Temperature-based Climate Projections of Pinot noir Suitability in the Willamette Valley American Viticultural Area

Abstract

In this study, we consider the complete archive of the 32 Coupled Model Intercomparison Project Phase 5 (CMIP5) daily Localized Constructed Analogs (LOCA) downscaled historic datasets and their observational data that were used for downscaling and bias corrections to develop an ensemble that optimises calculation of the growing season average temperature (GST) viticulture climate classification index throughout the Willamette Valley (WV) American Viticultural Area (AVA). Ensemble directed spatiotemporal calculations, using LOCA CMIP5 historic and RCP4.5 future datasets of minimum and maximum daily temperature, were performed throughout the WV AVA for the GST index and Pinot noir specific applications of the grapevine sugar ripeness (GSR) model at a 220 g/L target sugar concentration. The GST index and GSR model evaluations were calculated on a mean decadal basis from the 1950s to the 2090s for the WV AVA. The GST index and GSR model calculations both revealed a warming trend with time for the WV AVA. A 3.1 °C increase in the GST index is predicted from the 1950s to the 2090s. The GSR model indicated a rate advance of 2.9 days a decade from the 1960s to the 2080s. However, the application of the GST index and the GSR model portray markedly different characterisations about the suitability of Pinot noir throughout the WV AVA with time. A strong invertible relationship between the GST index and GSR model calculations is observed and exploited to update the Pinot noir specific lower and upper bounds (14.8 °C, 17.6 °C) for the GST index throughout the WV AVA. Pinot noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot noir production is currently at or near its peak value in the upper 80s to the lower 90s.

Viticultural Suitability Analysis Based on Multi-Source Data Highlights Climate-Change-Induced Decrease in Potential Suitable Areas: A Case Analysis in Ningxia, China

“…Although several environment variables were chosen to assess the ecological suitability of wine grape, selected variables were mainly climatic factors [5,34,40], followed by soil and topography [28,33]. In this study, we combined the data of climate, soil, and topography and remote sensing data (NDVI and LST) and divided phenological stages of grapevines into four periods to precisely estimate potential suitable areas.…”

“…The results provided support to develop new planting areas, which are potentially suitable but are not planted currently. Although previous studies mainly estimated potential suitable areas combining the MaxEnt model with climate and soil variables in different wine regions of world [5,28,33,34], we applied traditional variables of climate, soil, and topography, as well as remote-sensing-related indices and divided climate and remote sensing data into four periods based on phenological stages to accurately confirm which phenological period mainly affects the distribution of wine grape. Since grapevines possess a long life span of 30-50 years, it is not sufficient to explore currently potential suitable areas of wine grapes under continuously changing climate.…”

“…Previous research has evaluated viticultural suitability worldwide using different methodologies. One approach is to evaluate the ecological suitability based on selected environment indicators related to growth and development of grapevine [30][31][32][33][34]. The other approach is to establish a species distribution model combining the actual plantation of grapevine with its habitat variables [3,5,28,35,36], and the latter is more objective compared with the first, minimizing differences caused by diverse research scales [36].…”

Sign of Observed California Temperature Trends Depends on Data Set Homogenization: Implications for Weighting and Downscaling

“…(2021); Skahill et al. (2022) performed a similar exercise using LOCA RCP 4.5 simulations for, among other variables, growing season average temperature to study climate projections for the Willamette Valley wine region. Notably, these studies all employed the Livneh (v1.2) observational data set for their historical comparisons.…”

“…We build off of previous work, including Wootten et al (2020) which created weighted estimates of precipitation in the south-central United States using LOCA-downscaled precipitation for the Representative Concentration Pathway 8.5 (RCP 8.5) scenario (Van Vuuren et al, 2011). Skahill et al (2021); Skahill et al (2022) performed a similar exercise using LOCA RCP 4.5 simulations for, among other variables, growing season average temperature to study climate projections for the Willamette Valley wine region. Notably, these studies all employed the Livneh (v1.2) observational data set for their historical comparisons.…”