Open data
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Deployed on AWS
The Community Earth System Model (CESM) Large Ensemble Numerical Simulation (LENS) dataset includes a 40-member ensemble of climate simulations for the period 1920-2100 using historical data (1920-2005) or assuming the RCP8.5 greenhouse gas concentration scenario (2006-2100), as well as longer control runs based on pre-industrial conditions. The data comprise both surface (2D) and volumetric (3D) variables in the atmosphere, ocean, land, and ice domains. The total data volume of the original dataset is ~500TB, which has traditionally been stored as ~150,000 individual CF/NetCDF files on disk or magnetic tape made available through the NCAR Climate Data Gateway for download or via web services.
NCAR has copied a subset (currently ~70 TB) of CESM LENS data to Amazon S3 as part of the AWS Public Datasets Program. To optimize for large-scale analytics we have represented the data as ~275 Zarr stores format accessible through the Python Xarray library. Each Zarr store contains a si[...]
Overview
The Community Earth System Model (CESM) Large Ensemble Numerical Simulation (LENS) dataset includes a 40-member ensemble of climate simulations for the period 1920-2100 using historical data (1920-2005) or assuming the RCP8.5 greenhouse gas concentration scenario (2006-2100), as well as longer control runs based on pre-industrial conditions. The data comprise both surface (2D) and volumetric (3D) variables in the atmosphere, ocean, land, and ice domains. The total data volume of the original dataset is ~500TB, which has traditionally been stored as ~150,000 individual CF/NetCDF files on disk or magnetic tape made available through the NCAR Climate Data Gateway for download or via web services.
NCAR has copied a subset (currently ~70 TB) of CESM LENS data to Amazon S3 as part of the AWS Public Datasets Program. To optimize for large-scale analytics we have represented the data as ~275 Zarr stores format accessible through the Python Xarray library. Each Zarr store contains a single physical variable for a given model run type and temporal frequency (monthly, daily, 6-hourly).
Features and programs
Open Data Sponsorship Program
This dataset is part of the Open Data Sponsorship Program, an AWS program that covers the cost of storage for publicly available high-value cloud-optimized datasets.
Pricing
This is a publicly available data set. No subscription is required.
Legal
Content disclaimer
Vendors are responsible for their product descriptions and other product content. AWS does not warrant that vendors' product descriptions or other product content are accurate, complete, reliable, current, or error-free.
Delivery details
AWS Data Exchange (ADX)
AWS Data Exchange is a service that helps AWS easily share and manage data entitlements from other organizations at scale.
Open data resources
Available with or without an AWS account.
- How to use
- To access these resources, reference the Amazon Resource Name (ARN) using the AWS Command Line Interface (CLI). Learn more
- Description
- Project data files
- Resource type
- S3 bucket
- Amazon Resource Name (ARN)
- arn:aws:s3:::ncar-cesm-lens
- AWS region
- us-west-2
- AWS CLI access (No AWS account required)
- aws s3 ls --no-sign-request s3://ncar-cesm-lens/
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How to cite
Community Earth System Model Large Ensemble (CESM LENS) was accessed on DATE from https://registry.opendata.aws/ncar-cesm-lens .
Similar products
The US National Center for Atmospheric Research partnered with the IBS Center for Climate Physics in South Korea to generate the CESM2 Large Ensemble which consists of 100 ensemble members at 1 degree spatial resolution covering the period 1850-2100 under CMIP6 historical and SSP370 future radiative forcing scenarios. Data sets from this ensemble were made downloadable via the Climate Data Gateway on June 14th, 2021.
NCAR has copied a subset (currently ~500 TB) of CESM2 LENS data to Amazon S3 as part of the AWS Public Datasets Program. To optimize for large-scale analytics we have represented the data as ~275 Zarr stores format accessible through the Python Xarray library. Each Zarr store contains a single physical variable for a given model run type and temporal frequency (monthly, daily).
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