SEARCH · Search NASA

Results for “Cryosphere”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

NASA NTRS2017

A Closer Look at the ABI on the GOES-R Series

The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) is America's next-generation geostationary advanced imager. GOES-R launched on 19 November 2016. The ABI is a state-of-the-art 16-band radiometer, with spectral bands covering the visible, near-infrared, and infrared portions of the electromagnetic spectrum. Many attributes of the ABI-such as spectral, spatial, and temporal resolution; radiometrics; and image navigation/registration-are much improved from the current series of GOES imagers. This paper highlights and discusses the expected improvements of each of these attributes. From ABI data many higher-level-derived products can be generated and used in a large number of environmental applications. The ABI's design allows rapid-scan and contiguous U.S. imaging automatically interleaved with full-disk scanning. In this paper the expected instrument attributes are covered, as they relate to signal-to-noise ratio, image navigation and registration, the various ABI scan modes, and other parameters. There will be several methods for users to acquire GOES-R imagery and products depending on their needs. These include direct reception of the imagery via the satellite downlink and an online-accessible archive. The information from the ABI on the GOES-R series will be used for many applications related to severe weather, tropical cyclones and hurricanes, aviation, natural hazards, the atmosphere, the ocean, and the cryosphere.

GOES-R↗

NASA NTRS2018

NASA's Earth Observing Data and Information System - Near-Term Challenges

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, digital elevation, atmosphere dynamics and composition, and inter-disciplinary research, and many others. One of the key components of EOSDIS is a set of twelve discipline-based Distributed Active Archive Centers (DAACs) distributed across the United States. Managed by NASA's Earth Science Data and Information System (ESDIS) Project at Goddard Space Flight Center, these DAACs serve over 3 million users globally. The ESDIS Project provides the infrastructure support for EOSDIS, which includes other components such as the Science Investigator-led Processing systems (SIPS), common metadata and metrics management systems, specialized network systems, standards management, and centralized support for use of commercial cloud capabilities. Given the long-term requirements, and the rapid pace of information technology and changing expectations of the user community, EOSDIS has evolved continually over the past three decades. However, many challenges remain. Challenges addressed in this paper include: growing volume and variety, achieving consistency across a diverse set of data producers, managing information about a large number of datasets, migration to a cloud computing environment, optimizing data discovery and access, incorporating user feedback from a diverse community, keeping metadata updated as data collections grow and age, and ensuring that all the content needed for understanding datasets by future users is identified and preserved.

Remote Sensing↗

NASA NTRS2017

The Earth Observing System (EOS)

The Earth Observing System is a US National Aeronautics and Space Administration (NASA) program consisting of a science segment, a data system, and a space segment made up of a series of polar-orbiting and mid-inclination satellites for long-term monitoring of the Earth as an integrated system, including observations of the land surface, biosphere, atmosphere, cryosphere, and oceans. Initially conceived in the mid-late 1980s, it was implemented as a series of large "flagship" missions and smaller focused satellites, often in partnership with instruments and sometimes spacecraft from other nations. In 1984 NASA formed several instrument panels to develop concepts for “facility instruments” that would provide comprehensive support to the scientific and applications’ communities, each with a supporting science team competitively selected via peer-review. An Announcement of Opportunity was released in 1988 and proposals were solicited for three types of proposals: (i) instrument investigations that would include the provision of instrumentation for flight on a polar platform, including non-Earth science payloads requiring polar orbits (PI instruments), (ii) research facility instrument team member and team leader investigations for facility instruments, and (iii) interdisciplinary science investigations to provide data analysis and modeling, preparing to use data acquired from the space platforms. The initial selections made in 1989 included support for 24 instrument investigations, 6 research facility instrument investigations, and 28 interdisciplinary investigations. Although considerable changes were made over the years in the structure and orbital configuration of the various instruments and platforms, a total of 10 different missions were eventually flown, as shown in Fig. 1. These included three multiinstrument flagship platforms known as Terra (launched in 1999), Aqua (launched in 2002), and Aura (launched in 2004), where the Terra mission emphasis was primarily on land processes, Aqua on the hydrological cycle, and Aura on atmospheric chemistry. In addition to these flagship missions the EOS missions included Landsat 7 (land cover classification and change), QuikScat (wind speed and direction over the oceans), Jason-1 (ocean surface topography and sea level), ACRIMSAT (total solar irradiance (TSI)), SAGE III (stratospheric aerosol and ozone levels), ICESat (ice, cloud, and land elevation), and SORCE (Solar Radiation and Climate Experiment; total and spectral solar irradiance). In addition EOS supported CERES (an Earth radiation budget sensor) and LIS (a lightning sensor), that flew as part of the NASA/JAXA Tropical Rainfall Measuring Mission (1997), and SeaWinds (wind speed and direction), that flew as part of the short-lived ADEOS II (Midori II, 2002) mission of JAXA (Japan Aerospace Exploration Agency). The EOS contributions are too numerous to present in detail in this article, but can be viewed for convenience as a means of obtaining global measurements (with appropriate characteristics) of the 24 variables and variable groups listed in Table 1. This table was created by the EOS community in the late 1990s as a way to succinctly indicate which instruments on the various EOS platforms were expected to contribute to each of the specified variables in primary (bold), secondary (bold italics), or contributing (roman) roles. All of the science data products produced by these space missions are available without charge throughout the world, and are thus highly valued for their many contributions to applications such as air quality, fires, land cover change, and the state of the oceans, as well as for science and monitoring of the state of the Earth system and its changes over time. These and other international satellites have played a crucial role in understanding and documenting global change, including (i) global surface temperature and atmospheric temperature and water vapor profiles, (ii) glacial retreat, (iii) sea ice extent and change, (iv) solar radiation into and out of the Earth-atmosphere system, (v) atmospheric aerosol and cloud properties, (vi) sources and sinks of

