Articles | Volume 16, issue 6
https://doi.org/10.5194/tc-16-2147-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-2147-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
09 Jun 2022
Research article |
| 09 Jun 2022
| 09 Jun 2022
Homogeneity assessment of Swiss snow depth series: comparison of break detection capabilities of (semi-)automatic homogenization methods
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Institute of Geography, University of Bern, Bern, Switzerland
John Coll
CGG, Crawley, United Kingdom
Johannes Aschauer
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Michael Begert
Federal Office of Meteorology and Climatology (MeteoSwiss), Zurich Airport, Zurich, Switzerland
Stefan Brönnimann
Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Institute of Geography, University of Bern, Bern, Switzerland
Barbara Chimani
Klimamonitoring und Kryosphäre, Zentralanstalt für Meteorologie und Geodynamik (ZAMG), Vienna, Austria
Gernot Resch
Department of Geography and Regional Science, University of Graz, Graz, Austria
Wolfgang Schöner
Department of Geography and Regional Science, University of Graz, Graz, Austria
Christoph Marty
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Related authors
Moritz Buchmann, Gernot Resch, Michael Begert, Stefan Brönnimann, Barbara Chimani, Wolfgang Schöner, and Christoph Marty
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
Short summary
Short summary
Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
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
Short summary
Short summary
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.
Tiago Silva, Brandon Samuel Whitley, Elisabeth Machteld Biersma, Jakob Abermann, Katrine Raundrup, Natasha de Vere, Toke Thomas Høye, Verena Haring, and Wolfgang Schöner
Biogeosciences, 22, 4601–4626, https://doi.org/10.5194/bg-22-4601-2025, https://doi.org/10.5194/bg-22-4601-2025, 2025
Short summary
Short summary
Ecosystems in Greenland have experienced significant changes over recent decades. We show the consistency of a high-resolution polar-adapted reanalysis product to represent bio-climatic factors influencing ecological processes. Our results describe the relevance/interaction between snowmelt and soil water content before the growing season onset, infer how the thermal growing season relates to changes in spectral greenness, and describe regions of ongoing changes in vegetation distribution.
Matthew B. Switanek, Jakob Abermann, Wolfgang Schöner, and Michael L. Anderson
EGUsphere, https://doi.org/10.5194/egusphere-2025-3881, https://doi.org/10.5194/egusphere-2025-3881, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Extreme precipitation is expected to increase in a warming climate. Measurements of precipitation and dew point temperature are often used to estimate observed precipitation-temperature scaling rates. In this study, we use three different approaches which rely on either raw or normalized data to estimate scaling rates and produce predictions of extreme precipitation. Our findings highlight the importance of using normalized data to obtain accurate observation-based scaling estimates.
Bettina Richter and Christoph Marty
EGUsphere, https://doi.org/10.5194/egusphere-2025-3518, https://doi.org/10.5194/egusphere-2025-3518, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
We developed a literature-based approach for projecting future snow depths, which was applied to four measurement stations in Switzerland under a +2 °C temperature scenario, revealing significant declines in snow depths. Validation against published data shows that the approach captures key trends in snow loss. This resource-efficient method provides a practical tool for estimating climate change related snow depth declines, which are lacking highly resolved climate projections.
Jonathan Fipper, Jakob Abermann, Ingo Sasgen, Henrik Skov, Lise Lotte Sørensen, and Wolfgang Schöner
EGUsphere, https://doi.org/10.5194/egusphere-2025-3381, https://doi.org/10.5194/egusphere-2025-3381, 2025
Short summary
Short summary
We use measurements conducted with uncrewed aerial vehicles (UAVs) and reanalysis data to study the drivers of vertical air temperature structures and their link to the surface mass balance of Flade Isblink, a large ice cap in Northeast Greenland. Surface properties control temperature structures up to 100 m above ground, while large-scale circulation dominates above. Mass loss has increased since 2015, with record loss in 2023 associated with frequent synoptic conditions favoring melt.
