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NASA NTRSDate not supplied

Informing Disaster Response through Earth Observation: A User-Centric Model for Enhancing Disaster Response Using Geospatial Assets

Satellite observations can provide critical insights to building situational awareness and filling data gaps during disaster response. The National Aeronautics and Space Administration (NASA) Earth Science Division’s Disasters Program aims to advance Earth science data and information to support management decisions that prevent or mitigate the impacts of disasters. In support of this goal, NASA’s Disasters Response Coordination System (DRCS) employs a “One NASA” approach to coordinate and mobilize the Agency’s assets and expertise to provide geospatial information during disasters. The DRCS advances the utility of Earth observation information for supporting disaster response needs and builds skills in the emergency management and disaster response communities through improved coordination, engagement, and learning. The DRCS aims to support reduction of impact to lives and livelihoods by empowering communities to more effectively respond to disasters. The DRCS is organized across six NASA centers and managed by a project office located at NASA Langley, working in alignment with NASA Headquarters. The DRCS employs a user-centered framework that begins with requests from disaster responders (state, local, federal government and non-profits working at a national scale) and ends with after-action assessments that feed lessons learned and process improvements. This poster introduces the DRCS model and approach to expanding the use of Earth observations and geospatial information to support disaster response, share use cases for recent event activations working with decision-making organizations, and highlight initial lessons learned.

Remote Sensing↗

NASA NTRS2018

Exploring Synergistic Tools from NASA Satellite Data for Air Quality

Space-borne earth observation has been important to monitor the earth condition and played a critical role in validating other instruments or modeling's outputs. However, the data from satellite earth observation are usually very complex in terms of science contents, formats, and spatiotemporal granularities, making them difficult to use from many aspects. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), one of the 12 official NASA data centers, archives and distributes rich collections of data from multiple satellite missions and model results. The GES DISC is also the official archive center for data from the Ozone Monitoring Instrument (OMI) aboard NASA's Aura mission since 2004. Recently, the GES DISC has been evolving and improving its data management and services in order to promote NASA data to be easily discovered and accessed, as well as to facilitate interoperability. We'll show in this presentation how to explore and analyze NASA earth observation data for air quality through a suite of user-friendly tools - from Worldview to Giovanni, demonstrating in using this set of tools prepares us to serve the Sentinel 5P TROPOMI to the community.

air quality↗

NASA NTRS2018

Temperature Anomalies from the AIRS Product in Giovanni for the Climate Community

The Atmospheric Infrared Sounder (AIRS) mission began with the launch of Aqua in 2002. Over 15 years of AIRS products have been used by the climate research and application communities. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), in collaboration with NASA Sounder Team at JPL, provides processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding Suomi National Polar-Orbiting Partnership (SNPP) Cross-track Infrared Sounder (CrIS) mission. We generated a Multi-year Monthly Mean and Anomaly product using 14 years of AIRS standard monthly product. The product includes Air Temperature at the Surface and Surface Skin Temperature, both in Ascending/Daytime and Descending/Nighttime mode. The temperature variables and their anomalies are deployed to Giovanni, a Web-based application developed by the GES DISC. Giovanni provides a simple and intuitive way to visualize, analyze, and access vast amounts of Earth science remote sensing data without having to download the data. It is also a powerful tool that stakeholders can use for decision support in planning and preparing for increased climate variability. In this presentation, we demonstrate the functions in Giovanni with use cases employing AIRS Multi-year Monthly Mean and Anomaly variables.

Giovann↗

NASA NTRS2010

Data Access Services that Make Remote Sensing Data Easier to Use

This slide presentation reviews some of the processes that NASA uses to make the remote sensing data easy to use over the World Wide Web. This work involves much research into data formats, geolocation structures and quality indicators, often to be followed by coding a preprocessing program. Only then are the data usable within the analysis tool of choice. The Goddard Earth Sciences Data and Information Services Center is deploying a variety of data access services that are designed to dramatically shorten the time consumed in the data preparation step. On-the-fly conversion to the standard network Common Data Form (netCDF) format with Climate-Forecast (CF) conventions imposes a standard coordinate system framework that makes data instantly readable through several tools, such as the Integrated Data Viewer, Gridded Analysis and Display System, Panoply and Ferret. A similar benefit is achieved by serving data through the Open Source Project for a Network Data Access Protocol (OPeNDAP), which also provides subsetting. The Data Quality Screening Service goes a step further in filtering out data points based on quality control flags, based on science team recommendations or user-specified criteria. Further still is the Giovanni online analysis system which goes beyond handling formatting and quality to provide visualization and basic statistics of the data. This general approach of automating the preparation steps has the important added benefit of enabling use of the data by non-human users (i.e., computer programs), which often make sub-optimal use of the available data due to the need to hard-code data preparation on the client side.

