Deliverable 6.11 Climate model initialization V2

• Main Authors: Kruschke, Tim, Karami, Mehdi Pasha, Navarro, Juan C. Acosta, Vladimir Lapin, Pablo Ortega, Counillon, François, Gustafsson, David
• Format: Report
• Language: English
• Published: 2021
• Subjects: Arctic; INTAROS; Climate Model; Climate Prediction; Sea Ice Concentration; River Discharge; Observation Systems; North Atlantic; Sea ice
• Online Access: https://zenodo.org/record/7138627; https://doi.org/10.5281/zenodo.7138627

This report describes the final results of the work performed in Task 6.1, which has the main goal of improving the skill of climate predictions, investigating the benefits related to the exploitation of INTAROS data. Such benefits demonstrate a clear potential for users of Arctic data and stakeholders of climate prediction. A key ingredient to skillful seasonal-to-decadal climate prediction is the use of high-quality observational data, that cover a sufficiently long period, typically at least a few decades to test robustly their impact. This emphasizes the need - from a user perspective - to sustain and continue the production of the various iAOS products. The works in the task made use of three different datasets produced in INTAROS, namely CERSAT sea-ice concentrations, SMOS sea-thickness, and Arctic-HYCOS river discharges. The results found in Task 6.1 are: 1. CERSAT sea-ice concentrations were successfully used to assess the skill of SMHI’s quasi-operational decadal climate predictions with EC-Earth3 regarding September Northern Hemisphere sea-ice area for a lead time of 11 months (based on the period 1992-2020; correlation of 0.83) and the quality of new assimilation experiments providing potentially better initial conditions for climate predictions (correlation of 0.9 including long-term trend; 0.58 for detrended data, i.e. interannual variability). 2. CERSAT sea-ice concentrations were assimilated for BSC’s seasonal climate prediction system employing EC-Earth3. It is shown that the assimilation of sea-ice concentrations does not yield significant benefit for winter seasonal predictions (started on 1 November) but do have a remarkable positive impact on summer seasonal predictions (started on 1 May) regarding the sea-ice edge but also remote North Atlantic SSTs. The latter is shown to be the result of a so-called atmospheric bridge translating the improved sea-ice representation via more realistic large-scale atmospheric variability into the SST-signal. 3. Anomalies derived from sea-ice concentrations ...