CAM6 Data Assimilation Research Testbed (DART) Reanalysis: Cloud-Optimized Dataset
Overview
This is a cloud-hosted subset of the CAM6+DART (Community Atmosphere Model version 6 Data Assimilation Research Testbed) Reanalysis dataset. These data products are designed to facilitate a broad variety of research using the NCAR CESM 2.1 (National Center for Atmospheric Research’s Community Earth System Model version 2.1), including model evaluation, ensemble hindcasting, data assimilation experiments, and sensitivity studies. They come from an 80 member ensemble reanalysis of the global troposphere and stratosphere using DART and CAM6. The data products represent states of the atmosphere consistent with observations from 2011 through 2019 at 1 degree horizontal resolution and weekly frequency. Each ensemble member is an equally likely description of the atmosphere, and is also consistent with dynamics and physics of CAM6. The dataset also contains corresponding land surface values at 6-hourly frequency. This dataset is a reformatting, with no change to numerical values, of data from the “CAM6 Data Assimilation Research Testbed (DART) Reanalysis”, DOI:10.5065/JG1E-8525.
Accessing CESM DART Data on AWS
- S3 bucket name: ncar-dart-cam6
- Region: us-west-2 region
- Amazon resource name: arn:aws:s3:::ncar-dart-cam6
- Bucket contents list: https://ncar-dart-cam6.s3.amazonaws.com/
Data Characteristics
- Variables
PS, T, US, VS, Q, CLDLIQ, CLDICEare atmospheric fields available from each ensemble member of the Community Atmosphere Model (CAM6). They provide weekly context for the other, more frequent, plant growth variablesER, HR, TSA, EFLX_LH_TOT, which come from the Community Land Model component of CESM.
Zarr format
The data on AWS are structured according to the Zarr storage format. There are independent Zarr stores for each time frequency/variable combination. The naming convention is: {frequency}/{variable}.zarr where:
- frequency =
weeklyorhourly6 - variable = one of the variable names listed in the table below.
The table shows available Zarr stores, including the variables, time ranges, and 2D or 3D nature (3D means multiple atmosphere levels). See also collection description and catalog file used by Intake-esm.
| variable | long_name | units | standard_name | vertical_levels | component | spatial_domain | start_time | end_time | frequency | path |
|---|---|---|---|---|---|---|---|---|---|---|
| HR | total heterotrophic respiration | g/m^2/s | surface_upward_mass_flux_of_carbon_dioxide_expressed_as_carbon_due_to_heterotrophic_respiration | 1 | lnd | global | 2012-01-01T06:00:00 | 2019-12-31T18:00:00 | hourly6 | s3://ncar-dart-cam6/hourly6/HR.zarr |
| TSA | 2m air temperature | K | air_temperature | 1 | lnd | global | 2012-01-01T06:00:00 | 2019-12-31T18:00:00 | hourly6 | s3://ncar-dart-cam6/hourly6/TSA.zarr |
| EFLX_LH_TOT | total latent heat flux [+ to atm] | W/m^2 | surface_upward_latent_heat_flux | 1 | lnd | global | 2012-01-01T06:00:00 | 2019-12-31T18:00:00 | hourly6 | s3://ncar-dart-cam6/hourly6/EFLX_LH_TOT.zarr |
| ER | total ecosystem respiration, autotrophic + heterotrophic | g/m^2/s | surface_upward_mass_flux_of_carbon_dioxide_expressed_as_carbon_due_to_total_ecosystem_respiration | 1 | lnd | global | 2012-01-01T06:00:00 | 2019-12-31T18:00:00 | hourly6 | s3://ncar-dart-cam6/hourly6/ER.zarr |
| VS | Meridional wind, staggered | m/s | northward_wind | 32 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/VS.zarr |
| PS | Surface pressure | Pa | surface_air_pressure | 1 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/PS.zarr |
| Q | Specific humidity | kg/kg | specific_humidity | 32 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/Q.zarr |
| US | Zonal wind, staggered | m/s | eastward_wind | 32 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/US.zarr |
| CLDICE | Grid box averaged cloud ice amount | kg/kg | mass_fraction_of_cloud_ice_in_air | 32 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/CLDICE.zarr |
| T | Temperature | K | air_temperature | 32 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/T.zarr |
| CLDLIQ | Grid box averaged cloud liquid amount | kg/kg | mass_fraction_of_cloud_liquid_water_in_air | 32 | atm | global | 2011-01-03T00:00:00 | 2019-12-30T00:00:00 | weekly | s3://ncar-dart-cam6/weekly/CLDLIQ.zarr |
Notebook Examples
- Jupyter Notebook creating a spaghetti plot of ensemble member values for any chosen variable, written in Python:
https://github.com/NCAR/ncar-dart-cam6/blob/main/notebooks/plot-ensemble-values.ipynb - Rendered (static) version of Jupyter Notebook: https://ncar-dart-cam6.s3-us-west-2.amazonaws.com/examples/plot-ensemble-values.html
Citations and Additional Resources
- AWS-hosted Subset: https://doi.org/10.26024/sprq-2d04
Bonnlander, B., and Raeder, K. (2021). “CAM6 Data Assimilation Research Testbed (DART) Reanalysis: Cloud-Optimized Dataset”, UCAR/NCAR Computational and Informations Systems Lab.
- Original Dataset: https://doi.org/10.5065/JG1E-8525
Data Assimilation Research Section/Computational & Information Systems/National Center for Atmospheric Research/University Corporation for Atmospheric Research (2020). “CAM6 Data Assimilation Research Testbed (DART) Reanalysis”, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Accessed 27 Oct 2021.
- Scientific Reports description of Original Dataset: https://doi.org/10.1038/s41598-021-92927-0
Raeder, K., Hoar, T.J., El Gharamti, M. et al (2021). “A new CAM6 + DART reanalysis with surface forcing from CAM6 to other CESM models”, Sci Rep 11, 16384.
- DART Software Home Page: https://docs.dart.ucar.edu/
- CESM Home Page: https://www.cesm.ucar.edu/
Contact
Data are freely available and reusable under the terms of the CC-BY-4.0 license. See Terms of Use. If you use these data, we request that you provide attribution in any derived products. The original, complete DART Reanalysis dataset and the AWS-hosted subset have different DOIs (Digital Object Identifiers) to reflect their differing scope and format.
If you have questions or want to request additional cloud-optimized variables from the original dataset, please reach out to us on our GitHub Discussions page or via email: rdahelp@ucar.edu.