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NASA NTRSDate not supplied

Publishing Variables Archived at GES DISC to Earth System Grid Federation (ESGF)

We present a straightforward and low-cost approach to publish variables archived at NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) to the Earth System Grid Federation (ESGF). An ESGF publication requires a single standard-name variable aggregated over time to facilitate data inter-comparison. It also contains significant metadata to enable searching in ESGF. We look up standard names on high demand in ESGF search history, and using OPeNDAP and NcML technologies we aggregate the corresponding variables available in the GES DISC archive with augmented metadata required by CMIP6 and obs4MIPs Data Specification version 2.1. At this writing 10 variables from a standard product of the Atmospheric Infrared Sounder along with the Tech Notes are published in ESGF by NASA Center for Climate Simulation (NCCS). Users can view, analyze, and subset remotely, and download these aggregated variables via links in any ESGF node after searching. We plan to work on and publish more variables and data from different NASA missions and experiments in our archive.

Fan Fang↗
NASA NTRSDate not supplied

"Giovanni at 20: Consistency and Persistency in Making Earth Remote Sensing Data Available (and Useful) to the Earth Science Community"

Since its creation in the year 2000, the NASA Geospatial Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) has been an exemplar of how to provide remotely-sensed satellite data and related Earth science datasets to a broad and globally diverse researcher community. One of the hallmarks of Giovanni system usage is that it is common to see practitioners of many branches of science – particularly those in fields not traditionally associated with remote-sensing data, such as animal behavior and paleooceanography – both accessing and employing datasets which the system provides. This usage pattern is attested to by the diversity of published science citing Giovanni. Giovanni has evolved through several versions, each of which increased analytical and visualization options while also enhancing ease-of-use. Information resources supporting Giovanni from the Goddard Earth Sciences Data and Information Services Center (GES DISC), which hosts the system, start with basic mapping and plotting functions and extend to “How-to” recipes demonstrating interusability with other data analysis systems and software. Giovanni is now being developed for use in a cloud environment, potentially expanding datasets the system can be applied to, and also improving performance for data having high spatial and temporal resolution. This presentation covers the system’s historical success with interesting examples of Giovanni-citing research, and will apply its current capabilities to a multi-dataset examination of derecho events associated with mesoscale convective phenomena in the summer of 2020, indicating how Giovanni is prepared for ongoing support of Earth science in a changing world.

Giovanni Derecho visualization↗
NASA NTRSDate not supplied

Atmospheric Infrared Sounder Version 7 Near-Real-Time Product and Imagery Released by NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of data processing, archive, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002. The GES DISC provides service to both AIRS routine and Near Real-Time (NRT) products. The AIRS NRT products are an important element in the Land, Atmosphere Near real-time Capability for EOS (LANCE). In collaboration with AIRS Project, the GES DISC has just released products from the Version 7 algorithm. The new version algorithm provides significant improvements over the previous version. The most substantial advances are: improved consistency between day and night water vapor; improved total column ozone and temperature; improved infrared-only (IR-only) retrievals, especially in high latitude regions; an improved Stochastic Cloud Clearing Neural Network used as a first guess at the initial value in the iterative retrieval process; and removal of ambiguity in surface classification in the IR-only retrieval algorithm. In addition, the GES DISC produces AIRS NRT imagery. The AIRS NRT imagery are generated by mosaicking and mapping the available AIRS 6-minute retrieval granules to a global projection. The images are constantly refreshed when new granules are produced. The AIRS NRT Viewer and LANCE Worldview provide visualization services to online users for AIRS NRT imagery. The data products used to generate this imagery include atmospheric temperature, humidity, precipitation, cloud, Dust Score, CO, and SO2. In this presentation, we will demonstrate visualization of the AIRS NRT imagery from the new Version 7, and demonstrate some improvements over the previous version. Progress on improving the AIRS NRT imagery, a collaboration project with the AIRS Applications Development Team at NASA Jet Propulsion Laboratory (JPL), will also be presented.