Nicolás Duque-Gardeazabal, Andrew R. Friedman, and Stefan Brönnimann
Hydrol. Earth Syst. Sci., 29, 3277–3295, https://doi.org/10.5194/hess-29-3277-2025, https://doi.org/10.5194/hess-29-3277-2025, 2025
Short summary
Short summary
Understanding hydrological variability is essential for ecological conservation and sustainable development. Evapotranspiration influences the carbon cycle, and finding what causes its variability is important for ecosystems. This study shows that ENSO (El Niño–Southern Oscillation) influences not only South America’s rainfall, soil moisture, radiation, and evaporation but also other phenomena in the Atlantic Ocean. The impacts change regionally depending on the season analysed and have implications for heat extremes.
Christian Pfister, Stefan Brönnimann, Laurent Litzenburger, Peter Thejll, Andres Altwegg, Rudolf Brázdil, Andrea Kiss, Erich Landsteiner, Fredrik Charpentier Ljungqvist, and Thomas Pliemon
EGUsphere, https://doi.org/10.5194/egusphere-2025-3242, https://doi.org/10.5194/egusphere-2025-3242, 2025
This preprint is open for discussion and under review for Climate of the Past (CP).
Short summary
Short summary
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
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-249, https://doi.org/10.5194/essd-2025-249, 2025
Preprint under review for ESSD
Short summary
Short summary
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.
Lucas Pfister, Lena Wilhelm, Yuri Brugnara, Noemi Imfeld, and Stefan Brönnimann
Weather Clim. Dynam., 6, 571–594, https://doi.org/10.5194/wcd-6-571-2025, https://doi.org/10.5194/wcd-6-571-2025, 2025
Short summary
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.
Christoph Marty, Adrien Michel, Tobias Jonas, Cynthia Steijn, Regula Muelchi, and Sven Kotlarski
EGUsphere, https://doi.org/10.5194/egusphere-2025-413, https://doi.org/10.5194/egusphere-2025-413, 2025
Short summary
Short summary
This work presents the first long-term (since 1962), daily, 1 km gridded dataset of snow depth and water storage for Switzerland. Its quality was assessed by comparing yearly, monthly, and weekly values to a higher-quality model and in-situ measurements. Results show good overall performance, though some limitations exist at low elevations and short timescales. Despite this, the dataset effectively captures trends, offering valuable insights for climate monitoring and elevation-based changes.
Florina Roana Schalamon, Sebastian Scher, Andreas Trügler, Lea Hartl, Wolfgang Schöner, and Jakob Abermann
EGUsphere, https://doi.org/10.5194/egusphere-2024-4060, https://doi.org/10.5194/egusphere-2024-4060, 2025
Short summary
Short summary
Atmospheric patterns influence the air temperature in Greenland. We investigate two warming periods, from 1922–1932 and 1993–2007, both showing similar temperature increases. Using a neural network-based clustering method, we defined predominant atmospheric patterns for further analysis. Our findings reveal that while the connection between these patterns and local air temperature remains stable, the distribution of patterns changes between the warming periods and the full period (1900–2015).
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
Short summary
Short summary
We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better-quality maps. The correction can then be extended backwards and forwards in time for periods when better-quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Matthew Switanek, Gernot Resch, Andreas Gobiet, Daniel Günther, Christoph Marty, and Wolfgang Schöner
The Cryosphere, 18, 6005–6026, https://doi.org/10.5194/tc-18-6005-2024, https://doi.org/10.5194/tc-18-6005-2024, 2024
Short summary
Short summary
Snow depth plays an important role in water resources, mountain tourism, and hazard management across the European Alps. Our study uses station-based historical observations to quantify how changes in temperature and precipitation affect average seasonal snow depth. We find that the relationship between these variables has been surprisingly robust over the last 120 years. This allows us to more accurately estimate how future climate will affect seasonal snow depth in different elevation zones.
Jorrit van der Schot, Jakob Abermann, Tiago Silva, Kerstin Rasmussen, Michael Winkler, Kirsty Langley, and Wolfgang Schöner
The Cryosphere, 18, 5803–5823, https://doi.org/10.5194/tc-18-5803-2024, https://doi.org/10.5194/tc-18-5803-2024, 2024
Short summary
Short summary
We present snow data from nine locations in coastal Greenland. We show that a reanalysis product (CARRA) simulates seasonal snow characteristics better than a regional climate model (RACMO). CARRA output matches particularly well with our reference dataset when we look at the maximum snow water equivalent and the snow cover end date. We show that seasonal snow in coastal Greenland has large spatial and temporal variability and find little evidence of trends in snow cover characteristics.
