Abstract

This study presents a new global gridded dataset of bioclimatic indicators at 0.5° by 0.5° resolution for historical and future conditions. The dataset, called CMCC-BioClimInd, provides a set of 35 bioclimatic indices, expressed as mean values over each time interval, derived from post-processing both climate reanalysis for historical period (1960–1999) and an ensemble of 11 bias corrected CMIP5 simulations under two greenhouse gas concentration scenarios for future climate projections along two periods (2040–2079 and 2060–2099). This new dataset complements the availability of spatialized bioclimatic information, crucial aspect in many ecological and environmental wide scale applications and for several disciplines, including forestry, biodiversity conservation, plant and landscape ecology. The data of individual indicators are publicly available for download in the commonly used Network Common Data Form 4 (NetCDF4) format.

Highlights

  • Background & SummaryClimate change impacts, affecting primarily ecosystems’ functions and human sectors, have become a crucial topic within the scientific community and most recently across the whole society and sustainable development efforts

  • Under faster and faster environmental modifications over lands[4], climate datasets and efficient processing chains applied on them allow answering many urgent questions of biogeographical sciences about climate change impacts on living organisms, even through the interactions they have with the surrounding natural resources, like water and soil

  • The primary data source to derive BioClimInd for future time horizons are the outputs of climate model simulations that, despite the substantial progress occurred in the last few decades, are still affected by both systematic and random errors preventing their direct use in climate impact studies without affecting their reliability[13,14,15]

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Summary

Background & Summary

Climate change impacts, affecting primarily ecosystems’ functions and human sectors, have become a crucial topic within the scientific community (https://www.ipcc.ch/working-group/wg2/) and most recently across the whole society and sustainable development efforts (https://sustainabledevelopment.un.org/sdg[13]). The primary data source to derive BioClimInd for future time horizons are the outputs of climate model simulations that, despite the substantial progress occurred in the last few decades, are still affected by both systematic and random errors preventing their direct use in climate impact studies without affecting their reliability[13,14,15]. The CMCC-BioClimInd dataset contributes to widening the availability of spatial information useful to the community by (1) providing an ensemble of bioclimatic indicators for the historical and future time frames (e.g. Figs 1 and 2) (2) adopting models and/or other analysis methods for robust (i.e. taking into account uncertainty) climate change impacts’ assessments, at broad scale and in a wide range of research fields such as wildlife ecology, natural resources’ conservation and management, climate impacts’ mitigation. The exploitation of indicators instead of just raw climate variables enables easier inferring of relationships between the studied topic (species occurrence, resources availability etc.) and the climate regime to support decision for complex systems[36]; on the other hand, using the ensemble allows considering the variability across simulations due to the different models’ physics and the uncertain future development pathways[37]

Methods
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