A multi-decadal 1 km gridded database of continental-scale spring onset products

The timing of spring onset is a particularly sensitive climate change indicator that also allows the study of weather interannual variations and extremes. This indicator can be derived from a suite of phenological models called the Extended Spring Indices (SI-x). These models transform daily minimum and maximum temperatures into a set of consistent indices that track the timing of first leaf and first bloom for key indicator plant species. The SI-x also enables the calculation of the so-called frost damage index. Using new computational technologies and high spatial resolution gridded weather data, here we present and evaluate a multi-decadal 1 km spatial resolution version of the SI-x models, which cover North American (1980 to 2022) and European areas (1950 to 2020). Because of the generally good agreement with ground phenological observations, this continental-scale and high spatial resolution product can support both scientists and decision makers in their quest to hind- and forecast weather and climate change impacts.

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Publication Details

Journal
Scientific Data
Published
2024-08-21
DOI
https://doi.org/10.1038/s41597-024-03710-5
Citations
1
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
0.28

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article

A multi-decadal 1 km gridded database of continental-scale spring onset products

R. Zurita‐Milla, Emma Izquierdo‐Verdiguier
1 citations
Scientific Data
Plant Water Relations and Carbon Dynamics
0.28
article

A multi-decadal 1 km gridded database of continental-scale spring onset products

R. Zurita‐Milla, Emma Izquierdo‐Verdiguier
article en
1 citations

Abstract

The timing of spring onset is a particularly sensitive climate change indicator that also allows the study of weather interannual variations and extremes. This indicator can be derived from a suite of phenological models called the Extended Spring Indices (SI-x). These models transform daily minimum and maximum temperatures into a set of consistent indices that track the timing of first leaf and first bloom for key indicator plant species. The SI-x also enables the calculation of the so-called frost damage index. Using new computational technologies and high spatial resolution gridded weather data, here we present and evaluate a multi-decadal 1 km spatial resolution version of the SI-x models, which cover North American (1980 to 2022) and European areas (1950 to 2020). Because of the generally good agreement with ground phenological observations, this continental-scale and high spatial resolution product can support both scientists and decision makers in their quest to hind- and forecast weather and climate change impacts.

Scientific DataVol. 11(1)
BOKU University (AT), University of Twente (NL)
Universität für Bodenkultur Wien, U.S. Geological Survey
Climate action
Openalex Percentile: Top 43%
Plant Water Relations and Carbon Dynamics
0.28
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