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Extended Spring Indices, Continental United States, 1981 - Current Year
datasetposted on 28.04.2021, 21:10 by USA National Phenology Network
The USA National Phenology Network has available a series of gridded products enabling researchers to analyze historical and contemporary data related to the Extended Spring Indices. The Extended Spring Indices are mathematical models that predict the "start of spring" (timing of leaf out or bloom for species active in early spring) at a particular location (Schwartz 1997, Schwartz et al. 2006, Schwartz et al. 2013). These models were constructed using historical observations of the timing of first leaf and first bloom in a cloned lilac cultivar (Syringa x chinensis 'Red Rothomagensis') and two cloned honeysuckle cultivars (Lonicera tatarica 'Arnold Red' and L. korolkowii 'Zabelii'). Primary inputs to the model are temperature and weather events, beginning January 1 of each year (Ault et al. 2015). The model output is the day of year that a particular location met the requirements of one of the Spring Index models (First Leaf or First Bloom).
As the Extended Spring Index models are based on individual models for each of three calibration species, model output is available for each of these species individually, or as an average of the three species. The original Spring Indices (Schwartz 1997) included a chilling requirement. In a more recent version of the model (Schwartz et al. 2013), referred to as the Extended Spring Indices, the chilling requirement was excluded, allowing the index to be extended across the entire U.S. Spring index products in the USA National Phenology Network's gridded data product suite are based on the Extended Spring Indices.
The data are accessible via the USA-NPN Visualization Tool (https://www.usanpn.org/data/visualizations) and the USA-NPN Geoserver (user access facilitated by the Geoserver Request Builder: https://www.usanpn.org/geoserver-request-builder).
For all inquiries regarding this dataset, please contact the USA-NPN. This data is subject to the USA-NPN's Data Use Policy.