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North American Land Data Assimilation (NLDAS) Data and Services at NASA GES DISC

The North American Land Data Assimilation System (NLDAS, https://ldas.gsfc.nasa.gov/nldas) integrates a large quantity of observation-based and model reanalysis data to drive offline (not coupled to the atmosphere) land surface models (LSMs) to produce fields of soil moisture, snow, and surface fluxes. The NLDAS-2 data sets currently archived at, and distributed by, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC, https://disc.gsfc.nasa.gov) have been updated to NLDAS Version 2.0 (NLDAS-2.0). This presentation provides an overview of the updated NLDAS-2.0 data at NASA GES DISC and discusses the methods for the public to access the data as well as the data services available.

Ashley Heath↗

Listening to the user: A case study

The managers of the NASA Scientific and Technical Information System consistently maintain that whatever scientific and technical information services and products are provided must be geared primarily to user needs and not simply system compatibility and convenience. A system evaluation study begun in 1973 and continued to the present is described. The thrust of this on-going examination is to regularly evaluate the usefulness of the present information system to those it is intended to serve, engineers and scientists working in their professional roles, and to identify areas and ways in which the system can be made more responsive to user needs. Techniques used have covered the range from personal, in-depth interviews to widely distributed questionnaires. The findings have been positive. Many refinements made to on-going programs and projects and new endeavors begun in direct response to stated user needs are discussed. In the main these needs are not unreasonable and thus can be responded to with cost effective system modifications.

Pryor, H. E.↗

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↗

Improving Earth Science Dataset Search with Publication

The NASA Goddard Earth Sciences Data and Information Services Center (GESDISC) archives a large number of Earth observational datasets. Thousands of the publications are created each year based on these datasets. The content of these publications can be used for discovery of the datasets based on the characteristics of applicational research. We leverage the content of these publications to retrieve the information about phenomena and domains where measurements from the datasets were utilized through linking these publications and dataset in Knowledge Graph. We retrieve phenomena and domain information using SWEET ontology and produce the set of keywords that are linked to the datasets. Further, we evaluate this link strength according to the frequency of dataset usage in the papers mentioning these keywords. We demonstrate how this linkage can improve dataset search by comparing the search results obtained from Common Metadata Repository (CMR) search and the publications based data.

Kristina Stoyanova↗

GPM, TRMM, and Other Global Precipitation Products and Services at NASA GES DISC

Precipitation is a key environmental variable. For example, in agriculture, precipitation, temperature, water (soil moisture), solar radiation, NDVI, etc., are key variables.Rainfed agriculture – major farming practices that rely on rainfall for water.Rainfed agriculture: >95% of farmed land (sub-Saharan Africa); 90% (Latin America); 75% (Near East and North Africa); 65% (East Asia); 60% (South Asia).Droughts and floods can cause severe crop loss. The Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA data centers, is located in Greenbelt, Maryland, USA. The NASA GES DISC is a major data archive center for global precipitation, water & energy cycles, atmospheric composition, and climate variability.

Liu, Z.↗

Making NASA GES DISC Level 2 Data GIS Analysis Ready

There are many valuable data hosted by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for GIS applications in the areas of extreme weather events, climatic anomaly, and public health. However, using NASA Earth Science Data poses some challenges for GIS users. Many of these users are not experts in Earth Observation and have little knowledge about NASA's Earth science data. In the GIS community, GeoTiff is the most widely used raster format, whereas NASA's data is primarily in complex multidimensional netCDF and HDF formats. This complexity makes it difficult for GIS users, especially those who are unfamiliar with these formats. Although GIS software like ArcGIS has made progress in processing multidimensional netCDF data, certain issues still remain, particularly with level 2 data. In this study, we use TROPSpheric Monitoring instrument (TROPOMI) level 2 data as an example to demonstrate how to make such data GIS analysis ready. The process involves: 1. Creating a feature layer from the TROPOMI level 2 data. 2. Converting the feature layer to a gridded raster dataset. 3. Mosaicking gridded raster datasets into a raster dataset covering the entire desired extent. 4. Generating a symbology with a GIBS-specific style that aligns with the visual standards and requirements of GIBS. 5. Publishing image services. By performing these preprocessing and transformation steps, NASA level 2 data can be made compatible and ready for use within GIS software for various spatial analysis and visualization tasks.

