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NASA NTRSDate not supplied

Characterizing Wildfires in Western US.: A Cloud-based Case Study for Interdisciplinary Research using NASA Resources

This presentation will demonstrate a case study of interdisciplinary research done in the Amazon Web Services (AWS) cloud platform, in addition to in the local machine. We conduct data analysis next to data by leveraging various cloud-based data in NASA Earthdata Cloud, which are distributed by different missions/NASA Distributed Active Archive Centers (DAACs), and cloud computing resources at NASA. For instance, we directly access multiple datasets stored in the AWS Simple Storage Service (S3) buckets using a Python Jupyter notebook through a JupyterHub interface hosted in AWS (without having to download data), and conduct data analysis next to data in the cloud. We will also show how to share the research results following Open Source policy. This case study characterizes the change in wildfire events in the western United States during the past 20 years. In particular, we focus on the wildfires in California in 2021, one of the most severe wildfire years occurring in the most recent 20 years in California. We will analyze the possible causes of wildfires, such as drought conditions and climate variability, and examine the impacts of wildfires on air quality and atmospheric composition, and on land cover. We will examine the data distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), including aerosols and meteorological data from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), precipitation from the Global Precipitation Measurement (GPM) and Global Precipitation Climate Project (GPCP), and aerosol index from Ozone Monitoring Instrument (OMI). We also utilize the data distributed by the Physical Oceanography (PO) DAAC, such as Sea Surface Temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST), and the data distributed by Land Processes (LP) DAAC, such as Normalized Difference Vegetation Index (NDVI).

Xiaohua Pan↗
NASA NTRS2022

NASA's Next Generation of Atmospheric Data Science

The Multi-Angle Imager for Aerosols (MAIA) and the Tropospheric Emission: Monitoring of Pollution(TEMPO) are NASA’s next-generation satellite missions for air quality monitoring. These missions will produce high-quality, high-resolution air quality data to support cross-displinary research. The MAIA mission is collaborating with health science researchers and epidemiologists to study the impacts of air quality on health outcomes. TEMPO aims to improve our understanding of tropospheric air pollution chemistry and our ability to make predictions about air quality and climate forcing. TEMPO will offer hourly measurements of tropospheric ozone, aerosols, and clouds focused on North America at high-spatial resolution, while MAIA will produce high-resolution measurements of speciated particulate matter targeting densely populated cities around the globe. Data from these missions will help improve our understanding of the sources, types, and interactions among the aerosols and trace gases that are polluting Earth’s atmosphere, as well as our understanding of the impact of air pollution on pollution on a wide range of important areas including human health, agriculture, weather, and climate change. The challenges of cross-disciplinary research, computationally expensive multi-variate analyses, and high-resolution data at both local and global scales are driving substantial changes across all of NASA’s Distributed Active Archive Centers (DAACs). High resolution data at scales such these requires a new approach to data ingest, archive, and publication. Like other NASA DAACs, the Atmospheric Science Data Center (ASDC), the DAAC that will be responsible for publishing MAIA and TEMPO data products has historically archived and distributed data on premise. DAACs of the future will archive and distribute data in the cloud, enabling them to remake themselves as research-focused data centers that will support on-demand, data-intensive computations for highly accurate retrospective analyses and predictions. Under the new paradigm, data formats and metadata must support on-demand spatial and temporal sub-setting, as well as other data transformation services such as re-gridding and re-sampling. This presentation will discuss work being done to address data formatting and metadata requirements in this dynamic new environment. In addition to the changes in data stewardship practices at the ASDC, the increased focus on supporting scientific research is driving changes in the relationship between DAACs and researchers. While the ASDC will continue to provide first rate data management and stewardship, it is increasingly focused on serving as a partner not only to the science teams that gather and produce the data it publishes, but to the researchers that use that data.

