Articles | Volume 6, issue 2
https://doi.org/10.5194/wcd-6-571-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-6-571-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 May 2025
Research article |
| 21 May 2025
| 21 May 2025
Weather type reconstruction using machine learning approaches
Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
Institute of Geography, University of Bern, Bern 3012, Switzerland
Lena Wilhelm
Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
Institute of Geography, University of Bern, Bern 3012, Switzerland
Yuri Brugnara
Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
Institute of Geography, University of Bern, Bern 3012, Switzerland
now at: Empa, Dübendorf 8600, Switzerland
Noemi Imfeld
Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
Institute of Geography, University of Bern, Bern 3012, Switzerland
Stefan Brönnimann
Oeschger Centre for Climate Change Research, University of Bern, Bern 3012, Switzerland
Institute of Geography, University of Bern, Bern 3012, Switzerland
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Clim. Past, 20, 2327–2348, https://doi.org/10.5194/cp-20-2327-2024, https://doi.org/10.5194/cp-20-2327-2024, 2024
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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 analyzing past weather events and their impacts in detail.
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The year 1740 was the coldest in central Europe since at least 1421. New monthly global climate reconstructions, together with daily weather reconstructions, allow a detailed view of this climatic event. Following several severe cold spells in January and February, a persistent circulation pattern with blocking over the British Isles caused northerly flow towards western Europe during a large part of the year. It was one of the strongest, arguably unforced excursions in European temperature.
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Climate reconstructions give insights into monthly and seasonal climate variability of the past few hundred years. However, to understand past extreme weather events and to relate them to impacts, for example to periods of extreme floods, reconstructions on a daily timescale are needed. Here, we present a reconstruction of 258 years of high-resolution daily temperature and precipitation fields for Switzerland covering the period 1763 to 2020, which is based on instrumental measurements.
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We digitized dozens of weather journals containing temperature measurements from in and around Bern and Zurich. They cover over a century before the creation of a national weather service in Switzerland. With these data we could create daily temperature series for the two cities that span the last 265 years. We found that the pre-industrial climate on the Swiss Plateau was colder than suggested by previously available instrumental data sets and about 2.5 °C colder than the present-day climate.
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This preprint is open for discussion and under review for Climate of the Past (CP).
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Narrative historical records of wine production in Central Europe date back to 1200. A study of taxes paid to authorities in the French-Luxembourg Moselle region, Germany, and the Swiss Plateau over the last few centuries shows that wine yields provide indirect indications of summer temperatures when the impact of heavy frosts is taken into account. This enables climate reconstructions based on tree rings to be refined and confirmed. Occasionally, poor harvests gave rise to witch hunts.
Noemi Imfeld and Stefan Brönnimann
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We extend Swiss daily climate reconstructions from 1763 to 2020 to six additional variables at 1×1 km resolution using analogue resampling and data assimilation. Wind and temperature reconstructions show reasonable skill, while humidity and sunshine duration perform less well. Application to historical wild fire events demonstrates the data set’s potential for impact studies. This is the first Swiss data set providing several variables at a high-resolution of 1x1 km and going back to 1763.
Killian P. Brennan and Lena Wilhelm
EGUsphere, https://doi.org/10.5194/egusphere-2024-3924, https://doi.org/10.5194/egusphere-2024-3924, 2024
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In this study, we discovered that natural dust carried into Europe significantly increases the likelihood of hailstorms. By analyzing dust data, weather records, and hail reports, we found that moderate dust levels lead to more frequent hail, while very high or low dust amounts reduce it. Adding dust information into statistical models improved forecasting skills. We aimed to understand how dust affects hailstorms.
Richard Warren, Niklaus Emanuel Bartlome, Noémie Wellinger, Jörg Franke, Ralf Hand, Stefan Brönnimann, and Heli Huhtamaa
Clim. Past, 20, 2645–2662, https://doi.org/10.5194/cp-20-2645-2024, https://doi.org/10.5194/cp-20-2645-2024, 2024
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In our study we used statistical models to reconstruct past hail days in Switzerland from 1959–2022. This new time series reveals a significant increase in hail day occurrences over the last 7 decades. We link this trend to increases in moisture and instability variables in the models. This time series can now be used to unravel the complexities of Swiss hail occurrence and to understand what drives its year-to-year variability.
Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann
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Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
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Stefan Brönnimann and Yuri Brugnara
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Stefan Brönnimann
Clim. Past, 19, 1345–1357, https://doi.org/10.5194/cp-19-1345-2023, https://doi.org/10.5194/cp-19-1345-2023, 2023
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Weather reconstructions could help us to better understand the mechanisms leading to, and the impacts caused by, climatic changes. This requires daily weather information such as diaries. Here I present the weather diary by Georg Christoph Eimmart from Nuremberg covering the period 1695–1704. This was a particularly cold period in Europe, and the diary helps to better characterize this climatic anomaly.
