Documentary climate data describe evidence of past climate arising from predominantly written historical documents such as diaries, chronicles, newspapers, or logbooks. Over the past decades, historians and climatologists have generated numerous document-based time series of local and regional climates. However, a global dataset of documentary climate time series has never been compiled, and documentary data are rarely used in large-scale climate reconstructions. Here, we present the first global multi-variable collection of documentary climate records. The dataset DOCU-CLIM comprises 621 time series (both published and hitherto unpublished) providing information on historical variations in temperature, precipitation, and wind regime. The series are evaluated by formulating proxy forward models (i.e., predicting the documentary observations from climate fields) in an overlapping period. Results show strong correlations, particularly for the temperature-sensitive series. Correlations are somewhat lower for precipitation-sensitive series. Overall, we ascribe considerable potential to documentary records as climate data, especially in regions and seasons not well represented by early instrumental data and palaeoclimate proxies.

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.

Annual-to-decadal variability in northern midlatitude temperature is predominantly dominated by the cold season. However, climate field reconstructions, which are essential for understanding the underlying mechanisms, are often based on tree rings. These mainly represent the growing season and allow limited insight on cold season effects. Plant and ice phenology data, on the other hand, are a rich source of cold season information that remains largely overlooked in climate reconstructions to date and could help to fill the seasonal gap. Here, we present Northern Hemispheric temperature field reconstructions for the extended cold season (October-to-May average) for 1701-1905 based entirely on phenological data. Time series of freezing and thawing dates of rivers together with a few early-spring plant observations covering a large area of the northern midlatitudes are used in a simple data assimilation framework. The reconstructions allow a 320-yr perspective of climate variability and change of boreal cold season climate and unveil that the temperature of the northern midlatitude land areas exceeded the variability range of the 18th and 19th centuries by the 1940s, to which recent warming has added another 1.5 °C. We also find 5-10 year long sequences of cold northern midlatitude winters. The most prominent example lasted from 1808/9 to 1815/6. The conspicuously cooling during that period is associated with two volcanic eruptions (1808/9 and 1815), which caused cooling as a direct effect. The years between the eruptions are characterized by weak southwesterly atmospheric flow over the Atlantic-European sector in early winter. This lead to low Eurasian temperatures, which persisted into spring while the flow pattern did not. Twentieth century data and model simulations confirm this persistence and point to increased snow cover as a cause. This is consistent with independent information on Eurasian snow in the early 19th century.

The great phenological accelerationTo the Editor -The world's longest time series of plant blooming and leaf-out in spring reveal unprecedented shifts since the middle of the 1980s in line with the acceleration of global warming.These long-term time series provide powerful evidence of the impact of global warming on life on Earth and can help raising awareness among citizens, decision makers, and future generations of the urgent need to mitigate greenhouse gas emissions.

Caption: Lightning discharges appear in various colours depending on the scatter of light inside the thundercloud and in the atmosphere.The intracloud lightning discharges in the centre of the thundercloud appear to be white with a bluish tint, and the cloud-to-ground discharge below appears to be orange.The right hand side of the thundercloud exhibits a green tint that is attributed to the unique composition of hydrometeors inside the thundercloud.The photo was taken in the late evening of 10 September 2013, near Tarragona in northeastern Spain.

Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Icon Share MailTo Twitter LinkedIn Tools Icon Tools Get Permissions Cite Icon Cite Search Site Citation Regina Wollenmann, Christine Moos, This Rutishauser; Mit Schutzwald das Risiko managen – heute und morgen Gérer le risque avec la forêt protectrice – aujourd’hui et demain. Schweizerische Zeitschrift fur Forstwesen 1 July 2022; 173 (4): 168–169. doi: https://doi.org/10.3188/2235-1469-173.4.168 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest Search

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.

AbstractEditor’s note: For easy download the posted pdf of the State of the Climate for 2019 is a low-resolution file. A high-resolution copy of the report is available by clicking here. Please be patient as it may take a few minutes for the high-resolution file to download.

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 Pan European Phenology (PEP) project is a European infrastructure to promote and facilitate phenological research, education, and environmental monitoring. The main objective is to maintain and develop a Pan European Phenological database (PEP725) with an open, unrestricted data access for science and education. PEP725 is the successor of the database developed through the COST action 725 "Establishing a European phenological data platform for climatological applications" working as a single access point for European-wide plant phenological data. So far, 32 European meteorological services and project partners from across Europe have joined and supplied data collected by volunteers from 1868 to the present for the PEP725 database. Most of the partners actively provide data on a regular basis. The database presently holds almost 12 million records, about 46 growing stages and 265 plant species (including cultivars), and can be accessed via http://www.pep725.eu/ . Users of the PEP725 database have studied a diversity of topics ranging from climate change impact, plant physiological question, phenological modeling, and remote sensing of vegetation to ecosystem productivity.

The responses of plant phenology to temperature variability have many consequences for ecological processes, agriculture, forestry, and human health. Temperature sensitivity (S-T) of phenology could measure how and to what degree plant could phenologically track climate change. The long-term trends and spatial patterns in S-T have been well studied for vegetative phenology such as leaf unfolding, but trends to be expected for reproductive phenology in the future remain unknown. Here we investigate trends and factors driving the temporal variation of S-T of first bloom date (FBD). Using the long-term FBD records during 1963-2013 for common lilac (Syringa vulgaris) from 613 stations in Europe, we compared changes in S-T from the beginning to the end of the study period. The Spearman partial correlations were used to assess the importance of four influencing factors. The results showed that the temporal changes in S-T of FBD varied considerably among time scales. Mean S-T decreased significantly by 0.92days degrees C-1 from 1963-1972 to 2004-2013 (P<0.01), but remained stable from 1963-1987 to 1989-2013. The strength of FBD and temperature relationship, the spring temperature variance, and winter chill all impact S-T in an expected way at most stations. No consistent responses of S-T on photoperiod were found. Our results imply that the trends and variability in S-T of flowering phenology are driving by multiple factors and impacted by time scales. Continued efforts are still needed to further examine the flowering-temperature relationship for other plant species in other climates and environments using similar methods to our study.

Editor’s note: For easy download the posted pdf of the State of the Climate for 2018 is a low-resolution file. A high-resolution copy of the report is available by clicking here . Please be patient as it may take a few minutes for the high-resolution file to download.

Planning for the future requires a detailed understanding of how climate change affects a wide range of systems at spatial scales that are relevant to humans. Understanding of climate change impacts can be gained from observational and reconstruction approaches and from numerical models that apply existing knowledge to climate change scenarios. Although modeling approaches are prominent in climate change assessments, observations and reconstructions provide insights that cannot be derived from simulations alone, especially at local to regional scales where climate adaptation policies are implemented. Here, we review the wealth of understanding that emerged from observations and reconstructions of ongoing and past climate change impacts in Switzerland, with wider applicability in Europe. We draw examples from hydrological, alpine, forest, and agricultural systems, which are of paramount societal importance, and are projected to undergo important changes by the end of this century. For each system, we review existing model-based projections, present what is known from observations, and discuss how empirical evidence may help improve future projections. A particular focus is given to better understanding thresholds, tipping points and feedbacks that may operate on different time scales. Observational approaches provide the grounding in evidence that is needed to develop local to regional climate adaptation strategies. Our review demonstrates that observational approaches should ideally have a synergistic relationship with modeling in identifying inconsistencies in projections as well as avenues for improvement. They are critical for uncovering unexpected relationships between climate and agricultural, natural, and hydrological systems that will be important to society in the future.