Machine learning-based detection of atmospheric rivers in CESM1.3
d651086
These data are the results of high resolution simulations with the Community Earth System Model, version 1.3 (CESM1.3). These data form the basis of a publication analyzing machine learning based-detection of atmospheric rivers and associated precipitation. The CESM1.3 data include simulations with historical (years 2000-2005), RCP2.6 (years 2006-2015), and RCP8.5 (years 2086-2100) climate forcing. The temporal resolution is 3-hourly, the horizontal resolution is 0.25 degree, and the spatial domain is global.
dataset
https://gdex.ucar.edu/datasets/d651086/
protocol: https
name: Dataset Description
description: Related Link
function: information
https://gdex.ucar.edu/datasets/d651086/dataaccess/
protocol: https
name: Data Access
description: Related Link
function: download
climatologyMeteorologyAtmosphere
dataset
revision
2021-03-30
CESM > NCAR Community Earth System Model
revision
2026-08-05
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PRESSURE > SEA LEVEL PRESSURE
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR INDICATORS > TOTAL PRECIPITABLE WATER
EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS > UPPER LEVEL WINDS > U/V WIND COMPONENTS
revision
2026-08-05
2000
2100
publication
2026-07-27
notPlanned
Creative Commons Attribution 4.0 International License
None
pointOfContact
NSF NCAR Geoscience Data Exchange
name: NSF NCAR Geoscience Data Exchange
description: The Geoscience Data Exchange (GDEX), managed by the Computational and Information Systems Laboratory (CISL) at NSF NCAR, contains a large collection of meteorological, atmospheric composition, and oceanographic observations, and operational and reanalysis model outputs, integrated with NSF NCAR High Performance Compute services to support atmospheric and geosciences research.
function: download
pointOfContact
2026-08-10T14:32:24Z