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
Short summary
Short summary
This paper introduces the ClimeApp web application. The app provides quick access to the ModE-RA global climate reanalysis. Users can calculate and plot anomalies, composites, correlations, regressions and annual cycles across three different datasets and four climate variables. By re-examining the 1815 Tambora eruption, we demonstrate how combining results from different datasets and sources can help us investigate the historical palaeoclimate and integrate it into human history.
Bernhard Hynek, Daniel Binder, Michele Citterio, Signe Hillerup Larsen, Jakob Abermann, Geert Verhoeven, Elke Ludewig, and Wolfgang Schöner
The Cryosphere, 18, 5481–5494, https://doi.org/10.5194/tc-18-5481-2024, https://doi.org/10.5194/tc-18-5481-2024, 2024
Short summary
Short summary
An avalanche event in February 2018 caused thick snow deposits on Freya Glacier, a peripheral mountain glacier in northeastern Greenland. The avalanche deposits contributed significantly to the mass balance, leaving a strong imprint in the elevation changes in 2013–2021. The 8-year geodetic mass balance (2013–2021) of the glacier is positive, whereas previous estimates by direct measurements were negative and now turned out to have a negative bias.
Peter Stucki, Lucas Pfister, Yuri Brugnara, Renate Varga, Chantal Hari, and Stefan Brönnimann
Clim. Past, 20, 2327–2348, https://doi.org/10.5194/cp-20-2327-2024, https://doi.org/10.5194/cp-20-2327-2024, 2024
Short summary
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 analyzing past weather events and their impacts in detail.
Stefan Brönnimann, Janusz Filipiak, Siyu Chen, and Lucas Pfister
Clim. Past, 20, 2219–2235, https://doi.org/10.5194/cp-20-2219-2024, https://doi.org/10.5194/cp-20-2219-2024, 2024
Short summary
Short summary
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.
Christian Pfister, Stefan Brönnimann, Andres Altwegg, Rudolf Brázdil, Laurent Litzenburger, Daniele Lorusso, and Thomas Pliemon
Clim. Past, 20, 1387–1399, https://doi.org/10.5194/cp-20-1387-2024, https://doi.org/10.5194/cp-20-1387-2024, 2024
Short summary
Short summary
This bottle of Riesling from the traditional Bassermann Jordan winery in Deidesheim (Germany) is a relic of the premium wine harvested in 1811. It was named “Comet Wine” after the bright comet that year. The study shows that wine quality can be used to infer summer weather conditions over the past 600 years. After rainy summers with cold winds, wines turned sour, while long periods of high pressure led to excellent qualities. Since 1990, only good wines have been produced due to rapid warming.
Stefan Brönnimann, Yuri Brugnara, and Clive Wilkinson
Clim. Past, 20, 757–767, https://doi.org/10.5194/cp-20-757-2024, https://doi.org/10.5194/cp-20-757-2024, 2024
Short summary
Short summary
The early 20th century warming – the first phase of global warming in the 20th century – started from a peculiar cold state around 1910. We digitised additional ship logbooks for these years to study this specific climate state and found that it is real and likely an overlap of several climatic anomalies, including oceanic variability (La Niña) and volcanic eruptions.
Noemi Imfeld, Koen Hufkens, and Stefan Brönnimann
Clim. Past, 20, 659–682, https://doi.org/10.5194/cp-20-659-2024, https://doi.org/10.5194/cp-20-659-2024, 2024
Short summary
Short summary
Climate and weather in spring are important because they can have far-reaching impacts, e.g. on plant growth, due to cold spells. Here, we study changes in climate and phenological indices for the period from 1763 to 2020 based on newly published reconstructed fields of daily temperature and precipitation for Switzerland. We look at three cases of extreme spring conditions, namely a warm spring in 1862, two frost events in 1873 and 1957, and three cold springs in 1785, 1837, and 1852.
