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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Implementing Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) Cloud-Clearing Algorithm into the NASA GEOS: Focus on the 2017 Atlantic Tropical Cyclone Season

Numerical Weather Prediction (NWP) centers assimilate cloud-free infrared (IR) radiances because the assimilation of all-sky IR radiances is not yet operationally achievable. The cloud-clearing procedure offers a simpler, but effective strategy that produces cloud-affected radiances suitable for assimilation in partially cloudy regions. Several studies conducted by this team have demonstrated that IR Cloud-Cleared Radiances (CCRs), if thinned more aggressively than clear-sky radiances, can improve analysis and forecasts, particularly in meteorologically active areas. However, CCRs are not used by operational centers due partly to the thought that the process of cloud-clearing may affect latency and introduce difficult-to-control external dependencies. This study presents the results of implementing an Atmospheric Infrared Sounder (AIRS) and Cross-Track Infrared Sounder (CrIS) cloud-clearing procedure into the NASA Goddard Earth Observing System (GEOS) to demonstrate the portability of the procedure. The AIRS and CrIS cloud-clearing algorithms have been deprived of external dependencies, made customizable to any specific model, and the computational efficiency has been improved via parallelization. The revised AIRS and CrIS cloud-clearing algorithms allow a customized choice of channel selection, the use of a user-specified model's fields as first guess, and can perform in real time. Data assimilation experiments with the hybrid 4DEnVar GEOS system were successfully performed for the 2017 tropical cyclones (TC) season with a focus on three major hurricanes (Harvey, Irma, and Maria). This study shows that assimilation of locally-generated CCRs have a positive impact on both global skill and TC representation, compared to the assimilation of AIRS and CrIS clear-sky radiances, and a comparable or slightly improved impact compared to assimilation of CCRs produced by external sources, such as NASA's Distributed Active Archive Centers and NOAA’s Comprehensive Large Array-data Stewardship System. The customization and computational efficiency of the revised procedure would enable its usability in a real-time forecast context.

Niama Boukachaba↗
NASA NTRSDate not supplied

INCREASING THE TRANSPARENCY AND REPRODUCIBILITY OF SPACE RADIATION SCIENCE: THE RADIATION BIOLOGY ONTOLOGY

Among the primary objectives of the Open/Open-Source Science paradigm are making scientific investigation data transparent and results reproducible [1], objectives shared by the FAIR principles [2]. To accomplish this, the conceptual framework that includes all the investigation objects needs to be accurately captured and communicated to all data consumers. A large part of this requires using metadata standards to annotate data collected. These standards should be readily accessible, informed by scientific community consensus and sufficiently specific to encompass all of the important aspects of the investigation. Starting in 2020 we have been co-leading an open consortium to develop a new metadata standard, the Radiation Biology Ontology (RBO), through the Open Biological and Biomedical Ontologies (OBO) Foundry [3]. We began by transforming many of the terms from the National Council on Radiation Protection and Measurement into concepts that can be formally related to existing OBO Foundry classes or attributes. We then identified and imported into the RBO existing OBO Foundry classes that have obvious relevance for radiation biomedicine (for example, concepts from the Environment Ontology that describe radiative processes, and concepts from the Gene Ontology dealing with molecular and cellular responses to radiation). Finally, we scrutinized datasets from investigations of radiation effects held in NASA GeneLab and LSDA repositories and added additional classes, instances, and attributes into the RBO that should be used to annotate these data. We developed the RBO using the open-source tools of GitHub and publish the RBO periodically through the NIH/NCBI BioPortal website, so systems worldwide can leverage the knowledge it contains [4]. This initial phase of concept modeling has yielded an RBO that at present has more than 300 declared concepts, with more than 3500 additional concepts imported from other OBO Foundry ontologies. While this first phase has focused on concepts for annotating samples, environments, exposures, and measurements, the next phase will center on supporting annotation of results and findings, such as concept models of molecular, cellular and tissue effects. The value of the RBO will be determined in part by our ability to engage the community in its development, and we have established a Radiobiology Informatics Consortium with unrestricted membership as the owner of the RBO in order to encourage investigators, system owners and other to join in this effort. Anyone can report issues or request new concept modeling or other features directly on GitHub. By using the BioPortal application programming interface, systems can pose dynamic queries to the latest version of the RBO for information on individual classes or entire hierarchies; this design eliminates the need for systems to be updated in order to use newer versions of the RBO. We hope to contribute to the advancement of open radiobiological science through the continued, open development of the RBO, that will provide more precise, machine-interpretable descriptions of investigations, as well as support data meta-analysis through machine learning or other artificial intelligence methods. REFERENCES [1] Open science in space. Nature Medicine, 2021. 27(9): p. 1485-1485. [2] Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. [3] Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5. [4] Whetzel, P.L., et al., BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications. Nucleic Acids Res, 2011. 39(Web Server issue): p. W541-5.

