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Gridded observational products of the main climate parameters are essential in climate science. Current interpolation approaches, implemented to derive such products, often lack of a proper uncertainty propagation and representation. In this study, we introduce a Bayesian spatiotemporal approach based on the integrated nested Laplace approximation (INLA) and the stochastic partial differential equation (SPDE). The method is described and discussed by using a real case study based on high‐resolution monthly 2‐m maximum (Tmax) and minimum (Tmin) air temperature over Italy in 1961–2020. The INLA‐SPDE based approach is able to properly take into account uncertainties in the final gridded products and offers interesting promising advantages to deal with nonstationary and non‐Gaussian multisource data. [ABSTRACT FROM AUTHOR]

We review, analyse, and discuss the recent evolution and the future sustainability of rice paddy fields in Italy—the largest European producer—using outcomes from available literature and new analysis of agricultural statistics from local authorities, land‐use and surface temperature data from remote sensing, hydrological and climate data from observations, and numerical models. We show that Italy can be considered a good representative for rice cultivation in temperate regions that are not freshwater‐limited. However, this situation is changing. We report strong evidence linking the largest European reduction of seasonal surface water that have gradually occurred since 2000 over the rice cultivation area of Northern Italy, to the change in paddy management from traditional continuous flooding to a less greenhouse‐gases‐emitting practice, that is, dry‐seeding with postponed flooding. This change was accompanied by several improvements in agro‐practices and crop varieties. Concurrently, regional climate rapidly shifted towards sunnier weather conditions that partly contributed to higher rice yields and stability, decoupling yields from inter‐annual climate variability, but also reducing water availability. In Northern Italy, a complete shift of rice cultivation towards dry‐seeding is not compatible with seasonal water availability, and a number of drawbacks, with respect to the traditional wet seeding, are also identified from literature review. Therefore, in the context of near‐term climate change, sustainable rice cultivation in the middle latitudes seems achievable (without limiting production and/or increasing volatility) by balancing traditional and dry‐seeding. [ABSTRACT FROM AUTHOR]

An analysis of Italian seasonal temperatures from 1961 to 2006 was carried out, using homogenized data from 49 synoptic stations well distributed throughout Italy. The results show remarkable differences among seasons. Stationarity characterizes winter series, except for Northern Italy (where a warming trend from 1961 is identified); a positive trend over the entire period is recognized for spring series. Summer series are marked by a negative trend until 1981 and by a positive trend afterwards; finally, autumn series show a warming starting from 1970. The relationship between seasonal temperatures and four teleconnection patterns (North Atlantic Oscillation, East Atlantic Pattern, Scandinavian Pattern and Arctic Oscillation) influencing European climate was investigated through Spearman rank correlation and composites. Among the results, the strong linear correlation with the East Atlantic Pattern in all seasons but autumn is remarkable; moreover, the explained variance varies between 31.9% and 50.4% (leaving out autumn). Besides these four atmospheric patterns the role of other factors (e.g. soil moisture) is not dealt with, but their importance and the need for more investigation is pointed out. [ABSTRACT FROM AUTHOR]

The article presents an analysis of annual and seasonal precipitation series of period 1961-2006 developed from 59 synoptic meteorological stations across Italy. It applied rotated principal component analysis (PCA) to monthly data and generated loading maps. The study found that annual cumulated precipitation series did not show significant levels of change and that only in winter was a precipitation trend seen in northern and Central Italy.

Statistical, data-driven methods are considered good alternatives to process-based models for the sub-national monitoring of cereal crop yields, since they can flexibly handle large datasets and can be calibrated simultaneously to different areas. Here, we assess the influence of several characteristics on the ability of these methods to forecast cereal yields at the local scale. We look at two diverse agro-climatic Italian regions and analyze the most relevant types of cereal crops produced (wheat, barley, maize and rice). Models of different complexity levels are built for all species by considering six meteorological and remote sensing indicators as candidate predictive variables. Yield data at three different spatial aggregation scales were retrieved from a comprehensive, farm-level dataset over the period 2001–2015. Overall, our results suggest the better predictability of summer crops compared to winter crops, irrespective of the model considered, reflecting a more intricate relationship among winter cereals, their physiology and weather patterns. At higher spatial resolutions, more sophisticated modelling techniques resting on feature selection from multiple indicators outperformed more parsimonious linear models. These gains, however, vanished as data were further aggregated spatially, with the predictive ability of all competing models converging at the agricultural district and province levels. Feature-selection models tended to elicit more satellite-based than meteorological indicators, with a preference for temperature indicators in summer crops, whereas variables describing the water content of the soil/plant were more often selected in winter crops. The selected features were, in general, equally distributed along the plant growing cycle. [ABSTRACT FROM AUTHOR]

The largest European rice production is located in northern Italy, where paddy field flooding management evolved from the traditional continuous flooding to a less greenhouse-gases-emitting practice i.e. dry seeding with postponed flooding. This agro-management and land-use change resulted in the largest anthropogenic reduction of seasonal surface water extent detected in Europe around year 2000. At the same time, regional climate rapidly changed towards sunnier weather conditions that contributed to higher rice yields and stability, but also reduced water availability. Before 2000, yields were strongly anti-correlated to the downstream river discharge, which acted as a proxy for unfavorable weather conditions. Analogue conditions currently characterise other important rice producing countries such as Uruguay, Argentina, North Korea and USA. In the context of near-term climate changes, sustainable rice cultivation in the middle latitudes seems achievable without limiting production and/or increasing volatility. However, albeit saving water, the shift to rice dry seeding is inconsistent with the seasonality of water availability in northern Italy. This analysis also identifies environmental disadvantages of dry seeding compared to the traditional wet seeding. [ABSTRACT FROM AUTHOR]