Probabilistic climate change scenarios for viticultural potential in Québec
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Climate conditions for Québec’s viticultural potential (VP) during upcoming decades are estimated through high-resolution probabilistic climate scenarios (PCS) based on a large ensemble of simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). VP is investigated through four temperature-related indices identified as current limiting factors for cold, northern latitudes: length of frost-free season (CNFD), growing degree-days (DDB10), annual winter minimum temperature (AWMT), and annual number of very cold days (ANVCD). Results show that by 2040–2050, most of southern Québec can reasonably expect favorable climatic conditions, with enough consecutive frost-free days and growing degree-days for growing current hybrid-grape varieties, as well as some Vitis vinifera grape varieties. Regions with new VP are identified, for example southern Outaouais and along the St-Lawrence River. Cold winter temperatures remain problematic, but technical solutions to this limiting factor exist.
KeywordsClimate Index Representative Concentration Pathway Grape Variety Wine Industry Pinot Noir
Viticultural viability and quality of a given region depends strongly on climate, with inter-annual climate variability playing an important role in wine quality (Jones et al. 2005; Jones and Webb 2010) while extreme temperatures (hot and cold) act as important limiting factors for viability (White et al. 2006). Furthermore, climate change has already had measurable impacts on the wine industry worldwide (Battaglini et al. 2009; Jones 2012). During the next decades, evolving climatic conditions could result in the collapse of currently vulnerable wine-producing regions, as well as the rise of new ones (White et al. 2006; Hannah et al. 2013).
Southern Québec is located at latitudes comparable to southern France, but cannot presently exploit vine varieties such as those grown in Bordeaux for example, partly due to climatic differences, with harsh winters being a major difference. Measured bright-sunshine hours are higher in southern Québec than Bordeaux, Languedoc and New Zealand (Jones 2012). A wine industry developed about four decades ago in Québec, with the first commercial winery (La Vitacée) established in 1977 in Sainte-Barbe (Dubois 2001) and an estimated increase in total stock from 82,925 vine stocks in 1985 to 512,000 in 2000 (Dubois 2001), representing a fivefold growth in only 15 years. Since 2000, the sector has continued to grow rapidly, and in early 2017, there were 142 wine-category permits issued by the Régie des alcools des courses et de jeux du Québec (personal communication).
Due to climatic constraints, most winegrowers select grapes varieties that are suitable for a cold climate. Moreover, since southern Québec is not a traditional viticultural region, the recognition and marketing of the cold-hardy hybrid grapes varieties remains challenging. Observed climatic change over recent decades has prompted some winegrowers to grow Vitis viniferas (e.g., Pinot Noir, Cabernet Franc, Chardonnay), which typically attract higher prices, as they are well recognized around the world for their organoleptic qualities (Wolf 2008).
Here, we show the evolution of Québec’s VP over 1961—2070 (Fig. 1), using probabilistic climate scenarios (PCS) (e.g., Palmer and Räisänen, 2002; Tebaldi and Knutti 2007). PCS is an approach used to assign a probability-density function to a climate variable or a probability for a given event to occur, based on an ensemble of climate scenarios. While such an approach cannot avoid subjective assumptions (Parker 2010), it has legitimacy based on the fact that in the absence of pragmatic information, decision-makers will implicitly build their own probabilities, which may depart substantially from experts’ best guess (Hall et al. 2005).
Also shown is the degree to which future climate conditions indicate potential for growing V. vinifera, derived from climate-indicator thresholds associated with early ripening V. vinifera grape varieties such as Pinot Noir, Gamay, and Chardonnay. Under climate change, limiting conditions are expected to approach or exceed suitability thresholds for V. vinifera, increasing the potential to grow this variety.
