Very high resolution bioclimatic zoning of Portuguese wine regions: present and future scenarios

Wine production is strongly affected by weather and climate and thus highly vulnerable to climate change. In Portugal, viticulture and wine production are an important economic activity. In the present study, current bioclimatic zoning in Portugal (1950–2000) and its projected changes under future climate conditions (2041–2070) are assessed through the analysis of an aggregated, categorized bioclimatic index (CatI) at a very high spatial resolution (near 1 km). CatI incorporates the most relevant bioclimatic characteristics of a given region, thus allowing the direct comparison between different regions. Future viticultural zoning is achieved using data from 13 climate model transient experiments following the A1B emission scenario. These data are downscaled using a two-step method of spatial pattern downscaling. This downscaling approach allows characterizing mesoclimatic influences on viticulture throughout Portugal. Results for the recent past depict the current spatial variability of Portuguese viticultural regions. Under future climate conditions, the current viticultural zoning is projected to undergo significant changes, which may represent important challenges for the Portuguese winemaking sector. The changes are quite robust across the different climate models. A lower bioclimatic diversity is also projected, resulting from a more homogeneous warm and dry climate in most of the wine regions. This will lead to changes in varietal suitability and wine characteristics of each region.

Ensemble projections for wine production in the Douro Valley of Portugal

Wine production is largely governed by atmospheric conditions, such as air temperature and precipitation, together with soil management and viticultural/enological practices. Therefore, anthropogenic climate change is likely to have important impacts on the winemaking sector worldwide. An important winemaking region is the Portuguese Douro Valley, which is known by its world-famous Port Wine. The identification of robust relationships between atmospheric factors and wine parameters is of great relevance for the region. A multivariate linear regression analysis of a long wine production series (1932–2010) reveals that high rainfall and cool temperatures during budburst, shoot and inflorescence development (February-March) and warm temperatures during flowering and berry development (May) are generally favourable to high production. The probabilities of occurrence of three production categories (low, normal and high) are also modelled using multinomial logistic regression. Results show that both statistical models are valuable tools for predicting the production in a given year with a lead time of 3–4 months prior to harvest. These statistical models are applied to an ensemble of 16 regional climate model experiments following the SRES A1B scenario to estimate possible future changes. Wine production is projected to increase by about 10 % by the end of the 21st century, while the occurrence of high production years is expected to increase from 25 % to over 60 %. Nevertheless, further model development will be needed to include other aspects that may shape production in the future. In particular, the rising heat stress and/or changes in ripening conditions could limit the projected production increase in future decades.