Enhanced climate models synchronised
Climate predictions are increasingly being used to inform policy at national and international levels. However, predicting climate and its impacts remains a major challenge, with large uncertainties existing, particularly at a regional level. The EU-funded project STEPS (Strategies toward enhancing prediction of climate and its impacts) worked to contribute to the creation of a climate super model. The team aimed to reduce model error and thereby improve climate predictions. Researchers built a super model by joining two versions of one climate model together only at the ocean-atmosphere interface. The result was a significant improvement in simulating the climate of the tropical Pacific. On enhancing synchronisation of climate models, STEPS developed generic software that combines different climate model components. STEPS also increased understanding of the Atlantic multi-decadal variability (AMV), a North Atlantic basin-wide sea surface temperature fluctuation on multi-decadal timescales. Researchers constructed a multi-proxy record that extends to 90 years before the instrumental record, thereby demonstrating the persistence of AMV in the Atlantic Ocean. Researchers analysed atmospheric model simulations to increase understanding of tropical cyclones, which may change regionally because of global warming. STEPS showed how unusual warming in the central Pacific impacts large-scale atmospheric circulation and reduced rainfall over Ethiopia. The project found that up to 50 % of seasonal rainfall variability over parts of the Ethiopian highlands is driven by warming anomalies over the tropical Pacific. STEPs outcomes will help close the knowledge gap between predicting climate and its associated impacts, such as changes to major crops and spread of vector-borne diseases. Project developments will help scientists and decision-makers make more accurate predictions at the regional level.