Beth Huffer↗
NASA NTRSDate not supplied

Making Better Use of Satellite Data: The Satellite Needs Working Group

The U.S. Group on Earth Observations (USGEO) initiated in 2016 the Satellite Needs Working Group (SNWG) to identify and communicate the Earth observation needs of U.S. federal agencies. The SNWG identifies such needs through a biennial survey followed by interviews and follow-up discussions by the satellite Earth data providers of the U.S. Government: the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Geological Survey (USGS). Solutions and services are identified that leverage current or upcoming satellite missions to meet the identified needs; implementation of services that are estimated to significantly increase the level of satisfaction of multiple U.S. agencies are funded by NASA. The SNWG process has resulted in the implementation of numerous services that have impacted operations of not only U.S. agencies but of academic and international institutions as well. Notable examples include the Harmonized Landsat Sentinel-2 project that leverages European Space Agency (ESA) and NASA satellite assets to generate a global, analysis-ready, surface reflectance product with a temporal resolution of two days; the Airborne Data Management Group that curates and provides access to relevant resources, information and data from existing and past NASA field campaigns; and the Dynamic Surface Water Extent product which consists of harmonized but independent water extents derived from both from optical and radar data. These and other products are hosted at the NASA Distributed Active Archive Centers (DAACs) for free and open access. The SNWG Management Office at NASA’s Interagency Implementation and Advanced Concepts Team (IMPACT) manages the implementation of selected solutions and, importantly, NASA’s response to the needs of federal agencies through a Stakeholder Engagement Program. The impact of implemented services and solutions is hampered without efforts to build capacity around the use of the services. The Stakeholder Engagement Program ensures relevant training and outreach to SNWG agencies in collaboration with each solution implementation team.

remote sensing↗
NASA NTRSDate not supplied

What is LAADS DAAC? How to Download Data from NASA's Source for Cloud and Aerosol Data

The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) primarily archives and distributes data on clouds and aerosols in Earth’s atmosphere in addition to providing Level 0 and 1 Moderate Imaging Radiometer Suite (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and airborne data as well as data from the European Space Agency’s Sea and Land Surface Temperature Radiometer (SLSTR) and the Ocean and Land Colour Instrument (OLCI). Secondarily, LAADS DAAC serves as a backup source for MODIS and VIIRS land products. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS DAAC provides a gateway to data through multiple tools. The newest, View Data, allows users to preview data sets before downloading or applying any post-processing transformations. Learn about how to access LAADS DAAC data, get up-to-date information about LAADS DAAC's migration to hosting data in the cloud, and discover how to use the View Data tool.

Tassia Owen↗
NASA NTRSDate not supplied

LAADS DAAC Migrates to the Cloud: Lessons Learned from Communicating About Earth Science Data on the Cloud

The Level-1 and Atmosphere Archive Distribution System (LAADS) Distributed Active Archive Center (DAAC) is migrating data to the cloud. As one of twelve DAACS supported by NASA’s Earth Science Data and Information System (ESDIS), LAADS is using moving away from on premise data storage facilities to migrating to Amazon Web Services, where the massive archive of data from the Moderate Imaging Spectroradiometer (MODIS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) will be available for download and post-processing transformations online. The migration is happening in three phases and LAADS is concluding its beta testing period. This poster shows the lessons learned from communicating with a select group of users about how to effectively educate data users on using data in the cloud.

Tassia Owen↗
NASA NTRS2023

Satellite-Derived Estimates of Suspended CaCO3 Mud Con-Centrations from the West Florida Shelf Induced by Hurricane Ian

In the days following the passage of Hurricane Ian over the West Florida Shelf, a large plume of calcium carbonate (CaCO3) mud slurry was observed extending from west of the Dry Tortugas and curving to the east into the Straits of Florida. This discreet target offered a unique opportunity to quantify the suspended mass of CaCO3 in the slurry. Estimating the concentration of sediment in a plume of suspended CaCO3 by satellite sensor observations has been stymied up to now owing to a lack of in situ suspended sediment measurements during storm events, as “sea truth” data for such events is difficult to acquire. However, the Particulate Inorganic Carbon (PIC) standard product provided by the NASA Ocean Biology Distributed Active Archive Center (OBDAAC) is based on Moderate Resolution Imaging Spectroradiometer (MODIS) observations of a plume of coccolith chalk released from a ship in the “Chalk-Ex” experiment. Due to the similarities (particle size, mineralogy, and reflectance properties) of the suspended chalk features and the Ian-induced slurry, we utilized this data product to make initial estimates of the concentration of suspended sediment in the plume.