Florian Lippl, Alexander Maringer, Margit Kurka, Jakob Abermann, Wolfgang Schöner, and Manuela Hirschmugl
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-12, https://doi.org/10.5194/essd-2024-12, 2024
Preprint withdrawn
Short summary
Short summary
The aim of our work was to give an overview of data currently available for the National Park Gesäuse and Johnsbachtal relevant to the European long-term ecosystem monitoring. This data, further was made available on respective data repositories, where all data is downloadable free of charge. Data presented in our paper is from all compartments, the atmosphere, social & economic sphere, biosphere and geosphere. We consider our approach as an opportunity to function as a showcase for other sites.
Maral Habibi, Iman Babaeian, and Wolfgang Schöner
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-48, https://doi.org/10.5194/hess-2024-48, 2024
Publication in HESS not foreseen
Short summary
Short summary
Our study investigates how snow melting affects droughts in Iran's Urmia Lake Basin, revealing that future droughts will likely become more severe due to reduced snowmelt and increased evaporation. This is crucial for understanding water availability in the region, affecting millions. We used advanced climate models and drought indices to predict changes, aiming to inform water management strategies.
Eric Samakinwa, Christoph C. Raible, Ralf Hand, Andrew R. Friedman, and Stefan Brönnimann
Clim. Past Discuss., https://doi.org/10.5194/cp-2023-67, https://doi.org/10.5194/cp-2023-67, 2023
Publication in CP not foreseen
Short summary
Short summary
In this study, we nudged a stand-alone ocean model MPI-OM to proxy-reconstructed SST. Based on these model simulations, we introduce new estimates of the AMOC variations during the period 1450–1780 through a 10-member ensemble simulation with a novel nudging technique. Our approach reaffirms the known mechanisms of AMOC variability and also improves existing knowledge of the interplay between the AMOC and the NAO during the AMOC's weak and strong phases.
Sonika Shahi, Jakob Abermann, Tiago Silva, Kirsty Langley, Signe Hillerup Larsen, Mikhail Mastepanov, and Wolfgang Schöner
Weather Clim. Dynam., 4, 747–771, https://doi.org/10.5194/wcd-4-747-2023, https://doi.org/10.5194/wcd-4-747-2023, 2023
Short summary
Short summary
This study highlights how the sea ice variability in the Greenland Sea affects the terrestrial climate and the surface mass changes of peripheral glaciers of the Zackenberg region (ZR), Northeast Greenland, combining model output and observations. Our results show that the temporal evolution of sea ice influences the climate anomaly magnitude in the ZR. We also found that the changing temperature and precipitation patterns due to sea ice variability can affect the surface mass of the ice cap.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866, https://doi.org/10.5194/gmd-16-4853-2023, https://doi.org/10.5194/gmd-16-4853-2023, 2023
Short summary
Short summary
ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Klaus Haslinger, Wolfgang Schöner, Jakob Abermann, Gregor Laaha, Konrad Andre, Marc Olefs, and Roland Koch
Nat. Hazards Earth Syst. Sci., 23, 2749–2768, https://doi.org/10.5194/nhess-23-2749-2023, https://doi.org/10.5194/nhess-23-2749-2023, 2023
Short summary
Short summary
Future changes of surface water availability in Austria are investigated. Alterations of the climatic water balance and its components are analysed along different levels of elevation. Results indicate in general wetter conditions with particular shifts in timing of the snow melt season. On the contrary, an increasing risk for summer droughts is apparent due to increasing year-to-year variability and decreasing snow melt under future climate conditions.
Johannes Aschauer, Adrien Michel, Tobias Jonas, and Christoph Marty
Geosci. Model Dev., 16, 4063–4081, https://doi.org/10.5194/gmd-16-4063-2023, https://doi.org/10.5194/gmd-16-4063-2023, 2023
Short summary
Short summary
Snow water equivalent is the mass of water stored in a snowpack. Based on exponential settling functions, the empirical snow density model SWE2HS is presented to convert time series of daily snow water equivalent into snow depth. The model has been calibrated with data from Switzerland and validated with independent data from the European Alps. A reference implementation of SWE2HS is available as a Python package.
