Search

The “Year Without a Summer” in 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 opportunity 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, followed by 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.

Global surface air temperature increased by ca. 0.5 °C from the 1900s to the mid-1940s, also known as Early 20th Century Warming (ETCW). However, the ETCW started from a particularly cold phase, peaking in 1908–1911. The cold phase was global but more pronounced in the Southern Hemisphere than in the Northern Hemisphere and most pronounced in the Southern Ocean, raising the question of whether uncertainties in the data might play a role. Here we analyse this period based on reanalysis data and reconstructions, complemented with newly digitised ship data from 1903–1916, as well as land observations. The cooling is seen consistently in different data sets, though with some differences. Results suggest that the cooling was related to a La-Niña-like pattern in the Pacific, a cold tropical and subtropical South Atlantic, a cold extratropical South Pacific, and cool southern midlatitude land areas. The Southern Annular Mode was positive, with a strengthened Amundsen–Bellingshausen seas low, although the spread of the data products is considerable. All results point to a real climatic phenomenon as the cause of this anomaly and not a data artefact. Atmospheric model simulations are able to reproduce temperature and pressure patterns, consistent with a real and perhaps ocean-forced signal. Together with two volcanic eruptions just before and after the 1908–1911 period, the early 1900s provided a cold start into the ETCW.

Astronomer and calendar maker Gottfried Kirch was a keen weather observer and made weather notes in his diary starting in 1677 in Leipzig. In parallel, his second wife Maria Margaretha Winkelmann started a weather diary in 1700 in Berlin. The diaries also contain instrumental measurements of temperature and later pressure. After the death of Gottfried in 1710 and Maria Margaretha in 1720, observations were continued by their son Christfried and then for another 44 years by their daughter Christine. The last measurements date to 1774. Together, the diaries span almost a century of weather observations. The instrumental measurements constitute the oldest part of Germany's longest temperature series, which was however only available as monthly means up to now. Here we publish the imaged diaries, together amounting to 10 445 images. Further, we present the digitized instrumental series, which will serve as the starting point for a new, daily Berlin series. By comparing the series to neighbouring records, we show that the pressure data are reliable in a quantitative sense, whereas this is true for the temperature data only in a qualitative sense as the temperature scale was not converted.

Climate reconstructions give insights in monthly and seasonal climate variability in the past few hundred years. However, for understanding past extreme weather events and for relating them to impacts, for example through crop yield simulations or hydrological modelling, reconstructions on a weather timescale are needed. Here, we present a data set of 258 years of daily temperature and precipitation fields for Switzerland from 1763 to 2020. The data set was reconstructed with the analogue resampling method, which resamples meteorological fields for a historical period based on the most similar day in a reference period. These fields are subsequently improved with data assimilation for temperature and bias correction for precipitation. Even for an early period prior to 1800 with scarce data availability, we found good validation results for the temperature reconstruction especially in the Swiss Plateau. For the precipitation reconstruction, skills are considerably lower, which can be related to the few precipitation measurements available and the heterogeneous nature of precipitation. By means of a case study of the wet and cold years from 1769 to 1772, which triggered widespread famine across Europe, we show that this data set allows more detailed analyses than hitherto possible.

The winter 1788/89 was one of the coldest winters Europe had witnessed in the past 300 years. Fortunately, for historical climatologists, this extreme event occurred at a time when many stations across Europe, both private and as part of coordinated networks, were making quantitative observations of the weather. This means that several dozen early instrumental series are available to carry out an in-depth study of this severe cold spell. While there have been attempts to present daily spatial information for this winter, there is more to be done to understand the weather variability and day-to-day processes that characterised this weather extreme. In this study, we seek to reconstruct daily spatial high-resolution temperature and sea level pressure fields of the winter 1788/89 in Europe from November through February. The reconstruction is performed with an analogue resampling method (ARM) that uses both historical instrumental data and a weather type classification. Analogue reconstructions are then post-processed through an ensemble Kalman fitting (EnKF) technique. Validation experiments show good skill for both reconstructed variables, which manage to capture the dynamics of the extreme in relation to the large-scale circulation. These results are promising for more such studies to be undertaken, focusing on different extreme events and other regions in Europe and perhaps even further back in time. The dataset presented in this study may be of sufficient quality to allow historians to better assess the environmental and social impacts of the harsh weather.