informatics↗
NASA NTRSDate not supplied

Modern Scientific Data Governance Framework

Science has entered the era of Big Data with new challenges related to data governance, stewardship, and management. The existing data governance practices must catch up to ensure proper data management. Existing data governance policies and stewardship best practices tend to be disconnected from operational data management practices and enforcement and mainly exist in well-meaning documents or reports. These governance policies are, at best, partially implemented and rarely monitored or audited. In addition, existing governance policies keep adding additional data management steps that require a human, ‘a data steward’, in the loop, and the cost of data management can no longer scale proportionately with the current and future increased data volume and complexity. The goal for developing an updated data governance framework is to modernize scientific data governance to the reality of Big data and align it with the current technology trends such as cloud computing and AI. The goals of this framework are two folds. One is to ensure thoroughness that the governance adequately covers the entire data life cycle. Two, provide a practical approach that offers a consistent and repeatable process for different projects. Three core principles ground this framework. First, focus on just enough governance and prevent data governance from becoming a roadblock toward the scientific process. Remove any unnecessary processes and steps. Second, automate data management steps where possible. Actively remove steps that require ‘human in the loop’ within the management process to be efficient and scale with increasing data. Third, all the processes should continually be optimized using quantified metrics to streamline the monitoring and auditing workflows.

Rahul Ramachandran↗
NASA NTRS1991

Stewardship of very large digital data archives

An archive is a permanent store. There are relatively few very large digital data archives in existence. Most business records are expired within five or ten years. Many kinds of business records that do have long lives are embedded in data bases that are continually updated and re-issued cyclically. Also, a great deal of permanent business records are actually archived as microfilm, fiche, or optical disk images - their digital version being an operational convenience rather than an archive. The problems forseen in stewarding the very large digital data archives that will accumulate during the mission of the Earth Observing System (EOS) are addressed. It focuses on the function of shepherding archived digital data into an endless future. Stewardship entails storing and protecting the archive and providing meaningful service to the community of users. The steward will (1) provide against loss due to physical phenomena; (2) assure that data is not lost due to storage technology obsolescence; and (3) maintain data in a current formatting methodology.

Savage, Patric↗
NASA NTRS1992

Stewardship of very large digital data archives

This paper addresses the problems foreseen by the author in stewarding the very large digital data archives that will accumulate during the mission of the Earth Orbiting Satellite (EOS). It focuses on the function of 'shepherding' archived digital data into an endless future. Stewardship entails a great deal more than storing and protecting the archive. It also includes all aspects of providing meaningful service to the community of users (scientists) who will want to access the data. The complete steward will be required to do the following: (1) provide against loss due to physical phenomena; (2) assure that data is not 'lost' due to storage technology obsolescence; (3) maintain data in a current formatting methodology with the additional requirement of being able to reconstitute the data to its original, as-received format; (4) secure against loss or pollution of data due to accidental, misguided, or willful software intrusion; (5) prevent unauthorized electronic access to the data, including unauthorized placement of data into the archive; (6) index the data in a metadatabase so that all anticipatable queries can be served without searching through the data itself; (7) provide responsive access to the metadatabase; (8) provide appropriately responsive access to the data; (9) incorporate additions and changes to the archive (and to the metadatabase) in a timely way; and (10) deliver only copies of data to clients - retain physical custody of the 'official' data. Items 1 through 4 are discussed in this paper.