Stefan Brönnimann and Yuri Brugnara
Clim. Past, 19, 1435–1445, https://doi.org/10.5194/cp-19-1435-2023, https://doi.org/10.5194/cp-19-1435-2023, 2023
Short summary
Short summary
We present the weather diaries of the Kirch family from 1677–1774 containing weather observations made in Leipzig and Guben and, from 1701 onward, instrumental observations made in Berlin. We publish the imaged diaries (10 445 images) and the digitized measurements (from 1720 onward). This is one of the oldest and longest meteorological records from Germany. The digitized pressure data show good agreement with neighbouring stations, highlighting their potential for weather reconstruction.
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
Short summary
Short summary
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
Short summary
Short summary
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
The Cryosphere, 17, 653–671, https://doi.org/10.5194/tc-17-653-2023, https://doi.org/10.5194/tc-17-653-2023, 2023
Short summary
Short summary
Our current knowledge of spatial and temporal snow depth trends is based almost exclusively on time series of non-homogenised observational data. However, like other long-term series from observations, they are susceptible to inhomogeneities that can affect the trends and even change the sign. To assess the relevance of homogenisation for daily snow depths, we investigated its impact on trends and changes in extreme values of snow indices between 1961 and 2021 in the Swiss observation network.
Jianquan Dong, Stefan Brönnimann, Tao Hu, Yanxu Liu, and Jian Peng
Earth Syst. Sci. Data, 14, 5651–5664, https://doi.org/10.5194/essd-14-5651-2022, https://doi.org/10.5194/essd-14-5651-2022, 2022
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
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.
Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
Short summary
Short summary
To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
Thomas Goelles, Tobias Hammer, Stefan Muckenhuber, Birgit Schlager, Jakob Abermann, Christian Bauer, Víctor J. Expósito Jiménez, Wolfgang Schöner, Markus Schratter, Benjamin Schrei, and Kim Senger
Geosci. Instrum. Method. Data Syst., 11, 247–261, https://doi.org/10.5194/gi-11-247-2022, https://doi.org/10.5194/gi-11-247-2022, 2022
Short summary
Short summary
We propose a newly developed modular MObile LIdar SENsor System (MOLISENS) to enable new applications for small industrial light detection and ranging (lidar) sensors. MOLISENS supports both monitoring of dynamic processes and mobile mapping applications. The mobile mapping application of MOLISENS has been tested under various conditions, and results are shown from two surveys in the Lurgrotte cave system in Austria and a glacier cave in Longyearbreen on Svalbard.
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
Short summary
Short summary
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.
Yves Bühler, Peter Bebi, Marc Christen, Stefan Margreth, Lukas Stoffel, Andreas Stoffel, Christoph Marty, Gregor Schmucki, Andrin Caviezel, Roderick Kühne, Stephan Wohlwend, and Perry Bartelt
Nat. Hazards Earth Syst. Sci., 22, 1825–1843, https://doi.org/10.5194/nhess-22-1825-2022, https://doi.org/10.5194/nhess-22-1825-2022, 2022
Short summary
Short summary
To calculate and visualize the potential avalanche hazard, we develop a method that automatically and efficiently pinpoints avalanche starting zones and simulate their runout for the entire canton of Grisons. The maps produced in this way highlight areas that could be endangered by avalanches and are extremely useful in multiple applications for the cantonal authorities, including the planning of new infrastructure, making alpine regions more safe.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Achille Capelli, Franziska Koch, Patrick Henkel, Markus Lamm, Florian Appel, Christoph Marty, and Jürg Schweizer
The Cryosphere, 16, 505–531, https://doi.org/10.5194/tc-16-505-2022, https://doi.org/10.5194/tc-16-505-2022, 2022
Short summary
Short summary
Snow occurrence, snow amount, snow density and liquid water content (LWC) can vary considerably with climatic conditions and elevation. We show that low-cost Global Navigation Satellite System (GNSS) sensors as GPS can be used for reliably measuring the amount of water stored in the snowpack or snow water equivalent (SWE), snow depth and the LWC under a broad range of climatic conditions met at different elevations in the Swiss Alps.
