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NASA NTRS2015

Explore GPM IMERG and Other Global Precipitation Products with GES DISC GIOVANNI

New features and capabilities in the newly released GIOVANNI allow exploring GPM IMERG (Integrated Multi-satelliE Retrievals for GPM) Early, Late and Final Run global half-hourly and monthly precipitation products as well as other precipitation products distributed by the GES DISC such as TRMM Multi-Satellite Precipitation Analysis (TMPA), MERRA (Modern Era Retrospective-Analysis for Research and Applications), NLDAS (North American Land Data Assimilation Systems), GLDAS (Global Land Data Assimilation Systems), etc. GIOVANNI is a web-based tool developed by the GES DISC (Goddard Earth Sciences and Data Information Services Center) to visualize and analyze Earth science data without having to download data and software. The new interface in GIOVANNI allows searching and filtering precipitation products from different NASA missions and projects and expands the capabilities to inter-compare different precipitation products in one interface. Knowing differences in precipitation products is important to identify issues in retrieval algorithms, biases, uncertainties, etc. Due to different formats, data structures, units and so on, it is not easy to inter-compare precipitation products. Newly added features and capabilities (unit conversion, regridding, etc.) in GIOVANNI make inter-comparisons possible. In this presentation, we will describe these new features and capabilities along with examples.

Giovanni↗
NASA NTRS2014

Open Source GIS Connectors to NASA GES DISC Satellite Data

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) houses a suite of high spatiotemporal resolution GIS data including satellite-derived and modeled precipitation, air quality, and land surface parameter data. The data are valuable to various GIS research and applications at regional, continental, and global scales. On the other hand, many GIS users, especially those from the ArcGIS community, have difficulties in obtaining, importing, and using our data due to factors such as the variety of data products, the complexity of satellite remote sensing data, and the data encoding formats. We introduce a simple open source ArcGIS data connector that significantly simplifies the access and use of GES DISC data in ArcGIS.

user↗
NASA NTRS2014

Data Preservation, Information Preservation, and Lifecyle of Information Management at NASA GES DISC

Data lifecycle management awareness is common today; planners are more likely to consider lifecycle issues at mission start. NASA remote sensing missions are typically subject to life cycle management plans of the Distributed Active Archive Center (DAAC), and NASA invests in these national centers for the long-term safeguarding and benefit of future generations. As stewards of older missions, it is incumbent upon us to ensure that a comprehensive enough set of information is being preserved to prevent the risk for information loss. This risk is greater when the original data experts have moved on or are no longer available. Preservation of items like documentation related to processing algorithms, pre-flight calibration data, or input-output configuration parameters used in product generation, are examples of digital artifacts that are sometimes not fully preserved. This is the grey area of information preservation; the importance of these items is not always clear and requires careful consideration. Missing important metadata about intermediate steps used to derive a product could lead to serious challenges in the reproducibility of results or conclusions. Organizations are rapidly recognizing that the focus of life-cycle preservation needs to be enlarged from the strict raw data to the more encompassing arena of information lifecycle management. By understanding what constitutes information, and the complexities involved, we are better equipped to deliver longer lasting value about the original data and derived knowledge (information) from them. The NASA Earth Science Data Preservation Content Specification is an attempt to define the content necessary for long-term preservation. It requires new lifecycle infrastructure approach along with content repositories to accommodate artifacts other than just raw data. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) setup an open-source Preservation System capable of long-term archive of digital content to augment its raw data holding. This repository is being used for such missions as HIRDLS, UARS, TOMS, OMI, among others. We will provide a status of this implementation; report on challenges, lessons learned, and detail our plans for future evolution to include other missions and services.

data management↗
NASA NTRS2016

Exploring Climatology and Long-Term Variations of Aerosols from NASA Reanalysis MERRA-2 with Giovanni

Dust plays important roles in energy cycle and climate variations. The dust deposition is the major source of iron in the open ocean, which is an essential micronutrient for phytoplankton growth and therefore may influence the ocean uptake of atmospheric CO2. Mineral dust can also act as fertilizer for forests over long time periods. Over 35 years of simulated global aerosol products from NASA atmospheric reanalysis, second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) are available from NASA Goddard Earth Science Data and Information Services Center (GES DISC). The MERRA-2 covers the period 1980-present, continuing as an ongoing climate analysis. Aerosol assimilation is included throughout the period, using MODIS, MISR, AERONET, and AVHRR (in the pre-EOS period). The aerosols are assimilated by using MERRA-2 aerosol model, which interact directly with the radiation parameterization, and radiatively coupled with atmospheric model dynamics in the Goddard Earth Observing System Model, Version 5 (GEOS-5). Dust deposition data along with other major aerosol compositions (e.g. black carbon, sea salt, and sulfate, etc.) are simulated as dry and wet deposition, respectively. The hourly and monthly data are available at spatial resolution of 0.5ox0.625o (latitude x longitude). Quick data exploration of climatology and interannual variations of MERRA-2 aerosol can be done through the online visualization and analysis tool, Giovanni. This presentation, using dust deposition as an example, demonstrates a number of MERRA-2 data services at GES DISC. Global distributions of dust depositions, and their seasonal and inter-annual variations are investigated from MERRA-2 monthly aerosol products.

