Skip to main content
NCAR is Sponsored by the National Science Foundation
DASH Search
  • 首頁
  • 資源
  • Collections
  • 關於
  1. 首頁
  2. 組織
  3. CISL
  4. Machine learning-based...
  • 資源
  • 動態牆
  • Gravatar admin created the 資料集 Machine learning-based detection of weather fronts and associated extreme precipitation in CESM1.3
    1 個月前

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

  • 關於DASH Search
  • CKAN API
  • 登入

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.