Identification

Title

CESM1 CAM5 Decadal Prediction Large Ensemble

Alternative title(s)

d651028

Abstract

<p>The CESM Decadal Prediction Large Ensemble (DPLE) is a set of simulations carried out at NCAR to support research into near-term Earth System prediction. The DPLE comprises 62 distinct ensembles, one for each of 62 initialization times (November 1 of 1954, 1955, ..., 2014, 2015). For each start date, a 40-member ensemble was generated by randomly perturbing the atmospheric initial condition at the round-off level. The simulations were integrated forward for 122 months after initialization. Observation-based ocean and sea ice initial conditions for the 1954-2015 period were obtained from a reanalysis-forced simulation of the CESM ocean and sea ice models. The initial conditions for the atmosphere and land models were obtained from CESM Large Ensemble (LENS) simulations at corresponding historical times. Full field initialization was used for all component models, and so drift adjustment prior to analysis is generally recommended.</p>

Resource type

dataset

Resource locator

https://gdex.ucar.edu/datasets/d651028/

protocol: https

name: Dataset Description

description: Related Link

function: information

https://gdex.ucar.edu/datasets/d651028/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

2025-10-03

Keyword set

keyword value

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC PRESSURE > SEA LEVEL PRESSURE

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC TEMPERATURE > UPPER AIR TEMPERATURE

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

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

EARTH SCIENCE > ATMOSPHERE > ATMOSPHERIC WINDS > WIND DYNAMICS > VERTICAL WIND VELOCITY/SPEED

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > LIQUID PRECIPITATION > RAIN

EARTH SCIENCE > ATMOSPHERE > PRECIPITATION > PRECIPITATION PROFILES > LATENT HEAT FLUX

originating controlled vocabulary

title

reference date

date type

revision

effective date

2025-10-03

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

1954-11-01

End position

2015-11-30

Dataset reference date

date type

publication

effective date

2018-01-19

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

2025-10-09T01:36:25Z

Metadata language