71 Climate Extreme Indices in 1 dataset
Climate

71 Climate Extreme Indices in 1 dataset

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A High-Resolution Global Gridded Historical Dataset of Climate Extreme Indices
Malcolm Mistry
Data , 2019, 4(1), 41 - 13/03/2019

The open access Climate Extreme Indices dataset we just released is the first of its kind for the high spatial resolution of 0.25° x 0.25° (~ 25 x 25 km grid) covering the period 1970-2016.

This set of annual – some also monthly – 71 indices of temperature and precipitation extremes, is defined and recommended by the World Meteorological Organization (WMO) Expert Teams on Climate Change Detection and Indices (ETCCDI) and Sector-specific Climate Indices (ET-SCI).

The indices are assembled using near-surface daily meteorological variables: minimum and maximum temperature, and precipitation, from the Global Land Data Assimilation System (GLDAS), a new generation quality controlled reanalysis data product developed jointly by NASA Goddard Space Flight Center and the National Center for Environmental Prediction.

These Climate Extreme Indices fall broadly under four categories: ‘duration’, ‘thresholds’, ‘absolute’ and ‘percentiles’, accounting for both moderate and severe extremes. In particular, the indices are tailored to be representative of droughts, precipitation extremes, heatwaves and coldwaves, characterizing spells and durations, as well as magnitude and intensity.

The dataset is mirrored on KNMI Climate Explorer, a popular one-stop shop for researchers to search, download, subset, analyse and visualize climate data. This will enable the research community (especially those focusing on regional impacts), to select only the desired spatio-temporal subset of the huge dataset available for impact analysis.  

The Climate Extreme Indices included in this dataset are suitable for sectoral impacts assessment, especially in agriculture, health, energy, and water resources sectors, both at regional and national scales. We hope this dataset will offer opportunities to researchers for potential applications in identification of hotspots (e.g. clusters of regions showing similar historical trends or regions with high vulnerability to extreme weather events).

Just that you know… we are also working on a second comprehensive set of sectoral climate indices, this time specifically for health and energy impact modelers. To be released by Summer 2019, stay tuned!

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