Savage, Patric↗
NASA NTRS2016

Stewardship of NASA's Earth Science Data and Ensuring Long-Term Active Archives

Program, NASA has followed an open data policy, with non-discriminatory access to data with no period of exclusive access. NASA has well-established processes for assigning and or accepting datasets into one of 12 Distributed Active Archive Centers (DAACs) that are parts of EOSDIS. EOSDIS has been evolving through several information technology cycles, adapting to hardware and software changes in the commercial sector. NASA is responsible for maintaining Earth science data as long as users are interested in using them for research and applications, which is well beyond the life of the data gathering missions. For science data to remain useful over long periods of time, steps must be taken to preserve: (1) Data bits with no corruption, (2) Discoverability and access, (3) Readability, (4) Understandability, (5) Usability' and (6). Reproducibility of results. NASAs Earth Science data and Information System (ESDIS) Project, along with the 12 EOSDIS Distributed Active Archive Centers (DAACs), has made significant progress in each of these areas over the last decade, and continues to evolve its active archive capabilities. Particular attention is being paid in recent years to ensure that the datasets are published in an easily accessible and citable manner through a unified metadata model, a common metadata repository (CMR), a coherent view through the earthdata.gov website, and assignment of Digital Object Identifiers (DOI) with well-designed landing product information pages.

Data Management↗
NASA NTRSDate not supplied

NASA Life Sciences Portal (NLSP): Supporting Scientific Transparency and Reproducibility

NASA’s Life Sciences Ports (NLSP) serves the scientific community by providing curated data from space life science experiment. The Human Research Program (HRP) with the help of NLSP is currently transforming their life sciences data archive systems and processes to improve compliance with the FAIR principles [1]. Some of these improvements will at the same time support the twin pillars of Open Science [2]: transparency of methods and reproducibility of results. Scientific transparency is marked by the easily intelligible communication of what has been investigated: what were the procedures for collecting sample and the characteristics of samples collected? what kinds of measurements were made, what were the environmental conditions of the measurements? What were the analysis techniques of the collected data? Reproducibility of the results and findings from the investigation requires a high level of transparency for all but the simplest investigations; the slightest deviation in communicating and replicating complex experimental procedures or data analyses can often yield quite different data and even findings, thwarting their validation. One of the ways the NLSP is aiming to improve the communication of scientific information is through the use of ontology-driven metadata. Ontologies are powerful, graph-based knowledge representation structures, which can be leveraged to increase data interoperability, the area of the FAIR principles in which many data systems most lack compliance. Over the past decade, there has been a concerted effort in the biomedical community to develop modular and narrowly focused domain and application-specific ontologies in a common, open-source framework, the Open Biological and Biomedical Ontology (OBO) Foundry [3]. The open sharing and modular nature of this effort promises huge increases in harmonized data sharing for systems that leverage these models. Which is in line with the FAIR Data Principles of Findability, Accessibility, Interoperability, and Reuse for scientific data management and stewardship. 1. Wilkinson, M.D., et al., The FAIR Guiding Principles for scientific data management and stewardship. Sci Data, 2016. 3: p. 160018. 2. National Academies of Sciences, E. and Medicine, Open Science by Design: Realizing a Vision for 21st Century Research. 2018, Washington, DC: The National Academies Press. 232. 3. Smith, B., et al., The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotechnol, 2007. 25(11): p. 1251-5.

Life Sciences data↗
NASA NTRS2007

The Joint Aerosol-Monsoon Experiment (JAMEX): A Core Element for the Asian Monsoon Year (2008-2009)