Feng Ding↗
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 NTRS2021

PBL Height from AIRS, GPS RO, and MERRA-2 Products in NASA GES DISC and Their 10 Year Seasonal Mean Intercomparison

Within the planetary boundary layer (PBL), surface forcing response, drag, turbulence, and vertical mixing are important processes and play a more critical role here than in the overlying “free atmosphere”. The PBL Height (PBLH) is an important parameter in climate models, weather forecasts, and air quality prediction. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides data processing, archiving, and distribution services for numerous Earth science products. PBLH is a parameter in three products served by GES DISC, which are from the Atmospheric Infrared Sounder (AIRS), the Global Positioning System (GPS) radio occultation (RO) experiment, and the NASA reanalysis product Modern-Era Retrospective analysis for Research and Applications – 2 (MERRA-2). These products have different spatial and temporal resolutions and coverages, and their PBLH definitions are also different. To better serve the PBL research community, we have summarized the specifications of these products. A ten-year seasonal mean intercomparison is also conducted to provide further guidance to users. The intercomparison results show that MERRA-2 has a much shallower PBL than AIRS and GPS RO. An experimental study indicates the different PBLH definition in MERRA-2 caused smaller values of PBLH. The improvement of the water vapor retrieval in AIRS version 7 over version 6 results in the version 7 PBLH agreeing better with GPS RO and MERRA-2 than version 6, especially near the equator and low latitudes.

Feng Ding↗
NASA NTRSDate not supplied

NASA's Earthdata Forum: Bringing the Science Community Together

The Earthdata Forum is an actively maintained and operational user forum for all participating NASA EOSDIS Distributed Active Archive Centers (DAACs) and GCMD. The Forum serves as a cross-DAAC platform from which user communities can obtain authoritative information relating to NASA Earth Science. The Atmospheric Science Data Center (ASDC) DAAC takes on the role of both Project Manager and Hosting Organization. As Project Manager, the ASDC leads and facilitates the project's efforts. The Forum launched February 2020 with five participating DAACs: Atmospheric Science Data Center (ASDC), Crustal Dynamics Data Information System (CDDIS), Goddard Earth Science Data and Information Services Center (GES DISC), Global Hydrology Resource Center (GHRC), and Land Processes DAAC (LP DAAC). Since February 2020, the of Level 1 and Atmosphere Archive and Distribution System DAAC (LAADS), the Ocean Biology DAAC (OBDAAC) and Global Change Master Directory (GCMD) have also joined the Forum. The Forum assumes both a proactive and reactive approach to NASA products scientific queries, allowing the scientific community to ask questions about NASA's products, tools, and services and receive announcements and news regarding products, new data releases, and such. In this presentation, we will describe the Earthdata Forum approach to support the scientific community in detail and discuss the successes and challenges of this approach.

Ingrid Garcia-Solera↗
NASA NTRSDate not supplied

Integrating Multi-agency Data Products in a Cloud-based Platform for Streamlined Discovery, Visualization, and Use

Earth science data users almost always have an interest in utilizing geospatial data from multiple agencies. As computing capability and cloud-based infrastructures accelerate the pace at which scientific research can be done, there is a growing need to enable search, discovery, and use of multi-agency geospatial observations relevant for a common use case - without undergoing the search and discovery process in a less efficient, disparate path with each agency. NASA’s Earth Observing System Data and Information System (EOSDIS) and NOAA’s National Environmental Satellite, Data and Information Service (NESDIS) both support a wide range of Earth science disciplines’ research, operations, and applications activities. Presently, however, there are few examples of data discovery frameworks supporting an inquiry of both NASA’s and NOAA’s extensive archives of Earth observations that are equally suitable for a particular science scenario, regardless of the agency that “owns” the data. NASA and NOAA are collaborating on a data expedition platform for exploring fire weather using data products from both agencies. Users will be able to search, discover, and visualize NASA and NOAA products in one interface. Each agency will curate metadata for its respective datasets, providing for a rich search experience. The collaboration will pilot a shared search interface into these metadata datastores. Data products will be stored in the cloud in cloud-optimized format(s). These formats will allow for optimized data access and visualization to support the “data expedition”. Avenues for further development and application of this cloud-based, multi-agency data provisioning platform will also be discussed.

cloud-based technology↗
NASA NTRSDate not supplied

Senteniel-6 Radio Occultation Product Released by NASA GES DISC to Supplement Satellite Remote Sensing Datasets for PBL Study