Geographic Information System↗

An Oveview of TROPESS Data Products and Services at the NASA GES DISC

The TRopospheric Ozone and Precursors from Earth System Sounding (TROPESS) project generates Earth System Data Records (ESDRs) of ozone, and other atmospheric constituents (CH4,CO, H2O, HDO, NH3, PAN and temperature) by processing data from multiple satellites through a common retrieval algorithm and ground data system. Satellite Level-1B input data used in generating the TROPESS L2 data products include CrIS NOAA-20 (JPSS-1), CrIS SNPP, AIRS Aqua, OMI Aura, and TROPOMI S5P. The common retrieval framework is known as the MUlti-SpEctra, MUlti-SpEcies, Multi-SEnsors (MUSES) science data processing system (MUSES-SDPS). Several of the TROPESS data products are now available from the NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) for users to download. In this presentation we provide an overview of the various TROPESS data products. These data products can be divided into the following Forward Stream types: Standard Products, Summary Products, and Full-Archival Products. Standard Products are for users that are doing full analysis with avenging kernel and covariance corresponding to retrieved vertical profiles. Summary products have a smaller file size and are more convenient for first-look and rapid analysis, include total and partial columns, as well as column averaging kernels. The Full-Archival Products will contain all information used in creating the data. TROPESS also creates Special Products, provided on an as-needed and as-available basis to support NASA field missions and individual-investigator requests over specific regions. Eventually, TROPESS will also produce and deliver a set of Reanalysis Stream products. Data at the GES DISC are being transitioned into the "Cloud". This will allow users with "Cloud” access to perform data analysis directly on the data without downloading the data to their system. Services, such as subsetting and data visualization, will also be provided for TROPESS data products at the GES DISC.

James Johnson↗

Satellite and Reanalysis Air Quality Data and Services at NASA GES DISC for Public Health Study

Outbreaks of infectious diseases and health can be influenced by airborne and water-borne pollutants. Furthermore, air and water quality are associated with climate variability, industrialization, land use and land cover change, and water resource management. It is therefore crucial to understand environment-disease connections with existing long-term observed and modeled data, particularly for development of early warning systems for infectious disease outbreaks. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) (https://disc.gsfc.nasa.gov) archives large volumes of global environment data that are useful for research and applications regarding environmental factors and public health. Examples of air quality measurements are: Daily satellite remotely sensed data, including Aerosol Index (AI), O3, SO2, CO, and NO2 from Aura/OMI (October 2014 to present), and OMPS-NPP (January 2012 to present, currently research data products only) Hourly and monthly reanalysis modeled data, including PM2.5, O3, CO, SO2, BC, dust, AOD, and aerosol types from MERRA-2 (January 1980 to present) Examples of surface meteorology and land surface measurements are: hourly, daily, and monthly satellite precipitation from TRMM (December 1997 to March 2015) 30-minute and monthly satellite precipitation from GPM (March 2014 to present); Hourly and monthly modeled surface meteorology and land surface condition from MERRA-2 (January 1980 to present) and land surface assimilation models (January 1948 to present), including precipitation, surface temperature, relative humidity, wind, and soil moisture.This presentation will give an overview of relevant environmental data at the NASA GES DISC. Through a number of use cases, such as dust events and active fires, we will introduce data services that assist in finding the right data, enable visualization and analysis of the data online, and allow downloading of data in user-preferred format.

remote sensing data↗

NASA GES DISC DAAC Satellite Data for GIS

NASA's Goddard Earth Science (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC) makes available a large and continually growing collection of spatially continuous global satellite observations of environmental parameters. These products include those from the MODIS (Moderate Resolution Imaging Spectroradiometer) on both Terra and Aqua platforms, and the Tropical Rainfall Measuring Mission (TRMM). These data products are well suited for use within Geographic Information Systems (GIS), as both backdrops to cartographic products as well as spatial analysis. However, data format, file size, and other issues have limited their widespread use by traditional GIS users. To address these data usability issues, the GES DISC DAAC recently updated tools and improved documentation of conversion procedures. In addition, the GES DISC DAAC has also been working with a major GIS software vendor to incorporate the ability to read the native Hierarchial Data Format (HDF), the format in which most of the NASA data is stored. The result is the enabling of GIS users to realize the benefit of GES DISC DAAC data without a substantial expenditure in resources to incorporate these data into their GIS. Several documents regarding the potential uses of GES DISC DAAC satellite data in GIS have recently been created. These show the combinations of concurrent data from different satellite products with traditional GIS vector products for given geographic areas. These map products include satellite imagery of Hurricane Isabel and the California wildfires, and can be viewed at http://daac.gsfc.nasa.gov/MODIS/GIS/.