Noemi Imfeld, Lucas Pfister, Yuri Brugnara, and Stefan Brönnimann
Clim. Past, 19, 703–729, https://doi.org/10.5194/cp-19-703-2023, https://doi.org/10.5194/cp-19-703-2023, 2023
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Climate reconstructions give insights into monthly and seasonal climate variability of the past few hundred years. However, to understand past extreme weather events and to relate them to impacts, for example to periods of extreme floods, reconstructions on a daily timescale are needed. Here, we present a reconstruction of 258 years of high-resolution daily temperature and precipitation fields for Switzerland covering the period 1763 to 2020, which is based on instrumental measurements.
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
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We produced a new dataset of global station-based daily maximum wet-bulb temperature (GSDM-WBT) through the calculation of wet-bulb temperature, data quality control, infilling missing values, and homogenization. The GSDM-WBT covers the complete daily series of 1834 stations from 1981 to 2020. The GSDM-WBT dataset handles stations with many missing values and possible inhomogeneities, which could better support the studies on global and regional humid heat events.
Duncan Pappert, Mariano Barriendos, Yuri Brugnara, Noemi Imfeld, Sylvie Jourdain, Rajmund Przybylak, Christian Rohr, and Stefan Brönnimann
Clim. Past, 18, 2545–2565, https://doi.org/10.5194/cp-18-2545-2022, https://doi.org/10.5194/cp-18-2545-2022, 2022
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We present daily temperature and sea level pressure fields for Europe for the severe winter 1788/1789 based on historical meteorological measurements and an analogue reconstruction approach. The resulting reconstruction skilfully reproduces temperature and pressure variations over central and western Europe. We find intense blocking systems over northern Europe and several abrupt, strong cold air outbreaks, demonstrating that quantitative weather reconstruction of past extremes is possible.
Chantal Camenisch, Fernando Jaume-Santero, Sam White, Qing Pei, Ralf Hand, Christian Rohr, and Stefan Brönnimann
Clim. Past, 18, 2449–2462, https://doi.org/10.5194/cp-18-2449-2022, https://doi.org/10.5194/cp-18-2449-2022, 2022
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We present a novel approach to assimilate climate information contained in chronicles and annals from the 15th century to generate climate reconstructions of the Burgundian Low Countries, taking into account uncertainties associated with the descriptions of narrative sources. Our study aims to be a first step towards a more quantitative use of available information contained in historical texts, showing how Bayesian inference can help the climate community with this endeavor.
Yuri Brugnara, Chantal Hari, Lucas Pfister, Veronika Valler, and Stefan Brönnimann
Clim. Past, 18, 2357–2379, https://doi.org/10.5194/cp-18-2357-2022, https://doi.org/10.5194/cp-18-2357-2022, 2022
Short summary
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We digitized dozens of weather journals containing temperature measurements from in and around Bern and Zurich. They cover over a century before the creation of a national weather service in Switzerland. With these data we could create daily temperature series for the two cities that span the last 265 years. We found that the pre-industrial climate on the Swiss Plateau was colder than suggested by previously available instrumental data sets and about 2.5 °C colder than the present-day climate.
Gilles Delaygue, Stefan Brönnimann, and Philip D. Jones
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-33, https://doi.org/10.5194/wcd-2022-33, 2022
Revised manuscript not accepted
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We test whether any association between solar activity and meteorological conditions in the north Atlantic – European sector could be detected. We find associations consistent with those found by previous studies, with a slightly better statistical significance, and with less methodological biases which have impaired previous studies. Our study should help strengthen the recognition of meteorological impacts of solar activity.
Moritz Buchmann, John Coll, Johannes Aschauer, Michael Begert, Stefan Brönnimann, Barbara Chimani, Gernot Resch, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 16, 2147–2161, https://doi.org/10.5194/tc-16-2147-2022, https://doi.org/10.5194/tc-16-2147-2022, 2022
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Knowledge about inhomogeneities in a data set is important for any subsequent climatological analysis. We ran three well-established homogenization methods and compared the identified break points. By only treating breaks as valid when detected by at least two out of three methods, we enhanced the robustness of our results. We found 45 breaks within 42 of 184 investigated series; of these 70 % could be explained by events recorded in the station history.
Stefan Brönnimann, Peter Stucki, Jörg Franke, Veronika Valler, Yuri Brugnara, Ralf Hand, Laura C. Slivinski, Gilbert P. Compo, Prashant D. Sardeshmukh, Michel Lang, and Bettina Schaefli
Clim. Past, 18, 919–933, https://doi.org/10.5194/cp-18-919-2022, https://doi.org/10.5194/cp-18-919-2022, 2022
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Floods in Europe vary on time scales of several decades. Flood-rich and flood-poor periods alternate. Recently floods have again become more frequent. Long time series of peak stream flow, precipitation, and atmospheric variables reveal that until around 1980, these changes were mostly due to changes in atmospheric circulation. However, in recent decades the role of increasing atmospheric moisture due to climate warming has become more important and is now the main driver of flood changes.