Lynnes, Christopher↗

NASA NTRS2015

AIRS Mission Support from GES DISC

This talk will describe the support and distribution of AIRS (Atmospheric Infra Red Sounding) data products that are archived and distributed from the Goddard Earth Sciences Data and Information Services Center. Along with data stewardship, an important mission of GES DISC is to enhance the usability of data and broaden the user base. We will provide a brief summary of the current online archive and distribution metrics for the AIRS v5 and v6 products. We will also describe collaborative data sets and services (e.g., visualization and potential science applications) and solicit feedback for potential future services.

version↗

NASA NTRS2017

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

EOSDIS is a data system created by NASA to manage its collection of Earth Science data. This presentation is a brief description of the data system provided to the general user community. The presentation reviews the data types, management and software development techniques in use to organize the system.

science data management↗

NASA NTRS2018

Data, Meet Compute: NASA's Cumulus Ingest Architecture

NASA's Earth Observing System Data and Information System (EOSDIS) houses nearly 30PBs of critical Earth Science data and with upcoming missions is expected to balloon to between 200PBs-300PBs over the next seven years. In addition to the massive increase in data collected, researchers and application developers want more and faster access - enabling complex visualizations, long time-series analysis, and cross dataset research without needing to copy and manage massive amounts of data locally. NASA has looked to the cloud to address these needs, building its Cumulus system to manage the ingest of diverse data in a wide variety of formats into the cloud. In this talk, we look at what Cumulus is from a high level and then take a deep dive into how it manages complexity and versioning associated with multiple AWS Lambda and ECS microservices communicating through AWS Step Functions across several disparate installations

EOSDIS↗

NASA NTRS2018

Earthdata Cloud Analytics Project

This presentation describes a nascent project in NASA to develop a framework to support end-user analytics of NASA's Earth science data in the cloud. The chief benefit of migrating EOSDIS (Earth Observation System Data and Information Systems) data to the cloud is to position the data next to enormous computing capacity to allow end users to process data at scale. The Earthdata Cloud Analytics project will user a service-based approach to facilitate the infusion of evolving analytics technology and the integration with non-NASA analytics or other complementary functionality at other agencies and in other nations.

data services↗

NASA NTRS2023

User Guide for TROPICS Data Products

This document provides information for using the data products available from the “Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats” (TROPICS) mission. The TROPICS mission will produce a range of data products that will be available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). The data products will be produced at the TROPICS Data Processing Center (UW-M SSEC), and consist of Level-1 radiances (antenna and brightness temperatures), Level-2a unified resolution radiance, Level-2b Atmospheric Vertical Temperature Profiles (AVTP), Level-2b Atmospheric Vertical Moisture Profiles (AVMP), Level-2b Instantaneous Surface Rain Rate (ISRR), and Level-2b Tropical Cyclone (TC) intensity algorithms to estimate two primary variables: Minimum Sea Level Pressure (MSLP) and Maximum Sustained Winds (MSW). Two independent intensity estimation methods are included: 1) the Tropical Cyclone Intensity Estimate algorithm (TCIE) developed at the University of Wisconsin/CIMSS using native microwave brightness temperatures and 2) the Hurricane Intensity and Structure Algorithm (HISA) developed at Colorado State University/CIRA using microwave retrievals of temperature, moisture, and integrated quantities. In addition to MSW and MSLP, HISA also provides estimates of surface wind radii and 2D winds at standard pressure levels. TROPICS is adapting the NOAA STAR Microwave Integrated Retrieval System (MIRS) to retrieve the AVTP and AVMP data products. The ISRR algorithm uses the NASA Goddard Precipitation Retrieval and Profiling Scheme (PRPS).

