Dataset: Large Ensemble pCO2 Testbed from 3D climate models interpolated to 1x1 spatial grid over time period 1982-2017

Name: Large Ensemble pCO2 Testbed from 3D climate models interpolated to 1x1 spatial grid over time period 1982-2017
Published: 2021-02-09
Keywords: oceans

Final no updates expectedVersion 1 (2021-02-09)Dataset Type:model results

Principal Investigator: Galen A. McKinley (Lamont-Doherty Earth Observatory)

Contact: Lucas Gloege (Columbia University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)

Program: Ocean Carbon and Biogeochemistry (OCB)

Project: Collaborative Research: Uncertainty in Predictions of 21st Century Ocean Biogeochemical Change (ESM Uncertainty)

Abstract

These Large Ensemble Testbed (LET) data come from 3D climate models. The intention of this dataset was to evaluate ocean pCO2 gap-filling techniques. See Gloege et al. (2021) for further details about the Earth System Models run for the Large Ensembles. For more information about the large ensembles see https://www.cesm.ucar.edu/projects/community-projects/MMLEA. The methodology was an earth system model (ESM) large ensemble initialized with small perturbations such that the climate state e...

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Spatial Extent: N:90.00 E:180.00 S:-90.00 W:-180.00
Temporal Extent: 1982-01-01 - 2017-01-01

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File(s)	Type	Description	Action

Supplemental File(s)	Type	Description	Action
large_ensemble_testbed-code_840334_v1.zip (12.47 MB)	ZIP Archive (ZIP)	Analysis scripts in python to produce from Large Ensemble Testbed model output the figures in : Gloege, L., G.A. McKinley, P. Landschützer, A. Fay, T. Frölicher, J.C. Fyfe, T. Illyina, S.D. Jones, N.S. Lovenduski, C. Rödenbeck, K.B. Rodgers, S. Schlunegger and Y. Takano: Quantifying errors in observationally-based estimates of ocean carbon sink variability, in review 2020. https://doi.org/10.1002/essoar.10502036.2 The “Notebooks” directory includes notebooks to create each figure, and are labeled by figure. The “Scripts” and “Processing_scripts” directories include auxiliary scripts. The files in this .zip package were forked from original github repository https://github.com/lgloege/large_ensemble_testbed to BCO-DMO for archival purposes. Commit forked from https://github.com/lgloege/large_ensemble_testbed was d177ae3 by Lucas Gloege committed on Sep 2, 2020.	Download

Files

Supplemental Files

Filename: large_ensemble_testbed-code_840334_v1.zip (12.47 MB)
Type: ZIP Archive (ZIP)
Description: Analysis scripts in python to produce from Large Ensemble Testbed model output the figures in : Gloege, L., G.A. McKinley, P. Landschützer, A. Fay, T. Frölicher, J.C. Fyfe, T. Illyina, S.D. Jones, N.S. Lovenduski, C. Rödenbeck, K.B. Rodgers, S. Schlunegger and Y. Takano: Quantifying errors in observationally-based estimates of ocean carbon sink variability, in review 2020. https://doi.org/10.1002/essoar.10502036.2 The “Notebooks” directory includes notebooks to create each figure, and are labeled by figure. The “Scripts” and “Processing_scripts” directories include auxiliary scripts. The files in this .zip package were forked from original github repository https://github.com/lgloege/large_ensemble_testbed to BCO-DMO for archival purposes. Commit forked from https://github.com/lgloege/large_ensemble_testbed was d177ae3 by Lucas Gloege committed on Sep 2, 2020.

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In total, there are 100 unique ensemble members across four large ensembles (CanESM2, CESM-LENS, GFDL, MPI-GE). Testbed data can be downloaded from https://figshare.com/collections/Large_ensemble_pCO2_testbed/4568555.

The large ensemble testbed data are a collection of randomly selected ensemble members from 4 the following large ensemble projects:

- CanESM2 (http://data.ec.gc.ca/data/climate/scientificknowledge/the-eccc-climate-model-datasets-for-climate-science-and-impacts-research/the-canadian-earth-system-model-large-ensembles/)

- CESM-LENS (http://www.cesm.ucar.edu/projects/community-projects/LENS/)

- GFDL ( http://poseidon.princeton.edu)

- MPI-GE (https://mpimet.mpg.de/en/grand-ensemble/)

Analysis scripts in python are provided to produce from these model output the figures of Gloege et al. (2021). See "Data Files" for access to the analysis scripts. The “Notebooks” directory includes notebooks to create each figure, and are labeled by figure. The “Scripts” and “Processing_scripts” directories include auxiliary scripts.