remote sensing↗
NASA NTRSDate not supplied

pyQuARC: Preparing for Full Release

Metadata holds the contextual information about data and is the underlying structure for many data search portals. High quality metadata optimizes search results, allowing users to quickly retrieve the data they need. With the abundant volume and diversity of Earth observation datasets, data discovery and metadata quality are critical for end users. The Common Metadata Repository (CMR), for example, currently hosts metadata for over 9,000 Earth observation data products archived across 12 NASA Distributed Active Archive Centers (DAACs). The Analysis and Review of CMR (ARC) Team, located at Marshall Space Flight Center, assesses the completeness, correctness, and consistency of these metadata records to ensure they are accessible, usable, and discoverable. In 2021, ARC began developing pyQuARC, an open source library for Earth Observation Metadata Quality Assessment to automate this effort. The tool uses ARC’s existing metadata quality framework to provide prioritized recommendations for metadata improvement. During initial testing, pyQuARC automatically identified 58% of metadata findings when compared with a sample of manually reviewed records. Using the results from initial testing, this presentation will focus on recent advancements and improvements of the tool as the ARC team prepares for pyQuARC’s full release. It will also demonstrate pyQuARC's enrichment value, not only for the ARC team, but the broader EOSDIS metadata community as well.

Essence Raphael↗
NASA NTRSDate not supplied

Blast from the Past: ASDC Curation for NASA Suborbital Legacy Missions to Promote Data Discovery and Accessibility

NASA has an extensive history of conducting suborbital field campaigns to further advances in atmospheric sciences. Beginning with the Chemical Instrument Test and Evaluation (CITE) conducted in 1983-1984, NASA has completed many suborbital campaigns over the past three decades. Since the early 2010s, suborbital missions are typically assigned to a NASA Distributed Active Archive Center (DAAC) prior to the mission for long-term archival and distribution. Efforts are being made by NASA’s Earth Science Data and Information System (ESDIS) Project and the Airborne Data Management Group (ADMG) to assign legacy missions to DAACs for permanent archival and distribution, so that these valuable datasets remain to be available to the scientific community. NASA’s Atmospheric Science Data Center (ASDC) has been named the assigned DAAC for nearly 20 atmospheric composition legacy missions, including missions conducted as part of the Global Tropospheric Experiment (GTE) and expects to be named the assigned DAAC for more of these missions over the next few years. The primary goal of the ASDC is to provide access to the datasets as they are currently formatted to the broad user community and enhance their findability and accessibility. However, data reporting standards have evolved significantly since 1983 and the datasets span a wide variety of file formats, including text, Ames, GTE, and ICARTT (International Consortium for Atmospheric Research on Transport and Transformation), and the amount of metadata and relevant information included in the files also varies greatly and can not be readily extracted without subject matter knowledge. This has caused challenges for the ASDC’s suborbital metadata extraction pipeline in ensuring that accurate and necessary metadata is being provided for the missions by all the ASDC’s existing search mechanisms. To make the data more findable and accessible, the ASDC has begun researching ways to further enhance the datasets, including distributing value-added products (i.e. consistent file format such as ICARTT or netCDF), adding standard names from the ESDIS Standards Coordination Office (ESCO)-approved Atmospheric Composition Variable Standard Names Convention (ACVSNC), and creating outreach materials such as ArcGIS StoryMaps, User Guides, and Micro Articles, providing overviews of the missions and what type of data was collected during the missions. These efforts also help support NASA’s Open-Source Science by enhancing the FAIRness of the legacy data products. This presentation will review the ASDC’s ongoing efforts, progress made, and future plans for legacy missions.

Megan Buzanowicz↗
NASA NTRSDate not supplied

Open-Source Science-Driven Development of the Science Data System (SDS) for Earth System Observatory (ESO) Atmospheric Missions

The NASA Earth System Observatory (ESO) atmospheric missions will provide space-based and suborbital observations of collocated cloud, dynamic, precipitation and aerosol processing leading to improved weather, air quality, and climate predictions. The Science Data System (SDS) will deploy the adaptive processing system (APS) developed within the Cloud to manage the research and operational processing of ESO atmospheric mission orbital and suborbital sensors and curate these data for near real-time and collection reprocessing and transfer them to a NASA Distributed Active Archive Center (DAAC) for long-term storage and distribution. Further, the SDS will follow guidelines provided by NASA Earth Science Data Systems (ESDS) program including standard conventions for data file formats, naming, and metadata to improve data interoperability, interpretability, usability, discovery, provenance, and spatiotemporal representativeness. The SDS follows NASA’s commitment to Open-Source Science (OSS) including the sharing of data, software, and knowledge in an open and timely manner. Each of the SDS system components will be developed with open-source concepts including components of APS itself as well as ESO atmospheric mission algorithms. This presentation describes the framework of the SDS and its integral part in facilitating OSS within the ESO atmospheric missions.