Johannes Aschauer and Christoph Marty
Geosci. Instrum. Method. Data Syst., 10, 297–312, https://doi.org/10.5194/gi-10-297-2021, https://doi.org/10.5194/gi-10-297-2021, 2021
Short summary
Short summary
Methods for reconstruction of winter long data gaps in snow depth time series are compared. The methods use snow depth data from neighboring stations or calculate snow depth from temperature and precipitation data. All methods except one are able to reproduce the average snow depth and maximum snow depth in a winter reasonably well. For reconstructing the number of snow days with snow depth ≥ 1 cm, results suggest using a snow model instead of relying on data from neighboring stations.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
Short summary
Short summary
The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Aguilar, E. and Llanso, P.: Guidelines on climate metadata and homogenization, World Meteorological Organization, WCDMP-No. 53, https://library.wmo.int/doc_num.php?explnum_id=10751 (last access: 8 June 2022), 2003. a
Alexandersson, H.: A homogeneity test applied to precipitation data, J. Climatol., 6, 661–675, https://doi.org/10.1002/joc.3370060607, 1986. a
Alexandersson, H. and Moberg, A.: Homogenization of Swedish temperature data. Part I: Homogeneity test for linear trends, Int. J. Climatol., 17, 25–34, https://doi.org/10.1002/(sici)1097-0088(199701)17:1<25::aid-joc103>3.0.co;2-j, 1997. a, b, c
Aschauer, J. and Marty, C.: Providing Data Provision for a Sensitivity Analysis of Snow Time Series, resreport, WSL Institute for Snow and Avalanche Research SLF, research Report for GCOS Switzerland,
https://www.meteoschweiz.admin.ch/content/dam/meteoswiss/en/Forschung-und-Zusammenarbeit/Internationale-Zusammenarbeit/GCOS/doc/Final_report_Poviding_Data_Provision_for_a_Sensitivity_Analysis_of_Snow_Time_Series.pdf (last access: 8 June 2022), 2020. a
Begert, M., Schlegel, T., and Kirchhofer, W.: Homogeneous temperature and precipitation series of Switzerland from 1864 to 2000, Int. J. Climatol., 25, 65–80, https://doi.org/10.1002/joc.1118, 2005. a
Begert, M., Zenklusen, E., Häberli, C., Appenzeller, C., and Klok, L.: An automated procedure to detect discontinuities; performance assessment and application to a large European climate data set, Meteorol. Z., 17, 663–672, https://doi.org/10.1127/0941-2948/2008/0314, 2008. a
Brugnara, Y., Good, E., Squintu, A. A., van der Schrier, G., and Brönnimann, S.: The EUSTACE global land station daily air temperature dataset, Geosci. Data J., 6, 189–204, https://doi.org/10.1002/gdj3.81, 2019. a
Brugnara, Y., Auchmann, R., Rutishauser, T., Gehrig, R., Pietragalla, B., Begert, M., Sigg, C., Knechtl, V., Konzelmann, T., Calpini, B., and Brönnimann, S.: Homogeneity assessment of phenological records from the Swiss Phenology Network, Int. J. Biometeorol., 64, 71–81, https://doi.org/10.1007/s00484-019-01794-y, 2020. a, b
Buchmann, M., Begert, M., Brönnimann, S., and Marty, C.: Local-scale variability of seasonal mean and extreme values of in situ snow depth and snowfall measurements, The Cryosphere, 15, 4625–4636, https://doi.org/10.5194/tc-15-4625-2021, 2021a. a
Buchmann, M., Begert, M., Brönnimann, S., and Marty, C.: Evaluating the robustness of snow climate indicators using a unique set of parallel snow measurement series, Int. J. Climatol., 41, E2553–E2563, https://doi.org/10.1002/joc.6863, 2021b. a, b, c
Buchmann, M., Aschauer, J., Begert, M., and Marty, C.: Input data for break point detection of Swiss snow depth time series, EnviDat [data set], https://doi.org/10.16904/envidat.297, 2022. a
