The application of high-resolution atmospheric modelling to weather and climate variability in vineyard regions

Sturman, Andrew; Zawar-Reza, Peyman; Soltanzadeh, Iman; Katurji, Marwan; Bonnardot, Valérie; Parker, Amber; Trought, Michael C. T.; Quénol, Hervé; Roux, Renan Le; Gendig, Eila; Schulmann, Tobias

doi:10.20870/oeno-one.2017.51.2.1538

Cited by 14 publications

(10 citation statements)

References 12 publications

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“…The climate and especially temperature variability of the Marlborough vineyard region has previously been described and related to vine phenology (Felix et al, ; Sturman et al, ), and the WRF model has been run operationally for several growing seasons to provide a short‐term forecast and to map the ongoing status of the current grapevine growing season. Hence, the research presented here is not focused on improving knowledge of the small‐scale temperature variability of the Marlborough region.…”

Section: Discussionmentioning

confidence: 99%

Analysis of spatio‐temporal bias of Weather Research and Forecasting temperatures based on weather pattern classification

Roux

Katurji

Zawar-Reza

et al. 2018

Intl Journal of Climatology

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Viticulture is a key economic activity for many countries around the world, and temperature is one of the most important parameters in grapevine response. Many studies have shown that variability of temperature at the vineyard scale has a significant effect on physiological development of the grapevine and, ultimately, wine quality. The Weather Research and Forecasting (WRF) model has been widely used to dynamically downscale from the synoptic and larger scale atmospheric circulation in order to provide a high-resolution analysis of weather and climate in regions of complex terrain. The temperature bias of the WRF model in a vineyard region is analysed using 18 automatic weather stations in order to understand the spatial variation in the bias due to local conditions. The WRF-predicted temperatures exhibited an average bias that was relatively consistent between measurement sites, although the consistency of this bias was found to vary in relation to weather type, time of day and season. These factors therefore need to be taken into account in order to properly correct temperatures produced by the WRF model.

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Section: Discussionmentioning

confidence: 99%

Analysis of spatio‐temporal bias of Weather Research and Forecasting temperatures based on weather pattern classification

Roux

Katurji

Zawar-Reza

et al. 2018

Intl Journal of Climatology

Self Cite

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“…The spatial resolution (0.05 • grid) used to perform the climate change scenario analysis enabled us to produce information at the regional level, but it does not account for finer aspects of topography and complex climate interactions that can occur at a lower resolution, particularly in the context of the NZ maritime temperate climate (Parker et al, 2015;Sturman et al, 2017). Given the complex terrain of NZ, the extension of our analysis to finer spatial resolutions would likely provide additional insights on phenological responses.…”

Section: Scope Implications and Limitations Of This Studymentioning

confidence: 99%

Projected Wine Grape Cultivar Shifts Due to Climate Change in New Zealand

et al. 2021

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Climate change has already been affecting the regional suitability of grapevines with significant advances in phenology being observed globally in the last few decades. This has significant implications for New Zealand, where the wine industry represents a major share of the horticultural industry revenue. We modeled key crop phenological stages to better understand temporal and spatial shifts in three important regions of New Zealand (Marlborough, Hawke's Bay, Central Otago) for three dominant cultivars (Merlot, Pinot noir, and Sauvignon blanc) and one potential new and later ripening cultivar (Grenache). Simulations show an overall advance in flowering, véraison, and sugar ripeness by mid-century with more pronounced advance by the end of the century. Results show the magnitude of changes depends on the combination of greenhouse gas emission pathway, grape cultivar, and region. By mid-century, in the Marlborough region for instance, the four cultivars would flower 3 to 7 days earlier and reach sugar ripeness 7 to 15 days earlier depending on the greenhouse gas emission pathway. For growers to maintain the same timing of key phenological stages would require shifting planting of cultivars to more Southern parts of the country or implement adaptation strategies. Results also show the compression of time between flowering and véraison for all three dominant cultivars is due to a proportionally greater advance in véraison, particularly for Merlot in the Hawke's Bay and Pinot noir in Central Otago. Cross-regional analysis also raises the likelihood of the different regional cultivars ripening within a smaller window of time, complicating harvesting schedules across the country. However, considering New Zealand primarily accommodates cool climate viticulture cultivars, our results suggest that late ripening cultivars or extended ripening window in cooler regions may be advantageous in the face of climate change. These insights can inform New Zealand winegrowers with climate change adaptation options for their cultivar choices.

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“…The extent of the variation in performance of the same vines between seasons largely excludes factors that are stable between seasons as primary causes. For example, factors such as within-block differences in meso-climate (Sturman et al, 2017), soil physical properties (Bramley et al, 2011;Trought and Bramley 2011;Bramley et al, 2019), long-term plant health status (virus, trunk disease) (Mundy et al, 2009) and plant genetics can probably be ruled out. Variations in management or environment x management (E x M) interactions of the same vine from year to year seem the most likely contributors to variation.…”

Section: Vine Yieldmentioning

confidence: 99%

Vintage by vine interactions most strongly influence Pinot noir grape composition in New Zealand

et al. 2020

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Vine genetics, fruit maturity, region and vineyard are perceived as factors that strongly influence Pinot noir grape and wine composition. Our study aims to understand the relationship between grape (and ultimately wine) composition and the physical appearance and performance characteristics of a vine (i.e. vine ideotype). Our experimental approach controlled these variables by studying within-block differences in vine performance across multiple seasons and vineyards. Grapes were sourced at commercial harvest from 20 single vines from 12 vineyard sites in three Pinot noir growing regions (Central Otago, Martinborough and Marlborough) of New Zealand.Across three vintages yields ranged from 0.1 kg to 6.3 kg per metre, but there was no general relationship between yield and berry soluble solids. On a vine by vine basis normalised yields did not correlate among seasons. Berry extract colour measures were, on average, three-fold higher in 2019 than in 2018.Principal Component Analysis has indicated that vintage dominated berry composition effects that might otherwise be associated with yield per vine, region and vineyard. The extent of the variation in performance of the same vines between seasons largely excludes factors that are stable between seasons as primary causes. Changes in management of the same vine from year to year appeared the most likely contributors to variation. We have derived highly significant negative linear relationships between vine yield class and the frequency of vines that were within a benchmark specification established for icon vines, providing evidence of the quality risk associated with higher yield. The results also indicate that a proportion of vines meet the benchmark specification at higher yields. From results to date we can further our research confident in the knowledge that factors such as vine yield, region or vineyard are, in themselves, unlikely to be the principal drivers of major differences in Pinot noir grape and wine composition.

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The application of high-resolution atmospheric modelling to weather and climate variability in vineyard regions

Cited by 14 publications

References 12 publications

Analysis of spatio‐temporal bias of Weather Research and Forecasting temperatures based on weather pattern classification

Analysis of spatio‐temporal bias of Weather Research and Forecasting temperatures based on weather pattern classification

Projected Wine Grape Cultivar Shifts Due to Climate Change in New Zealand

Vintage by vine interactions most strongly influence Pinot noir grape composition in New Zealand

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