Daniel Steinfeld, Adrian Peter, Olivia Martius, and Stefan Brönnimann
EGUsphere, https://doi.org/10.5194/egusphere-2022-92, https://doi.org/10.5194/egusphere-2022-92, 2022
Preprint archived
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We assess the performance of various fire weather indices to predict wildfire occurrence in Northern Switzerland. We find that indices responding readily to weather changes have the best performance during spring; in the summer and autumn seasons, indices that describe persistent hot and dry conditions perform best. We demonstrate that a logistic regression model trained on local historical fire activity can outperform existing fire weather indices.
Duncan Pappert, Yuri Brugnara, Sylvie Jourdain, Aleksandra Pospieszyńska, Rajmund Przybylak, Christian Rohr, and Stefan Brönnimann
Clim. Past, 17, 2361–2379, https://doi.org/10.5194/cp-17-2361-2021, https://doi.org/10.5194/cp-17-2361-2021, 2021
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This paper presents temperature and pressure measurements from the 37 stations of the late 18th century network of the Societas Meteorologica Palatina, in addition to providing an inventory of the available observations, most of which have been digitised. The quality of the recovered series is relatively good, as demonstrated by two case studies. Early instrumental data such as these will help to explore past climate and weather extremes in Europe in greater detail.
Moritz Buchmann, Michael Begert, Stefan Brönnimann, and Christoph Marty
The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, https://doi.org/10.5194/tc-15-4625-2021, 2021
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We investigated the impacts of local-scale variations by analysing snow climate indicators derived from parallel snow measurements. We found the largest relative inter-pair differences for all indicators in spring and the smallest in winter. The findings serve as an important basis for our understanding of uncertainties of commonly used snow indicators and provide, in combination with break-detection methods, the groundwork in view of any homogenization efforts regarding snow time series.
Claudia Timmreck, Matthew Toohey, Davide Zanchettin, Stefan Brönnimann, Elin Lundstad, and Rob Wilson
Clim. Past, 17, 1455–1482, https://doi.org/10.5194/cp-17-1455-2021, https://doi.org/10.5194/cp-17-1455-2021, 2021
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The 1809 eruption is one of the most recent unidentified volcanic eruptions with a global climate impact. We demonstrate that climate model simulations of the 1809 eruption show generally good agreement with many large-scale temperature reconstructions and early instrumental records for a range of radiative forcing estimates. In terms of explaining the spatially heterogeneous and temporally delayed Northern Hemisphere cooling suggested by tree-ring networks, the investigation remains open.
Noemi Imfeld, Leopold Haimberger, Alexander Sterin, Yuri Brugnara, and Stefan Brönnimann
Earth Syst. Sci. Data, 13, 2471–2485, https://doi.org/10.5194/essd-13-2471-2021, https://doi.org/10.5194/essd-13-2471-2021, 2021
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Upper-air data form the backbone of reanalysis products, particularly in the pre-satellite era. However, historical upper-air data are error-prone because measurements at high altitude were especially challenging. Here, we present a collection of data from historical intercomparisons of radiosondes and error assessments reaching back to the 1930s that may allow us to better characterize such errors. The full database, including digitized data, images, and metadata, is made publicly available.
Stefan Brönnimann and Sylvia Nichol
Atmos. Chem. Phys., 20, 14333–14346, https://doi.org/10.5194/acp-20-14333-2020, https://doi.org/10.5194/acp-20-14333-2020, 2020
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Historical column ozone data from New Zealand and the UK from the 1950s are digitised and re-evaluated. They allow studying the ozone layer prior to the era of ozone depletion. Day-to-day changes are addressed, which reflect the flow near the tropopause and hence may serve as a diagnostic for atmospheric circulation in a time and region of sparse radiosondes. A long-term comparison shows the amount of ozone depletion at southern mid-latitudes and indicates how far we are from full recovery.
Stefan Brönnimann
Clim. Past, 16, 1937–1952, https://doi.org/10.5194/cp-16-1937-2020, https://doi.org/10.5194/cp-16-1937-2020, 2020
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Scientists often reconstruct climate from proxy data such as tree rings or historical documents. Here, I do the reverse and produce a weather diary from historical numerical weather data. Such "synthetic weather diaries" may be useful for historians, e.g. to compare with other sources or to study the weather experienced during a journey or a military operation. They could also help train machine-learning approaches, which could then be used to reconstruct weather from historical diaries.
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Short summary
Our work compares different machine learning approaches for creating long-term classifications of daily atmospheric circulation patterns using input data from surface meteorological observations. Our comparison reveals that a feedforward neural network performs best at this task. Using this model, we present a daily reconstruction of a commonly used weather type classification for central Europe that dates back to 1728.
Our work compares different machine learning approaches for creating long-term classifications...