ICESat↗

NASA NTRS2018

GEOS S2S-2_1 File Specification: GMAO Seasonal and Sub-Seasonal Forecast Output

The NASA GMAO seasonal (9 months) and subseasonal (45 days) forecasts are produced with the Goddard Earth Observing System (GEOS) Atmosphere-Ocean General Circulation Model and Data Assimilation System Version S2S-2_1. The new system replaces version S2S-1.0 described in Borovikov et al (2017), and includes upgrades to many components of the system. The atmospheric model includes an upgrade from a pre-MERRA-2 version running on a latitude-longitude grid at approx. 1 degree resolution to a current version running on a cubed sphere grid at approximately 1/2 degree resolution. The important developments are related to the dynamical core (Putman et al., 2011), the moist physics (''two-moment microphysics'' of Barahona et al., 2014) and the cryosphere (Cullather et al., 2014). As in the previous GMAO S2S system, the land model is that of Koster et al (2000). GMAO S2S-2_1 now includes the Goddard Chemistry Aerosol Radiation and Transport (GOCART, Colarco et al., 2010) single moment interactive aerosol model that includes predictive aerosols including dust, sea salt and several species of carbon and sulfate. The previous version of GMAO S2S specified aerosol amounts from climatology, which were used to inform the atmospheric radiation only. The ocean model includes an upgrade from MOM4 to MOM5 (Griffies 2012), and continues to be run on the tripolar grid at approximately 1/2 degree resolution in the tropics with 40 vertical levels. As in S2S-1.0, the sea ice model is from the Los Alamos Sea Ice model (CICE4, Hunke and Lipscomb 2010). The Ocean Data Assimilation System (ODAS) has been upgraded from the one described in Borovikov et al., 2017 to one that uses a modified version of the Penny, 2014 Local Ensemble Transform Kalman Filter (LETKF), and now assimilates along-track altimetry. The ODAS also does a nudging to MERRA-2 SST and sea ice boundary conditions. The atmospheric data assimilation fields used to constrain the atmosphere in the ODAS have been upgraded from MERRA to a MERRA-2 like system. The system is initialized using a MERRA-2-like atmospheric reanalysis (Gelaro et al. 2017) and the GMAO S2S-2_1 ocean analysis. Additional ensemble members for forecasts are produced with initial states at 5-day intervals, with additional members based on perturbations of the atmospheric and ocean states. Both subseasonal and seasonal forecasts are submitted to the National MultiModel Ensemble (NMME) project, and are part of the US/Canada multimodel seasonal forecasts (http://www.cpc.ncep.noaa.gov/products/NMME/). A large suite of retrospective forecasts (''hindcasts'') have been completed, and contribute to the calculation of the model's baseline climatology and drift, anomalies from which are the basis of the seasonal forecasts.

