Toward background error covariance hybridization for climate prediction
Description
The Norwegian Climate Prediction Model (NorCPM) combines the Norwegian Earth System Model (NorESM) with the Ensemble Kalman Filter (EnKF) and aims at providing seasonal to decadal climate predictions. On nowadays supercomputer, it is not computationally tractable to run more than 30 members (and 5 members with the high resolution version of NorCPM), which results in sampling issues when estimating the background error covariance matrix.
To overcome these issues, an hybridization method derived from previous work from (Hamill and Snyder, 2000) has been used and led to the implemeantion of 2 methods: climatological hybridization and dual resolution. These 2 methods allow for a reduction of sampling error when compared to standard EnKF.
The hybrid covariance method are tested with the quasi-geostrophic model within the DAPPER package. It is shown that the method outperforms the standard implementation of the EnKF in particular for small ensemble size.
Further work will assesses the performance of the two methods with NorCPM in the context of twin experiments.
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climate_prediction_workshop.pdf
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Additional details
Funding
- Blue-Action – Arctic Impact on Weather and Climate 727852
- European Commission
- PRIMAVERA – PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment 641727
- European Commission
- CRESCENDO – Coordinated Research in Earth Systems and Climate: Experiments, kNowledge, Dissemination and Outreach 641816
- European Commission
- APPLICATE – Advanced Prediction in Polar regions and beyond: Modelling, observing system design and LInkages associated with ArctiC ClimATE change 727862
- European Commission
- EUCP – European Climate Prediction system 776613
- European Commission