TROPICS↗

NASA NTRSDate not supplied

Verification of TROPOMI NO2 Product Using OMI NO2 algorithm

We evaluated S5P TROPOspheric Monitoring Instrument (TROPOMI) operational nitrogen dioxide (NO2) product by comparing with the NO2 retrievals from Ozone Monitoring Instrument (OMI) onboard NASA’s Aura satellite. We compared spatially matched NO2 vertical column density (VCD) data from OMI and TROPOMI to identify any discrepancies between the two operational products. We also applied OMI Air-Mass Factor (AMF) algorithm to TROPOMI Slant Column Density (SCD) data (v02.03.01) aiming to create long-term merged NO2 Earth Science Data Record (https://disc.gsfc.nasa.gov/datasets/TROPOMI_MINDS_NO2_1.1/summary ). The algorithm (version 4.0) uses new Geometry-dependent Lambertian Equivalent surface Reflectivity (GLER) product available for each TROPOMI pixel. GLER is pre-calculated using the vector linearized discrete ordinate radiative transfer (VLIDORT) model, which uses as input high-resolution bidirectional reflectance distribution function (BRDF) information from NASA's Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the wind-dependent Cox–Munk wave-facet slope distribution over water, the latter with a contribution from the water-leaving radiance based on MODIS gap-filled in-water chlorophyll-a data. The GLER data, combined with consistently retrieved cloud parameters, provide improved information for the calculation of the scattering weight profiles. Additional AMF improvements result from using high resolution (0.25o latitude x 0.25o longitude) a priori NO2 profile shapes and other auxiliary information from the Global Modeling Initiative (GMI) Replay simulation sampled using S5P orbital simulator. Our TROPOMI_MINDS_NO2 algorithm employs the stratosphere-troposphere separation scheme, de-striping, and surface snow/ice treatment consistently with the latest OMI NO2 re-processing (version 4). We evaluate the TROPOMI_MINDS_NO2 product by comparing with the S5P operational NO2 product as well as with independent NO2 observations from ground-based Pandora and aircraft observations. Our results indicate that the new TROPOMI_MINDS_NO2 retrievals are generally higher than the S5P operational NO2 product over polluted regions and show improved agreement with independent validation data.

TROPOMI↗

NASA NTRSDate not supplied

Informing Disaster Response: An Introduction to the NASA Disaster Response Coordination System

Satellite observations provide information about the Earth that can be critical to building situational awareness and filling in data gaps during disaster response. The National Aeronautics and Space Administration (NASA) Earth Science Division’s Disasters Program aims to advance Earth science data and information to support management decisions that prevent or mitigate the impacts of disasters. In support of this goal, NASA’s Disaster Response Coordination System (DRCS) manages a One-NASA approach to coordinate and mobilize the Agency’s assets and expertise to provide geospatial information during disasters. The purpose of the DRCS is to advance the utility of Earth observation information for supporting disaster response decision support, build skilled and effective response communities through improved coordination, engagement, and learning, and reduce impact to lives and livelihoods by empowering communities to respond to disasters more effectively. The DRCS employs a user-centered, activation framework that begins with direct requests from responders and ends with after-action assessments that feed lessons learned and process improvements. This poster will introduce the DRCS model and approach to expanding the use of Earth observations and geospatial information to support disaster response, share use cases for recent event activations, and highlight initial lessons learned.

Disaster Response↗

NASA NTRS2018

Analyzing NASA Earth Observation Data with ArcGIS Technology

NASA satellite Earth Observation (EO) data are critical to a wide range of GIS research and applications. Yet the EO data are usually very complex in terms of science contents, formats, and spatiotemporal granularities, making them difficult to use for many GIS analysts. We'll show in this presentation how to easily obtain and analyze NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) EO data through ArcGIS's data/image services and Web GIS capabilities.

earth observation↗

NASA NTRS2000

EOSDIS: Archive and Distribution Systems in the Year 2000

Earth Science Enterprise (ESE) is a long-term NASA research mission to study the processes leading to global climate change. The Earth Observing System (EOS) is a NASA campaign of satellite observatories that are a major component of ESE. The EOS Data and Information System (EOSDIS) is another component of ESE that will provide the Earth science community with easy, affordable, and reliable access to Earth science data. EOSDIS is a distributed system, with major facilities at seven Distributed Active Archive Centers (DAACs) located throughout the United States. The EOSDIS software architecture is being designed to receive, process, and archive several terabytes of science data on a daily basis. Thousands of science users and perhaps several hundred thousands of non-science users are expected to access the system. The first major set of data to be archived in the EOSDIS is from Landsat-7. Another EOS satellite, Terra, was launched on December 18, 1999. With the Terra launch, the EOSDIS will be required to support approximately one terabyte of data into and out of the archives per day. Since EOS is a multi-mission program, including the launch of more satellites and many other missions, the role of the archive systems becomes larger and more critical. In 1995, at the fourth convening of NASA Mass Storage Systems and Technologies Conference, the development plans for the EOSDIS information system and archive were described. Five years later, many changes have occurred in the effort to field an operational system. It is interesting to reflect on some of the changes driving the archive technology and system development for EOSDIS. This paper principally describes the Data Server subsystem including how the other subsystems access the archive, the nature of the data repository, and the mass-storage I/O management. The paper reviews the system architecture (both hardware and software) of the basic components of the archive. It discusses the operations concept, code development, and testing phase of the system. Finally, it describes the future plans for the archive.