Nickless, Darryl↗

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗

Harmonizing Multi-Disciplinary Data for Applied Research: A Comprehensive Analysis of GES DISC Datasets through NLP and TF-IDF Techniques

Data centers distribute data encompassing multiple disciplines, making it necessary to evaluate dataset applicability to applied research. Typically, these datasets are generated by specialized science teams and consist of single-discipline data, such as atmospheric temperature, pressure, and precipitation, leading to unique dataset formats and access services. However, in applied research, the utilization of datasets from multiple disciplines is commonly necessary. The increasing availability of research literature citing Earth Science datasets presents an opportunity to analyze the usage of datasets in multi-disciplinary research. This study proposes a novel approach wherein research publications citing datasets archived at the GES DISC (Goddard Earth Sciences Data and Information Services Center) are collected, and each publication is associated with specific research topics through the application of Natural Language Processing (NLP), using the Term Frequency Inverse Document Frequency (TF-IDF) technique on the publication titles and abstracts. Through this analysis, we gain insights into the distribution of dataset disciplines as they are being used in various applied research areas. This knowledge is essential for the development of dataset tools and services tailored to effectively support applied research studies, as it enhances a data center's comprehension of how datasets from multiple disciplines are integrated into research endeavors.

Infometrics↗

The value of volume and growth measurements in timber sales management of the National Forests

This paper summarizes work performed in the estimation of gross social value of timber volume and growth rate information used in making regional harvest decisions in the National Forest System. A model was developed to permit parametric analysis. The problem is formulated as one of finding optimal inventory holding patterns. Public timber management differs from other inventory holding problems in that the inventory, itself, generates value over time in providing recreational, aesthetic and environmental goods. 'Nontimber' demand estimates are inferred from past Forest Service harvest and sales levels. The solution requires a description of the harvest rates which maintain the optimum inventory level. Gross benefits of the Landsat systems are estimated by comparison with Forest Service information gathering models. Gross annual benefits are estimated to be $5.9 million for the MSS system and $7.2 million for the TM system.

Lietzke, K. R.↗

Tropical Rainfall Measuring Mission (TRMM) Precipitation Data and Services for Research and Applications

Precipitation is a critical component of the Earth's hydrological cycle. Launched on 27 November 1997, TRMM is a joint U.S.-Japan satellite mission to provide the first detailed and comprehensive data set of the four-dimensional distribution of rainfall and latent heating over vastly under-sampled tropical and subtropical oceans and continents (40 S - 40 N). Over the past 14 years, TRMM has been a major data source for meteorological, hydrological and other research and application activities around the world. The purpose of this short article is to inform that the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides TRMM archive and near-real-time precipitation data sets and services for research and applications. TRMM data consist of orbital data from TRMM instruments at the sensor s resolution, gridded data at a range of spatial and temporal resolutions, subsets, ground-based instrument data, and ancillary data. Data analysis, display, and delivery are facilitated by the following services: (1) Mirador (data search and access); (2) TOVAS (TRMM Online Visualization and Analysis System); (3) OPeNDAP (Open-source Project for a Network Data Access Protocol); (4) GrADS Data Server (GDS); and (5) Open Geospatial Consortium (OGC) Web Map Service (WMS) for the GIS community. Precipitation data application services are available to support a wide variety of applications around the world. Future plans include enhanced and new services to address data related issues from the user community. Meanwhile, the GES DISC is preparing for the Global Precipitation Measurement (GPM) mission which is scheduled for launch in 2014.

Liu, Zhong↗

Development of Web Mapping Service Capabilities to Support NASA Disasters Applications/App Development

During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short‐term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end‐user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.