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) curates hyperspectral atmospheric sounder remote sensing and numerical model reanalysis datasets which have been utilized in the Planetary Boundary Layer (PBL) research and applications. The hyperspectral sounder remote-sensing datasets include the Atmospheric Infrared Sounder (AIRS) on the Aqua satellite to the Cross-track Infrared Sounder (CrIS) on Suomi--National Polar- orbiting Partnership (NPP) and National Oceanic and Atmospheric Administration -20 (N NOAA-20)/ Joint Polar-orbiting Satellite System -1 (JPSS-1). The Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) global reanalysis product provides a data record commencing in 1980. The sounder remote sensing and reanalysis datasets include temperature, water vapor, and trace gas profile down to the PBL, and also have a derived PBL height as well. A nearly 10-year (June 2006 to December 2015) seasonal and annual PBL height climatology dataset from COSMIC Global Navigation Satellite System (GNSS) radio occultation (RO) measurement is also available from the GES DISC. In collaboration with Sentinel-6 Project, the GES DISC is implementing curation activities for GNSS RO products from the Sentinel-6A/Sentinel-6 Michael Freilich satellite launched on November 21, 2020. Sentinel-6A RO products provide refractivity, temperature, and humidity profile with finer vertical resolution, leveraging PBL research and application as a supplement to the hyperspectral sounder remote sensing and reanalysis products. The public release of Sentinel- 6A RO products is scheduled for mid-October of 2021. In this presentation, we will introduce all Senitnel-6A products and services, and demonstrate use cases studying the PBL by combining these products with other GES DISC archived data products.

Feng Ding↗
NASA NTRSDate not supplied

What (and How) MERRA-2 Reanalysis Data are Used in Applied Sciences

The Modern Era Retrospective-analysis for Research and Applications, Version 2 (MERRA-2) is the global atmospheric data reanalysis for the satellite era produced by NASA’s Global Modeling and Assimilation Office (GMAO), using the Goddard Earth Observing System Model (GEOS)version 5.12.4. The data are officially distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data have been widely used by the Earth sciences and application community. Since MERRA-2 data were released in early 2016, the number of registered data users has grown steadily from 1,252 in 2016 to 6477 in 2020. By the end of October 2021, ~16 petabytes (over 360 million files) of data have been distributed to more than 18,900 users. Searching in Google Scholar (https://scholar.google.com/), we have found over 7,000 articles, published between January 2017 and May 2021, involving the use ofMERRA-2 data. The figure shows the numbers for various application areas in which theMERRA-2 data have been used, covering almost all of the application areas defined in NASA Applied Sciences (http://appliedsciences.nasa.gov). The largest number of articles are found in disaster research, with the subcategories ordered in flood, wildfires, hurricanes and cyclones, and other forms of severe weather. In this presentation, we will discuss the preliminary findings from a review of the selected literature that uses MERRA-2 data in applied sciences. The current analytic and interoperable data services at GES DISC are listed, such as the on-the-fly subset and analysis service, NASA Giovanni; THREDDS Data Server(TDS); and Python Jupyter notebooks. In addition, we will introduce two new services for supporting the open sciences: My Dashboard and Related Publications.

data management↗
NASA NTRSDate not supplied

Constructing a Knowledge Graph & Applying Graph Algorithms to Draw Insights about GES-DISC Jira Tickets

In order to assess the complexities of Jira tickets created by NASA Goddard Earth Sciences Data and Information Services Center (GES-DISC), it was beneficial to create a knowledge graph. The knowledge graph receives ticket data through the Jira API. The creation of a knowledge graph will help to answer high-level questions about internal structure, knowledge gaps, and team organization within GES-DISC. To work towards this goal, the knowledge graph was constructed in adockerizedNeo4j graph database. Once the graph had been created, graph algorithms were applied to answer high-level questions, such as exploring the role of staff in relation to projects, which qualities of a ticket contribute to the formation of communities within the graph, etc. To answer these questions, centrality and community detection algorithms were applied using Cypher querying language. The analysis of the results of the algorithms indicated that, as expected, certain individuals were more connected to some projects, while others were serving as hub nodes between two or more projects. Similarly, specific keywords are more likely to increase a Jira ticket’s centrality in the graph. In terms of community detection, when tickets in a community have certain qualities, it is more probable for them to be grouped together. To best visualize which nodes had higher centrality scores or were grouped into certain communities, interactive graphs were created in Python using Plotly and Matplotlib. Ultimately, the project was successful in creating and deploying a knowledge graph to better understand the relationships between data in GES-DISC Jira tickets

