Preprints
https://doi.org/10.5194/egusphere-2023-2918
https://doi.org/10.5194/egusphere-2023-2918
15 Jan 2024
 | 15 Jan 2024
Status: this preprint is open for discussion and under review for Climate of the Past (CP).

Dynamical downscaling and data assimilation for a cold-air outbreak in the European Alps during the Year Without Summer 1816

Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann

Abstract. The “Year Without Summer” of 1816 was characterized by extraordinarily cold and wet periods in Central Europe, and it was associated with severe crop failures, famine, and socio-economic disruptions. From a modern perspective and beyond its tragic consequences, the summer of 1816 represents a rare occasion to analyze the adverse weather (and its impacts) after a major volcanic eruption. However, given the distant past, obtaining the high-resolution data needed for such studies is a challenge. In our approach, we use dynamical downscaling, in combination with 3D-variational data assimilation of early instrumental observations, for assessing a cold-air outbreak in early June 1816. We find that the cold spell is well represented in the coarse-resolution 20th Century Reanalysis product, which is used for initializing the regional Weather Research and Forecasting Model. Our downscaling simulations (including a 19th-century land-use scheme) reproduce and explain meteorological processes well at regional to local scales, such as a foehn wind situation over the Alps with much lower temperatures on its northern side. Simulated weather variables, such as cloud cover or rainy days, are simulated in good agreement with (eye) observations and (independent) measurements, with small differences between the simulations with and without data assimilation. However, validations with partly independent station data show that simulations with assimilated pressure and temperature measurements are closer to the observations, e.g. regarding temperatures during the coldest night, for which snowfall as low as the Swiss Plateau was reported, and a rapid pressure increase thereafter. General improvements from data assimilation are also evident in simple quantitative analyses of temperature and pressure. In turn, data assimilation requires careful selection, preprocessing and bias-adjustment of the underlying observations. Our findings underline the great value of digitizing efforts of early instrumental data and provide novel opportunities to learn from extreme weather and climate events as far back as 200 years or more.

Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann

Status: open (until 28 Mar 2024)

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  • RC1: 'Comment on egusphere-2023-2918', Anonymous Referee #1, 28 Feb 2024 reply
Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann

Data sets

Dynamical downscaling and data assimilation for a cold-air outbreak in the European Alps during the Year Without Summer 1816 Peter Stucki https://doi.org/10.48350/189671

Model code and software

Dynamical downscaling and data assimilation for a cold-air outbreak in the European Alps during the Year Without Summer 1816 Peter Stucki https://doi.org/10.48350/189671

Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann

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Short summary
In our work, we reconstruct the weather of the extremely cold and wet summer in 1816 using a weather forecasting model to obtain high-resolution, three-dimensional weather simulations. We refine our simulations with surface pressure and temperature observations, representing a novel approach for this period. Our results show that this approach yields detailed and accurate weather reconstructions, opening the door to analysing past weather events and their impacts in detail.