We describe the compilation of two early instrumental daily temperature series from Bern and Zurich, Switzerland, starting from 1760 and 1756, respectively. The series are a combination of numerous small segments from different observers at different locations within and outside the two cities that are converted to modern units and homogenized. In addition, we introduce a methodology to estimate the errors affecting daily and monthly mean values derived from early instrumental observations. Given the frequent small data gaps, we merge the two daily series into a more complete series representing the central Swiss Plateau. We finally compare the homogenized monthly series with other temperature reconstructions for Switzerland. We find significant differences before 1860, pointing to biases that might affect some of the most widely used instrumental data sets. In general, the homogenization of temperature measurements at the transition between the early instrumental and national weather service eras remains a problematic issue in historical climatology and has significant implications for other fields of climate research.

European flood frequency and intensity change on a multidecadal scale. Floods were more frequent in the 19th (central Europe) and early 20th century (western Europe) than during the mid-20th century and again more frequent since the 1970s. The causes of this variability are not well understood and the relation to climate change is unclear. Palaeoclimate studies from the northern Alps suggest that past flood-rich periods coincided with cold periods. In contrast, some studies suggest that more floods might occur in a future, warming world. Here we address the contribution of atmospheric circulation and of warming to multidecadal flood variability. For this, we use long series of annual peak streamflow, daily weather data, reanalyses, and reconstructions. We show that both changes in atmospheric circulation and moisture content affected multidecadal changes of annual peak streamflow in central and western Europe over the past two centuries. We find that during the 19th and early 20th century, atmospheric circulation changes led to high peak values of moisture flux convergence. The circulation was more conducive to strong and long-lasting precipitation events than in the mid-20th century. These changes are also partly reflected in the seasonal mean circulation and reproduced in atmospheric model simulations, pointing to a possible role of oceanic variability. For the period after 1980, increasing moisture content in a warming atmosphere led to extremely high moisture flux convergence. Thus, the main atmospheric driver of flood variability changed from atmospheric circulation variability to water vapour increase.

In recent years, instrumental observations have become increasingly important in climate research, allowing past daily-to-decadal climate variability and weather extremes to be explored in greater detail. The 18th century saw the formation of several short-lived meteorological networks of which the one organised by the Societas Meteorologica Palatina is arguably the most well known. This network stood out as one of the few that efficiently managed to control its members, integrating, refining, and publishing measurements taken from numerous stations around Europe and beyond. Although much has been written about the network in both history, science, and individual prominent series used for climatological studies, the actual measurements have not yet been digitised and published in extenso. This paper represents an important step towards filling this perceived gap in research. Here, we provide an inventory listing the availability of observed variables for the 37 stations that belonged to the society's network and discuss their historical context. Most of these observations have been digitised, and a considerable fraction has been converted and formatted. In this paper, we focus on the temperature and pressure measurements, which have been corrected and homogenised. We then demonstrate their potential for climate research by analysing two cases of extreme weather. The recovered series will have wide applications and could contribute to a better understanding of the mechanisms behind climatic variations and extremes as well as the societal reactions to adverse weather. Even the shorter series could be ingested into reanalyses and improve the quality of large-scale reconstructions.

Upper-air data form the backbone of weather analysis and reanalysis products, particularly in the pre-satellite era. However, they are particularly prone to errors and uncertainties, especially data from the early days of aerology. Information that allows us to better characterize the errors of radiosonde data is important. This paper reports on an attempt to collect data from historical upper-air intercomparisons and from historical error assessments reaching back to the 1930s. The digitized numerical data will be made available through Copernicus Climate Change Services; here we publish the full information that includes images, literature, and other metadata that may be relevant and can be used to inform homogenization approaches or reanalysis production. The data collection described in this paper is available on PANGAEA: https://doi.org/10.1594/PANGAEA.925860 (Imfeld et al., 2021).