Seasonal Forecast↗

NASA NTRS2018

NASA's Experiences with Microwave Radiometers from Ground to Space

Passive microwave sensing is sensitive to a wide variety of geophysical parameters in the atmosphere, oceans, cryosphere, and on land. For example, spaceborne passive microwave atmospheric sounders provide the highest-impact observations for state-of-the-art weather forecast models used by meteorological agencies around the world. The ability of passive microwave sensors (radiometers) to observe day or night through cloud cover and other obstacles (wavelength dependent, of course) partially compensates for their sometimes large footprint size compared to other sensor types. Examples will be presented of radiometers deployed on the ground, on aircraft, and on satellites. Each of these environments presents different challenges in obtaining accurate observations. And while many standard radiometer designs and techniques have been developed, every user re-discovers that even the "standard" approach requires careful attention in order to achieve full potential.

calibration↗

NASA NTRS2018

Aquarius Final Release Product and Full Range Calibration of L-band Radiometers

Aquarius final product V5.0 has been released. The dataset includes close to four years of global radiometric measurements at L-band. The mission's objective was to monitor sea surface salinity, but other applications of its data over land and the cryosphere have been developed. For this reason, it is important to have accurate calibration over the full range of antenna temperatures from natural targets. It is also needed in order to combine Aquarius measurements with other L-band sensors. Aquarius calibration is strongly focused on the ocean. We present a research product which is part of the final release and aims at producing an accurate calibration from the low end (celestial sky) to the high end (land and ice) of the brightness temperature scale. We calibrate the Aquarius radiometers using measurements over the Sky and oceans and assess the new calibration using measurements over land.

Radiometry↗

NASA NTRS2018

NASA GMAO Integrated Earth System Analysis

An Integrated Earth System Analysis (IESA) is the only possible way to assimilate all the available observations of separate components of the earth system (atmosphere, ocean, cryosphere, land, constituents, etc) into a single consistent Coupled Data Assimilation System (CDAS). The NASA Global Modeling and Assimilation Office (GMAO) is developing an IESA for Reanalysis in an incremental fashion by coupling different components- one at a time, for e.g., the MERRA-2 reanalysis coupled aerosol and meteorological data assimilation systems. Following a similar approach the ocean (including sea-ice) is being coupled to the atmosphere, starting with the air-sea interface. This presentation briefly outlines GMAO's reanalysis road map and summarizes our recent work in that direction.

Akella, Santha↗

NASA NTRS2018

Sub-Seasonal Forecasting of the Stratospheric Wave Events, Sudden Stratospheric Warmings, and Their Influence on the Troposphere

Stratospheric wave events and major sudden stratospheric warming (SSW) events are well captured in high-resolution global forecasts out to 10 days. Tropospheric influences of SSW include statistically significant shifts in the storm tracks and associated surface temperature and precipitation pattern changes. Since these events can in turn influence the troposphere on time scales of 30-60 days the ability to predict these events and the subsequent long-term response on time scales beyond 10 days is of interest. Here we examine the prediction of stratospheric wave events and their evolution using the NASA GMAO (Global Modeling and Assimilation Office) Sub-Seasonal to Seasonal (S2S) system. This is a recently released subseasonal to seasonal forecast system, GEOS-S2S version 2.1. Compared to GMAO's previous system, the new version runs at higher atmospheric resolution (approximately 1/2 degree globally), contains a substantially improved model of the cryosphere, includes additional interactive aerosol model components, and the ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter. Results are based on a comprehensive series of hindcasts starting from the year 2000. They show that while the S2S system is not as accurate at 10 days in forecasting major SSW events as the NASA GMAO Forward Processing system, it can usefully predict stratospheric anomalies out to 20 days and the subsequent stratospheric/tropospheric evolution beyond 30 days.