The objective of the Joint Aerosol-Monsoon Experiment (JAMEX) is to unravel the physical mechanisms and multi-scale interactions associated with aerosol-monsoon water cycle in the Asian Indo-Pacific region towards improved prediction of rainfall in land regions of the Asian monsoon. JAMEX will be planned as a five-year (2007-201 1) multi-national aerosol-monsoon research project, aimed at promoting collaboration, partnership and alignment of ongoing and planned national and international programs. Two coordinated special observing periods (SOP), covering the pre-monsoon (April-May) and the monsoon (June-August) periods is tentatively targeted for 2008 and 2009. The major work on validation and reference site coordination will take place in 2007 through the spring of 2008. A major science workshop is planned after SOP-I1 in 2010. Modeling and satellite data utilization studies will continue throughout the entire period to help in design of the observation arrays and measurement platforms for SOPS. The tentative time schedule, including milestones and research activities is shown in Fig. 1. One of the unique aspects of JAMEX is that it stems from grass-root scientific and societal imperatives, and it bridges a gap in existing national and international research programs. Currently we have identified 10 major national and international projects/programs separately for aerosols and monsoon research planned in the next five years in China, India, Japan, Italy, and the US, that could be potential contributors or partners with JAMEX. These include the Asian-Indo- Pacific Ocean (AIPO) Project and Aerosol Research Project from China, Monsoon Asian Hydro- Atmospheric Science Research and predication Initiative (MAHASRI) from Japan, Continental Tropical Convergence Zone (CTCZ) and Severe Thunderstorm: Observations and Regional Modeling (STORM) from India, Share-Asia from Italy, Atmospheric Brown Cloud (ABC), Pacific Aerosol-Cloud-Dust Experiment (PACDEX), East Asia Study of Tropospheric Aerosol: an International Regional Experiment (East-AIRE), and Radiation Aerosol Joint Observations - Monsoon Experiments over the Gangetic Himalayas Area (Rajo-Megha: dust cloud in Sanskrit) from the US, and Monsoon Asia Integrated Regional Study (MAIR) under the Earth Systems I Science Partnership (ESSP) and WCRP. For JAMEX to succeed, it is crucial for an international body, such as CEOP or an organization under WCRP to provide the science oversight, data policy and stewardship, and to promote collaboration and partnership among national programs. It makes eminent sense for WCRP to expand the concept and the prototype proposed by JAMEX to include all monsoon countries to expand AMY08-09 into an International Monsoon Era (2008- 2013). Such an establishment followed by establishment of an international body for science oversight, and data stewardship will go a long way in promoting coordination and connection among various existing monsoon research programs within WCRP, and with burgeoning national programs on monsoon and aerosol research.

Lau, William K.M.↗
NASA NTRS2007

The Joint Aerosol-Monsoon Experiment (JAMEX): A Core Element for the Asian Monsoon Year (2008-2009)

The objective of the Joint Aerosol-Monsoon Experiment (JAMEX) is to unravel the physical mechanisms and multi-scale interactions associated with aerosol-monsoon water cycle in the Asian Indo-Paczj?c region towards improved prediction of rainfall in land regions of the Asian monsoon. JAMEX will be planned as a five-year (2007-201 1) multi-national aerosol-monsoon research project, aimed at promoting collaboration, partnership and alignment of ongoing and planned national and international programs. Two coordinated special observing periods (SOP), covering the pre-monsoon (April-May) and the monsoon (June-August) periods is tentatively targeted for 2008 and 2009. The major work on validation and reference site coordination will take place in 2007 through the spring of 2008. A major science workshop is planned after SOP-I1 in 2010. Modeling and satellite data utilization studies will continue throughout the entire period to help in design of the observation arrays and measurement platforms for SOPS. The tentative time schedule, including milestones and research activities is shown in Fig. 1. One of the unique aspects of JAMEX is that it stems from grass-root scientific and societal imperatives, and it bridges a gap in existing national and international research programs. Currently we have identified 10 major national and international projects/programs separately for aerosols and monsoon research planned in the next five years in China, India, Japan, Italy, and the US, that could be potential contributors or partners with JAMEX. These include the Asian-Indo- Pacific Ocean (AIPO) Project and Aerosol Research Project from China, Monsoon Asian Hydro- Atmospheric Science Research and predication Initiative (MAHASRI) from Japan, Continental Tropical Convergence Zone (CTCZ) and Severe Thunderstorm: Observations and Regional Modeling (STORM) from India, Share-Asia from Italy, Atmospheric Brown Cloud (ABC), Pacific Aerosol-Cloud-Dust Experiment (PACDEX), East Asia Study of Tropospheric Aerosol: an International Regional Experiment (East-AIRE), and Radiation Aerosol Joint Observations - Monsoon Experiments over the Gangetic Himalayas Area (Rajo-Megha: dust cloud in Sanskrit) from the US, and Monsoon Asia Integrated Regional Study (MAIR) under the Earth Systems Science Partnership (ESSP) and WCRP. For JAMEX to succeed, it is crucial for an international body, such as CEOP or an organization under WCRP to provide the science oversight, data policy and stewardship, and to promote collaboration and partnership among national programs. It makes eminent sense for WCRP to expand the concept and the prototype proposed by JAMEX to include all monsoon countries to expand AMY08-09 into an International Monsoon Era (2008- 2013). Such an establishment followed by establishment of an international body for science oversight, and data stewardship will go a long way in promoting coordination and connection among various existing monsoon research programs within WCRP, and with burgeoning national programs on monsoon and aerosol research.