data services↗
NASA NTRS2016

National Climate Assessment - Land Data Assimilation System (NCA-LDAS) Data at NASA GES DISC

As part of NASA's active participation in the Interagency National Climate Assessment (NCA) program, the Goddard Space Flight Center's Hydrological Sciences Laboratory (HSL) is supporting an Integrated Terrestrial Water Analysis, by using NASA's Land Information System (LIS) and Land Data Assimilation System (LDAS) capabilities. To maximize the benefit of the NCA-LDAS, on completion of planned model runs and uncertainty analysis, NASA will provide open access to all NCA-LDAS components, including input data, output fields, and indicator data, to other NCA-teams and the general public. The NCA-LDAS data will be archived at the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) and can be accessed via direct ftp, THREDDS, Mirador search and download, and Giovanni visualization and analysis system.

land surface↗
NASA NTRS2014

Temperature and Humidity Profiles in the TqJoint Data Group of AIRS Version 6 Product for the Climate Model Evaluation

The Atmospheric Infrared Sounder (AIRS) mission is entering its 13th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing long-wave radiation, cloud properties, and trace gases. Thus AIRS data have been widely used, among other things, for short-term climate research and observational component for model evaluation. One instance is the fifth phase of the Coupled Model Intercomparison Project (CMIP5) which uses AIRS version 5 data in the climate model evaluation. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the AIRS mission. The GES DISC, in collaboration with the AIRS Project, released data from the version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. The ongoing Earth System Grid for next generation climate model research project, a collaborative effort of GES DISC and NASA JPL, will bring temperature and humidity profiles from AIRS version 6. The AIRS version 6 product adds a new "TqJoint" data group, which contains data for a common set of observations across water vapor and temperature at all atmospheric levels and is suitable for climate process studies. How different may the monthly temperature and humidity profiles in "TqJoint" group be from the "Standard" group where temperature and water vapor are not always valid at the same time? This study aims to answer the question by comprehensively comparing the temperature and humidity profiles from the "TqJoint" group and the "Standard" group. The comparison includes mean differences at different levels globally and over land and ocean. We are also working on examining the sampling differences between the "TqJoint" and "Standard" group using MERRA data.

climate model evaluation↗
NASA NTRS2016

Analyzing and Visualizing Precipitation and Soil Moisture in ArcGIS

Precipitation and soil moisture are among the most important parameters in many land GIS (Geographic Information System) research and applications. These data are available globally from NASA GES DISC (Goddard Earth Science Data and Information Services Center) in GIS-ready format at 10-kilometer spatial resolution and 24-hour or less temporal resolutions. In this presentation, well demonstrate how rainfall and soil moisture data are used in ArcGIS to analyze and visualize spatiotemporal patterns of droughts and their impacts on natural vegetation and agriculture in different parts of the world.

precipitation↗
NASA NTRS2016

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

knowledge base↗
NASA NTRS2016

Constructing an AIRS Climatology for Data Visualization and Analysis to Serve the Climate Science and Application Communities

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for NASA sounders: the present Aqua AIRS mission and the succeeding SNPP CrIS mission. The AIRS mission is entering its 15th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released product from the version 6 algorithm in early 2013. Giovanni, a Web-based application developed by the GES DISC, 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. Most important variables from version 6 AIRS product are available in Giovanni. We are developing a climatology product using 14-year AIRS retrievals. The study can be a good start for the long term climatology from NASA sounders: the AIRS and the succeeding CrIS. This presentation will show the impacts to the climatology product from different aggregation methods. The climatology can serve climate science and application communities in data visualization and analysis, which will be demonstrated using a variety of functions in version 4 Giovanni. The highlights of these functions include user-defined monthly and seasonal climatology, inter annual seasonal time series, anomaly analysis.

