USA NPN National Phenology Network

Taking the Pulse of Our Planet

You are here

Lilac Flowers


Image credit:
L. Barnett

Extended Spring Indices


The Extended Spring Indices (SI-x) are models that scientists have developed to predict the “start of spring” at a particular location. Using historical observations of the timing of first leaf and first bloom in cloned lilacs and honeysuckles, as well as daily observations from nearby weather stations, scientists have been able to determine the weather conditions that precede general spring leaf-out for a wide range of plants. Like many other deciduous plants in temperate systems, these plants put on their leaves as temperatures warm in late winter and early spring. Recent work extended the original Spring Indices (SI-o; Schwartz 1997) from high latitude regions to subtropical environments by removing a chilling requirement (Schwartz et al 2013, Ault et al 2015a). 

Using the Extended Spring Index models, scientists can look at how much the start of spring has varied from one year to the next at a particular location, and whether recent years are dramatically different from the past or not. The models can also be used to forecast when selected plants might bloom or put on leaves in future years.


The spring indices are now being used at the national level to understand the impacts of climate change: 

Access Phenology Map Products

The provisional Spring Index First Leaf and First Bloom maps can be explored in the USA-NPN Visualization Tool.

Raster data files can also be accessed via the USA-NPN Geoserver instance. Available products include:

  • Current day and 6-day forecast maps of Spring Index First Leaf and First Bloom, updated nightly
  • Current year anomaly maps of First Leaf and First Bloom, generated by comparing current year maps to 30-year (1981-2010) averages
  • First Leaf and First Bloom for each year, 1981-2015
  • 30-year (1981-2010) average maps for First Leaf and First Bloom dates

Geoserver Documentation

How to Cite Spring Index Map Products

USA National Phenology Network. Year of dataset access. Name of data product, USA-NPN, Tucson, Arizona, USA. Data set accessed YYYY-MM-DD at      

USA-NPN Data Use Policy


Ault, T. R., M. D. Schwartz, R. Zurita-Milla, J. F. Weltzin, and J. L. Betancourt (2015): Trends and natural variability of North American spring onset as evaluated by a new gridded dataset of spring indices. Journal of Climate 28: 8363-8378.

Ault, T., Zurita-Milla, R., and Schwartz, M.D. (2015). A Matlab© toolbox for calculating spring indices from dailty meteorological data. Computers and Geosciences 83: 46-53.

Schwartz, M. D. 1997.  Spring index models: an approach to connecting satellite and surface phenology. Phenology in seasonal climates I, 23-38.

Schwartz, M. D., T. R. Ault, and J. L. Betancourt, 2013: Spring onset variations and trends in the continental United States: past and regional assessment using temperature-based indices. International Journal of Climatology, 33, 2917–2922, 10.1002/joc.3625.