Lau, WIlliam K. M.↗
NASA NTRS1991

Data principles for the U.S. Global Change Research Program

The U.S. Interagency Working Group on Data Management for Global Change has developed a set of data management and access principles. The overall purpose of these statements of principle is to stimulate responsible stewardship for data and related information and to facilitate full and open access to them. These statements have been accepted by the U.S. Agencies responsible for the Global Change Research Program. The statements of principle are presented and discussed.

Ludwig, George H.↗
NASA NTRS2016

Managing Sustainable Data Infrastructures: The Gestalt of EOSDIS

EOSDIS epitomizes a System of Systems, whose many varied and distributed parts are integrated into a single, highly functional organized science data system. A distributed architecture was adopted to ensure discipline-specific support for the science data, while also leveraging standards and establishing policies and tools to enable interdisciplinary research, and analysis across multiple scientific instruments. The EOSDIS is composed of system elements such as geographically distributed archive centers used to manage the stewardship of data. The infrastructure consists of underlying capabilities connections that enable the primary system elements to function together. For example, one key infrastructure component is the common metadata repository, which enables discovery of all data within the EOSDIS system. EOSDIS employs processes and standards to ensure partners can work together effectively, and provide coherent services to users.

remote sensing↗
NASA NTRSDate not supplied

Stewardship Best Practices for Improved Discovery and Reuse of Heterogeneous and Cross-Disciplinary Earth System Data

Some of the Earth system data products such as those from NASA airborne and field investigations (a.k.a. campaigns), are highly heterogeneous and cross-disciplinary, making the data extremely challenging to manage. For example, airborne and field campaign measurements tend to be sporadic over a period of time, with large gaps. Data products generated are of various processing levels and utilized for a wide range of inter- and cross-disciplinary research and applications. Data and derived products have been historically stored in a variety of domain-specific standard (and some non-standard) formats and in various locations such as NASA Distributed Active Archive Centers (DAACs), NASA airborne science facilities, field archives, or even individual scientists’ computer hard drives. As a result, airborne and field campaign data products have often been managed and represented differently, making it onerous for data users to find, access, and utilize campaign data. Some difficulties in discovering and accessing the campaign data originate from the incomplete data product and contextual metadata that may contain details relevant to the campaign (e.g. campaign acronym and instrument deployment locations), but tend to lack other significant information needed to understand conditions surrounding the data. Such details can be burdensome to locate after the conclusion of a campaign. Utilizing consistent terminology, essential for improved discovery and reuse, is also challenging due to the variety of involved disciplines. To help address the aforementioned challenges faced by many repositories and data managers handling airborne and field data, this presentation will describe stewardship practices developed by the Airborne Data Management Group (ADMG) within the Interagency Implementation and Advanced Concepts Team (IMPACT) under the NASA’s Earth Science Data systems (ESDS) Program.

best practices↗
NASA NTRSDate not supplied

A New ML-Based Adaptive Thinning Methodology to Improve the Impact of AIRS and CrIS Assimilation on Global Tropical Cyclone Forecasts

This work builds on previous research performed by this team to improve the forecast of Tropical Cyclones (TCs) by assimilating AIRS and CrIS radiances into the NASA Global Earth Observing System (GEOS). Past published work demonstrated that the assimilation of radiances with variable density was beneficial to TC forecasting in the GEOS. In the previous setup, a fixed-size moving square named 'TC domain' was activated by the so-called TC-vitals, an international real-time message accessible to all NWP forecasting centers, that documents the existence of a TC, its estimated position, and its size. The information from TC-vitals activated a switch in the GEOS, which allowed to reduce the distance used for thinning AIRS and CrIS data inside a 15 degrees by 15 degrees moving TC domain centered on the storm, so that more data were assimilated in the vicinity of the TC during its lifetime. The methodology produced improved TC analyses and led to better forecasts, particularly related to intensity, without damaging the global forecast skill. In the new version, the adaptive thinning methodology is based on a machine-learning technique. The technique searches for TCs and creates TC masks by using cloud-top temperatures from all geostationary satellites without the need for additional information. It is being trained against the International Best Track Archive for Climate Stewardship (IBTrACS) data base. Once a TC mask is created, a switch identical to the one used in the previous adaptive thinning method is activated, allowing the GEOS to ingest more data in the TC-shaped size-changing domain that follows the storm. As of today, the team has been able to successfully assimilate data inside the ML-detected TC domains. Future work includes an improved capability of reducing false alarm rates (i.e., cloud systems that are erroneously labeled as TCs).

