Articles | Volume 13, issue 2
https://doi.org/10.5194/esd-13-911-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-13-911-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Downscaling of climate change scenarios for a high-resolution, site-specific assessment of drought stress risk for two viticultural regions with heterogeneous landscapes
Marco Hofmann
CORRESPONDING AUTHOR
Department of General and Organic Viticulture, Hochschule Geisenheim University, Geisenheim, 65366, Germany
Claudia Volosciuk
Science and Innovation Department, World Meteorological Organization, Geneva, 1211, Switzerland
Deutscher Wetterdienst, Offenbach am Main, 63067, Germany
Martin Dubrovský
Institute of Atmospheric Physics, The Czech Academy of Sciences,
Prague, 141 00, Czech Republic
Global Change Research Institute, The Czech Academy of Sciences, Brno, 603 00, Czech Republic
Douglas Maraun
Wegener Center for Climate and Global Change, University of Graz,
Graz, 8010, Austria
Hans R. Schultz
Department of General and Organic Viticulture, Hochschule Geisenheim University, Geisenheim, 65366, Germany
Related authors
No articles found.
Colin Manning, Martin Widmann, Douglas Maraun, Anne F. Van Loon, and Emanuele Bevacqua
Weather Clim. Dynam., 4, 309–329, https://doi.org/10.5194/wcd-4-309-2023, https://doi.org/10.5194/wcd-4-309-2023, 2023
Short summary
Short summary
Climate models differ in their representation of dry spells and high temperatures, linked to errors in the simulation of persistent large-scale anticyclones. Models that simulate more persistent anticyclones simulate longer and hotter dry spells, and vice versa. This information is important to consider when assessing the likelihood of such events in current and future climate simulations so that we can assess the plausibility of their future projections.
Yi Yang, Douglas Maraun, Albert Ossó, and Jianping Tang
Nat. Hazards Earth Syst. Sci., 23, 693–709, https://doi.org/10.5194/nhess-23-693-2023, https://doi.org/10.5194/nhess-23-693-2023, 2023
Short summary
Short summary
This study quantifies the spatiotemporal variation and characteristics of compound long-duration dry and hot events in China over the 1961–2014 period. The results show that over the past few decades, there has been a substantial increase in the frequency of these compound events across most parts of China, which is dominated by rising temperatures. We detect a strong increase in the spatially contiguous areas experiencing concurrent dry and hot conditions.
Raphael Knevels, Helene Petschko, Herwig Proske, Philip Leopold, Aditya N. Mishra, Douglas Maraun, and Alexander Brenning
Nat. Hazards Earth Syst. Sci., 23, 205–229, https://doi.org/10.5194/nhess-23-205-2023, https://doi.org/10.5194/nhess-23-205-2023, 2023
Short summary
Short summary
In summer 2009 and 2014, rainfall events occurred in the Styrian Basin (Austria), triggering thousands of landslides. Landslide storylines help to show potential future changes under changing environmental conditions. The often neglected uncertainty quantification was the aim of this study. We found uncertainty arising from the landslide model to be of the same order as climate scenario uncertainty. Understanding the dimensions of uncertainty is crucial for allowing informed decision-making.
Douglas Maraun and Martin Widmann
Hydrol. Earth Syst. Sci., 22, 4867–4873, https://doi.org/10.5194/hess-22-4867-2018, https://doi.org/10.5194/hess-22-4867-2018, 2018
Short summary
Short summary
Cross-validation of free-running bias-corrected climate change simulations against observations is misleading, because it is typically dominated by internal variability. In particular, a sensible bias correction may be rejected and a non-sensible bias correction may be accepted. We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations. Instead, one should evaluate temporal, spatial and
process-based aspects.
Emanuele Bevacqua, Douglas Maraun, Ingrid Hobæk Haff, Martin Widmann, and Mathieu Vrac
Hydrol. Earth Syst. Sci., 21, 2701–2723, https://doi.org/10.5194/hess-21-2701-2017, https://doi.org/10.5194/hess-21-2701-2017, 2017
Short summary
Short summary
We develop a conceptual model to quantify the risk of compound events (CEs), i.e. extreme impacts to society which are driven by statistically dependent climatic variables. Based on this model we study compound floods, i.e. joint storm surge and high river level, in Ravenna (Italy). The model includes meteorological predictors which (1) provide insight into the physical processes underlying CEs, as well as into the temporal variability, and (2) allow us to statistically downscale CEs.