Each ensemble member was interpolated from its native grid to a 1x1 degree lat/lon grid. The variables are monthly over the 1982-2017 time frame and sampled as the SOCATv5 data product. Historical atmospheric CO2 is used up to 2005 with RCP8.5 after 2005.

Gap-filling techniques can be evaluated across 100 unique climate states.

The methodology is an earth system model (ESM) large ensemble. The ESM is initialized with small perturbations such that the climate state evolves along a different phase of internal variability in each ensemble member. The forcing scenario is historical through 2005, then RCP8.5 after.

For more methodology details refer to the following publications.

MPI ocean pCO2 testbed:
N. Maher, et al., Th e Max Planck Institute Grand Ensemble-Enabling the Exploration of Climate System Variability. Journal of Advances in Modeling Earth Systems 11, 2050–2069 (2019).

GFDL ocean pCO2 testbed:
K. B. Rodgers, J. Lin, T. L. Frölicher, Emergence of multiple ocean ecosystem drivers in a large ensemble suite with an Earth system model. Biogeosciences 12, 3301–3320 (2015).

CESM ocean pCO2 testbed:
J. E. Kay, et al., The Community Earth System Model (CESM) large ensemble project: A community resource for studying climate change in the presence of internal climate variability. Bulletin of the American Meteorological Society 96, 1333–1349 (2015).

CanESM2 ocean pCO2 testbed:
J. C. Fyfe, et al., Large near-term projected snowpack loss over the western United States. Nature communications 8, 14996 (2017).

Related Datasets

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.8798999.v1

Gloege, L. (2019). CESM ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.8798999.V1

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.11477874.v1

Gloege, L. (2019). CanESM2 ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.11477874.V1

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.11477946.v1

Gloege, L. (2019). GFDL ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.11477946.V1

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.11477949.v1

Gloege, L. (2019). MPI ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.11477949.V1

CESM Large Ensemble Community Project (n.d.). Community Earth System Model - CESM®. CESM-LENS. http://www.cesm.ucar.edu/projects/community-projects/LENS.

Related Publications

Results

Gloege, L., McKinley, G. A., Landschützer, P., Fay, A. R., Frölicher, T. L., Fyfe, J. C., … Takano, Y. (2021). Quantifying Errors in Observationally Based Estimates of Ocean Carbon Sink Variability. Global Biogeochemical Cycles, 35(4). doi:10.1029/2020gb006788

Results

McKinley, G. A., Fay, A. R., Eddebbar, Y. A., Gloege, L., & Lovenduski, N. S. (2020). External Forcing Explains Recent Decadal Variability of the Ocean Carbon Sink. AGU Advances, 1(2). doi:10.1029/2019av000149

Different Version

Gloege, L. (2020). Large ensemble pCO2 testbed. figshare. https://doi.org/10.6084/M9.FIGSHARE.C.4568555.V2

Different Version

McKinley, G. (2020). Upper Open Carbon Box Model, McKinley et al. 2020, AGU Advances. figshare. https://doi.org/10.6084/M9.FIGSHARE.11983947.V1

Methods

Fyfe, J. C., Derksen, C., Mudryk, L., Flato, G. M., Santer, B. D., Swart, N. C., … Jiao, Y. (2017). Large near-term projected snowpack loss over the western United States. Nature Communications, 8(1). doi:10.1038/ncomms14996

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Dataset: Large Ensemble pCO2 Testbed from 3D climate models interpolated to 1x1 spatial grid over time period 1982-2017

Final no updates expectedVersion 1 (2021-02-09)Dataset Type:model results

Principal Investigator: Galen A. McKinley (Lamont-Doherty Earth Observatory)

Contact: Lucas Gloege (Columbia University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)

Program: Ocean Carbon and Biogeochemistry (OCB)

Project: Collaborative Research: Uncertainty in Predictions of 21st Century Ocean Biogeochemical Change (ESM Uncertainty)

Abstract

Cite Dataset

Spatial Extent: N:90.00 E:180.00 S:-90.00 W:-180.00
Temporal Extent: 1982-01-01 - 2017-01-01

