NCAS-M Data Management and Sharing Policy

Overview and Data Submission

NCAS-M follows NOAA’s Data Management Plan to ensure that environmental datasets collected or produced by NCAS-M institutions are preserved, documented, and accessible. Without proper care, valuable data can be lost or stored with questionable quality. This plan ensures long-term integrity, discoverability, and accessibility of all NCAS-M data products.

NCAS-M participants include research institutions that collect and produce significant volumes of environmental data (see NCAS-M Environmental Observations and Data Elements below). Proper storage and indexing enable investigators to locate and use datasets efficiently.

Data Sharing Plan

  • NCAS-M data is freely available upon request.
  • Requests should be sent in writing (email) to the appropriate NCAS-M scientist, specifying intended use and publication plans in the metadata.
  • Contact the data provider for the most recent version of the dataset.
  • Acknowledge NCAS-M and the funding agency in all publications.
  • Redistribution through third parties is not permitted.

If Principal Investigators (PIs) wish to be acknowledged or offered co-authorship, this will be discussed and agreed upon before publication. If the request overlaps with a PI’s active research, they may ask to publish their findings first. All publications using NCAS-M data should be submitted as reprints to the NCAS-M data archive.

NCAS-M-funded environmental data will be made publicly available within two years of collection or production, unless restricted by ethical, privacy, or intellectual property concerns. Each institution is responsible for submitting its datasets within the required timeframe.
NCAS-M identifies three main data types:

  • Direct observations
  • Derived datasets from observations
  • Model outputs

Data Description and Metadata

Each dataset must include a clear file name, format, units, and stable format (e.g., ASCII, NetCDF). Metadata will be generated for each new dataset and should include:

  • Description and type (observation, derived, model output)
  • Origin: instrument manufacturer/model or model name
  • QA/QC methods for observation and derived data
  • Formulas and corrections applied (for derived data) *
  • Model formulation/parameterization details and references **
  • Non-proprietary formats (or accompanying code for proprietary/binary files) ***
  • Contact information and acknowledgments
  • References

* Source code for derived data should be submitted (e.g., Fortran, MATLAB).

** For custom models, submit source code.

*** For binary/proprietary formats, provide the necessary software or scripts to read the data.

Storage and Data Access

NCAS-M maintains a dedicated data server at Howard University in Washington, D.C., managed by a designated data manager. Researchers can upload data via an online form, which automatically generates the required metadata.
Public access includes:

  • Online metadata submission form
  • NCAS-M data policy
  • Dataset summaries
  • Graphical data displays
  • Metadata pages
  • Linked publications and student theses

Summary datasets (e.g., 30-minute or hourly averages) are available for anonymous download. Raw or large datasets are available upon request.

NCAS-M Environmental Observations and Data Elements

Institution Data Type
Jackson State University Air quality model output; Barnet Reservoir: surface fluxes, meteorology (fixed/mobile), radiosonde, ceilometer
Howard University AEROSE Campaigns: aerosols, gases, meteorology, radiation, ceilometer, radiosonde/ozonesonde
AEROSE Program
Beltsville Site: aerosols, gases, meteorology/micrometeorology, radiation, ceilometer, sondes, Raman lidar, microwave radiometer
University at Albany, SUNY NY Mesonet: 125 standard sites (weather, radiation, soil moisture/temp), 17 enhanced sites (profiling radiometer, Doppler lidar, sky imager, flux tower)
University of Maryland, College Park CWRF model outputs: seasonal prediction, climate change projections, extreme event analysis
University of Puerto Rico, Mayaguez Water quality data
University of Texas at El Paso Ceilometer, radiation
University of Maryland Baltimore County Ceilometer, microwave radiometer, lidar network (aerosol/PBL), sondes, Doppler lidar
San Jose State University Weather station; ozone analyzer; GHG analyzer (CO₂, CO, CH₄, H₂O); nephelometer; ceilometer; disdrometer