Claudia Volosciuk, Douglas Maraun, Mathieu Vrac, and Martin Widmann
Hydrol. Earth Syst. Sci., 21, 1693–1719, https://doi.org/10.5194/hess-21-1693-2017, https://doi.org/10.5194/hess-21-1693-2017, 2017
Short summary
Short summary
For impact modeling, infrastructure design, or adaptation strategy planning, high-quality climate data on the point scale are often demanded. Due to the scale gap between gridbox and point scale and biases in climate models, we combine a statistical bias correction and a stochastic downscaling model and apply it to climate model-simulated precipitation. The method performs better in summer than in winter and in winter best for mild winter climate (Mediterranean) and worst for continental winter.
D. Maraun and M. Widmann
Hydrol. Earth Syst. Sci., 19, 3449–3456, https://doi.org/10.5194/hess-19-3449-2015, https://doi.org/10.5194/hess-19-3449-2015, 2015
Related subject area
Earth system interactions with the biosphere: ecosystems
Opening Pandora's box: reducing global circulation model uncertainty in Australian simulations of the carbon cycle
Persistent La Niñas drive joint soybean harvest failures in North and South America
Spatiotemporal changes in the boreal forest in Siberia over the period 1985–2015 against the background of climate change
Global climate change and the Baltic Sea ecosystem: direct and indirect effects on species, communities and ecosystem functioning
Widespread greening suggests increased dry-season plant water availability in the Rio Santa valley, Peruvian Andes
Spatiotemporal patterns and drivers of terrestrial dissolved organic carbon (DOC) leaching into the European river network
Impacts of compound hot–dry extremes on US soybean yields
Vulnerability of European ecosystems to two compound dry and hot summers in 2018 and 2019
Modelling forest ruin due to climate hazards
Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts
Diverging land-use projections cause large variability in their impacts on ecosystems and related indicators for ecosystem services
Impacts of land use change and elevated CO2 on the interannual variations and seasonal cycles of gross primary productivity in China
Investigating the applicability of emergent constraints
Tidal impacts on primary production in the North Sea
Global vegetation variability and its response to elevated CO2, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data
Steering operational synergies in terrestrial observation networks: opportunity for advancing Earth system dynamics modelling
Contrasting terrestrial carbon cycle responses to the 1997/98 and 2015/16 extreme El Niño events
Low-frequency variability in North Sea and Baltic Sea identified through simulations with the 3-D coupled physical–biogeochemical model ECOSMO
Vegetation–climate feedbacks modulate rainfall patterns in Africa under future climate change
Climate change increases riverine carbon outgassing, while export to the ocean remains uncertain
Spatial and temporal variations in plant water-use efficiency inferred from tree-ring, eddy covariance and atmospheric observations
Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest
Establishment and maintenance of regulating ecosystem services in a dryland area of central Asia, illustrated using the Kökyar Protection Forest, Aksu, NW China, as an example
Do Himalayan treelines respond to recent climate change? An evaluation of sensitivity indicators
The impact of land cover generated by a dynamic vegetation model on climate over east Asia in present and possible future climate
Bimodality of woody cover and biomass across the precipitation gradient in West Africa
Critical impacts of global warming on land ecosystems
The influence of vegetation dynamics on anthropogenic climate change
Quantifying the thermodynamic entropy budget of the land surface: is this useful?
Lina Teckentrup, Martin G. De Kauwe, Gab Abramowitz, Andrew J. Pitman, Anna M. Ukkola, Sanaa Hobeichi, Bastien François, and Benjamin Smith
Earth Syst. Dynam., 14, 549–576, https://doi.org/10.5194/esd-14-549-2023, https://doi.org/10.5194/esd-14-549-2023, 2023
Short summary
Short summary
Studies analyzing the impact of the future climate on ecosystems employ climate projections simulated by global circulation models. These climate projections display biases that translate into significant uncertainty in projections of the future carbon cycle. Here, we test different methods to constrain the uncertainty in simulations of the carbon cycle over Australia. We find that all methods reduce the bias in the steady-state carbon variables but that temporal properties do not improve.