David M. Giles↗
NASA NTRSDate not supplied

NASA's CLARREO Pathfinder Mission: The Reflected Solar’s First SITSat

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder mission will take reflected solar (RS) highly accurate measurements needed to monitor Earth’s climate and will be the first RS SI-traceable Satellite Sensor (SITSat). The mission includes a RS spectrometer that will be installed on the International Space Station (ISS) and take measurements for at least one year. CLARREO Pathfinder (CPF) will use on-orbit calibration to achieve an unprecedented high accuracy with SI-traceability and the inter-calibration of other on-orbit instruments. The spectrometer is based on the HyperSpectral Imager for Climate Science (HySICS) instrument developed by the University of Colorado/Laboratory for Atmospheric and Space Physics of Boulder, CO, USA. HySICS is being designed to have a radiometric uncertainty of 0.3% (1-sigma), a five to ten times improvement over existing spaceflight RS instruments. High accuracy SI-traceable measurements such as these are critical to develop long-term climate-quality data sets. Additionally, by measuring spectral reflectance with high accuracy the CPF instrument will serve as an on-orbit intercalibration radiometric reference for operational Earth-viewing sensors, such as the Clouds and Earth’s Radiant Energy System (CERES) broadband shortwave instrument and the Visible/Infrared Imaging Radiometer Suite (VIIRS). Two-axis pointing, a spectral range from 350 nm to 2300 nm, and a spectral resolution ≤6 nm enable CPF to provide nearly coincident temporal, spatial, angular, and spectral matching of intercalibration targets, with sampling sufficient to reduce random errors. The intercalibration method will refine knowledge of target sensors’ effective offsets, gain, non-linearity, spectral response, and polarization sensitivity (as is relevant). Calibrated reflectance and reflected radiance spectra will be distributed to the scientific community through a NASA Distributed Active Archive Center (DAAC). We will present an overview of the CLARREO Pathfinder mission, its anticipated impact on monitoring climate variability, and the novel CPF direct intercalibration approach.

climate↗
NASA NTRSDate not supplied

Enhancing Dataset Discovery and Usage Tracking in Earth Sciences: Integrating Knowledge Graphs and Large Language Models

NASA's Data Active Archive Centers (DAACs) have played a crucial role in supporting a wide range of applied research in Earth and Environmental sciences. To date, over 20,000 publications have been collected, citing more than 3,000 NASA Earth science datasets. We present an innovative approach that links datasets and collected publications through a knowledge graph (KG). This KG enables the tracking of dataset citations throughout the dataset's lifecycle, revealing patterns of dataset usage across various applied research areas. We fine-tuned the pre-trained NASA IMPACT INDUS-Base Retriever Large Language Model (LLM) using a set of labeled publication abstracts. Our results indicate that 87% of the publications were classified into one of twenty applied research areas, while the remaining 13% were categorized into non-applied research areas. The classified publications linked to datasets are used to discover datasets by users interested in specific applied research and by dataset providers to determine dataset usage for applications.

open-source↗
NASA NTRS1991

The NASA Ocean Data System at the Jet Propulsion Laboratory

Global change studies require satellite oceanographic observations archived in an active data center. This paper describes the activities of an experimental active oceanographic data archive center specializing in distribution of high-level oceanographic data products produced by research oceanographers from satellite altimeter, scatterometer, and microwave and infrared radiometer measurements. Methods to encourage data sharing practices were developed. Services initiated to help oceanographers conduct research more effectively included rapid delivery of data, reprocessing data sets, subsetting of large data sets, and distribution of multiple data sets on a single medium.

Halpern, David↗
NASA NTRS1985

Tropical Ocean and Global Atmosphere (TOGA) heat exchange project: A summary report

A pilot data center to compute ocean atmosphere heat exchange over the tropical ocean is prposed at the Jet Propulsion Laboratory (JPL) in response to the scientific needs of the Tropical Ocean and Global Atmosphere (TOGA) Program. Optimal methods will be used to estimate sea surface temperature (SET), surface wind speed, and humidity from spaceborne observations. A monthly summary of these parameters will be used to compute ocean atmosphere latent heat exchanges. Monthly fields of surface heat flux over tropical oceans will be constructed using estimations of latent heat exchanges and short wave radiation from satellite data. Verification of all satellite data sets with in situ measurements at a few locations will be provided. The data center will be an experimental active archive where the quality and quantity of data required for TOGA flux computation are managed. The center is essential to facilitate the construction of composite data sets from global measurements taken from different sensors on various satellites. It will provide efficient utilization and easy access to the large volume of satellite data available for studies of ocean atmosphere energy exchanges.