Data assimilation approaches such as the ensemble Kalman filter method have become an important technique for paleoclimatological reconstructions and reanalysis. Different sources of information, from proxy records and documentary data to instrumental measurements, were assimilated in previous studies to reconstruct past climate fields. However, precipitation reconstructions are often based on indirect sources (e.g., proxy records). Assimilating precipitation measurements is a challenging task because they have high uncertainties, often represent only a small region, and generally do not follow a Gaussian distribution. In this paper, experiments are conducted to test the possibility of using information about precipitation in climate reconstruction with monthly resolution by assimilating monthly instrumental precipitation amounts or the number of wet days per month, solely or in addition to other climate variables such as temperature and sea-level pressure, into an ensemble of climate model simulations. The skill of all variables (temperature, precipitation, sea-level pressure) improved over the pure model simulations when only monthly precipitation amounts were assimilated. Assimilating the number of wet days resulted in similar or better skill compared to assimilating the precipitation amount. The experiments with different types of instrumental observations being assimilated indicate that precipitation data can be useful, particularly if no other variable is available from a given region. Overall the experiments show promising results because with the assimilation of precipitation information a new data source can be exploited for climate reconstructions. The wet day records can become an especially important data source in future climate reconstructions because many existing records date several centuries back in time and are not limited by the availability of meteorological instruments.

We describe a dataset of recently digitised meteorological observations from 40 locations in today's Switzerland, covering the 18th and 19th centuries. Three fundamental variables – temperature, pressure, and precipitation – are provided in a standard format after they have been converted into modern units and quality-controlled. The raw data produced by the digitisation, often including additional variables and annotations, are also provided. Digitisation was performed by manually typing the data from photographs of the original sources, which were in most cases handwritten weather diaries. These observations will be important for studying past climate variability in Central Europe and in the Alps, although the general scarcity of metadata (e.g. detailed information on the instruments and their exposure) implies that some caution is required when using them. The data described in this paper can be found at https://doi.org/10.1594/PANGAEA.909141 (Brugnara, 2020).

In 1970, the Institute of Geography of the University of Bern initiated the phenological observation network BernClim. Seasonality information from plants, fog and snow was originally available for applications in urban and regional planning and agricultural and touristic suitability and is now a valuable data set for climate change impact studies. Covering the growing season, volunteer observers record the dates of key development stages of hazel (Corylus avellana), dandelion (Taraxacum officinale), apple tree (Pyrus malus) and beech (Fagus sylvatica). All observations consist of detailed site information, including location, altitude, exposition (aspect) and inclination, that makes BernClim unique in its richness in detail on decadal timescales. Quality control (QC) by experts and statistical analyses of the data have been performed to flag impossible dates, dates outside the biologically plausible range, repeated dates in the same year, stretches of consecutive identical dates and statistically inconsistent dates (outliers in time or in space). Here, we report BernClim data of 7414 plant phenological observations from 1970 to 2018 from 1304 sites at 110 stations, the QC procedure and selected applications (Rutishauser et al., 2019: https://doi.org/10.1594/PANGAEA.900102). The QC points to very good internal consistency (only 0.2 % were flagged as internally inconsistent) and likely high quality of the data. BernClim data indicate a trend towards an extended growing season. They also track the regime shift in the late 1980s well to pronounced earlier dates like numerous other phenological records across the Northern Hemisphere.

The decadal variability of weather and its extremes are still poorly understood. This is partly due to the scarcity of records, which, for many parts of the world, only allow for studies of 20th century weather. However, the 18th and early 19th centuries saw some pronounced climatic variations, with equally pronounced impacts on the environment and society. Considerable amounts of weather data are available even for that time but have not yet been digitised. Given recent progress in the quantitative reconstruction of subdaily weather, such data could form the basis of weather reconstructions. In Switzerland, measurements before 1864 (the start of the national network) have never been systematically compiled except for three prominent series (Geneva, Basel, Great St. Bernard Pass). Here we provide an overview of early instrumental meteorological measurements in Switzerland resulting from an archive survey. Our inventory encompasses 334 entries from 206 locations, providing an estimated 3640 station years and reaching back to the early 18th century. Most of the data sheets have been photographed and a considerable fraction is undergoing digitisation. This paper accompanies the online publication of the imaged data series and metadata. We provide a detailed inventory of the series, discuss their historical context, and provide the photographed data sheets. We demonstrate their usefulness on behalf of two historical cases and show how they complement the existing series in Europe. If similar searches in other countries yield similarly rich results, an extension of daily weather reconstructions for Europe back to the 1760s is possible.

