Constraining low-frequency variability in climate projections to predict climate on decadal to multi-decadal timescales – a poor man's initialized prediction system

Mahmood, Rashed; Donat, Markus G.; Ortega, Pablo; Doblas-Reyes, Francisco J.; Delgado-Torres, Carlos; Samsó, Margarida; Bretonnière, Pierre-Antoine

doi:https://doi.org/10.5194/esd-13-1437-2022

Articles | Volume 13, issue 4

https://doi.org/10.5194/esd-13-1437-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/esd-13-1437-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 4

Research article

|

19 Oct 2022

Research article |

| 19 Oct 2022

Constraining low-frequency variability in climate projections to predict climate on decadal to multi-decadal timescales – a poor man's initialized prediction system

Rashed Mahmood, Markus G. Donat, Pablo Ortega, Francisco J. Doblas-Reyes, Carlos Delgado-Torres, Margarida Samsó, and Pierre-Antoine Bretonnière

Supplement

https://doi.org/10.5194/esd-13-1437-2022-supplement

Data sets

NOAA Extended Reconstructed SST V5 NOAA https://psl.noaa.gov/data/gridded/data.noaa.ersst.v5.html

Temperature Climate Research Unit https://crudata.uea.ac.uk/cru/data/temperature/

High-resolution gridded datasets (and derived products) Climate Research Unit https://crudata.uea.ac.uk/cru/data/hrg/

GPCC DWD https://www.dwd.de/EN/ourservices/gpcc/gpcc.html

ERA5 ECMWF https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5

Gridded Dataset NOAA https://www.ncei.noaa.gov/access/monitoring/global-temperature-anomalies/grid

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Short summary

Near-term climate change projections are strongly affected by the uncertainty from internal climate variability. Here we present a novel approach to reduce such uncertainty by constraining decadal-scale variability in the projections using observations. The constrained ensembles show significant added value over the unconstrained ensemble in predicting global climate 2 decades ahead. We also show the applicability of regional constraints for attributing predictability to certain ocean regions.