Data

Segmented Linear Integral Correlation Kernel Ensemble Reconstruction computer code and examples

Australian Antarctic Division
Roberts, J.L. ; ROBERTS, JASON LEIGH
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26179/cb03-d954&rft.title=Segmented Linear Integral Correlation Kernel Ensemble Reconstruction computer code and examples&rft.identifier=10.26179/cb03-d954&rft.publisher=Australian Antarctic Data Centre&rft.description=Segmented Linear Integral Correlation Kernel Ensemble Reconstruction (SLICKER) is a numerical method to reconstruct a (typically climate) time-series from multiple proxy data-series. SLICKER allows for- Univariate or multivariate reconstructions - Uneven and different data-spacing between allow proxies and the reconstruction target- Different linear and non-linear relationships between the target and each proxy- Ensembles to allow for robust estimates of the central tendency, uncertainty in the central tendency, and spread of the reconstruction- Parallel execution is available via OpenMPSLICKER is written in FORTRAN, with wrappers for MATLAB, Python and R. A windows executable is also supplied for users without access to a FORTRAN compiler.This code is also available at https://github.com/jlr581/SLICKERProgress Code: completed&rft.creator=Roberts, J.L. &rft.creator=ROBERTS, JASON LEIGH &rft.date=2025&rft.coverage=westlimit=147.28233; southlimit=-43.00132; eastlimit=147.30233; northlimit=-42.97132&rft.coverage=westlimit=147.28233; southlimit=-43.00132; eastlimit=147.30233; northlimit=-42.97132&rft_rights=These data are publicly available for download from the provided URL.&rft_rights=Attribution 4.0 International (CC BY 4.0) https://creativecommons.org/licenses/by/4.0/legalcode&rft_rights=This data set conforms to the CCBY Attribution License (http://creativecommons.org/licenses/by/4.0/). Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4537_Segmented_Linear_Integral_Correlation_Kernel_Ensemble_Reconstruction when using these data.&rft_rights=This metadata record is publicly available.&rft_subject=climatologyMeteorologyAtmosphere&rft_subject=EARTH SCIENCE > PALEOCLIMATE > PALEOCLIMATE RECONSTRUCTIONS&rft_subject=Computer > Computer&rft_subject=NOT APPLICABLE&rft_subject=AMD/AU&rft_subject=AMD&rft_subject=CEOS&rft_subject=GEOGRAPHIC REGION > POLAR&rft_subject=CONTINENT > AUSTRALIA/NEW ZEALAND > AUSTRALIA&rft.type=dataset&rft.language=English Access the data
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Attribution 4.0 International (CC BY 4.0)
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These data are publicly available for download from the provided URL.

This data set conforms to the CCBY Attribution License (http://creativecommons.org/licenses/by/4.0/). Please follow instructions listed in the citation reference provided at http://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4537_Segmented_Linear_Integral_Correlation_Kernel_Ensemble_Reconstruction when using these data.

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Segmented Linear Integral Correlation Kernel Ensemble Reconstruction (SLICKER) is a numerical method to reconstruct a (typically climate) time-series from multiple proxy data-series. SLICKER allows for
- Univariate or multivariate reconstructions
- Uneven and different data-spacing between allow proxies and the reconstruction target
- Different linear and non-linear relationships between the target and each proxy
- Ensembles to allow for robust estimates of the central tendency, uncertainty in the central tendency, and spread of the reconstruction
- Parallel execution is available via OpenMP

SLICKER is written in FORTRAN, with wrappers for MATLAB, Python and R. A windows executable is also supplied for users without access to a FORTRAN compiler.

This code is also available at https://github.com/jlr581/SLICKER

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Progress Code: completed

Notes

Purpose
Computer code (FORTRAN, with wrappers for MATLAB, Python and R) to reconstruct climate time-series from proxy data sets. The code works by generating an ensemble of reconstructions that all have the required correlation (calculated using the Segmented Linear Integral Correlation Kernel - SLICK) between each ensemble member and the proxies. Details of the SLICK correlation method can be found in Roberts JL, Jong LM, McCormack FS, Curran MA, Moy AD, Etheridge DM, et al. Integral correlation for uneven and differently sampled data, and its application to the Law Dome Antarctic climate record. Sci Rep. 2020;10(1):17477. https://doi.org/10.1038/s41598-020-74532-9 PMID: 33060793

Data time period: 2020-11-01 to 2023-09-30

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147.30233,-42.97132 147.30233,-43.00132 147.28233,-43.00132 147.28233,-42.97132 147.30233,-42.97132

147.29233,-42.98632

text: westlimit=147.28233; southlimit=-43.00132; eastlimit=147.30233; northlimit=-42.97132

Subjects
AMD | AMD/AU | CEOS | CONTINENT > AUSTRALIA/NEW ZEALAND > AUSTRALIA | Computer > Computer | EARTH SCIENCE > PALEOCLIMATE > PALEOCLIMATE RECONSTRUCTIONS | GEOGRAPHIC REGION > POLAR | NOT APPLICABLE | climatologyMeteorologyAtmosphere |

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Other Information
Download the dataset. (GET DATA > DIRECT DOWNLOAD)

url : https://data.aad.gov.au/eds/6146/download

Public information for AAS project 4537 (PROJECT HOME PAGE)

url : https://projects.aad.gov.au/report_project_public.cfm?project_no=4537

Citation reference for this metadata record and dataset. (VIEW RELATED INFORMATION)

url : https://data.aad.gov.au/aadc/metadata/citation.cfm?entry_id=AAS_4537_Segmented_Linear_Integral_Correlation_Kernel_Ensemble_Reconstruction

Identifiers
  • DOI : 10.26179/CB03-D954
  • global : AAS_4537_Segmented_Linear_Integral_Correlation_Kernel_Ensemble_Reconstruction
ACN 633 798 857