Cimel Sunphotometer Almucantar Sky Radiance Data, Version 3
This is unscreened Almucantar sky radiance (version 3) data ingested from Aeronet.
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This is unscreened Almucantar sky radiance (version 3) data ingested from Aeronet.
The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) dataset released by the Precipitation Processing System (PPS) will be updated to a final version within the next year. These updates are based on increased knowledge in recent years of radiometer calibration and sensor performance issues. In particular, the Global Precipitation Measurement (GPM) Microwave Imager (GMI) is used as a model for many of the TMI version updates. This paper discusses four aspects of the TMI data product that will be improved: spacecraft attitude, calibration and quality control, along-scan bias corrections, and sensor pointing accuracy. These updates will be incorporated into the final TMI data version, improving the quality of the data product and ensuring accurate geophysical parameters can be derived from TMI.
These data are the results of a systematic review that investigated how data standards and reporting formats are documented on the version control platform GitHub. Our systematic review identified 32 data standards in earth science, environmental science, and ecology that use GitHub for version control of data standard documents. In our analysis, we characterized the documents and content within each of the 32 GitHub repositories to identify common practices for groups that version control their documents on GitHub.In this data package, there are 8 CSV files that contain data that we characterized from each repository, according to the location within the repository. For example, in 'readme_pages.csv' we characterize the content that appears across the 32 GitHub repositories included in our systematic review. Each of the 8 CSV files has an associated data dictionary file (names appended with '_dd.csv' and here we describe each content category within CSV files.There is one file-level metadata file (flmd.csv) that provides a description of each file within the data package.
Abstract Data standardization combined with descriptive metadata facilitate data reuse, which is the ultimate goal of the Findable, Accessible, Interoperable, and Reusable (FAIR) principles. Community data or metadata standards are increasingly created through an approach that emphasizes collaboration between various stakeholders. Such an approach requires platforms for collaboration on the development process that centers on sharing information and receiving feedback. Our objective in this study was to conduct a systematic review to identify data standards and reporting formats that use version control for developing data standards and to summarize common practices, particularly in earth and environmental sciences. Out of 108 data standards and reporting formats identified in our review, 32 used GitHub as the version control platform, and no other platforms were used. We found no universally accepted methodology for developing and publishing data standards. Many GitHub repositories did not use key features that could help developers to gather user feedback, or to create and revise standards that build on previous work. We provide guidance for community‐driven standard development and associated documentation on GitHub based on a systematic review of existing practices.
This data package contains three templates that can be used for creating README files and Issue Templates, written in the markdown language, that support community-led data reporting formats. We created these templates based on the results of a systematic review (see related references) that explored how groups developing data standard documentation use the Version Control platform GitHub, to collaborate on supporting documents. Based on our review of 32 GitHub repositories, we make recommendations for the content of README Files (e.g., provide a user license, indicate how users can contribute) and so 'README_template.md' includes headings for each section. The two issue templates we include ('issue_template_for_all_other_changes.md' and 'issue_template_for_documentation_change.md') can be used in a GitHub repository to help structure user-submitted issues, or can be modified to suit the needs of data standard developers. We used these templates when establishing ESS-DIVE's community space on GitHub (https://github.com/ess-dive-community) that includes documentation for community-led data reporting formats. We also include file-level metadata 'flmd.csv' that describes the contents of each file within this data package. Lastly, the temporal range that we indicate in our metadata is the time range during which we searched for data standards documented on GitHub.
A plotting package has been developed to simplify the task of plotting meteorological data. The calling sequences and examples of high level yet flexible routines which allow contouring, vectors and shading of cylindrical, polar, orthographic and Mollweide (egg) projections are given. Routines are also included for contouring pressure-latitude and pressure-longitude fields with linear or log scales in pressure (interpolation to fixed grid interval is done automatically). Also included is a fairly general line plotting routine. The present version (1.5) produces plots on WMS laser printers and uses graphics primitives from WOLFPLOT.
To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 2.0 in 2018, and a new version of FRED is now available. FRED 3.0 has more than 150,000 observations of more than 330 root traits, with data collected from more than 1400 data sources. FRED 3.0 has 45% more root trait observations than FRED 2.0, particularly in the categories of root anatomy, morphology, and microbial associations; ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. However, FRED accepts data collected from roots of all sizes, and already contains several observations of coarse roots. Data collection will continue for the foreseeable future.
