Synthetic weather diaries: concept and application to Swiss weather in 1816

Brönnimann, Stefan

doi:10.5194/cp-16-1937-2020

Cited by 4 publications

(2 citation statements)

References 34 publications

(44 reference statements)

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“…First are Bayesian new approaches to integrating heterogeneous evidence and multiple reconstructions. Examples include techniques to extend weather reanalyses back into the 19th century (Devers et al, 2020) as well as reconstruction of daily to weekly weather patterns: for example, "Lamb-type" weather series for western Europe since the 18th century (Delaygue et al, 2019) and daily "synthetic weather diaries" for Switzerland since the 19th century (Brönnimann, 2020). In addition, researchers have developed Bayesian approaches for combining diverse sources of information at different scales into single reconstructions of climate variables.…”

Section: Bayesian Approaches To Integrating Evidencementioning

confidence: 99%

New perspectives on historical climatology

White

Pei

Kleemann

et al. 2022

WIREs Climate Change

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Historical climatology is an interdisciplinary field of research encompassing the reconstruction of past climate and weather from written sources and artifacts, as well the application of climate reconstructions to the study of human history. Historical climatology has grown in recent years, and this growth has brought both insights and challenges. Research has expanded into new regions and periods and diversified into novel sources, methods, and interdisciplinary collaborations. At the same time, the heterogeneity of evidence and approaches has complicated the integration of multiple climate and weather reconstructions. Moreover, the diversity of disciplinary perspectives, terminologies, and perspectives can create miscommunication among scholars in the field, particularly on issues of historical knowledge and causation. Innovative approaches in the field, including Bayesian methods, may help address these challenges.

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Section: Bayesian Approaches To Integrating Evidencementioning

confidence: 99%

New perspectives on historical climatology

White

Pei

Kleemann

et al. 2022

WIREs Climate Change

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show abstract

“…Weather diaries are not available from the late 20 th century, and instrumental data have different properties. Therefore, to train machine learning approaches, "synthetic weather diaries" and "pseudo early instrumental data" need to be generated from other data sources [129]. However, weather reconstructions based on machine learning techniques will undoubtedly become frequent in years to come and will provide an additional data source.…”

Section: Plos Climatementioning

confidence: 99%

From climate to weather reconstructions

Brönnimann

2022

PLOS Clim

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Climate reconstructions have contributed tremendously to our understanding of changes in the climate system and will continue to do so. However, in climate science the focus has partly shifted away from past seasonal and annual mean climate towards weather variability and extreme events. Weather events are more directly relevant for climate impacts and they capture the scale at which important processes take place. Weather reconstructions therefore help to better understand atmospheric processes, particularly during extreme events, to assess decadal-to-multidecadal climate variability through the lens of weather changes, and they allow impact modelling of past events. Consequently, attempts are currently undertaken to extend weather data sets far back into the past. In this review I discuss methods of weather reconstructions that are in use today. The methods range from expert analyses to data assimilation, from analog approaches to machine learning. Products range from weather types to four-dimensional fields. The methods complement each other as they are based on different assumptions and are based on different data sets. Weather reconstructions require more meteorological data than climate reconstructions. Additional data rescue efforts are therefore needed.

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A comparison between different methods to fill gaps in early precipitation series

et al. 2022

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The aim of this work is to analyse and compare different methodologies to fill gaps in early precipitation series, and to evaluate which time resolution is reachable, i.e. monthly or daily one. The following methods are applied and tested to fill the 1764–1767 gap in the precipitation series of Padua: (1) using a relationship between monthly amounts and frequencies; (2) transforming a daily log with visual observations into numerical values through analysis, classification, and calibration; (3) substituting the missing values with an instrumental record from a nearby, contemporary station in the same climatic area. To apply the second method, the descriptions reported in the Morgagni Logs are grouped in 37 classes and transformed into numerical values, using for calibration the observed amounts in the Poleni record over the 24-year common period. As a third method, the series of Temanza and Pollaroli in Venice is used to fill the gap, and the application of a factor scale based on the ratio Padua/Venice tempted. The results of these three methods are discussed and commented.

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Synthetic weather diaries: concept and application to Swiss weather in 1816

Cited by 4 publications

References 34 publications

New perspectives on historical climatology

New perspectives on historical climatology

From climate to weather reconstructions

A comparison between different methods to fill gaps in early precipitation series

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