Oreste Reale↗
NASA NTRS2020

Representation of Tropical Storms by the Modern-Era Retrospective Analysis for Research and Applications Version 2

This study examines the veracity of the tropical cyclone (TC) statistics estimated from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) global atmospheric reanalysis, focusing on the climatological-mean genesis regions, tracks and their lifetime maximum intensity, as well as the interannual and intraseasonal variations in TC activity. The results are validated against the International Best Track Archive for Climate Stewardship (IBTrACS) data for 1980-2016. MERRA-2 represents the spatial distribution of the TC genesis location and the tracks realistically well over all main development regions (MDRs), but with notable discrepancies including too weak TC activity over the Arabian Sea and the South China Sea and too strong activity over the North Indian Ocean. Over the western North Pacific and the North Atlantic, MERRA-2 underestimates recurving TCs steered by background westerlies in the mid-latitudes and thereby exaggerates northwestward moving TCs, resulting in an overestimate of the landfall probability in East Asia and North America. Excessive development of TCs over the Bay of Bengal also tends to exaggerate the landfall probability in India. In spite of the discrepancies in the annual TC number, the seasonal variation of TC genesis is realistic in MERRA-2. MERRA-2 also captures the TC intensity relationship between the minimum pressure and the maximum surface wind speed at the mature stage, although the maximum intensity is weaker than in the observations. While MERRA-2 tends to reproduce the interannual variations of the observed TC number and the power dissipation index (PDI), the level of accuracy depends on the region. MERRA-2 describes the changes in the TC genesis region and tracks realistically according to the different phases of El Nino and the Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO), although it is less realistic over the North Indian Ocean.

International Best Track Archive for Climate Stewa↗
DOE OSTI2025

Microbiome data management in action workshop: Atlanta, GA, USA, June 12–13, 2024

Microbiome research is revolutionizing human and environmental health, but the value and reuse of microbiome data are significantly hampered by the limited development and adoption of data standards. While several ongoing efforts are aimed at improving microbiome data management, significant gaps still remain in terms of defining and promoting adoption of consensus standards for these datasets. The Strengthening the Organization and Reporting of Microbiome Studies (STORMS) guidelines for human microbiome research have been endorsed and successfully utilized by many research organizations, publishers, and funding agencies, and have been recognized as a consensus community standard. No equivalent effort has occurred for environmental, synthetic, and non-human host-associated microbiomes. To address this growing need within the microbiome research community, we convened the Microbiome Data Management in Action Workshop (June 12–13, 2024, in Atlanta, GA, USA), to bring together key decision makers in microbiome science including researchers, publishers, funders, and data repositories. The 50 attendees, representing the diverse and interdisciplinary nature of microbiome research, discussed recent progress and challenges, and brainstormed actionable recommendations and paths forward for coordinated environmental microbiome data management and the modifications necessary for the STORMS guidelines to be applied to environmental, non-human host, and synthetic microbiomes. The outcomes of this workshop will form the basis of a formalized data management roadmap to be implemented across the field. These best practices will drive scientific innovation now and in years to come as these data continue to be used not only in targeted reanalyses but in large-scale models and machine learning efforts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1992

Satellite altimetry

Since altimetry data are not really old enough to use the term data archaeology, Mr. Cheney referred to the stewardship of these data. He noted that it is very important to document the basis for an altimetry data set as the algorithms and corrections used to arrive at the Geophysical Data Record (GDR) have been improving and are continuing to improve the precision of sea level data derived from altimetry. He noted that the GEOSAT Exact Repeat Mission (ERM) data set has recently been reprocessed by his organization in the National Ocean Service of NOAA and made available to the scientific community on CD/ROM disks by the National Oceanographic Data Center of the U.S. (NODC). The new data set contains a satellite orbit more precise by an order of magnitude together with an improved water vapor correction. A new, comprehensive GDR Handbook has also been prepared.

Cheney, Robert E.↗