Coy, L.↗

NASA NTRS2018

Impacts of NASA's Earth Observations on Subseasonal and Seasonal Forecasts

NASA's suite of Earth-observing satellites provides a unique view of many processes on Earth, with relevance on timescales ranging from hours to weeks and even years. NASA's observations span all parts of the Earth system: atmospheric, ocean, land and cryosphere, and include physical, chemical and biological components. This presentation explores use of NASA observations in extended-range prediction, from many days to months, using the Goddard Earth Observing System (GEOS) assimilation and predictive modeling capabilities. The skill of a weather forecast is linked to the fidelity of the initialization process (data assimilation) and the realistic representation of "fast" physical processes in the model. At longer time horizons, the slower "feedback" processes in the Earth System begin to take a more prominent role in the accuracy of the forecast. Simultaneously, forecast-skill attribution transitions away from feature-based metrics that emphasize smaller scales (e.g., representations of fronts and vortices) to metrics that emphasize the statistical distributions of large-scale features (e.g., ENSO diagnostics and teleconnections). This presentation will summarize studies performed using the GEOS-S2S (subseasonal to seasonal) system that explore the impacts of NASA observations on the fidelity of the forecasts. The GEOS-S2S system is configured for the atmosphere-ocean-land-ice model and is initialized using in-situ and space-based observations, including atmospheric aerosols and ozone which are not typically analyzed in such systems. The GEOS-S2S model routinely includes aerosol feedbacks, which systematically impact the realism of the forecasts, providing a first example of how suitable NASA observations impact the performance of the GEOS-S2S system. Studies in which a stratospheric chemistry module is activated in the GEOS-S2S system allow the impacts of ozone radiative feedbacks to be isolated. Space-based observations of sea-surface temperature and altimetry are routinely analyzed for the initialization of the GEOS-S2S system; recent advances allow the use of NASA's sea-surface salinity data, which are shown to impact the long-range skill of the forecasts.

Pawson, Steven↗

NASA NTRS2018

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Earth observations↗

NASA NTRS2018

GEOS S2S-2_1: The GMAO High Resolution Seasonal Prediction System

A new version of the coupled modeling and analysis system used to produce near real time subseasonal to seasonal forecasts was recently released by the NASA/Goddard Global Modeling and Assimilation Office. The new version runs at higher atmospheric resolution than the previous, (approximately 1/2 degree globally), contains a substantially improved model description of the cryosphere, and includes additional interactive earth system model components (aerosol model). In addition, the Ocean data assimilation system has been replaced with a Local Ensemble Transform Kalman Filter, and now includes the assimilation of along-track sea surface height. Here will describe the new system, along with the plans for the future (GEOS S2S-3_0) which will include a higher resolution ocean model and more interactive earth system model components (interactive vegetation, biomass burning from fires). We will also present results from a series of retrospective seasonal forecasts. Results show significant improvements in surface temperatures over much of the northern hemisphere and a much improved prediction of sea ice extent in both hemispheres. Analysis of the ensemble spread shows improvements relative to the previous system, including generally better reliability. The precipitation forecast skill is comparable to previous S2S systems, and the only tradeoff is an increased "double ITCZ", which is expected as we go to higher atmospheric resolution.

Molod, Andrea↗

NASA NTRS2019

NASA's Earth Observing Data and Information System (EOSDIS)

NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of the NASA Earth observation program since the 1990's. The data collected by NASA represent a significant public investment in research. Consequently, NASA developed a free, open and non-discriminatory policy consistent with existing international policies to maximize access to data. EOSDIS manages data covering a wide range of Earth science disciplines including cryosphere, land cover change, polar processes, field campaigns, ocean surface, geodesy, atmosphere dynamics and composition, and inter-disciplinary research, and many others.

Remote Sensing↗

NASA NTRS2019

NASA's Earth Observing Data and Information System (EOSDIS)

Data Systems↗

NASA NTRS2019

Near Real-Time Sub/Seasonal Prediction of Aerosol at NASA Global Modeling and Assimilation Office

A new version of the coupled modeling and analysis system used to produce near real time subseasonal to seasonal forecasts was released over a year ago by the NASA/Goddard Global Modeling and Assimilation Office. The model runs at approximately 1/2 degree globally in the atmosphere and ocean, contains a realistic description of the cryosphere, and includes an interactive aerosol model. The data assimilation used to produce initial conditions is weakly coupled, in which the atmosphere-only assimilated state is coupled to an ocean data assimilation system using a Local Ensemble Transform Kalman Filter. Here will briefly describe the new system, and show results of aerosol-derived air quality from an extensive series of retrospective forecasts. The interactive aerosol is shown to improve seasonal time scale prediction skill during some "forecasts of oppurtunity". Plans for a future version of the system with predicted biomass burning from fires will also be discussed.

