Wines & Vines

108 WINES&VINES Collector's Edition GRAPEGROWING T he Winkler Index or Winkler Scale is a standard for describing regional climates for viticulture in the United States. Developed by A.J. Winkler and M.A. Amerine at the University of Cali- fornia, Davis in the first half of the 20th century, the index was constructed to corre- late wine quality with climate, focusing on California viticulture. Wine-producing regions of California were broken into five climatic regions using heat summations above 50° F, or growing degree days (GDD). Heat summa- tions are a way of looking at accumulated temperatures over a given time period. De- spite the common usage of the Winkler Index, the classifications offer greater uncertainty than the system suggests. An obvious drawback to the Winkler Index is the focus on temperature alone. Winkler's groundbreaking resource "General Viticulture" notes the influence of "rainfall, fog, humidity and duration of sunshine," but Amerine and Winkler's work and subsequent research found that temperature plays the greatest role in the development of wine grapes. As the focus of Winkler and Amerine's wine-grape research was on California viticulture, their climatic regions had the luxury of ignoring precipita- tion, as little rain falls during the growing season. Indeed, Winkler et al. in "General Vi- ticulture" suggest that the vinifera grape "is not suited to humid summers, owing to its suscep- tibility to certain fungus diseases and insect pests that flourish under humid conditions." 9 Advances in viticulture have expanded the range of successful commercial vinifera pro- duction, while more recent research notes the importance of wind on photosynthesis rates. 2 Winkler et. al. also point out the importance of ongoing refinement of local variations, stat- ing, "It is hoped that refinements will be de- veloped so as to delimit subregions within the present regions, thereby ensuring the greatest potential for quality when the most favorable climatic subregion for a given variety is planted to that variety." Therefore, the Winkler Index was designed at a state scale, and not necessarily intended for smaller viticultural subregions or single vineyards. Methodology of the index Modern-day calculations of GDD most often utilize daily accumulations of degree days. That is to say that they sum the total degrees of aver- age daily temperatures above 50° F (10° C) for every day from April 1 to Oct. 31 [∑ Oct 31 Apr 1 daily (T_mean-50,0)]. If the average temperature for a given day is 75° F, then the total degree days added to the total sum for that specific date would be 25° F. Any average below 50° F con- stitutes zero GDD for the given day. An initial problem with some calculations is how "average" is determined. In most cases, average is calculated as the mean of the lowest recorded temperature and the highest re- corded temperature, so a high temperature of 85° F and a low temperature of 65° F would produce 75° F [(T max -T min )/2]. Another method to calculate average temperatures is to take the mean of all temperature readings for a given day. If a weather station reports hourly temperature readings, the mean of those tem- perature readings would constitute the average of the 24 daily temperature readings, while if a station reports in 15-minute intervals, the average temperature would be the mean of the 96 daily temperature readings. The simple difference in methodology for calculating aver- age temperatures can have an impact on GDD readings. A recent study of five weather sta- tions in the Livermore Valley AVA, for example, found variations in 10-year average GDD as high as 206 based on the methodology uti- lized. 6 As many weather stations have software generating GDD figures for the user, the meth- odology deployed is not always obvious. Fur- ther, many software programs will vary on GDD calculations, including but not limited to growing season, threshold (e.g., 50° F or some other number), and how temperatures below that threshold are handled. Some weather station software programs, for example, will not include temperatures below 50° F in the average temperature calculation. Daily accumulation methodologies, how- ever, are not consistent with the methodology deployed by Winkler and Amerine. Rather, Winkler and Amerine used monthly means. Specifically, the mean monthly temperature above 50° F was multiplied by the number of days in the month for each month from April to October, then summed for the entire grow- ing season [∑ Oct Apr monthly((T_mean-50)•30)]. Further, a 1998 assessment of temperatures in the city of Sonoma, Calif., determined that Amerine and Winkler's original calculations may have been simplified to account for only 30 days in each month. 7 Hence, GDD originally calculated in 1944 may have had four fewer days figured into the equation than what mod- ern assessments typically apply. The discrepancy between daily accumula- tion of degree days and monthly accumulation of degree days is most pronounced in early- season and late-season numbers, when mean daily temperatures may be below 50° F. As a simple example, assume that the average tem- perature for each day from April 1 to April 15 is 48° F and mean temperature for each day April 16 through April 30 is 54° F. Using the daily accumulation method, each day from April 1 to April 15 would have a degree-day total of 0, while each day from April 16 to April 30 would have a degree-day total of 4, for an April total of 60 degree days. With an average monthly temperature of 51° F, using the monthly average would yield a GDD total of 30 degree days for the month. Even with consistency in methodology, other factors impact the overall GDD total, and hence the climatic region assigned to that total. Equipment and placement of weather stations are considered, although most government and research weather stations, and even most The Limitations of the Winkler Index By Patrick L. Shabram FIGURE 1: GDD (°F) AT CAMINO, CALIF. USING TWO METHODOLOGIES Daily Accumulation Monthly Accumulation Lowest (1998) 2889 2752 Highest (2017) 4034 3932 30-Year Average 3439 3300 10-Year Average 3583 3465 5-Year Average 3821 3639 30-year average GDD based on 2017-1987 exclud- ing 1988 because of incomplete data in 1988. 10-year average GDD based on 2017-2008. 5-year average based on 2017-2013.

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