's needs for a global topographic model in support of remote sensing instruments aboard the Earth Observing System AM-1 spacecraft. SLA flew as a part of the STS-72 mission in January, 1996 observing the latitude band from +/- 28.5 deg, and on STS-85 in August, 1997 extending the observations to +/- 57 deg. Combining the SLA ranging data with shuttle position and pointing knowledge yields surface elevation data of very high vertical accuracy in an Earth-centered, absolute reference frame (2.8 m rms difference for SLA-01 with respect to ocean reference surface). Use of the well-determined mean sea surface reference for calibration allows propagation of high accuracy altimetry onto the continents. 436,635 SLA-01 land elevations were compared to the GTOPO30 grid after conversion to a mean sea level vertical datum using the Earth Geoid Model 96, jointly developed by Goddard and NIMA. The comparison reveals systematic elevation biases in southern Asia, Africa, Australia, and south America on the order 10's to 100 meters in the GTOPO30 compilation on spatial scales of 100's to 1000's of kilometers. These biases are likely due to vertical datum errors in the topographic source materials used to compile GTOPO30, which primarily consist of Defense Mapping Agency (DMA) digital elevation and topographic map products. These biases imply that elevation corrections applied to land gravity measurements using these DMA source materials will be biased, leading to errors in geoid models incorporating these land gravity data.

Harding, David J.↗

Handbook for the estimation of microwave propagation effects: Link calculations for earth-space paths (path loss and noise estimation)

A single model for a standard of comparison for other models when dealing with rain attenuation problems in system design and experimentation is proposed. Refinements to the Global Rain Production Model are incorporated. Path loss and noise estimation procedures as the basic input to systems design for earth-to-space microwave links operating at frequencies from 1 to 300 GHz are provided. Topics covered include gaseous absorption, attenuation by rain, ionospheric and tropospheric scintillation, low elevation angle effects, radome attenuation, diversity schemes, link calculation, and receiver noise emission by atmospheric gases, rain, and antenna contributions.

Crane, R. K.↗

The Surface Albedo of Sea Ice in CMIP6 and the Implications for the Surface Albedo Feedback

The Arctic has experienced rapid sea ice loss and a substantial decline in surface albedo, significantly impacting its radiation budget. Climate models from the Coupled Model Intercomparison Project (CMIP6) reproduce these changes. However, inconsistencies remain among models regarding the magnitude, spatial distribution, and seasonal patterns of Arctic surface albedo evolution. This study investigates these discrepancies by comparing model outputs with observation from the Clouds and the Earth's Radiant Energy System (CERES). We develop a decomposition method to assess the contributions of sea ice albedo, sea ice concentration, and sea ice extent to Arctic surface albedo. Over land, differences in snow cover account for the substantial inter-model spread in surface albedo, while over the ocean, sea ice albedo, concentration, and extent all contribute. Comparisons between CMIP6 and the Atmospheric Model Intercomparison Project (AMIP) simulations, which use identically prescribed sea ice concentrations, reveals considerable inter-model spread in Arctic Ocean surface albedo due to differences in sea ice albedo. Applying the decomposition method to projections shows that models predicting larger decreases in sea ice concentration and extent, especially in the Central Arctic, exhibit lower surface albedo and stronger sea ice albedo feedback. Beyond 2050, Arctic Ocean surface albedo decline is mainly influenced by sea ice extent indicating that the retreat of the ice edge is the most important process to constrain the surface albedo feedback. This study provides insights into factors contributing to the spread and changes in Arctic surface albedo and the associated sea ice albedo feedback.

Patrick C Taylor↗