This study is based on a large ensemble of climate scenarios from the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations (Taylor et al. 2011). A climate scenario is defined as a plausible future climate trajectory and is generally obtained by a post-processing method, which roughly consists of merging the observed historical climate information with the future trends simulated by a numerical climate model (Themeßl et al. 2012; Gennaretti et al. 2015). Uncertainty regarding the future climate trajectory is traditionally split into three sources: future anthropogenic emissions, variety in model formulation and natural climate variability (Hawkins and Sutton 2011).
Representative Concentration Pathways (RCP) 4.5 and 8.5 have been adopted as lower and higher boundaries for uncertainty of the “emissions” type. Simulations forced by these two RCPs form two distributions in terms of warming that start diverging around 2040 and still overlap in 2100. RCP2.6 has been judged too unrealistic during the second half of the 21st century to be used, and RCP6.0 already lies within the RCP4.5–RCP8.5 interval. The “model” and “natural variability” types of uncertainty are covered by the consideration of 26 models and 94 simulations.
2.2 Climate indices
Climate indices used for the assessment of viticultural potential
Maximum number of consecutive
< 150 (unsuitable)
days without frost (Tmin >= −2 ∘C)
> 150 (low)
> 156 (moderate)
> 166 (good)
> 180 (very good)
Growing degree days with base 10
< 900 (unsuitable)
between April 1st and October 31st
> 900 (low)
> 1000 (moderate)
> 1100 (good)
> 1250 (very good)
Annual winter minimum temperature
< −34 (unsuitable)
> −34 (low)
> −30 (moderate)
> −27 (good)
> −22 (very good)
Annual number of very cold days
> 30 (unsuitable)
(< −22 ∘C)
< 30 (low)
< 20 (moderate)
< 10 (good)
< 5 (very good)
These thresholds can be linked to some grape varieties. As stated earlier, hybrid grape varieties need less heat accumulation than V. vinifera. For example, Frontenac (1150 GDD), Marechal-Foch (951 GDD), Seyval (1050 GDD) needs fewer than 1250 GDD, while early-ripening V. vinifera needs a little more than 1250 GDD such as Pinot Noir (1251 GDD) or Chardonnay (1267 GDD) (Van Leeuwen et al. 2008). In terms of frost-free days, Pinot Noir and Chardonnay need a minimum of about 160 to 170 days. Hence, the combination of the “very good” thresholds can be seen as an approximation of a combined V. vinifera threshold while “moderate” threshold can be seen as an approximation of hybrid-variety threshold.
Harsh, cold winter temperatures can kill the vines or seriously reduce the production potential of non-hardy grapes such as V. vinifera and many French hybrid varieties. Without protection, temperatures below − 17 ∘C may kill the primary (as well as the secondary and tertiary) buds. Fortunately, adaptation techniques exist for this problem. This means that the temperature that will effectively kill the primary buds is somewhat lower. In a comprehensive experiment, Willwerth et al. (2014) showed that when vines are under soil, the temperature they experience could be as much as 18 ∘C different from the ambient temperature. Other techniques, such as covering vines with a polyester material did not perform as well, but still led to a mean difference of 4-to-6 ∘C from ambient temperatures. As such, the threshold used for V. vinifera grape varieties will be − 22 ∘C.
Finally, one aspect that is not covered in this study is late spring frost. Once enough warmth accumulates during spring, the vines are less tolerant to cold temperatures. If frost conditions (i.e., typically lower than − 2 ∘C) arise during this period of the year, it can kill the buds. Using the same PCS approach described in this paper, results show that the probability of late spring frost conditions is constant between 1961—2070 (Supplementary Materials). Although there appears to be a general shift towards early-spring conditions and longer growing seasons, the length of the transition period between winter conditions (e.g., temperature < 0 ∘C) and spring conditions (e.g., temperature > 0 ∘C) where there is a potential for frost damage does not seem to change greatly, resulting in constant probability of late spring frost.