Burks, Jason E.↗

Development of Web Mapping Service Capabilities to Support NASA Disasters Applications / App Development

During the last year several significant disasters have occurred such as Superstorm Sandy on the East coast of the United States, and Typhoon Bopha in the Phillipines, along with several others. In support of these disasters NASA's Short‐term Prediction Research and Transition (SPoRT) Center delivered various products derived from satellite imagery to help in the assessment of damage and recovery of the affected areas. To better support the decision makers responding to the disasters SPoRT quickly developed several solutions to provide the data using open Geographical Information Service (GIS) formats. Providing the data in open GIS standard formats allowed the end user to easily integrate the data into existing Decision Support Systems (DSS). Both Tile Mapping Service (TMS) and Web Mapping Service (WMS) were leveraged to quickly provide the data to the end‐user. Development of the deliver methodology allowed quick response to rapidly developing disasters and enabled NASA SPoRT to bring science data to decision makers in a successful research to operations transition.

Burks, Jason E.↗

NASA Earth Sciences Data Support System and Services for the Northern Eurasia Earth Science Partnership Initiative

The presentation describes the recently awarded ACCESS project to provide data management of NASA remote sensing data for the Northern Eurasia Earth Science Partnership Initiative (NEESPI). The project targets integration of remote sensing data from MODIS, and other NASA instruments on board US-satellites (with potential expansion to data from non-US satellites), customized data products from climatology data sets (e.g., ISCCP, ISLSCP) and model data (e.g., NCEP/NCAR) into a single, well-architected data management system. It will utilize two existing components developed by the Goddard Earth Sciences Data & Information Services Center (GES DISC) at the NASA Goddard Space Flight Center: (1) online archiving and distribution system, that allows collection, processing and ingest of data from various sources into the online archive, and (2) user-friendly intelligent web-based online visualization and analysis system, also known as Giovanni. The former includes various kinds of data preparation for seamless interoperability between measurements by different instruments. The latter provides convenient access to various geophysical parameters measured in the Northern Eurasia region without any need to learn complicated remote sensing data formats, or retrieve and process large volumes of NASA data. Initial implementation of this data management system will concentrate on atmospheric data and surface data aggregated to coarse resolution to support collaborative environment and climate change studies and modeling, while at later stages, data from NASA and non-NASA satellites at higher resolution will be integrated into the system.

Leptoukh, Gregory↗

Open Science Approach to Analyze Climate-Crop Relationships in the US Leveraging GES DISC and Galaxy Workflows

Understanding the intricate relationship between climate variability and agricultural production is crucial for ensuring food security. This study investigates the impact of climate parameters, such as temperature, precipitation, and soil moisture, on major US crop yields. Adopting an open science approach, the study analyzes the impact of climate on agricultural production in the United States. The Galaxy workflow engine serves as the primary tool for integrating climate data from the Goddard Earth Sciences Data and Information Services Center (GES DISC), retrieved via the Giovanni system, with yield statistics from the United States Department of Agriculture’s National Agricultural Statistics Service (USDA NASS). Extensions for reading, preprocessing, and analyzing external data have been developed, enabling the creation of workflows within the Galaxy platform. The development of a reproducible workflow allows for the calculation of seasonal climate averages, which are then assessed for their correlation with crop yields. This methodology ensures the replicability of the research, promoting transparency and collaboration in the scientific community. Correlational and regression analyses have been applied to different sub-zones and crops. The findings from this research offer valuable insights into the relationship between climate parameters and crop yields. These insights contribute to a deeper understanding of climate-crop relationships, providing a solid foundation for informed decision-making in the agricultural sector. The high correlation values indicate a significant relationship between climate parameters and crop yields, underscoring the importance of considering climate factors in agricultural planning and policymaking. This research also exemplifies the power of open science in advancing our understanding of complex environmental and agricultural phenomena. By leveraging open data and services, it provides a robust and replicable framework for future studies in this critical field.

Open science↗

Integrating Gridded NASA Hydrological Data into CUAHSI HIS

The amount of hydrological data available from NASA remote sensing and modeling systems is vast and ever-increasing;but, one challenge persists:increasing the usefulness of these data for, and thus their use by, end user communities. The Hydrology Data and Information Services Center (HDISC), part of the Goddard Earth Sciences DISC, has continually worked to better understand the hydrological data needs of different end users, to thus better able to bridge the gap between NASA data and end user communities. One effective strategy is integrating the data in to end user community tools and environments. There is an ongoing collaborative effort between NASA HDISC, NASA Hydrological Sciences Branch, and CUAHSI to integrate NASA gridded hydrology data in to the CUAHSI Hydrologic Information System (HIS).

Rui, Hualan↗