Molod, Andrea M.↗

NASA NTRS2019

Enhanced Habitability on High Obliquity Bodies near the Outer Edge of the Habitable Zone of Sun-Like Stars

High obliquity planets represent potentially extreme limits of terrestrial climate, as they exhibit large seasonality, a reversed annual-mean pole-to-equator gradient of stellar heating, and novel cryospheres. A suite of 3D global climate model simulations is performed for low and high obliquity planets with various stellar fluxes, CO2 concentrations, and initial conditions to explore the propensity for high obliquity climates to undergo global glaciation. We also simulate planets with thick CO2 or H2 atmospheres, such as those expected to develop near or beyond the outer edge of the habitable zone. We show that high obliquity planets are hotter than their low obliquity counterparts due to ice-albedo feedbacks for cold climates, and water vapor in warm climates. We suggest that the water vapor greenhouse trapping is greater on high obliquity bodies for a given global-mean temperature due to the different dynamical regimes that occur between the two states. While equatorial ice belts are stable at high obliquity in some climate regimes, it is substantially harder to achieve global glaciation than for a low obliquity planet. Temperate polar conditions can be present at high obliquity at forcings for which low obliquity planets would be in a hard snowball state. Furthermore, open ocean can persist even in the winter hemisphere and when global-mean temperatures are well below freezing. However, the influence of obliquity diminishes for dense atmospheres, in agreement with calculations from 1D energy balance models.

Planet and satellite atmospheres↗

NASA NTRS2019

Space-Based Observations for Understanding Changes in the Arctic-Boreal Zone

Observations taken over the last few decades indicate that dramatic changes are occurring in the ArcticBoreal Zone (ABZ), which are having significant impacts on ABZ inhabitants, infrastructure, flora and fauna, and economies. While suitable for detecting overall change, the current capability is inadequate for systematic monitoring and for improving process based and large scale understanding of the integrated components of the ABZ, which includes the cryosphere, biosphere, hydrosphere, and atmosphere. Such knowledge will lead to improvements in Earth system models, enabling more accurate prediction of future changes and development of informed adaptation and mitigation strategies. In this article, we review the strengths and limitations of current space based observational capabilities for several important ABZ components and make recommendations for improving upon these current capabilities. We recommend an interdisciplinary and stepwise approach to develop a comprehensive ABZ Observing Network (ABZON), beginning with an initial focus on observing networks designed to gain process based understanding for individual ABZ components and systems that can then serve as the building blocks for a comprehensive ABZON.

Bryan N Duncan↗

NASA NTRS2019

NASA GIBS and Worldview: Bringing 20 Years of Terra Data into View

For nearly 10 years, the NASA Global Imagery Browse Services (GIBS) and Worldview interactive mapping site have provided users full resolution visualizations of Terra land, cryosphere, ocean, and atmosphere science parameters available within hours of acquisition. Over that time, GIBS and Worldview have expanded their Terra visualization suite to include even more parameters covering the entire mission of science data. Users can now view daily visualizations of nearly 50 near-real time and over 125 science quality science parameters from Terra instruments. These visualizations provide a unique capability for a broad user base to interact and discover the wealth of information sense by instruments on the Terra platform. By viewing Terra-based visualizations in a single location, users can correlate retrievals across instruments. Additionally, GIBS and Worldview include visualizations from many other platforms, allowing for an even greater data discovery capability.The GIBS and Worldview teams continue to work with Terra instrument science teams to add more visualized layers, as well as supporting visualization updates as the data is continually improved. Additionally, the GIBS interfaces and Worldview site are actively working on improved visualization functionality, including vector- and granule/swath-based products, to better address the expanding needs of its user community. This presentation will focus on an overview of existing and future visualization products and capabilities that have supported, and will support, a broad use of Terra data in science, media, and application communities.

Cechini, Matthew↗

NASA NTRS2019

Near Real-Time Sub/Seasonal Prediction of Aerosol and Air Quality at the NASA Global Modeling and Assimilation Office

Version 2 of the coupled modeling and analysis system used to produce near real time subseasonal to seasonal forecasts was released almost two years ago by the NASA/Goddard Global Modeling and Assimilation Office. The model runs at approximately 1/2 degree globally in the atmosphere and ocean, contains a realistic description of the cryosphere, and includes an interactive aerosol model. The data assimilation used to produce initial conditions is weakly coupled, in which the atmosphere-only assimilated state is coupled to an ocean data assimilation system using a Local Ensemble Transform Kalman Filter. Results of aerosol-derived air quality (Particulate Matter) from an extensive series of retrospective forecasts will be shown, with particular focus on the continental United States and eastern Asia. In addition, under some circumstances, the interactive aerosol is shown to improve seasonal time scale prediction skill. Plans for a future version of the system with predicted biomass burning from fires will also be discussed.

Molod, Andrea↗