The eruption of Mount Tambora (Indonesia) in April 1815 is the largest documented volcanic eruption in history. It is associated with a large global cooling during the following year, felt particularly in parts of Europe and North America, where the year 1816 became known as the "year without a summer". This paper describes an effort made to collect surface meteorological observations from the early instrumental period, with a focus on the years of and immediately following the eruption (1815–1817). Although the collection aimed in particular at pressure observations, correspondent temperature observations were also recovered. Some of the series had already been described in the literature, but a large part of the data, recently digitised from original weather diaries and contemporary magazines and newspapers, is presented here for the first time. The collection puts together more than 50 sub-daily series from land observatories in Europe and North America and from ships in the tropics. The pressure observations have been corrected for temperature and gravity and reduced to mean sea level. Moreover, an additional statistical correction was applied to take into account common error sources in mercury barometers. To assess the reliability of the corrected data set, the variance in the pressure observations is compared with modern climatologies, and single observations are used for synoptic analyses of three case studies in Europe. All raw observations will be made available to the scientific community in the International Surface Pressure Databank.

The newly developed atmosphere–ocean–chemistry–climate model SOCOL-MPIOM is presented by demonstrating the influence of chemistry–climate interactions on the climate state and the variability. Therefore, we compare pre-industrial control simulations with (CHEM) and without (NOCHEM) interactive chemistry. In general, the influence of the chemistry on the mean state and the variability is small and mainly restricted to the stratosphere and mesosphere. The atmospheric dynamics mainly differ in polar regions, with slightly stronger polar vortices in the austral and boreal winter, respectively. The strengthening of the vortex is related to larger stratospheric temperature gradients, which are attributed to a parameterisation of the absorption of ozone and oxygen in different wavelength intervals, which is considered in the version with interactive chemistry only. A second reason for the temperature differences between CHEM and NOCHEM is related to diurnal variations in the ozone concentrations in the higher atmosphere, which are missing in NOCHEM. Furthermore, stratospheric water vapour concentrations substantially differ between the two experiments, but their effect on temperature is small. In both setups, the simulated intensity and variability of the northern polar vortex is inside the range of present-day observations. Additionally, the performance of SOCOL-MPIOM under changing external forcings is assessed for the period 1600–2000 using an ensemble of simulations. In the industrial period from 1850 onward SOCOL-MPIOM overestimates the global mean surface air temperature increase in comparison to observational data sets. Sensitivity simulations show that this overestimation can be attributed to a combination of factors: the solar forcing reconstruction, the simulated ozone changes, and incomplete aerosol effects and land use changes.

The aim of this work is to elucidate the impact of changes in solar irradiance and energetic particles versus volcanic eruptions on tropospheric global climate during the Dalton Minimum (DM, AD 1780–1840). Separate variations in the (i) solar irradiance in the UV-C with wavelengths λ < 250 nm, (ii) irradiance at wavelengths λ > 250 nm, (iii) in energetic particle spectrum, and (iv) volcanic aerosol forcing were analyzed separately, and (v) in combination, by means of small ensemble calculations using a coupled atmosphere–ocean chemistry–climate model. Global and hemispheric mean surface temperatures show a significant dependence on solar irradiance at λ > 250 nm. Also, powerful volcanic eruptions in 1809, 1815, 1831 and 1835 significantly decreased global mean temperature by up to 0.5 K for 2–3 years after the eruption. However, while the volcanic effect is clearly discernible in the Southern Hemispheric mean temperature, it is less significant in the Northern Hemisphere, partly because the two largest volcanic eruptions occurred in the SH tropics and during seasons when the aerosols were mainly transported southward, partly because of the higher northern internal variability. In the simulation including all forcings, temperatures are in reasonable agreement with the tree ring-based temperature anomalies of the Northern Hemisphere. Interestingly, the model suggests that solar irradiance changes at λ < 250 nm and in energetic particle spectra have only an insignificant impact on the climate during the Dalton Minimum. This downscales the importance of top–down processes (stemming from changes at λ < 250 nm) relative to bottom–up processes (from λ > 250 nm). Reduction of irradiance at λ > 250 nm leads to a significant (up to 2%) decrease in the ocean heat content (OHC) between 0 and 300 m in depth, whereas the changes in irradiance at λ < 250 nm or in energetic particles have virtually no effect. Also, volcanic aerosol yields a very strong response, reducing the OHC of the upper ocean by up to 1.5%. In the simulation with all forcings, the OHC of the uppermost levels recovers after 8–15 years after volcanic eruption, while the solar signal and the different volcanic eruptions dominate the OHC changes in the deeper ocean and prevent its recovery during the DM. Finally, the simulations suggest that the volcanic eruptions during the DM had a significant impact on the precipitation patterns caused by a widening of the Hadley cell and a shift in the intertropical convergence zone.

