Preprints
https://doi.org/10.5194/egusphere-2022-1058
https://doi.org/10.5194/egusphere-2022-1058
 
21 Oct 2022
21 Oct 2022
Status: this preprint is open for discussion.

Historical rainfall data in Northern Italy predict larger meteorological drought hazard than climate projections

Rui Guo and Alberto Montanari Rui Guo and Alberto Montanari
  • Department of Civil, Chemical, Environmental and Materials Engineering (DICAM), University of Bologna, Bologna, Italy

Abstract. Simulation of daily rainfall for the region of Bologna produced by 13 climate models for the period 1850–2100 are compared with the historical series of daily rainfall observed in Bologna for the period 1850–2014, and analysed to assess meteorological drought changes up to 2100. In particular, we focus on annual rainfall data, seasonality and drought events to derive information on the future development of critical events for water resources availability. The results prove that rainfall statistics, including seasonal patterns, are fairly well simulated by models, while the historical sequence of annual rainfall is not satisfactorily reproduced. In terms of meteorological droughts, we conclude that historical data analysis under the assumption of stationarity may depict a more critical future with respect to climate model simulations, therefore outlining important technical indications.

Rui Guo and Alberto Montanari

Status: open (until 16 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Rui Guo and Alberto Montanari

Rui Guo and Alberto Montanari

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Short summary
The present study refers to the region of Bologna, where the availability of a 209-year-long daily rainfall series allows us to make a unique assessment of global climate models' reliability and their predicted changes in rainfall and multiyear droughts. Our results suggest carefully considering the impact of uncertainty when designing climate change adaptation policies for droughts. Rigorous use and comprehensive interpretation of the available information are needed to avoid mismanagement.