ALBERT

Description: Tropical cyclones (TCs) are one of the most severe weather hazards in the tropics, causing many human deaths and substantial property loss. Therefore, it is always urgent to significantly reduce systematic errors that may hinder the accurate forecast of TC activity. To evaluate the ability of the Euro-Mediterranean Center for Climate Change (CMCC) forecast system to represent TC activity and to verify the feasibility of TCs forecast, we use a new version of the CMCC Seasonal Prediction System (SPS3.5), which configures with high spatial resolution (0.5 degrees) in the atmospheric component and a large (40) number of ensemble members. We compared SPS3.5 hindcasts from 1998 to 2016 July-September with observed TC tracks derived from the International Best Track Archive for Climate Stewardship (IBTrACS). To identify storms and track their trajectories in SPS3.5, we use the Geophysical Fluid Dynamics Laboratory (GFDL) Tropical Cyclone tracking algorithm and set strict thresholds to ensure the authenticity of the captured TCs. We find that the SPS3.5 system captures the spatial distributions in the North Hemisphere (R~0.8) well, although it underestimates TCs' number magnitude, which relates to the model resolution and thresholds. TCs spatial distribution is best captured over the Pacific, where the largest peak season (August) is covered by our dataset, while lower-skill is shown over the North Atlantic Ocean and the North Indian Ocean. For TC variability, the model performs well only in the Western North Pacific (R up to 0.6). We also investigate the relationship between TCs' intensity and interannual variability with ENSO.

Description: Dominant Euro-Atlantic modes of large-scale atmospheric variability, such as the North Atlantic Oscillation (NAO), the Eastern Atlantic pattern (EA), the Eastern Atlantic Western Russian pattern (EAWR) and the Scandinavian pattern (SCA) are known to significantly affect interannual-to-decadal climatic and hydroclimatic variability of the Mediterranean region especially during the winter season. Whereas previous studies assessed the impacts of these modes on air-sea heat and freshwater fluxes over the Mediterranean Sea, few studies explored the propagation of these signals from the surface towards the interior of the Mediterranean Sea and mostly they relied on the use of single model simulations.In this contribution we investigate the Mediterranean thermohaline response to winter forcing from NAO, EA, EAWR and SCA using a multi-model analysis of evaluation, historical and future scenarios simulations of the Med-Cordex initiative. We present results from a composite analysis around strong positive and negative phases of these modes to track the propagation of the associated signals from the sea surface towards the Mediterranean interior in key regions such as the South Adriatic, the Aegean and Levantine Seas and the Gulf of Lion. Different simulations show only a partial agreement as far as the identification of the modes mostly contributing to deep water formation is concerned.

Description: Aspects of low-frequency variability of the atmospheric circulation in the Euro-Atlantic domain, such as the frequency of wintertime blocking and the North Atlantic Oscillation, have been found to exhibit significant predictability in large-ensemble seasonal and decadal forecasts. Part of this predictability arguably stems from the realistic initialization of the North Atlantic ocean, which influences the atmospheric circulation through air–sea interaction. Yet, various model deficiencies, such as systematic model biases and the misrepresentation of coupled processes may be limiting the emergence of the associated predictable signals. We present results from three recent studies indicating that increasing model resolution (typically moving to 0.25° in the ocean and 0.5° in the atmosphere) is crucial for mitigating various such deficiencies. Specifically, we show that: (i) increasing model resolution in a multi-model ensemble of coupled historical HighResMIP simulations leads to mitigating certain long-standing extratropical SST biases that contribute to the under-representation of European blocking, (ii) increasing the atmospheric model resolution in a multi-model set of historical HighResMIP simulations forced with observed sea surface temperatures allows for the realistic representation of the atmospheric circulation response to interannual Gulf Stream variability, expectedly important for predictability, and (iii) increasing model resolution in a multi-model ensemble of coupled HighResMIP simulations improves the realism of extratropical North Atlantic atmosphere–ocean variability through mitigating oceanic biases that control the variability of the deep ocean circulation at multi-annual and longer timescales. Current work focuses on evaluating how such model deficiencies affect seasonal and decadal predictability.