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  • A Palaeoreanalysis To Understand Decadal Climate Variability; Binary Object; Binary Object (File Size); File content; Northern Hemisphere; PALAEO-RA; phenology; temperature reconstruction; winter  (1)
  • A Palaeoreanalysis To Understand Decadal Climate Variability; DATE/TIME; Description; ELEVATION; File name; GlobCover; Identification; LATITUDE; LONGITUDE; PALAEO-RA; Pressure, atmospheric, monthly mean; Station label; Station pressure, monthly mean; Uniform resource locator/link to source data file  (1)
  • A Palaeoreanalysis To Understand Decadal Climate Variability; de-duplication; early instrumental; GlobCover; PALAEO-RA; paleoclimatology; Paleometeorology; quality control; Time series  (1)
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  • 1
    Publication Date: 2024-04-20
    Description: Annual-to-decadal variability in northern extratropical temperature is dominated by the cold season. However, climate field reconstructions, which would be essential for understanding the underlying mechanisms, are often based on tree ring records. These represent the growing season and hardly capture cold season effects. Here we present cold-season (October-to-May average) temperature field reconstructions for 1701-1905 based entirely on phenological data. These include mainly the freezing and thawing dates of rivers and few early-spring plant observations. We digitized and processed ice-free periods of Russian rivers as a proxy for temperature back to 1720 from ca. 800 sites. These records were complemented with other ice phenology data from Europe and North America, documentary sea-ice records from Iceland and Labrador, and plant phenological proxy records. In total, we used 68 records for the field reconstruction. Furthermore, we utilized a Bayesian reweighting method, in which 30-member ensemble AGCM simulations serve as prior temperature fields while the phenological data constrains the likelihoods/weights of each field.
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; Binary Object; Binary Object (File Size); File content; Northern Hemisphere; PALAEO-RA; phenology; temperature reconstruction; winter
    Type: Dataset
    Format: text/tab-separated-values, 10 data points
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2024-04-27
    Description: There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and the 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 has been merged from 18250 original data files. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate data set for the preindustrial period.
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; de-duplication; early instrumental; GlobCover; PALAEO-RA; paleoclimatology; Paleometeorology; quality control; Time series
    Type: Dataset
    Format: application/zip, 24 datasets
    Location Call Number Limitation Availability
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  • 3
    Publication Date: 2024-04-20
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; DATE/TIME; Description; ELEVATION; File name; GlobCover; Identification; LATITUDE; LONGITUDE; PALAEO-RA; Pressure, atmospheric, monthly mean; Station label; Station pressure, monthly mean; Uniform resource locator/link to source data file
    Type: Dataset
    Format: text/tab-separated-values, 2381290 data points
    Location Call Number Limitation Availability
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