Teleconnections that link climate processes at widely separated spatial locations form a key component of the climate system. Their analysis has traditionally been based on means, climatologies, correlations, or spectral properties, which cannot always reveal the dynamical mechanisms between different climatological processes. More recently, causal discovery methods based either on time series at grid locations or on modes of variability, estimated through dimension-reduction methods, have been introduced. A major challenge in the development of such analysis methods is a lack of ground truth benchmark datasets that have facilitated improvements in many parts of machine learning. Here, we present a simplified stochastic climate model that outputs gridded data and represents climate modes and their teleconnections through a spatially aggregated vector-autoregressive model. The model is used to construct benchmarks and evaluate a range of analysis methods. The results highlight that the model can be successfully used to benchmark different causal discovery methods for spatiotemporal data and show their strengths and weaknesses. Furthermore, we introduce a novel causal discovery method at the grid level and demonstrate that it has orders of magnitude better performance than the current approaches. Improved causal analysis tools for spatiotemporal climate data are pivotal to advance process-based understanding and climate model evaluation.

This paper describes the relationships between large-scale modes of climate variability and its related weather types with the fluctuations in the yield of maize crops in Veneto, Italy. The teleconnections analysed in this work are the winter North Atlantic Oscillation (NAO) and the summer North Atlantic Oscillation (SNAO); the West African monsoon (WAM) and the Intertropical Front (ITF). Despite that these indices are not rigorously linked to one another, they result in being considerably related to atmospheric circulation regimes and associated weather types. They have an impact on temperature and precipitation patterns in Italy and on yields of maize crops in Veneto, a region located in northeast Italy. Yields are strongly affected by large-scale temperate and tropical variability directly through three main circulation regimes. Troughing weather regimes that produced below average temperatures depress yields over the entire Veneto region, as does the zonal regime that affects rainfall. Results confirm the relevance of large-scale modes and associated weather regimes and types on maize crop yields fluctuations in Veneto.

The paper presents results from a study examining the relationship between large-scale modes of climate variability with the fluctuations in the yield of barley, durum wheat, olives and sunflower crops in Tuscany, Italy. In particular, the blocking circulation over the growing season, with associated hot and dry conditions, decreased yield for olive crops, barley and durum wheat. The teleconnections analysed in this study are the winter North Atlantic Oscillation (NAO) and the Summer North Atlantic Oscillation (SNAO); the West African Monsoon (WAM) and the Intertropical Front (ITF); and although NAO, SNAO, ITF and WAM are not strictly related to each other, the values of these indices are strongly related to the atmospheric circulation regimes and related weather types. Thus, they have an impact on precipitation and temperature patterns in Italy and on yields of important crops in Tuscany. Results show that the large-scale temperate and tropical variability directly influences the crop yield through three main circulation regimes. These patterns illustrate the importance of the large-scale modes, which, together with the associated weather types, have an impact directly on Tuscan crop yields; both barley and olive yields decline significantly when the ITF is further north with warmer and drier conditions in Italy.

Millennial to submillennial marine oscillations that are linked with the North Atlantic's Heinrich events and Dansgaard–Oeschger cycles have been reported recently from the Alboran Sea, revealing a close ocean-atmosphere coupling in the Mediterranean region. We present a high-resolution record of lithogenic fraction variability along IMAGES Core MD 95-2043 from the Alboran Sea that we use to infer fluctuations of fluvial and eolian inputs to the core site during periods of rapid climate change, between 28,000 and 48,000 cal yr B.P. Comparison with geochemical and pollen records from the same core enables end-member compositions to be determined and to document fluctuations of fluvial and eolian inputs on millennial and faster timescales. Our data document increases in northward Saharan dust transports during periods of strengthened atmospheric circulation in high northern latitudes. From this we derive two atmospheric scenarios which are linked with the intensity of meridional atmospheric pressure gradients in the North Atlantic region.