# A Review of the Potential Climate Change Impacts and Adaptation Options for European Viticulture
## 6 Knowledge Gaps and Research Challenges  
Although research on potential impacts of climate change on viticulture is already largely developed, when compared to other crops, some important knowledge gaps remain. The use of climate projection datasets linked to grapevine simulation models represents the most feasible approach for predicting plant behaviour and production in the future [98], which can be complemented by climate chamber experiments, among others, for model development, calibration, and validation. In this regard, more experiments carried out under similar conditions and measuring the same variables are needed for a better comparison between studies and quantification of effects. Nonetheless, the evaluation of climate change impacts on any cultivated crop is sensitive to uncertainties in the future climate projections, deriving from model parameterizations, sub-grid scale processes, model initializations, intrinsic biases, radiative forcing scenarios, and other sources. Natural variability of the climate system needs also be taken into account, increasing the level of uncertainty with increasing distance into the future. These uncertainties need to be more thoroughly incorporated in the climate change projections and impact assessments, using more comprehensive probabilistic and risk analyses. This information should also be better communicated to stakeholders and decision-makers, instead of providing only ensemble means or other central tendency measures, which can be misleading and may impede or misguide an effective adaptation. Furthermore, these projections are available on platforms that are frequently not user-friendly, with data formats, as well as temporal and spatial scales, not being suitable for knowledge transfer to decision-makers [234]. A good example of an easy-to-use interface that is focused on cereal crops is the NASA (National Aeronautics and Space Administration) Harvest Crop Monitor interface, using remote sensing data to forecast crop conditions ([[https://cropmonitor.org/index.php/data-and-tools/cmet/](https://cropmonitor.org/index.php/data-and-tools/cmet/)]([https://cropmonitor.org/index.php/data-and-tools/cmet/](https://cropmonitor.org/index.php/data-and-tools/cmet/))). Although grapevine simulation models, usually process-based, are already able to satisfactorily reproduce different interactions between the soil-plant-atmosphere continuum at a very detailed level, further enhancements and integrations are undeniably necessary to improve model reliability. As an illustration, estimations of bud break occurrences are often based on forcing models, without considering the effect of chilling during dormancy. This shortcoming frequently leads to erratic estimations of bud break under warmer climates, with obvious implications throughout the simulation of the phenological cycle [235]. Although the isolated effects of CO\({}_{2}\) and temperature on the radiation use efficiency and transpiration have already been extensively reported, their opposite impact on evapotranspiration, and their combined effect in future warmer climates, are not fully understood yet [235; 236]. Furthermore, simulation models should incorporate the incidence level of pests and diseases [237] and the impact of nitrogen and water stress [238; 239], which are expected to have more impact on plants in a climate change context. Modelling approaches that would be able to incorporate aspects of grape quality will play a key role in understanding changes in berry metabolites [86]. Thus far, only a few grapevine models are currently available, and a very limited number of varieties can be simulated. More models, and more versatile models, are needed in order to implement multi-model ensemble scenarios, thereby enhancing the robustness of the projections. For a broader assessment on the effects on different varieties, the incorporation of key variables describing varietal behaviour is also lacking thus far.