Rebecca Lipton↗
NASA NTRSDate not supplied

Hyperspectral Sounder Products: SiFSAP and ClimFiSP

Infrared hyperspectral sounders have demonstrated to provide very high value information for a range of weather and climate applications. Traditional retrieval algorithms of hyperspectral sounders use the ‘cloud clearing’ methodology in the retrieval process due to the lack of means to account for cloud scattering effect. The corresponding Level-2 data products are therefore limited by two major factors: the degradation of spatial resolution as compared with the native resolution of the instruments and the lack of ‘radiance closure’ that is critically needed for climate trend studies. The single field-of-view (FOV) sounder atmospheric products (SiFSAP) algorithm has been developed to supplement existing operational products. The SiFSAP algorithm uses the principal component based radiative transfer model (PCRTM) that is ultra-fast and has been extensively validated for the cloud scattering simulation capability. The cloud properties are physically retrieved along with profiles of temperature, moisture, and trace gases of interest, surface properties simultaneously by fitting single FOV spectral measurements. Therefore, SiFSAP ensure the radiometric consistency between the retrieved geophysical properties and the top-of-atmosphere (TOA) spectral measurements. This presentation provides a general introduction of SiFSAP and details about the physical retrieval algorithm. Also introduced here is a derivative data product of SiFSAP, the climate fingerprinting Sounder Products (ClimFiSP). ClimFiSP include the space-time averaged properties of key climate variables that are derived from the space-time averaged radiances via the spectral fingerprinting scheme. The spectral fingerprinting method allows a low latency data update on ClimFiSP following any potential calibration update on satellite measurements. ClimFiSP also include the rigorously defined uncertainty characterization for trends or anomalies of climate variables, being critical for the construction of long-term climate data record. Both SiFSAP and ClimFiSP will be available to users through NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC).

Wan Wu↗
NASA NTRSDate not supplied

Future Airspace Operations

NASA is exploring a proposed new operating mode called digital flight, a complement to VFR and IFR. Under digital flight rules, the aircraft operator would use automation, traffic awareness, information services, and cooperative practices to ensure separation from other flights in VMC and IMC. The presentation describes how digital flight safely increases airspace access and operating flexibility for qualified operators, and its harmonizing approach to emerging future operations.

Airspace↗
NASA NTRSDate not supplied

Newly Released GPCP Version 3.2 Global Precipitation Datasets at NASA GES DISC

The Global Precipitation Climatology Project (GPCP) is the precipitation component of an internationally coordinated set of (mainly) satellite-based global products dealing with the Earth's water and energy cycles, under the auspices of the Global Water and Energy Experiment (GEWEX) Data and Assessment Panel (GDAP) of the World Climate Research Program. As the follow-on to the GPCP Version 2.X products, GPCP Version 3 (GPCP V3.2) seeks to continue the production of long, homogeneous precipitation record using modern input and calibration datasets. The GPCP V3.2 provides globally complete analyses of surface precipitation on a 0.5°x 0.5° latitude/longitude grid at both monthly and daily intervals, respectively covering 1983 to the present and June 2000 to the present. New data fields have been introduced to better characterize the precipitation, particularly including an estimate of the fraction of the precipitation that is liquid (rain) in both the Monthly and Daily, and a Quality Index for the Monthly. Compared to the operational GPCP V2.3 Monthly, the V3.2 Monthly provides a more reasonable climatology in the Southern Ocean, and increases the global average precipitation by about 4.46%, which is in line with recommendations of recent assessments. However, the two versions have comparable global and regional trends for 1983-2020. Compared to the operational One-Degree Daily (Version 1.3) product, the V3.2 Daily better represents the histogram of precipitation rates, particularly at high values. In this presentation, we will present the latest GPCP V3.2 daily and monthly datasets archived and distributed at NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) along with examples from NASA Giovanni.

Precipitation↗
NASA NTRSDate not supplied

Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS) Datasets Released by NASA GES DISC and Their Applications for Air Quality

Nitrogen dioxide (NO2), a pervasive air pollutant, comes from vehicles, power plants, industrial emissions, and off-road sources such as construction or lawn and gardening equipment. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) curates many remote sensing datasets with NO2 retrievals, which have been utilized for air quality research and applications. The remotely-sensed datasets include those generated by the Ozone Monitoring Instrument (OMI) on the Aura satellite, the TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S5P), and the Ozone Mapping and Profiling Suite (OMPS) Nadir-Mapper (NM) instrument on the Suomi National Polar-orbiting Partnership (S- NPP). In collaboration with the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Multi-Decadal Nitrogen Dioxide and Derived Products from Satellites (MINDS) project, the GES DISC recently released MINDS datasets. The NASA MEaSUREs MINDS project aims to develop long-term NO2 global data records by adapting a consistent retrieval algorithm to multiple instrument measurements. Long-term data records will be achieved by applying consistent retrieval approaches to multiple satellite instruments, including OMI (2004 - ); the Global Ozone Monitoring Experiment (GOME, 1995-2011) onboard the second European Remote Sensing satellite (ERS-2); the Scanning Imaging Spectrometer for Atmospheric Cartography (SCIAMACHY, 2002-2012) onboard the ENVIronmental SATellite (ENVISAT); GOME-2 on the Meteorological Operational satellites (MetOp-A and MetOp-B, 2006 - ); and TROPOMI onboard the Copernicus S5P (2017 - ). The long-term record (1995 to present) of MINDS datasets makes them very useful for air quality trend studies. Some MINDS datasets with high spatial resolution of only a few kilometers can be used for air quality research and applications at regional scales. In this presentation, we will introduce all of the MINDS products and services, and demonstrate use cases of MINDS data for studying air quality. We will also present a few other NO2 datasets acquired from NASA’s Health and Air Quality Applied Sciences Team (HAQAST), to be archived and distributed by the GES DISC, and highlight some of their applications for air quality and health.

