Introducing 2018 Springcasting!

For the rest of the month of April, we will now be updating these maps every 5 days as spring closes in on the Northeast and most of the rest of the US:

How do you know it's spring?
Back in the 1950s, Prof. Joe Caprio of Montana State University recruited a large network of volunteers across the western US to plant common lilacs and record the dates on which flowers (and later leaves) first burst from their buds. Similar efforts were conducted with cloned lilacs in the eastern US, and for honeysuckle as well. These species were targeted in part because they respond strongly to spring warmth, and at the same time they are perhaps one of the clearest sentinels of the start of spring; when the lilacs start putting on leaves, it "feels" like spring.

In the 1980s, as part of his dissertation, Prof. Mark D. Schwartz (University of Wisconsin-Milwaukee) developed a method for predicting lilac and honeysuckle phenological events from meteorological data alone. In the 1990s he expanded this approach to model phenology at continental scales, and by the early 2000s he had developed a first-of-its kind continental-scale "suite of spring indices," which is documented in the now classic paper Schwartz et al., 2006. Since then, Prof. Schwartz and Prof. Ault have collaborated on a number of extensions and applications of the spring indices along with Dr. Julio Betancourt (USGS) and the USA National Phenology Network (USA-NPN:, as well as many others. Notably, Schwartz et al., (2013) modified the original indices to extend their usability to subtropical regions, and Ault et al., 2015 developed the first "gridded" (e.g., spatially-complete) SI-x product for North America.

In 2016, the USA-NPN began issuing daily spring indices maps that track the start of spring as it unfolds across the US (, using NOAA National Centers for Environmental Prediction Real-Time Mesoscale Analysis temperature products. The timing of this development was especially useful for characterizing the exceptionally early spring that occurred across much of the US in 2017.

Looking ahead
This year we are starting a new experimental project to predict spring onset several weeks—perhaps even months—in advance. If we are successful, we hope that these seasonal outlooks could be used by growers and natural resource managers to make critical decisions about how to allocate resources on long-lead time horizons.

The map above shows our current predictions for the spring onset anomalies this year, expressed as the number of days “early” or “late” we expect the spring to start compared to average conditions from the period spanning 1981-2010. It is based off of state-of-the-art seasonal forecast data from the National Oceanic and Atmospheric Administration’s (NOAA) Climate Forecast System Version 2 (CFSv2). We have applied an additional post-processing step to this data product using a relatively novel statistical approach described here: Carrillo et al., in prep.

While the first map shows the anomalies predicted for this year, the second map shows the onset date itself. So, those early anomalous values mean that, for much of the southwest, spring onset has already “occurred,” which fits well with the recent warm weather experienced throughout much of that region.

These predictions will be updated twice a month, and can be readily compared with the Spring Leaf Index maps produced by the USA-NPN, shown below and described at The USA-NPN Spring Leaf Index maps display locations that have reached the requirements for the Spring Leaf Index model (based on NOAA National Centers for Environmental Prediction Real-Time Mesoscale Analysis temperature products) and how this year compares to the long-term average (1981-2010).

Stay tuned as our maps are updated and spring unfolds this season. For additional information, or to report problems, please contact

Although the data found using the Springcasting data have been produced and processed from sources believed to be reliable, no warranty, expressed or implied, is made regarding accuracy, adequacy, completeness, legality, reliability or usefulness of any information. This disclaimer applies to both isolated and aggregate uses of the information. The information is provided on an "as is" basis. All warranties of any kind, express or implied, including but not limited to the implied warranties of merchantability, fitness for a particular purpose, freedom from contamination by computer viruses and non-infringement of proprietary rights are disclaimed. Changes may be periodically made to the information herein; these changes may or may not be incorporated in any new version of the publication. If you have obtained Springcasting information from a source other than the ECRL or CICCS web site, be aware that electronic data can be altered subsequent to original distribution. Data can also quickly become out-of-date. It is recommended that careful attention be paid to the contents of any data associated with a file or image, and that the originator of the data or information be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to the webmaster.