Raed Hamed, Sem Vijverberg, Anne F. Van Loon, Jeroen Aerts, and Dim Coumou
Earth Syst. Dynam., 14, 255–272, https://doi.org/10.5194/esd-14-255-2023, https://doi.org/10.5194/esd-14-255-2023, 2023
Short summary
Short summary
Spatially compounding soy harvest failures can have important global impacts. Using causal networks, we show that soy yields are predominately driven by summer soil moisture conditions in North and South America. Summer soil moisture is affected by antecedent soil moisture and by remote extra-tropical SST patterns in both hemispheres. Both of these soil moisture drivers are again influenced by ENSO. Our results highlight physical pathways by which ENSO can drive spatially compounding impacts.
Wenxue Fu, Lei Tian, Yu Tao, Mingyang Li, and Huadong Guo
Earth Syst. Dynam., 14, 223–239, https://doi.org/10.5194/esd-14-223-2023, https://doi.org/10.5194/esd-14-223-2023, 2023
Short summary
Short summary
Climate change has been proven to be an indisputable fact and to be occurring at a faster rate in boreal forest areas. The results of this paper show that boreal forest coverage has shown an increasing trend in the past 3 decades, and the area of broad-leaved forests has increased more rapidly than that of coniferous forests. In addition, temperature rather than precipitation is the main climate factor that is driving change.
Markku Viitasalo and Erik Bonsdorff
Earth Syst. Dynam., 13, 711–747, https://doi.org/10.5194/esd-13-711-2022, https://doi.org/10.5194/esd-13-711-2022, 2022
Short summary
Short summary
Climate change has multiple effects on Baltic Sea species, communities and ecosystem functioning. Effects on species distribution, eutrophication and trophic interactions are expected. We review these effects, identify knowledge gaps and draw conclusions based on recent (2010–2021) field, experimental and modelling research. An extensive summary table is compiled to highlight the multifaceted impacts of climate-change-driven processes in the Baltic Sea.
Lorenz Hänchen, Cornelia Klein, Fabien Maussion, Wolfgang Gurgiser, Pierluigi Calanca, and Georg Wohlfahrt
Earth Syst. Dynam., 13, 595–611, https://doi.org/10.5194/esd-13-595-2022, https://doi.org/10.5194/esd-13-595-2022, 2022
Short summary
Short summary
To date, farmers' perceptions of hydrological changes do not match analysis of meteorological data. In contrast to rainfall data, we find greening of vegetation, indicating increased water availability in the past decades. The start of the season is highly variable, making farmers' perceptions comprehensible. We show that the El Niño–Southern Oscillation has complex effects on vegetation seasonality but does not drive the greening we observe. Improved onset forecasts could help local farmers.
Céline Gommet, Ronny Lauerwald, Philippe Ciais, Bertrand Guenet, Haicheng Zhang, and Pierre Regnier
Earth Syst. Dynam., 13, 393–418, https://doi.org/10.5194/esd-13-393-2022, https://doi.org/10.5194/esd-13-393-2022, 2022
Short summary
Short summary
Dissolved organic carbon (DOC) leaching from soils into river networks is an important component of the land carbon (C) budget, but its spatiotemporal variation is not yet fully constrained. We use a land surface model to simulate the present-day land C budget at the European scale, including leaching of DOC from the soil. We found average leaching of 14.3 Tg C yr−1 (0.6 % of terrestrial net primary production) with seasonal variations. We determine runoff and temperature to be the main drivers.
Raed Hamed, Anne F. Van Loon, Jeroen Aerts, and Dim Coumou
Earth Syst. Dynam., 12, 1371–1391, https://doi.org/10.5194/esd-12-1371-2021, https://doi.org/10.5194/esd-12-1371-2021, 2021
Short summary
Short summary
Soy yields in the US are affected by climate variability. We identify the main within-season climate drivers and highlight potential compound events and associated agricultural impacts. Our results show that soy yields are most negatively influenced by the combination of high temperature and low soil moisture during the summer crop reproductive period. Furthermore, we highlight the role of temperature and moisture coupling across the year in generating these hot–dry extremes and linked impacts.
Ana Bastos, René Orth, Markus Reichstein, Philippe Ciais, Nicolas Viovy, Sönke Zaehle, Peter Anthoni, Almut Arneth, Pierre Gentine, Emilie Joetzjer, Sebastian Lienert, Tammas Loughran, Patrick C. McGuire, Sungmin O, Julia Pongratz, and Stephen Sitch
Earth Syst. Dynam., 12, 1015–1035, https://doi.org/10.5194/esd-12-1015-2021, https://doi.org/10.5194/esd-12-1015-2021, 2021
Short summary
Short summary
Temperate biomes in Europe are not prone to recurrent dry and hot conditions in summer. However, these conditions may become more frequent in the coming decades. Because stress conditions can leave legacies for many years, this may result in reduced ecosystem resilience under recurrent stress. We assess vegetation vulnerability to the hot and dry summers in 2018 and 2019 in Europe and find the important role of inter-annual legacy effects from 2018 in modulating the impacts of the 2019 event.
