CIGAR-CS Global Ocean Reanalysis 1961-2022 Ocean Heat Content
Description
Dataset describing the CIGAR-CS (v1) reanalysis Ocean Heat Content.
CIGAR: The CNR ISMAR Global Historical Reanalysis (http://cigar.ismar.cnr.it)
CS: Contemporary Stream
CIGAR-CS is an ensemble ocean reanalysis with 32 members, covering the period from 1959 to real-time, and based on the NEMO4 model, a variational data assimilation scheme with variational quality control of in-situ profiles and time-varying background-error covariances, a surface correction scheme of air-sea fluxes, a deep-ocean bias correction scheme, and an advanced ensemble generation scheme with stochastic physics and perturbation of input datasets.
It includes yearly mean files for each of the 32 ensemble members from 1961-2022 for these selected variables:
- Ocean heat content (full column)
- Temperature analysis increments
- Surface net air-sea heat fluxes
Heat fluxes and analysis increments are provided for potential use in ocean warming attribution studies.
To ease the use of the OHC data, all fields are remapped from the irregular ORCA1 tripolar grid (1/3deg to 1deg of spatial resolution) to a regular 0.5degx0.5deg grid through bilinear interpolation.
(Note: all diagnostics in the reference paper were computed on the native irregular grid; possible differences, therefore, may exist and are due to the errors introduced by the interpolation)
Files
CIGAR-CS_OHC.zip
Files
(3.5 GB)
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md5:7a3c8d2260784fd10e286426f9860ff7
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Additional details
References
- Storto A and Yang C (2023) Stochastic schemes for the perturbation of the atmospheric boundary conditions in ocean general circulation models. Front. Mar. Sci. 10:1155803. https://doi.org/10.3389/fmars.2023.1155803
- Storto, A, Andriopoulos, P. A new stochastic ocean physics package and its application to hybrid-covariance data assimilation. Q J R Meteorol Soc . 2021; 1691–1725. https://doi.org/10.1002/qj.3990
- Yang, C., Storto, A. & Masina, S. Quantifying the effects of observational constraints and uncertainty in atmospheric forcing on historical ocean reanalyses. Clim Dyn 52 , 3321–3342 (2019). https://doi.org/10.1007/s00382-018-4331-z
- Storto A, Alvera-Azcárate A, Balmaseda MA, Barth A, Chevallier M, Counillon F, Domingues CM, Drevillon M, Drillet Y, Forget G, Garric G, Haines K, Hernandez F, Iovino D, Jackson LC, Lellouche J-M, Masina S, Mayer M, Oke PR, Penny SG, Peterson KA, Yang C and Zuo H (2019) Ocean Reanalyses: Recent Advances and Unsolved Challenges. Front. Mar. Sci. 6:418. https://doi.org/10.3389/fmars.2019.00418
- Storto A., Oddo P., Cipollone A., Mirouze I., Lemieux B. (2018). Extending an oceanographic variational scheme to allow for affordable hybrid and four-dimensional data assimilation. Ocean Modelling. 128, 67–86. https://doi.org/10.1016/j.ocemod.2018.06.005
- Yang, C., Masina, S. and Storto, A. (2017), Historical ocean reanalyses (1900–2010) using different data assimilation strategies. Q.J.R. Meteorol. Soc., 143: 479-493. https://doi.org/10.1002/qj.2936