The response of atmospheric chemistry and dynamics to volcanic eruptions and to a decrease in solar activity during the Dalton Minimum is investigated with the fully coupled atmosphere–ocean chemistry general circulation model SOCOL-MPIOM (modeling tools for studies of SOlar Climate Ozone Links-Max Planck Institute Ocean Model) covering the time period 1780 to 1840 AD. We carried out several sensitivity ensemble experiments to separate the effects of (i) reduced solar ultra-violet (UV) irradiance, (ii) reduced solar visible and near infrared irradiance, (iii) enhanced galactic cosmic ray intensity as well as less intensive solar energetic proton events and auroral electron precipitation, and (iv) volcanic aerosols. The introduced changes of UV irradiance and volcanic aerosols significantly influence stratospheric dynamics in the early 19th century, whereas changes in the visible part of the spectrum and energetic particles have smaller effects. A reduction of UV irradiance by 15%, which represents the presently discussed highest estimate of UV irradiance change caused by solar activity changes, causes global ozone decrease below the stratopause reaching as much as 8% in the midlatitudes at 5 hPa and a significant stratospheric cooling of up to 2 °C in the mid-stratosphere and to 6 °C in the lower mesosphere. Changes in energetic particle precipitation lead only to minor changes in the yearly averaged temperature fields in the stratosphere. Volcanic aerosols heat the tropical lower stratosphere, allowing more water vapour to enter the tropical stratosphere, which, via HOx reactions, decreases upper stratospheric and mesospheric ozone by roughly 4%. Conversely, heterogeneous chemistry on aerosols reduces stratospheric NOx, leading to a 12% ozone increase in the tropics, whereas a decrease in ozone of up to 5% is found over Antarctica in boreal winter. The linear superposition of the different contributions is not equivalent to the response obtained in a simulation when all forcing factors are applied during the Dalton Minimum (DM) – this effect is especially well visible for NOx/NOy. Thus, this study also shows the non-linear behaviour of the coupled chemistry-climate system. Finally, we conclude that especially UV and volcanic eruptions dominate the changes in the ozone, temperature and dynamics while the NOx field is dominated by the energetic particle precipitation. Visible radiation changes have only very minor effects on both stratospheric dynamics and chemistry.

Here we present a study of the 11 yr sunspot cycle's imprint on the Northern Hemisphere atmospheric circulation, using three recently developed gridded upper-air data sets that extend back to the early twentieth century. We find a robust response of the tropospheric late-wintertime circulation to the sunspot cycle, independent from the data set. This response is particularly significant over Europe, although results show that it is not directly related to a North Atlantic Oscillation (NAO) modulation; instead, it reveals a significant connection to the more meridional Eurasian pattern (EU). The magnitude of mean seasonal temperature changes over the European land areas locally exceeds 1 K in the lower troposphere over a sunspot cycle. We also analyse surface data to address the question whether the solar signal over Europe is temporally stable for a longer 250 yr period. The results increase our confidence in the existence of an influence of the 11 yr cycle on the European climate, but the signal is much weaker in the first half of the period compared to the second half. The last solar minimum (2005 to 2010), which was not included in our analysis, shows anomalies that are consistent with our statistical results for earlier solar minima.

The Modern Era Reanalysis (ModE-RA) is a global monthly paleo-reanalysis covering the period between 1421 and 2008. To reconstruct past climate fields an offline data assimilation approach is used, blending together information from an ensemble of transient atmospheric model simulations and observations. In the early period, ModE-RA utilizes natural proxies and documentary data, while from the 17 th century onward instrumental measurements are also assimilated. The impact of each observation on the reconstruction is stored in the observation feedback archive, which provides additional information on the input data such as preprocessing steps and the regression-based forward models. The monthly resolved reconstructions include estimates of the most important climate fields. Furthermore, we provide a reconstruction, ModE-RAclim, which together with ModE-RA and the model simulations allows to disentangle the role of observations and model forcings. ModE-RA is best suited to study intra-annual to multi-decadal climate variability and to analyze the causes and mechanisms of past extreme climate events., (© 2024. The Author(s).)

