Paper: One third of the Global soybean production failure in 2012 is attributable to climate change

Read the paper: In 2012, soybean crops failed in the three largest producing regions due to spatially compounded hot and dry weather across North and South America. Here, we present different impact storylines of the 2012 event, calculated by combining a statistical crop model with climate model simulations of 2012 conditions under pre-industrial, present-day (+1 °C), and future (+2 °C) conditions. These simulations use the ECHAM6 climate model and maintain the same observed seasonally evolving atmospheric circulation. Our results demonstrate that anthropogenic warming strongly amplifies the impacts of such a large-scale circulation pattern on global soybean production. Although the drought intensity is similar under different warming levels, larger crop losses are driven not only by warmer temperatures but also by stronger heat-moisture interactions. We estimate that one-third of the global soybean production deficit in 2012 is attributable to anthropogenic climate change. Future warming (+2 °C above pre-industrial) would further exacerbate production deficits by one-half compared to present-day 2012 conditions. This highlights the increasing intensity of global soybean production shocks with warming, requiring urgent adaptation strategies.

Paper: Artificial intelligence for modeling and understanding extreme weather and climate events

Read the paper: Artificial intelligence for modeling and understanding extreme weather and climate events
 » In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences, by improving weather forecasting, model emulation, parameter estimation, and the prediction of extreme events. The latter comes with specific challenges, such as developing accurate predictors from noisy, heterogeneous, small sample sizes and data with limited annotations. This paper reviews how AI is being used to analyze extreme climate events (like floods, droughts, wildfires, and heatwaves), highlighting the importance of creating accurate, transparent, and reliable AI models. (…) »
A collaboration between XAIDA and CLINT EU projects but also USMILE, AI4PEX, ELIAS, MeDiTwin, DeepCube and several national programmes.

Paper: Generative networks for spatio-temporal gap filling of Sentinel-2 reflectances

Read the paper: Generative networks for spatio-temporal gap filling of Sentinel-2 reflectances
« Earth observation from satellite sensors offers the possibility to monitor natural ecosystems by deriving spatially explicit and temporally resolved biogeophysical parameters. Optical remote sensing, however, suffers from missing data mainly due to the presence of clouds, sensor malfunctioning, and atmospheric conditions. This study proposes a novel deep learning architecture to address gap filling of satellite reflectances, more precisely the visible and near-infrared bands, and illustrates its performance at high-resolution Sentinel-2 data. (…) »

Paper: Attributing Venice Acqua Alta events to a changing climate and evaluating the efficacy of MoSE adaptation strategy

Read the paper: This research employs an innovative approach by utilizing analogues of atmospheric patterns to scrutinize four notable Acqua Alta events in the Venice lagoon, specifically those connected with intense Mediterranean cyclones that transpired in 1966, 2008, 2018, and 2019. The findings provide compelling evidence that modifications in atmospheric circulation, while not solely attributable to human activities, are undeniably linked to the increased severity of these events, thereby illuminating the vulnerability of Venice to the impacts of climate change. Furthermore, the study conducts a comprehensive assessment of the MoSE system, a crucial adaptation infrastructure designed to mitigate flooding in Venice, and underscores its effectiveness in protecting the city against events with historical analogues, particularly those akin to the catastrophic 1966 flood.

Paper: Heat Extremes in Western Europe warmed faster than simulated

Extract from the article, Figure 3.

Read the paper: Over the last 70 years, extreme heat in Western Europe has intensified with 3.4°C per degree global warming. A rate much larger than nearly anywhere else. Very few models capture the observed trend. None of them captures the large contribution from trends in atmospheric circulation.
The mismatch can be due to an underestimated circulation response to external forcing or underestimated unforced internal variability, or both. The former implies that heat extremes continue to intensify at an extreme rate, the latter that the trend continues but may slow down.