Skip to main content
NCAR is Sponsored by the National Science Foundation
DASH Search
  • Home
  • Resources
  • Collections
  • About
  1. Home
  2. Organizations
  3. OpenSky
  4. A deep-learning approach...
  • Resource
  • Activity Stream
  • Gravatar admin updated the dataset A deep-learning approach to soil moisture estimation with GNSS-R
    1 month ago
  • Gravatar admin created the dataset A deep-learning approach to soil moisture estimation with GNSS-R
    5 months ago

NCAR

  • NCAR Homepage
  • ACOM | Atmospheric Chemistry Observations & Modeling
  • CGD | Climate & Global Dynamics
  • CISL | Computational & Information Systems
  • EdEC | Education, Engagement & Early-Career Development
  • EOL | Earth Observing Laboratory
  • HAO | High Altitude Observatory
  • MMM | Mesoscale & Microscale Meteorology
  • RAL | Research Applications Laboratory

UCAR

  • UCAR Homepage
  • Community Programs
  • Education & Training
  • For Staff
  • Government Relations & External Engagement
  • Member Institutions
  • Tech Transfer & Engagement
  • University Collaboration

DASH Search

    Questions? Contact datahelp@ucar.edu

  • About DASH Search
  • CKAN API
  • Login

Powered by CKAN

ckan
Using 5bd556eb4 from branch HEAD.
Last updated 2025-02-17 13:02:01.
ckanext-dsetsearch
Using 1a68d3e from branch main.
Last updated 2025-06-18 16:41:00.
© 2024 UCAR Privacy Cookies Accessibility Terms of use Copyright issues Sponsored by NSF Report ethics concern
Postal Address: P.O. Box 3000, Boulder, CO 80307-3000 • Shipping Address: 3090 Center Green Drive, Boulder, CO 80301
NSF logo
This material is based upon work supported by the NSF National Center for Atmospheric Research, a major facility sponsored by the U.S. National Science Foundation and managed by the University Corporation for Atmospheric Research. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the U.S. National Science Foundation.