Liu, W. T.↗
NASA NTRS2011

Improvements in Space Geodesy Data Discovery at the CDDIS

The Crustal Dynamics Data Information System (CDDIS) supports data archiving and distribution activities for the space geodesy and geodynamics community. The main objectives of the system are to store space geodesy and geodynamics related data products in a central data bank. to maintain information about the archival of these data, and to disseminate these data and information in a timely manner to a global scientific research community. The archive consists of GNSS, laser ranging, VLBI, and DORIS data sets and products derived from these data. The CDDIS is one of NASA's Earth Observing System Data and Information System (EOSDIS) distributed data centers; EOSDIS data centers serve a diverse user community and arc tasked to provide facilities to search and access science data and products. Several activities are currently under development at the CDDIS to aid users in data discovery, both within the current community and beyond. The CDDIS is cooperating in the development of Geodetic Seamless Archive Centers (GSAC) with colleagues at UNAVCO and SIO. TIle activity will provide web services to facilitate data discovery within and across participating archives. In addition, the CDDIS is currently implementing modifications to the metadata extracted from incoming data and product files pushed to its archive. These enhancements will permit information about COOlS archive holdings to be made available through other data portals such as Earth Observing System (EOS) Clearinghouse (ECHO) and integration into the Global Geodetic Observing System (GGOS) portal.

Noll, C.↗
NASA NTRS2007

Science Archives in the 21st Century: A NASA LAMBDA Report

Lambda is a thematic data center that focuses on serving the cosmic microwave background (CMB) research community. LAMBDA is an active archive for NASA's Cosmic Background Explorer (COBE) and Wilkinson Microwave Anisotropy Probe (WMAP) mission data sets. In addition, LAMBDA provides analysis software, on-line tools, relevant ancillary data and important web links. LAMBDA also tries to preserve the most important ground-based and suborbital CMB data sets. CMB data is unlike other astrophysical data, consisting of intrinsically diffuse surface brightness photometry with a signal contrast of the order 1 part in 100,000 relative to the uniform background. Because of the extremely faint signal levels, the signal-to-noise ratio is relatively low and detailed instrument-specific knowledge of the data is essential. While the number of data sets being produced is not especially large, those data sets are becoming large and complex. That tendency will increase when the many polarization experiments currently being deployed begin producing data. The LAMBDA experience supports many aspects of the NASA data archive model developed informally over the last ten years-that small focused data centers are often more effective than larger more ambitious collections, for example; that data centers are usually best run by active scientists; that it can be particularly advantageous if those scientists are leaders in the use of the archived data sets; etc. LAMBDA has done some things so well that they might provide lessons for other archives. A lot of effort has been devoted to developing a simple and consistent interface to data sets, for example; and serving all the documentation required via simple 'more' pages and longer explanatory supplements. Many of the problems faced by LAMBDA will also not surprise anyone trying to manage other space science data. These range from persuading mission scientists to provide their data as quickly as possible, to dealing with a high volume of nuisance (spam) messages. Because so many data center problems and solutions are common across individual data centers and disciplines it would be very valuable to establish some new systems of communication - such as informal email lists for administrators and developers. But resources are very limited, so new timeconsuming and inefficient mechanisms - like too-frequent and too-structured meetingsshould be avoided. Although there are great advantages to being small, agile and independent, there are also some areas where science data centers within and without NASA could be better coordinated - for the assignment of persistent identifiers; to encourage the early adoption of useful standards and technologies; etc. Some super-structure to facilitate such coordination might be beneficial as long as it doesn't begin to control the other work of the archives, and become a "methodology police". In this respect the CCSDS "Reference Model for an Open Archive Information System" is a little worrying. It may be that the closer a data center gets to following such a detailed prescription, the less effective it will become. It is much better to have an informal coordination process than a bureaucratic straight-jacket.

Butterworth, P.↗