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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Cloud-optimized access to HDF5/NetCDF4 files using the Zarr API and the OPeNDAP DMR++
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File Specification for MERRA-2 Country-Level Surface PM2.5 Monthly Mean Products
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File Specification for GEOS-CF Products
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Creating Cloud-Optimized HDF5 Files
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Status of WG3 Internal Task 39-4: ORDEM 3.1 and MEM 3 data files for Analysis Code Benchmark Update
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File Specification for MERRA-2 Climate Statistics Products
The Modern Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) contains a wealth of information that can be used for weather and climate studies. By combining the assimilation of observations with a frozen version of the Goddard Earth Observing System (GEOS), a global analysis is produced at an hourly temporal resolution spanning from January 1980 through present (Gelaro et al., 2017). It can be difficult to parse through a multidecadal dataset such as MERRA-2 to evaluate the interannual variability of weather that occurs on a daily timescale, let alone determine the occurrence of an extreme weather event. Furthermore, it was recognized that standard metrics were needed to evaluate climate change among climate models and international research efforts. As a result of these concerns, the Expert Team on Climate Change Detection and Indices (ETCCDI) developed a set of indices that represent the frequency and intensity of extreme weather events using a daily time series of 2-m air temperature (T2m) and precipitation (Alexander et al., 2016). These indices were used as a basis to comprise a list of fields that represent daily extreme temperature and precipitation events, heatwaves, multi-day precipitation, as well monthly percentile statistics from the MERRA-2 dataset. Also included in this data product is a climatological long term mean and standard deviation representing the interannual variability on a monthly timescale.
GMAO Office Note No. 17 (Version 1.3) File Specification for GEOS-CF Products
The NASA Global Earth Observing System (GEOS) model has been expanded to provide global near-real-time forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (about 25 km). This GEOS Composition Forecast (GEOS-CF) system combines the GEOS weather analysis and forecasting system with the state-of-the-science GEOS-Chem chemistry module (Bey et al., 2001; Keller et al., 2014; Long et al., 2015) to provide detailed chemical analysis of a wide range of air pollutants including ozone, carbon monoxide, nitrogen oxides, and fine particulate matter (PM2.5). Full model description and evaluation of the GEOS-CF tropospheric simulation and forecast skill is given in Keller et al. (2021). For evaluation of GEOS-CF stratospheric composition see Knowland et al. (2021).
Toward Cloud-Optimized HDF5 Files
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File Specification for MERRA-2 Country-Level Surface PM2.5 Monthly Mean Products
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Cloud-Optimized HDF5 Files: 2023 ESIP Summer Meeting
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Strategies and Software for Optimizing HDF5/netCDF-4 Files in the Cloud
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QSF18 Nonresponse Follow-up Reminders Survey Data Supplemental File
This minimal data set contains anonymized study subject identifier (PARTICIPANT_ID) and non-response follow up type (group) from the single events surveys conducted during the Quiet Supersonic Flights 2018 risk reduction study in Galveston, Texas, in November 2018. Nonresponse follow up groups and procedures are defined and discussed in Page et al. 2020, Section 6.2 (NASA/CR-2020-220589/Volume I). The data cleaning conventions are consistent with the assumptions of Lee et al. in the treatment of the single events survey data (Lee, Rathsam, Wilson (2020). Journal of the Acoustical Society of America. 147, doi: 10.1121/10.0001021). Filename: reminder_groups.csv Dimensions: 371 rows by 2 columns. Variables: PARTICIPANT_ID, group PARTICPANT_ID: numeric (integer, six digits) group: character string taking one of four values ('Email - No Reminder'; 'Email - Reminder'; 'Text - No Reminder'; 'Text - Reminder').
Collaborating With Xarray to Enable Reading Hierarchical Data Files
NASA has a lot of expertise, but doesn’t need to write every single piece of code. Pangeo is a fantastic open-source community of tools for geoscience research. Xarray, a Python package, is a widely used part of this ecosystem for accessing and analyzing geoscience data.
Cloud Optimized HDF5 Files: Current Status
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Simplifying Analysis of Hierarchical HDF5 and NetCDF4 Files with Xarray-datatree
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