USA NPN National Phenology Network

Taking the Pulse of Our Planet

You are here

Lilacs in flower, one of the phenological stages used to help calculate the Extended Spring Index models.

Image credit:
L. Barnett

Extended Spring Indices


The USA National Phenology Network produces a series of gridded products enabling researchers to analyze historical and contemporary 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 (S. 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 (common and cloned lilacs are treated as a single 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 Extended Spring Indices have been used as an indicator of climate change by both the Environmental Protection Agency and the National Climate Assessment. The product suite supports understanding of spatial patterns in the timing of spring, including short-term forecasts to support resource management. Recent work using this products shows advancement in the timing of spring across the US National Park Service.


Format: USA National Phenology Network. [Year Published] [Dataset Title] {as of [DOY] (for continuous daily data) | Year(s) [Year(s)] (for annual products) | Date [Date] (for daily products) } for Region [Coordinates]. [Parameterized URL for Data Download] USA-NPN, Tucson, Arizona, USA. Dataset Accessed [Date of Access] at


Example: USA National Phenology Network. 2017. Spring Indices, Current Year - First Bloom - Spring Index Date 2017-08-02. Region: 49.9375,-66.4791667,24.0625,-125.0208333.‑builder?service=wms&layer=si‑x:average_bloom_ncep&date=2017‑08‑02&format=image/png&projection=4269&width=1700&height=800&colors=1 . USA-NPN, Tucson, Arizona, USA. Data set accessed 2017-8-2.

USA-NPN Data Use Policy


Spring Index products available from USA-NPN include:

  • Current year maps of Spring Index First Leaf and First Bloom dates
  • 6-day forecast maps of Spring Index First Leaf and First Bloom dates
  • Current year anomaly maps of First Leaf and First Bloom dates (current year compared to 30-year [1981-2010] mean)
  • Annual First Leaf and First Bloom date maps, 1981-2015
  • 30-year (1981-2010) mean maps for First Leaf and First Bloom dates
  • Annual First Leaf and First Bloom date maps, 1880-2013


Download Data Using the USA-NPN Geoserver Request Builder

  • Raster Data Files (GeoTiff, ArcGrid, NetCDF)
  • Map Image Files (PNG, TIF, GIF, PDF)


Web Services Available via the USA-NPN Geoserver ( request=GetCapabilities)

Visualize the Data Using the USA-NPN Visualization Tool
  • Extended Spring Index data can be viewed independently or in conjunction with in-situ plant or animal phenology observation data using the online USA-NPN Visualization Tool


Daily Accumulated Growing Degree Day and Spring Index Maps information sheet

Map Products Documentation: Crimmins, T.M., R.L. Marsh, J. Switzer, M.A. Crimmins, K.L. Gerst, A.H. Rosemartin, and J.F. Weltzin. 2017. USA National Phenology Network gridded products documentation. U.S. Geological Survey Open-File Report 2017–1003.  DOI: 10.3133/ofr20171003.


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.

Rosemartin, A. H., Denny, E. G., Weltzin, J. F., Marsh, R. L., Wilson, B. E., Mehdipoor, H., & Schwartz, M. D. (2015). Lilac and honeysuckle phenology data 1956–2014. Nature Scientific data, 2, doi:0.1038/sdata.2015.38

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.