2.3 Climate scenarios design
Interpolation and statistical adjustment of simulated time series
The daily climate-model outputs are interpolated onto the 10km National Resources Canada dataset grid (Hutchinson et al. 2009) through a standard Delaunay triangulation. The interpolated value is then corrected using a quantile-quantile mapping statistical adjustment (Themeßl et al. 2011; Grenier et al. 2015) with respect to the high-resolution NRCAN daily dataset. For each Julian day, a transfer function per quantile is estimated between the NRCAN and simulated-time series over the common period (1961—2070) and then applied to the 1961–2070 simulations. The reference dataset for a particular Julian day is comprised of a 30-day moving window centred on the Julian day of interest.
Resulting probability-time series are then filtered by a Gaussian filter (with parameter σ = 5) with the aim of smoothing the inter-annual variability to obtain the long-term component of the probability evolution.
2.4 Uncertainty on probabilities
Confidence intervals (CI) associated with the sampling uncertainty are calculated through a standard non-parametric bootstrapping approach (Efron 1979) with the bias corrected and accelerated percentile method (Efron 1987) and 10000 re-sampling iterations. Epistemic uncertainty (e.g., arising from an incomplete understanding of climate processes) is not addressed in this article and is not covered by the bootstrapped CI.
3.1 RCP handling and probability-time series
3.2 Composite probability
Analyzing each index separately is not necessarily optimal: a given year has no real potential if the frost-free season is long but there are not enough growing degree days. Hence, synchronicity between the climate indices is an important prerequisite and the composite probability shown here is simply the probability to exceed specified thresholds across indices. For our purposes, the interest is to pinpoint emerging viticultural regions (new VP) and regions where the suitability for some V. vinifera species could increase (improving VP).
Conclusions of this composite index are clear for 2050 and 2065: VP is relatively high in the southern part of the province (Montérégie, Outaouais, western part of Estrie) and along the St. Lawrence River. What is not clear however, is how these indices should be weighted: is one index more important to overall VP? Considering the protective techniques described above, unequal weights could potentially be considered for a more appropriate assessment. It is understood that growing degree days and the length of the frost-free season hold equal weight (personal communication). However, no clear consensus has been reached among end users about the relative weight of these two indices with respect to winter minimum temperatures. Moreover, the weights could vary spatially.
3.3 Type of vines
Grapevines climate/maturity groupings based on the growing season mean temperature
4.1 Interpretation of the probability results
Actors in the agricultural industry often use historical-occurrence frequencies as a form of probability, working with the formulation “X years out of Y.” This formulation might give the wrong picture in a context of non-stationary climate, where historical occurrence does not reflect future climate regime. In this sub-section, we discuss how these concepts (“X years out of Y” and the PCS approach) can be merged.
The first approach is the one where the user looks at a single simulation over a given period of years and answers such questions as “How many exceedances do I have over 10 years?” The second approach, represented by the black line, is the method proposed in this article: the proportion of scenarios exceeding a prescribed threshold for a given year, effectively reducing the information of the ensemble scenario for that year.
These results suggest that the PCS approach gives results close to the usual user formulation (“X years out of Y”) and that users could use the estimated PCS probabilities and associate them with their standard formulation, without much loss of generality. This also means that the PCS approach gives a good estimate of the climatological probabilities of exceeding a given threshold, in phase with the background climate change forcing, which is not the case with historical observations. However, this result indicates that natural variability creates a rather large distribution of possible trajectories for any given decade. We note that this possible difference between the estimated PCS probability and the actual climate trajectory probability for a given decade also applies to most, if not all, climatological statistics.
4.2 Uncertainties and limitations
Along with the RCP-related assumptions discussed in Section 2, one important limitation of the PCS approach is that the ensemble used might have common biases (e.g., processes unknown to climatologists). Hence, the ensemble is not guaranteed to represent the real climate system, meaning that estimated probabilities can have an associated bias. Moreover, our results represent only probabilities from a given “opportunity ensemble” (Tebaldi and Knutti 2007). The inclusion of other models and/or members will have an effect on the estimated probabilities. The potential extent of this effect is partially evaluated (see Supplementary Material). It must be noted that these biases represent a fundamental limitation in climate assessment from the use of climate models, and are not specific to the PCS approach presented here.
