The global historical climate database HCLIM

Abstract

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.

Description

Long-term instrumental meteorological series are crucial for the understanding of interannual-to-decadal variations in climate. Analyzed together with model simulations and climate proxies they may provide new insight into underlying climate mechanisms, such as long-lasting droughts, changes in atmospheric circulation, or effects of volcanic eruptions, and may serve as a basis for the generation of more comprehensive data products in reconstruction or data assimilation approaches. Long-term instrumental meteorological series also serve as a reference against which human induced climate change can be compared. For instance, Hawkins et al. (2017) suggested using the period 1720–1800 as a preindustrial reference, but only few records from this period are currently available. We define a record as a meteorological time series with one variable at one location.

Keywords

historical climatology, global climate, datasets, data rescue

Citation

Scientific Data 10, Article number 44 (2023)

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Except where otherwised noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 Poland