AIRS↗
NASA NTRS2017

GES DISC Datalist Enables Easy Data Selection For Natural Phenomena Studies

In order to investigate and assess natural hazards such as tropical storms, winter storms, volcanic eruptions, floods, and drought in a timely manner, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been developing an efficient data search and access service. Called "Datalist," this service enables users to acquire their data of interest "all at once," with minimum effort. A Datalist is a virtual collection of predefined or user-defined data variables from one or more archived data sets. Datalists are more than just data. Datalists effectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services (e.g., subset and OPeNDAP), all available from one-stop shopping. The predefined Datalists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend. The Datalist service is an extension of the new GES DISC website, which is completely data-driven. A Datalist, also known as "data bundle," is treated just as any other data set. Being a virtual collection, a Datalist requires no extra storage space.

natural hazards↗
NASA NTRS2016

Characterize Aerosols from MODIS MISR OMI MERRA-2: Dynamic Image Browse Perspective

Among the known atmospheric constituents, aerosols still represent the greatest uncertainty in climate research. To understand the uncertainty is to bring altogether of observational (in-situ and remote sensing) and modeling datasets and inter-compare them synergistically for a wide variety of applications that can bring far-reaching benefits to the science community and the broader society. These benefits can best be achieved if these earth science data (satellite and modeling) are well utilized and interpreted. Unfortunately, this is not always the case, despite the abundance and relative maturity of numerous satellite-borne sensors routinely measure aerosols. There is often disagreement between similar aerosol parameters retrieved from different sensors, leaving users confused as to which sensors to trust for answering important science questions about the distribution, properties, and impacts of aerosols. NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) have developed a new visualization service (NASA Level 2 Data Quality Visualization, DQViz)supporting various visualization and data accessing capabilities from satellite Level 2(MODISMISROMI) and long term assimilated aerosols from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2 displaying at their own native physical-retrieved spatial resolution. Functionality will include selecting data sources (e.g., multiple parameters under the same measurement), defining area-of-interest and temporal extents, zooming, panning, overlaying, sliding, and data subsetting and reformatting.

data quality↗
NASA NTRS2017

Global Precipitation Products at NASA GES DISC for Supporting Agriculture Research and Applications

This presentation describes precipitation products available at the NASA GES DISC that support agricultural research. XXXX Key environmental variables for agriculture: precipitation, temperature, water (soil moisture), solar radiation, NDVI, etc. 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). Precipitation is very important for rainfed agriculture. Droughts can cause severe damage. Precipitation information can be used to monitor the growing season. The Goddard Earth Sciences (GES) Data and Information Services Center (DISC), one of 12 NASA data centers, located in Greenbelt, Maryland, USA. The GES DISC is a major data archive center for global precipitation, water & energy cycles, atmospheric composition, and climate variability Global and regional precipitation datasets (satellite-based and data assimilation Data services (subsetting, format conversion, online visualization, etc.) User services are available FAQs, How to (recipes), Glossary, etc. Social media (Twitter, YouTube, User forum) Help desk (phone, email, online feedback) Training materials (ARSET => Applied Remote Sensing Training) Liu,

precipitation↗
NASA NTRS2017

Data Descriptor: A Land Data Assimilation System for Sub-Saharan Africa Food and Water Security Applications

Seasonal agricultural drought monitoring systems, which rely on satellite remote sensing and land surface models (LSMs), are important for disaster risk reduction and famine early warning. These systems require the best available weather inputs, as well as a long-term historical record to contextualize current observations. This article introduces the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS), a custom instance of the NASA Land Information System (LIS) framework. The FLDAS is routinely used to produce multi-model and multi-forcing estimates of hydro-climate states and fluxes over semi-arid, food insecure regions of Africa. These modeled data and derived products, like soil moisture percentiles and water availability, were designed and are currently used to complement FEWSNETs operational remotely sensed rainfall, evapotranspiration, and vegetation observations. The 30+ years of monthly outputs from the FLDAS simulations are publicly available from the NASA Goddard Earth Science Data and Information Services Center (GES DISC) and recommended for use in hydroclimate studies, early warning applications, and by agro-meteorological scientists in Eastern, Southern, and Western Africa.

albedo↗
NASA NTRS2017

Access NASA Satellite Global Precipitation Data Visualization on YouTube

Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. The collected and archived satellite data at 12 NASA data centers can also be used for STEM education and activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programming languages, etc. Over the years, many efforts including tools, training classes, and tutorials have been developed to improve satellite data access for users, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses a very popular online video sharing Web site, YouTube (https://www.youtube.com/), for accessing visualizations of our global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without the necessity to learn new software or download data. The dataset in this activity is a one-month animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellite Retrievals for GPM (IMERG). IMERG provides precipitation on a near-global (60 deg. N-S) coverage at half-hourly time interval, providing more details on precipitation processes and development compared to the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multisatellite Precipitation Analysis (TMPA, 3B42) product. When the retro-processing of IMERG during the TRMM era is finished in 2018, the entire video will contain more than 330,000 files and will last ~3.6 hours. Future plans include development of flyover videos for orbital data for an entire satellite mission or project. All videos, including the one-month animation, will be uploaded and available at the GES DISC site on YouTube (https://www.youtube.com/user/NASAGESDISC).