XXX

Views

XX

Downloads

X

Citations

Download All Add to Cart

File(s)	Type	Description	Action

Supplemental File(s)	Type	Description	Action
large_ensemble_testbed-code_840334_v1.zip (12.47 MB)	ZIP Archive (ZIP)	Analysis scripts in python to produce from Large Ensemble Testbed model output the figures in : Gloege, L., G.A. McKinley, P. Landschützer, A. Fay, T. Frölicher, J.C. Fyfe, T. Illyina, S.D. Jones, N.S. Lovenduski, C. Rödenbeck, K.B. Rodgers, S. Schlunegger and Y. Takano: Quantifying errors in observationally-based estimates of ocean carbon sink variability, in review 2020. https://doi.org/10.1002/essoar.10502036.2 The “Notebooks” directory includes notebooks to create each figure, and are labeled by figure. The “Scripts” and “Processing_scripts” directories include auxiliary scripts. The files in this .zip package were forked from original github repository https://github.com/lgloege/large_ensemble_testbed to BCO-DMO for archival purposes. Commit forked from https://github.com/lgloege/large_ensemble_testbed was d177ae3 by Lucas Gloege committed on Sep 2, 2020.	Download

Files

Supplemental Files

Download

The large ensemble testbed data are a collection of randomly selected ensemble members from 4 the following large ensemble projects:

- CanESM2 (http://data.ec.gc.ca/data/climate/scientificknowledge/the-eccc-climate-model-datasets-for-climate-science-and-impacts-research/the-canadian-earth-system-model-large-ensembles/)

- CESM-LENS (http://www.cesm.ucar.edu/projects/community-projects/LENS/)

- GFDL ( http://poseidon.princeton.edu)

- MPI-GE (https://mpimet.mpg.de/en/grand-ensemble/)

Gap-filling techniques can be evaluated across 100 unique climate states.

For more methodology details refer to the following publications.

CanESM2 ocean pCO2 testbed:
J. C. Fyfe, et al., Large near-term projected snowpack loss over the western United States. Nature communications 8, 14996 (2017).

Related Datasets

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.8798999.v1

Gloege, L. (2019). CESM ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.8798999.V1

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.11477874.v1

Gloege, L. (2019). CanESM2 ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.11477874.V1

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.11477946.v1

Gloege, L. (2019). GFDL ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.11477946.V1

HasPart

Dataset: https://doi.org/10.6084/m9.figshare.11477949.v1

Gloege, L. (2019). MPI ocean pCO2 testbed [Data set]. figshare. https://doi.org/10.6084/M9.FIGSHARE.11477949.V1

CESM Large Ensemble Community Project (n.d.). Community Earth System Model - CESM®. CESM-LENS. http://www.cesm.ucar.edu/projects/community-projects/LENS.

Related Publications

Results

Different Version

Gloege, L. (2020). Large ensemble pCO2 testbed. figshare. https://doi.org/10.6084/M9.FIGSHARE.C.4568555.V2

Different Version

McKinley, G. (2020). Upper Open Carbon Box Model, McKinley et al. 2020, AGU Advances. figshare. https://doi.org/10.6084/M9.FIGSHARE.11983947.V1

Methods

Dataset: Large Ensemble pCO2 Testbed from 3D climate models interpolated to 1x1 spatial grid over time period 1982-2017

Principal Investigator: Galen A. McKinley (Lamont-Doherty Earth Observatory)

Contact: Lucas Gloege (Columbia University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)

Program: Ocean Carbon and Biogeochemistry (OCB)

Project: Collaborative Research: Uncertainty in Predictions of 21st Century Ocean Biogeochemical Change (ESM Uncertainty)

Abstract

Metadata

XXX

XX

X

Files

Supplemental Files

Related Datasets

Related Publications

Dataset: Large Ensemble pCO2 Testbed from 3D climate models interpolated to 1x1 spatial grid over time period 1982-2017

Principal Investigator: Galen A. McKinley (Lamont-Doherty Earth Observatory)

Contact: Lucas Gloege (Columbia University)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)

Program: Ocean Carbon and Biogeochemistry (OCB)

Project: Collaborative Research: Uncertainty in Predictions of 21st Century Ocean Biogeochemical Change (ESM Uncertainty)

Abstract

Metadata

XXX

XX

X

Files

Supplemental Files

Related Datasets

Related Publications