Refining the climate indices is also something that could be examined. Current research indicates that periods of very high temperatures are unfavourable for crops in general (White et al. 2006; Schlenker and Roberts 2009) and may affect vines as well. Our indices of degree-days are calculated by naively adding temperature units over a given threshold and do not account for potential damage caused by very high temperatures. Since we can expect higher extreme temperatures in the coming century (IPCC 2012), this effect, as well as other extremes such as wind gusts and heavy rains, should potentially be considered in future assessments.
This study did not look at future precipitation regimes for Québec. At the end of the viticulture season, grapes benefit from dry conditions (helping sugar concentration). Historical precipitation conditions are not a limiting/helping factor in Québec. However, future climate scenarios show an increase of precipitation over the eastern part of North America. This should be documented, whether or not this increase limits viticulture.
An important protection measure against harsh cold is snow cover. Projections from climate models show a possible reduction in snow cover in southern Québec, combined with annual winter temperatures below the critical threshold for V. vinifera of − 17 ∘C. This means that growers will face another challenge and incur additional costs associated with alternative winter thermal protection.
Finally, even though sunshine hours are currently higher than in other traditional viticultural regions such as Bordeaux and New Zealand (Jones 2012), it is unclear how cloud cover will affect future sunshine hours in southern Québec. Cloud physics in climate models being mostly associated with sub-grid parameterizations, a rigorous assessment of future cloud cover is beyond the scope of this article and remains a challenging topic in climate research (Bony et al. 2015).
Probabilistic climate scenarios (PCS) of viticultural potential (VP) are provided for the province of Québec, in northeastern North America. Results indicate that climate change presents an opportunity for the northern vine-growing sector and that the PCS approach can provide rich information to a decision-making framework. However, potential negative effects related to climate change should not be cast aside: diseases, increased or new types of insect infestation, as well as a modified frost-thaw cycle represent only a few new challenges. Maps of occurrence year represent an interesting tool for potential growers who wish to evaluate the suitability of different regions for a given grape variety.
Québec can expect new wine-producing regions to emerge in coming decades (the Outaouais and along the St Lawrence River), where the probability of minimal growing degree days and season length is high. The southern part of the province has been a vine-growing region for the past three decades and should continue to be in the coming decades, with the added benefit of widespread potential for early-ripening varieties such as Vitis vinifera. However, winter temperatures continue to be a limiting factor, even for the hybrid varieties currently grown in Québec. Fortunately, mitigation methods, such as using soil or geotextile fabric for thermal protection, can be easily applied. These techniques should remain necessary in the coming decades, despite projected warmer conditions.
Although the focus of the study is in Québec, other Canadian provinces such as Ontario and British Columbia should see similar results. Similarly, although the focus of the study is on Québec, studies of other Canadian provinces such as Ontario and British Columbia should yield similar results. Similarly, other portions of the world with cold conditions are likely to experience similar phenomena. Provided that sufficient observations are available for the statistical adjustment of the simulated time series and that relevant climate indices can be defined for a region, this study can be replicated for any part of the world. The approach gives a rich overview of the impacts and economic potential of climate change for the wine industry and policymakers.
We acknowledge the World Climate Research Programme’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We also thank Dan McKenney and the team at the Canadian Forest Service of Natural Resources Canada for providing the observational product used.
P.R., P.G., E.B., and D.C. conceived the methodology. E.B. developed the climate indices. P.R. and P.G. wrote code and P.R., P.G., E.B., T.L., A.B., G.B. and D.C. analysed output data. T.L. conceived the maps. P.R. wrote the manuscript and P.G., E.B., T.L., A.B., G.B. and D.C. reviewed the manuscript.
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