There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far., (© 2023. The Author(s).)

Data assimilation techniques are becoming increasingly popular for climate reconstruction. They benefit from estimating past climate states from both observation information and from model simulations. The first monthly global paleo-reanalysis (EKF400) was generated over the 1600 and 2005 time period, and it provides estimates of several atmospheric fields. Here we present a new, considerably improved version of EKF400 (EKF400v2). EKF400v2 uses atmospheric-only general circulation model simulations with a greatly extended observational network of early instrumental temperature and pressure data, documentary evidences and tree-ring width and density proxy records. Furthermore, new observation types such as monthly precipitation amounts, number of wet days and coral proxy records were also included in the assimilation. In the version 2 system, the assimilation process has undergone methodological improvements such as the background-error covariance matrix is estimated with a blending technique of a time-dependent and a climatological covariance matrices. In general, the applied modifications resulted in enhanced reconstruction skill compared to version 1, especially in precipitation, sea-level pressure and other variables beside the mostly assimilated temperature data, which already had high quality in the previous version. Additionally, two case studies are presented to demonstrate the applicability of EKF400v2 to analyse past climate variations and extreme events, as well as to investigate large-scale climate dynamics., Competing Interests: The authors declare that they have no conflict of interest., (© 2021 The Authors. Geoscience Data Journal published by Royal Meteorological Society and John Wiley & Sons Ltd.)

Annual-to-decadal variability in northern midlatitude temperature is dominated by the cold season. However, climate field reconstructions are often based on tree rings that represent the growing season. Here we present cold-season (October-to-May average) temperature field reconstructions for the northern midlatitudes, 1701-1905, based on extensive phenological data (freezing and thawing dates of rivers, plant observations). Northern midlatitude land temperatures exceeded the variability range of the 18th and 19th centuries by the 1940s, to which recent warming has added another 1.5 °C. A sequences of cold winters 1808/9-1815/6 can be explained by two volcanic eruptions and unusual atmospheric flow. Weak southwesterlies over Western Europe in early winter caused low Eurasian temperatures, which persisted into spring even though the flow pattern did not. Twentieth century data and model simulations confirm this persistence and point to increased snow cover as a cause, consistent with sparse information on Eurasian snow in the early 19th century., (© 2022. The Author(s).)

Phenological data have become increasingly important as indicators of long-term climate change. Consequently, long-term homogeneity of the records is an important aspect. In this paper, we apply a breakpoint detection algorithm to the phenological series from the Swiss Phenology Network (SPN). A combination of three statistical tests is applied and different constraints are tested with respect to the choice of reference series. Breakpoint detection is only possible for a fraction of the series due to the shortness of some series and the lack of suitable reference series. Spring phases are more likely to be suitable than fall phases because of their higher spatial correlation. Out of nearly 3000 phenological series with at least 20 data points, only about 5% were found to be significantly inhomogeneous, although a visual validation indicates that many mid-sized breakpoints remained undetected. The detected breakpoints were compared with metadata and more than half of them could be attributed to a change of observer.

Climatic variations at decadal scales such as phases of accelerated warming or weak monsoons have profound effects on society and economy. Studying these variations requires insights from the past. However, most current reconstructions provide either time series or fields of regional surface climate, which limit our understanding of the underlying dynamics. Here, we present the first monthly paleo-reanalysis covering the period 1600 to 2005. Over land, instrumental temperature and surface pressure observations, temperature indices derived from historical documents and climate sensitive tree-ring measurements were assimilated into an atmospheric general circulation model ensemble using a Kalman filtering technique. This data set combines the advantage of traditional reconstruction methods of being as close as possible to observations with the advantage of climate models of being physically consistent and having 3-dimensional information about the state of the atmosphere for various variables and at all points in time. In contrast to most statistical reconstructions, centennial variability stems from the climate model and its forcings, no stationarity assumptions are made and error estimates are provided.