Spotted Wing Drosophila (SWD) degree-days (DDs) for selected Central US locations (updated daily)
Station Location (S to N) SWD DDs July 20, 2018
  College Stn Eerwood Fl TX   3876 DDs
10 days behind 2017
same as 2016
8 days ahead of normal
  Searcy Muni Apt AR   2908 DDs
same as 2017
1 days ahead of 2016
12 days ahead of normal
  Bowling Green-Warren C KY   2731 DDs
1 days ahead of 2017
5 days ahead of 2016
19 days ahead of normal
  Carbondale Murphysboro IL   2446 DDs
same as 2017
3 days ahead of 2016
13 days ahead of normal
  Quincy Reg-Baldwin Fld IL   2288 DDs
4 days ahead of 2017
7 days ahead of 2016
21 days ahead of normal
  Champaign Urbana Univ IL   2082 DDs
1 days behind 2017
4 days ahead of 2016
16 days ahead of normal
  Lafayette Purdue Univ IN   1947 DDs
5 days ahead of 2017
7 days ahead of 2016
12 days ahead of normal
  Peoria Greater Peoria IL   2145 DDs
4 days ahead of 2017
4 days ahead of 2016
17 days ahead of normal
  Rochelle Muni-Koritz F IL   1656 DDs
6 days ahead of 2017
3 days ahead of 2016
13 days ahead of normal
  Janesville-Rock County WI   1681 DDs
5 days ahead of 2017
3 days ahead of 2016
14 days ahead of normal
  Prairie Du Chien Muni WI   1711 DDs
8 days ahead of 2017
5 days ahead of 2016
13 days ahead of normal
  Baraboo Wisconsin Dell WI   1542 DDs
10 days ahead of 2017
4 days ahead of 2016
15 days ahead of normal
  Fond Du Lac Co Apt WI   1493 DDs
5 days ahead of 2017
3 days ahead of 2016
11 days ahead of normal
  Green Bay Austin Strau WI   1446 DDs
8 days ahead of 2017
6 days ahead of 2016
21 days ahead of normal
  Minneapolis / Blaine MN   1732 DDs
11 days ahead of 2017
4 days ahead of 2016
10 days ahead of normal

In presenting this information, we wish to stress that errors can occur. Use the information with caution. Predictive models do not replace the need for monitoring in the field. If you observe conditions that differ substantially from model predictions, please contact Len Coop to determine if the model inputs were incorrect, if the model functioning or weather data are in error, or if the model is inappropriate for your conditions.