Identification

Title

Machine learning-based detection of weather fronts and associated extreme precipitation in CESM1.3

Alternative title(s)

d583105

Abstract

These data are the results of high resolution simulations with the Community Earth System Model, version 1.3 (CESM1.3). These simulations form the basis of a publication analyzing machine learning based-detection of weather fronts and associated extreme 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. Depending on the variables, the temporal resolution is 3-hourly, 6-hourly, or monthly, the horizontal resolution is 0.25 degree or 1 degree, and the spatial domain is global or centered over North America.

Resource type

dataset

Resource locator

https://gdex.ucar.edu/datasets/d583105/

protocol: https

name: Dataset Description

description: Related Link

function: information

https://gdex.ucar.edu/datasets/d583105/dataaccess/

protocol: https

name: Data Access

description: Related Link

function: download

Unique resource identifier

code

codeSpace

Dataset language

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

climatologyMeteorologyAtmosphere

Keywords

Keyword set

keyword value

dataset

originating controlled vocabulary

title

reference date

date type

revision

effective date

2021-03-30

Keyword set

keyword value

CESM > NCAR Community Earth System Model

originating controlled vocabulary

title

reference date

date type

revision

effective date

2026-04-15

Keyword set

keyword value

EARTH SCIENCE > ATMOSPHERE > ALTITUDE > GEOPOTENTIAL HEIGHT

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PRESSURE > SEA LEVEL PRESSURE

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > SURFACE TEMPERATURE

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR INDICATORS > HUMIDITY > SPECIFIC HUMIDITY

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WATER VAPOR > WATER VAPOR INDICATORS > TOTAL PRECIPITABLE WATER

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS > SURFACE WINDS > U/V WIND COMPONENTS

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION AMOUNT

originating controlled vocabulary

title

reference date

date type

revision

effective date

2026-04-15

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

2000-01-01

End position

2100-12-31

Dataset reference date

date type

publication

effective date

2022-04-06

Frequency of update

notPlanned

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Creative Commons Attribution 4.0 International License

Limitations on public access

None

Responsible organisations

Responsible party

organisation name

email address

datahelp@ucar.edu

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact

organisation name

NSF NCAR Geoscience Data Exchange

email address

datahelp@ucar.edu

web address

https://gdex.ucar.edu

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

responsible party role

pointOfContact

Metadata date

2026-04-20T16:41:57Z

Metadata language