To address the need for a centralized root trait database, we compiled the Fine-Root Ecology Database (FRED) from published and unpublished data sources. We have continued to add to the FRED database since the release of FRED 1.0 in 2017, followed by 2.0 in 2018, and 3.0 in 2021. This new release of FRED 4.0 now has 213,941 observations of 238 root traits, for a combined total of roughly 3.4 million data fields for root traits and ancillary data together. FRED 4.0 has 39.8% more root trait observations than FRED 3.0 and a 34.4% increase in unique data sources. This release of FRED 4.0 also includes significant increases in geographic regions that have long been underrepresented in global datasets, notably in the tropical low latitudes. Ancillary data on associated site, vegetation, edaphic, and climatic conditions from across the globe have also increased concurrently with root trait observations. FRED is focused on fine roots (traditionally defined as roots less than 2 mm in diameter), as coarse roots are studied using different methodology, often at very different scales, and have different traits and trait interpretations. Despite this fine-root focus, FRED accepts data collected from roots of all sizes and contains observations of many root classes including coarse roots. Data collection will continue for the foreseeable future. The FRED4_Entire_Database_2026.csv file is the flat csv data file for FRED 4.0, and the FRED4_dd.csv file is the data dictionary of all columns available in FRED, including column IDs, column names, definitions, and unit (where applicable).
Open sourced agent files needed to run version 1.0.0 of the dGen model. Contains all national, ISO, and state level residential and commercial agents.
No abstract available
The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument installed on the International Space Station (ISS) has completed over three and a half years of data collection and production of science data products. The SAGE III/ISS is a solar and lunar occultation instrument that scans the light from the Sun and Moon through the limb of the Earth’s atmosphere to produce vertical profiles of aerosol, ozone, water vapor, and other trace gases. It continues the legacy of previous SAGE instruments dating back to the 1970s to provide data continuity of stratospheric constituents critical for assessing trends in the ozone layer. This presentation shows the improvements to the SAGE water vapor product with the release of the newest data version. It also focuses on validation by comparing SAGE III/ISS v5.2 ozone and water vapor vertical profiles with those of in situ and satellite data.
Data system development activities for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) must begin well before the scheduled 1994 launch. To assist in these activities, it is essential to develop a simulated SeaWiFS data set as soon as possible. Realism is of paramount importance in this data set, including SeaWiFS spectral bands, orbital and scanning characteristics, and known data structures. Development of the simulated data set can assist in identification of problem areas that can be addressed and solved before the actual data are received. This paper describes the creation of the first version of the simulated SeaWiFS data set. The data set includes the spectral band, orbital, and scanning characteristics of the SeaWiFS sensor and SeaStar spacecraft. The information is output in the data structure as it is stored onboard. Thus, it is a level-0 data set which can be taken from start to finish through a prototype data system. The data set is complete and correct at the time of printing, although the values in the telemetry fields are left blank. The structure of the telemetry fields, however, is incorporated. Also, no account for clouds has been included. However, this version facilitates early prototyping activities by the SeaWiFS data system, providing a realistic data set to assess performance.
After launch we discovered that the CALIOP daytime measurements were subject to thermally induced beamdrift,and this caused the calibration to vary by as much as 30% during the course of a single daytime orbit segment. Using an algorithm developed by Powell et al.(2010), empirically derived correction factors are now computed in near realtime as a function of orbit elapsed time, and these are used to compensate for the beam wandering effects.