Caussinus, H. and Lyazrhi, F.: Choosing a Linear Model with a Random Number of Change-Points and Outliers, Ann. I. Stat. Math., 49, 761–775, https://doi.org/10.1023/a:1003230713770, 1997. a
Caussinus, H. and Mestre, O.: Detection and correction of artificial shifts in climate series, J. Roy. Stat. Soc. C-App., 53, 405–425, https://doi.org/10.1111/j.1467-9876.2004.05155.x, 2004. a, b, c
Coll, J., Domonkos, P., Guijarro, J., Curley, M., Rustemeier, E., Aguilar, E., Walsh, S., and Sweeney, J.: Application of homogenization methods for Ireland's monthly precipitation records: Comparison of break detection results, Int. J. Climatol., 40, 6169–6188, https://doi.org/10.1002/joc.6575, 2020. a, b, c, d, e, f, g, h, i
Della-Marta, P. M. and Wanner, H.: A Method of Homogenizing the Extremes and Mean of Daily Temperature Measurements, J. Climate, 19, 4179–4197,
https://doi.org/10.1175/JCLI3855.1, 2006. a
Domonkos, P. and Coll, J.: Homogenisation of temperature and precipitation time series with ACMANT3: method description and efficiency tests, Int. J. Climatol., 37, 1910–1921, https://doi.org/10.1002/joc.4822, 2017. a, b
Domonkos, P. and Coll, J.: Impact of missing data on the efficiency of
homogenisation: experiments with ACMANTv3, Theor. Appl. Climatol., 136, 287–299, https://doi.org/10.1007/s00704-018-2488-3, 2019. a, b
Fioravanti, G., Piervitali, E., and Desiato, F.: A new homogenized daily data
set for temperature variability assessment in Italy, Int. J. Climatol., 39, 5635–5654, https://doi.org/10.1002/joc.6177, 2019. a
Haberkorn, A.: European Snow Booklet – an Inventory of Snow Measurements in Europe, EnviDat [data set], https://doi.org/10.16904/envidat.59, 2019. a
Hawkins, D. M.: Fitting multiple change-point models to data, Comput. Stat. Data An., 37, 323–341, https://doi.org/10.1016/S0167-9473(00)00068-2, 2001. a
Killick, R. E., Jolliffe, I. T., and Willett, K. M.: Benchmarking the performance of homogenisation algorithms on synthetic daily temperature data, Int. J. Climatol., 42, 3968–3986, https://doi.org/10.1002/joc.7462, 2021. a
Kuglitsch, F. G., Auchmann, R., Bleisch, R., Brönnimann, S., Martius, O., and Stewart, M.: Break detection of annual Swiss temperature series, J. Geophys. Res., 117, D13105, https://doi.org/10.1029/2012JD017729, 2012. a, b, c, d
Kuya, E. K., Gjelten, H. M., and Tveito, O. E.: Homogenization of Norwegian monthly precipitation series for the period 1961–2018, Tech. rep., Norwegian Meteorological Institute, mETreport,
https://www.met.no/publikasjoner/met-report/_/attachment/download/829d6a8e-1ec8-417d-8231-0268bddac4bb:7eb30ca105a6cf1d470453976bb8d729a64b25a4/METreport 04-21-Homogenization of precipitation 1961-2018.pdf (last access: 8 June 2022), 2021a. a, b, c, d, e, f
Kuya, E. K., Gjelten, H. M., and Tveito, O. E.: Homogenization of Norway's mean monthly temperature series, Tech. rep., Norwegian Meteorological Institute, mETreport, https://www.met.no/publikasjoner/met-report/_/attachment/download/94481ff9-6366-4569-84f5-881d8e671245:e83e7420a5810019bd2241684070d31d74a35c81/METreport03-2020.pdf (last access: 8 June 2022), 2021b. a
Luna, M. Y., Guijarro, J. A., and López, J. A.: A monthly precipitation database for Spain (1851–2008): reconstruction, homogeneity and trends, Adv. Sci. Res., 8, 1–4, https://doi.org/10.5194/asr-8-1-2012, 2012. a
Marcolini, G., Bellin, A., and Chiogna, G.: Performance of the Standard Normal Homogeneity Test for the homogenization of mean seasonal snow depth time series: performance of SNHT for snow depth time series, Int. J. Climatol., 37, 1267–1277, https://doi.org/10.1002/joc.4977, 2017. a, b, c, d