precipitation↗
NASA NTRS2017

GES DISC Datalist Improves Earth Science Data Discoverability

At American Geophysical Union(AGU) 2016 Fall Meeting, Goddard Earth Sciences Data Information Services Center (GES DISC) unveiled a novel way to access data: Datalist. Currently, datalist is a collection of predefined data variables from one or more archived datasets, curated by our subject matter expert (SME). Our science support team has curated a predefined Hurricane Datalist and received very positive feedback from the user community. Datalist uses the same architecture our new website uses and have the same look and feel as other datasets on our web site. and also provides a one-stop shopping for data, metadata, citation, documentation, visualization and other available services. Since the last AGU Meeting, we have further developed a few new datalists corresponding to the Big Earth Data Initiative (BEDI) Societal Benefit Areas and A-Train data. We now have four datalists: Hurricane, Wind Energy, Greenhouse Gas and A-Train. We have also started working with our User Working Group members to create their favorite datalists and working with other DAAC to explore the possibility to include their products in our datalists that may also lead to a future of potential federated (cross-DAAC) datalists. Since our datalist prototype effort was a success, we are planning to make datalist operational. It's extremely important to have a common metadata model to support datalist, this will also be the foundation of federated datalist. We mapped our datalist metadata model to the unpublished UMM(Universal Metadata Model)-Var (Variable) (June version) and found that the UMM-var together with UMM-C (Collection) and possible UMM-S (Service) will meet our basic requirements. For example: Dataset shortname, and version are already specified in UMM-C, variable name, long name, units, dimensions are all specified in UMM-Var. UMM-Var also facilitates Science Keywords to allow tagging at variable level and Characteristics for optional variable characteristics. Measurements is useful for grouping of the variables and Set is promising to define datalist. And finally, the UMM-Service model to specify the available services for the variable will be very beneficial. In summary, UMM-Var, UMM-C and UMM-S are the basis of federated datalist and the development and deployment of datalist will contribute to the evolution of the UMM.

datalist↗
NASA NTRS2017

AIRS-Only Product in Giovanni for Exploring Up-to-Date AIRS Observation and Comparing with AIRS+AMSU Product

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been the home of processing, archiving, and distribution services for the Atmospheric Infrared Sounder (AIRS) mission since its launch in 2002 for global observations of the atmospheric state. Giovanni, a Web-based application developed by the GES DISC, 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. Most important AIRS variables, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases, are available in Giovanni. AIRS is an instrument suite comprised of a hyperspectral infrared instrument (AIRS) and two multichannel microwave instruments, the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB). As HSB ceased operation in the very early stages of the AIRS mission, the AIRS project operates two parallel retrieval algorithms: one using both IR and MW measurements (AIRS+AMSU) and the other using only IR measurements (AIRS-only), which covers most of the mission duration. The AIRS+AMSU product is better quality, and the variables in Giovanni are from this product. However, generation of the AIRS+AMSU product has been suspended since the AMSU instrument anomaly occurred in late September 2016. To continue exploring up-to-date AIRS observations, the same set of variables from the AIRS-only product have been added to Giovanni by the GES DSIC. This will also support comparison of AIRS-only with AIRS+AMSU retrievals. In this presentation, we demonstrate the visualization of the AIRS-only product and plots/statistics of comparison with AIRS+AMSU product using Giovanni.

AIRS↗
NASA NTRS2017

Investigating Access Performance of Long Time Series with Restructured Big Model Data

Data sets generated by models are substantially increasing in volume, due to increases in spatial and temporal resolution, and the number of output variables. Many users wish to download subsetted data in preferred data formats and structures, as it is getting increasingly difficult to handle the original full-size data files. For example, application research users such as those involved with wind or solar energy, or extreme weather events are likely only interested in daily or hourly model data at a single point (or for a small area) for a long time period, and prefer to have the data downloaded in a single file. With native model file structures, such as hourly data from NASA Modern-Era Retrospective analysis for Research and Applications Version-2 (MERRA-2), it may take over 10 hours for the extraction of parameters-of-interest at a single point for 30 years. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is exploring methods to address this particular user need. One approach is to create value-added data by reconstructing the data files. Taking MERRA-2 data as an example, we have tested converting hourly data from one-day-per-file into different data cubes, such as one-month, or one-year. Performance is compared for reading local data files and accessing data through interoperable services, such as OPeNDAP. Results show that, compared to the original file structure, the new data cubes offer much better performance for accessing long time series. We have noticed that performance is associated with the cube size and structure, the compression method, and how the data are accessed. An optimized data cube structure will not only improve data access, but also may enable better online analysis services

reanalysis↗