Reacción a "The heavy rainfall of the Valencia DANA was mainly due to climate change, according to a study"

The study presents a comparative analysis of the formation of a DANA such as the one that occurred at the end of October in Spain, with respect to what this same DANA would have been like in the past (1979-2001). This analysis, carried out by a team with extensive experience in extreme meteorological phenomena, within the ClimaMeter framework, is based on the observation of variables such as: surface pressure, temperature, precipitation and wind. The approach used is to look for similar weather situations observed in the past to assess the influence of climate change on the intensity and characteristics of the event. This methodology allows us to identify significant increases in precipitation and temperatures in the Mediterranean region, suggesting that global warming may have intensified the event and its impact. In this sense, studies such as this one are crucial to anticipate future events, especially in vulnerable regions such as the Mediterranean, where HLDD can have devastating effects in social and economic terms.

However, the study also has limitations that need to be considered. The authors themselves acknowledge that confidence in the robustness of this approach is low due to the exceptionality of the event in the historical data record. To compensate for this lack of direct comparability, they have had to extend the analysis to analogous events that, although similar, do not share exactly the same characteristics. This limitation in the availability of specific historical data reduces the precision with which the event can be attributed solely to anthropogenic climate change. Furthermore, the complexity of factors such as the Atlantic Multidecadal Oscillation introduces uncertainty as to whether the event is a response to natural climate variability alone or to the direct influence of global warming.

From a personal perspective, I believe that this type of study is essential to improve the predictive capacity for future extreme events. Modelling also plays an essential role in this anticipation, as improving the accuracy of models through high-resolution simulations and real-time analysis, based on observations of physical variables, would allow more accurate forecasting of the intensity and location of storms.