Menne, M. J. and Williams, C. N.: Homogenization of Temperature Series via Pairwise Comparisons, J. Climate, 22, 1700–1717, https://doi.org/10.1175/2008jcli2263.1, 2009. a
Noone, S., Murphy, C., Coll, J., Matthews, T., Mullan, D., Wilby, R. L., and Walsh, S.: Homogenization and analysis of an expanded long-term monthly rainfall network for the Island of Ireland (1850–2010), Int. J. Climatol., 36, 2837–2853, https://doi.org/10.1002/joc.4522, 2016. a
Pérez-Zanón, N., Sigró, J., Domonkos, P., and Ashcroft, L.: Comparison of HOMER and ACMANT homogenization methods using a central Pyrenees temperature dataset, Adv. Sci. Res., 12, 111–119, https://doi.org/10.5194/asr-12-111-2015, 2015. a, b
Picard, F., Lebarbier, E., Hoebeke, M., Rigaill, G., Thiam, B., and Robin, S.: Joint segmentation, calling, and normalization of multiple CGH profiles, Biostatistics, 12, 413–428, https://doi.org/10.1093/biostatistics/kxq076, 2011. a, b
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 8 June 2022), 2021. a
Schöner, W., Koch, R., Matulla, C., Marty, C., and Tilg, A.-M.: Spatiotemporal patterns of snow depth within the Swiss-Austrian Alps for the past half century (1961 to 2012) and linkages to climate change, Int. J. Climatol., 39, 1589–1603, https://doi.org/10.1002/joc.5902, 2019. a, b, c, d
Toreti, A., Kuglitsch, F. G., Xoplaki, E., and Luterbacher, J.: A Novel Approach for the Detection of Inhomogeneities Affecting Climate Time Series, J. Appl. Meteorol. Clim., 51, 317–326, https://doi.org/10.1175/JAMC-D-10-05033.1, 2012. a
Tuomenvirta, H.: Homogeneity adjustments of temperature and precipitation series – Finnish and Nordic data, Int. J. Climatol., 21, 495–506, https://doi.org/10.1002/joc.616, 2001. a
Venema, V. K. C., Mestre, O., Aguilar, E., Auer, I., Guijarro, J. A., Domonkos, P., Vertacnik, G., Szentimrey, T., Stepanek, P., Zahradnicek, P., Viarre, J., Müller-Westermeier, G., Lakatos, M., Williams, C. N., Menne, M. J., Lindau, R., Rasol, D., Rustemeier, E., Kolokythas, K., Marinova, T., Andresen, L., Acquaotta, F., Fratianni, S., Cheval, S., Klancar, M., Brunetti, M., Gruber, C., Prohom Duran, M., Likso, T., Esteban, P., and Brandsma, T.: Benchmarking homogenization algorithms for monthly data, Clim. Past, 8, 89–115, https://doi.org/10.5194/cp-8-89-2012, 2012.
a, b, c
Venema, V. K. C., Trewin, B., and Wang, X.: Guidelines on Homogenization 2020 edition, Tech. rep., World Meteorological Organization, Issue WMO-No. 1245,
https://library.wmo.int/?lvl=notice_display&id=21756 (last access: 8 June 2022), 2020. a
Vertačnik, G., Dolinar, M., Bertalanič, R., Klančar, M., Dvoršek, D., and Nadbath, M.: Ensemble homogenization of Slovenian monthly air temperature series, Int. J. Climatol., 35, 4015–4026, https://doi.org/10.1002/joc.4265, 2015. a
Willett, K., Williams, C., Jolliffe, I. T., Lund, R., Alexander, L. V., Brönnimann, S., Vincent, L. A., Easterbrook, S., Venema, V. K. C., Berry, D., Warren, R. E., Lopardo, G., Auchmann, R., Aguilar, E., Menne, M. J., Gallagher, C., Hausfather, Z., Thorarinsdottir, T., and Thorne, P. W.: A framework for benchmarking of homogenisation algorithm performance on the global scale, Geosci. Instrum. Method. Data Syst., 3, 187–200, https://doi.org/10.5194/gi-3-187-2014, 2014. a
WMO: Web site of the task team on homogenization, World Meteorological Organization, http://www.climatol.eu/tt-hom/ (last access: 8 June 2022), 2017. a
Short summary
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.
Knowledge about inhomogeneities in a data set is important for any subsequent climatological...