Behnke, Jeanne↗

NASA NTRS2007

Understanding Local Structure Globally in Earth Science Remote Sensing Data Sets

Empirical probability distributions derived from the data are the signatures of physical processes generating the data. Distributions defined on different space-time windows can be compared and differences or changes can be attributed to physical processes. This presentation discusses on ways to reduce remote sensing data in a way that preserves information, focusing on the rate-distortion theory and using the entropy-constrained vector quantization algorithm.

massive data sets↗

NASA NTRS2014

Constructing Data Albums for Significant Severe Weather Events

There is need in the research community for weather-related case studies to improve prediction of and recovery after convective thunderstorms that produce damaging winds, hail, and tornadoes. One of the largest continuing challenges in any Earth Science investigation is the discovery of and access to useful science content from the increasingly large volumes of available Earth Science data. The Information Technology and Systems Center at the University of Alabama in Huntsville has developed a software system called Noesis 2.0 that can be used to produce Data Albums for weather events relevant to NASA Earth Science researchers. Noesis is an Internet search tool that combines relevant storm research, pictures and videos of an event or event aftermath, web pages containing news reports and official storm summaries, background information about damage, injuries, and deaths, and NASA datasets from field campaigns and satellites into a "one-stop shop" database. The Data Album concept has been previously applied to hurricane cases from 2010 to present. The objective of this paper is to extend that Hurricane Data Album concept to focus on development of an ontology for significant severe weather to aid in selecting appropriate NASA datasets for inclusion in a severe weather Data Album. Recent severe weather events in Moore and El Reno, Oklahoma will be analyzed as an example of how these events can be incorporated into a Data Album.

Greene, Ethan↗

NASA NTRS2013

Visualization and Analysis of Multi-scale Land Surface Products via Giovanni Portals

Large volumes of MODIS land data products at multiple spatial resolutions have been integrated into the Giovanni online analysis system to support studies on land cover and land use changes,focused on the Northern Eurasia and Monsoon Asia regions through the LCLUC program. Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) is a Web-based application developed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), providing a simple and intuitive way to visualize, analyze, and access Earth science remotely-sensed and modeled data.Customized Giovanni Web portals (Giovanni-NEESPI andGiovanni-MAIRS) have been created to integrate land, atmospheric,cryospheric, and societal products, enabling researchers to do quick exploration and basic analyses of land surface changes, and their relationships to climate, at global and regional scales. This presentation shows a sample Giovanni portal page, lists selected data products in the system, and illustrates potential analyses with imagesand time-series at global and regional scales, focusing on climatology and anomaly analysis. More information is available at the GES DISCMAIRS data support project portal: http:disc.sci.gsfc.nasa.govmairs.

Shen, Suhung↗

NASA NTRS2001

Syntactic and Semantic Validation without a Metadata Management System

The ability to maintain quality information is essential to securing the confidence in any system for which the information serves as a data source. NASA's Global Change Master Directory (GCMD), an online Earth science data locator, holds over 9000 data set descriptions and is in a constant state of flux as metadata are created and updated on a daily basis. In such a system, the importance of maintaining the consistency and integrity of these-metadata is crucial. The GCMD has developed a metadata management system utilizing XML, controlled vocabulary, and Java technologies to ensure the metadata not only adhere to valid syntax, but also exhibit proper semantics.

Pollack, Janine↗

NASA NTRS2008

Customer-oriented Data Formats and Services for Global Land Data Assimilation System (GLDAS) Products at the NASA GES DISC

The Global Land Data Assimilation System (GLDAS) is generating a series of land surface state (e.g., soil moisture and surface temperature) and flux (e.g., evaporation and sensible heat flux) products simulated by four land surface Models (CLM, Mosaic, Noah and VIC). These products are now accessible at the Hydrology Data and Information Services Center (HDISC), a component of NASA Goddard Earth Sciences Data and Information Services Center (GESDISC).

Fang, Hongliang↗