Improved degree-day maps on Enviroweather
New maps provide more accurate and extensive growing degree-day information to users making pest and crop decisions.
The Michigan State University Enviroweather’s “Current Degree-Day Maps” tool shows accumulated growing degree-days (base 50) across Michigan from March 1 to the present (or a user-selected date). Additional maps depict degree-day accumulations compared with normal. These maps are one of Enviroweather’s most accessed applications.
The tool was completely rebuilt just before the 2016 growing season. New maps are easier to read with improved color contrast and clearer numbers. We used a different data source from NOAA National Weather Service called UnRestricted Mesoscale Analysis (URMA) to produce the maps. URMA is a collection of gridded weather datasets with a spatial resolution of approximately 1.5 miles. It can provide highly detailed, contoured maps of weather variables across a region.
Based on extensive comparisons of the gridded data values versus observed point data, we decided to use the URMA data for Enviroweather products when feasible. These data provide a good estimate of conditions in a given area, especially when there are missing observations or observing sites.
As mentioned above, the “Current Degree-Day Maps” tool also includes maps of accumulated growing degree-days as compared with normal. The source of the data for calculating “normal” is new this year. Data for the “normal” calculations comes from the PRISM Climate Group at Oregon State University. Based on our evaluation, these data improve accuracy and precision. Data from the past 30 years (1981–2010) were used to calculate normal.
In 2017, we added another map that shows the calculated accumulated normal growing degree-days for the selected date.
As in previous years, Enviroweather also displays maps of accumulated growing degree-days ahead/behind normal as measured by time (days/weeks) and degree-days. In 2017, we changed the way we depict days ahead or behind. Now the program takes the current degree-day accumulation and looks to the normal data set to determine when (on which date) that accumulation normally occurs. The difference in days between the normal map and the current map is used to determine days ahead/days behind.
For example, imagine the degree-day accumulation in East Lansing on April 20, 2017, is 151 (base 50). The program looks to the normal data and determines that in East Lansing, 151 degree-days is normally reached on April 23. That means 2017 is three days ahead of normal (The degree-days have been reached three days before they normally would have been.).