Feng Ding↗
NASA NTRSDate not supplied

The NASA Merra-2 Reanalysis Products: Data and Tools Used for Aerosol and Air Quality Studies

The NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) is atmospheric reanalysis data spanning 1980 to present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). MERRA-2 data includes 100 collections of Earth system variables, mainly from the atmospheric model, such as aerosol fields and meteorological fields, radiation fields, and aerosol fields, guided by the assimilation of as many as six million observations every six hours. MERRA-2 has been one of the most popular datasets from NASA and is widely used in interdisciplinary research and applications, with increasing numbers of new users. For example, at least 7000 users accessed MERRA-2 data at GES DISC in the year 2021, ~1000 more users than in the year 2020. In this presentation, we will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use a wildfire case study to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and the level 3 and level 4 subsetter, and Jupyter Python notebook. We will also update the status of cloud migration of the MERRA-2 data to Amazon Web Services (AWS).

Xiaohua Pan↗
NASA NTRSDate not supplied

Data Assimilation and Reanalysis

This presentation introduces the Data Assimilation and Reanalysis principle, then details the NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2). The MERRA-2 is atmospheric reanalysis data spanning 1980 to the present. It has been produced by the NASA Global Modeling and Assimilation Office (GMAO) and is distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In this presentation, I will introduce the MERRA-2 datasets associated with aerosol and air quality studies and use case studies to demonstrate the data tools developed at GES DISC to analyze and visualize MERRA-2 data, such as Giovanni and Jupyter Python notebook.

Xiaohua Pan↗
NASA NTRSDate not supplied

Hydrological Data at the NASA GES DISC: Current Capabilities and New Opportunities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of twelve NASA Earth science data centers that document, process, archive and distribute data from Earth observation missions and projects. GES DISC maintains an archive of several hydrology datasets, including the Land Data Assimilation Systems (LDAS) and the Gravity Recovery and Climate Experiment (GRACE) Data Assimilation for Drought Monitoring (GRACE-DA-DM) data products. These datasets include model output of heat fluxes, rain, snow, soil temperature, soil moisture, and runoff; and observational forcing data, including surface pressure, temperature, precipitation, downward shortwave and longwave radiation, humidity, and wind. The temporal resolution of the hydrology data at GES DISC ranges from hourly to monthly, and spatial resolutions range from 0.1° to 1.0°. The GES DISC provides services which enable users to aggregate, temporally and spatially subset, regrid, and visualize archived data including the GES DISC Subsetter, Hydrology Data Rods, and the Geospatial Interactive Online Visualization and Analysis Infrastructure (GIOVANNI). The Hydrology Data Rods service optimally reorganizes large hydrological data sets as extended time series, providing more efficient access for the hydrological community. The time series data (aka “data rods”) were integrated into hydrology community tools, such as the Data Rods Explorer on HydroShare. Furthermore, the GES DISC is in the process of migrating its data and services to the cloud. Hydrological data available at the GES DISC are now available in the Amazon Web Services (AWS) cloud (us-west-2 region) providing users Direct S3 data access and the capability for cloud computing operations. In this presentation, the hydrology data products and services currently available at the GES DISC will be summarized. Also discussed are the migration to the cloud, user support through this transition, and the status of migrating the data rods service to the cloud.

Ashley Heath↗
NASA NTRSDate not supplied

How GES DISC is Opening Doors to Open Science

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is one of 12 NASA Earth Observing System data centers that document, process, archive, and distribute data from Earth science missions and related projects. GES DISC hosts numerous Earth Science products through various data formats and supports their access with several programming and website tools. The User Needs team at GES DISC is responsible for producing tutorials and resources to teach these tools, collecting and engaging with user feedback, and collaborating with other NASA data centers to enable science creation for everyone. This poster presentation outlines how GES DISC, and the User Needs team, are committed to enabling open science.

Christopher Battisto↗