Stratospheric Aerosol and Gas Experiment (SAGE II) version 7 (v7) ozone profiles are analyzed for their decadal-scale responses in the middle and upper stratosphere for 1991 and 1992-2005 and compared with those from its previous version 6.2 (v6.2). Multiple linear regression (MLR) analysis is applied to time series of its ozone number density vs. altitude data for a range of latitudes and altitudes. The MLR models that are fit to the time series data include a periodic 11 yr term, and it is in-phase with that of the 11 yr, solar UV (Ultraviolet)-flux throughout most of the latitude/ altitude domain of the middle and upper stratosphere. Several regions that have a response that is not quite in-phase are interpreted as being affected by decadal-scale, dynamical forcings. The maximum minus minimum, solar cycle (SClike) responses for the ozone at the low latitudes are similar from the two SAGE II data versions and vary from about 5 to 2.5% from 35 to 50 km, although they are resolved better with v7. SAGE II v7 ozone is also analyzed for 1984-1998, in order to mitigate effects of end-point anomalies that bias its ozone in 1991 and the analyzed results for 1991-2005 or following the Pinatubo eruption. Its SC-like ozone response in the upper stratosphere is of the order of 4%for 1984-1998 vs. 2.5 to 3%for 1991-2005. The SAGE II v7 results are also recompared with the responses in ozone from the Halogen Occultation Experiment (HALOE) that are in terms of mixing ratio vs. pressure for 1991-2005 and then for late 1992- 2005 to avoid any effects following Pinatubo. Shapes of their respective response profiles agree very well for 1992-2005. The associated linear trends of the ozone are not as negative in 1992-2005 as in 1984-1998, in accord with a leveling off of the effects of reactive chlorine on ozone. It is concluded that the SAGE II v7 ozone yields SC-like ozone responses and trends that are of better quality than those from v6.2.
Version of previously released anthropogenic SO2 emissions data re-generated with altered spatial distributions for shipping emissions for use in the Emissions-MIP model inter-comparison project. Also included are 30% and 60% global reductions in shipping SO2 emissions.
GLDAS-2.0 data have been reprocessed with updated Princeton meteorological forcing data within the Land Information System (LIS) Version 7, and temporal coverage have been extended to 1948-2012.Global Land Data Assimilation System Version 2 (GLDAS-2) has two components: GLDAS-2.0: entirely forced with the Princeton meteorological forcing data GLDAS-2.1: forced with atmospheric analysis and observation-based data after 2001In order to create more climatologically consistent data sets, NASA GSFC's Hydrological Sciences Laboratory (HSL) has recently reprocessed the GLDAS-2.0, by using updated Princeton meteorological forcing data within the LIS Version 7.GLDAS-2.0 data and data services are provided at NASA GES DISC Hydrology Data and Information Services Center (HDISC), in collaboration with HSL.
The PPIHYD evaluation data product provides distinct hydrometeor field statistics calculated from U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility scanning radar plan position indicator (PPI) scans. These statistics include the equivalent reflectivity factor and Doppler spectral width percentiles, min/max values, and first four moments (mean, standard deviation, skewness, and kurtosis) of distinct hydrometeor features (clustered hydrometeor fields). Statistics also include morphological properties, water content and precipitation rate parameterization-based estimates, and thermodynamic properties interpolated using the Interpolated Sonde value-added product (INTERPSONDE VAP). The data set is organized in tabular form and is accompanied by mask arrays with corresponding indices. This straightforward file structure simplifies scanning radar data processing and renders this data set useful for process understanding and model evaluation studies. This report describes the data set and its processing algorithm and provides some examples.
This document describes the second version of the simulated SeaWiFS data set. A realistic simulated data set is essential for mission readiness preparations and can potentially assist in all phases of ground support for a future mission. The second version improves on the first version primarily through additional realism and complexity. This version incorporates a representation of virtually every aspect of the flight mission. Thus, it provides a high-fidelity data set for testing several aspects of the ground system, including data acquisition, data processing, data transfers, calibration and validation, quality control, and mission operations. The data set is constructed for a seven-day period, 25-31 March 1994. Specific features of the data set include Global Area coverage (GAC), recorded Local Area Coverage (LAC), and realtime High Resolution Picture Transmission (HRPT) data for the seven-day period. A realistic orbit, which is propagated using a Brouwer-Lyddane model with drag, is used to simulate orbit positions. The simulated data corresponds to the command schedule based on the orbit for this seven-day period. It includes total (at-satellite) radiances not only for ocean, but for land, clouds, and ice. The simulation also utilizes a high-resolution land-sea mask. It includes the April 1993 SeaWiFS spectral responses and sensor saturation responses. The simulation is formatted according to July 1993 onboard data structures, which include corresponding telemetry (instrument and spacecraft) data. The methods are described and some examples of the output are given. The instrument response functions made available in April 1993 have been used to produce the Version 2 simulated data. These response functions will change as part of the sensor improvements initiated in July-August 1993.