Pascal Yiou and Nicolas Viovy
Earth Syst. Dynam., 12, 997–1013, https://doi.org/10.5194/esd-12-997-2021, https://doi.org/10.5194/esd-12-997-2021, 2021
Short summary
Short summary
This paper presents a model of tree ruin as a response to drought hazards. This model is inspired by a standard model of ruin in the insurance industry. We illustrate how ruin can occur in present-day conditions and the sensitivity of ruin and time to ruin to hazard statistical properties. We also show how tree strategies to cope with hazards can affect their long-term reserves and the probability of ruin.
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Weidong Guo, Sanaa Hobeichi, and Peter R. Briggs
Earth Syst. Dynam., 12, 919–938, https://doi.org/10.5194/esd-12-919-2021, https://doi.org/10.5194/esd-12-919-2021, 2021
Short summary
Short summary
Groundwater can buffer the impacts of drought and heatwaves on ecosystems, which is often neglected in model studies. Using a land surface model with groundwater, we explained how groundwater sustains transpiration and eases heat pressure on plants in heatwaves during multi-year droughts. Our results showed the groundwater’s influences diminish as drought extends and are regulated by plant physiology. We suggest neglecting groundwater in models may overstate projected future heatwave intensity.
Anita D. Bayer, Richard Fuchs, Reinhard Mey, Andreas Krause, Peter H. Verburg, Peter Anthoni, and Almut Arneth
Earth Syst. Dynam., 12, 327–351, https://doi.org/10.5194/esd-12-327-2021, https://doi.org/10.5194/esd-12-327-2021, 2021
Short summary
Short summary
Many projections of future land-use/-cover exist. We evaluate a number of these and determine the variability they cause in ecosystems and their services. We found that projections differ a lot in regional patterns, with some patterns being at least questionable in a historical context. Across ecosystem service indicators, resulting variability until 2040 was highest in crop production. Results emphasize that such variability should be acknowledged in assessments of future ecosystem provisions.
Binghao Jia, Xin Luo, Ximing Cai, Atul Jain, Deborah N. Huntzinger, Zhenghui Xie, Ning Zeng, Jiafu Mao, Xiaoying Shi, Akihiko Ito, Yaxing Wei, Hanqin Tian, Benjamin Poulter, Dan Hayes, and Kevin Schaefer
Earth Syst. Dynam., 11, 235–249, https://doi.org/10.5194/esd-11-235-2020, https://doi.org/10.5194/esd-11-235-2020, 2020
Short summary
Short summary
We quantitatively examined the relative contributions of climate change, land
use and land cover change, and elevated CO2 to interannual variations and seasonal cycle amplitude of gross primary productivity (GPP) in China based on multi-model ensemble simulations. The contributions of major subregions to the temporal change in China's total GPP are also presented. This work may help us better understand GPP spatiotemporal patterns and their responses to regional changes and human activities.
Alexander J. Winkler, Ranga B. Myneni, and Victor Brovkin
Earth Syst. Dynam., 10, 501–523, https://doi.org/10.5194/esd-10-501-2019, https://doi.org/10.5194/esd-10-501-2019, 2019
Short summary
Short summary
The concept of
emergent constraintsis a key method to reduce uncertainty in multi-model climate projections using historical simulations and observations. Here, we present an in-depth analysis of the applicability of the method and uncover possible limitations. Key limitations are a lack of comparability (temporal, spatial, and conceptual) between models and observations and the disagreement between models on system dynamics throughout different levels of atmospheric CO2 concentration.
Changjin Zhao, Ute Daewel, and Corinna Schrum
Earth Syst. Dynam., 10, 287–317, https://doi.org/10.5194/esd-10-287-2019, https://doi.org/10.5194/esd-10-287-2019, 2019
Short summary
Short summary
Our study highlights the importance of tides in controlling the spatial and temporal distributions North Sea primary production based on numerical experiments. We identified two different response chains acting in different regions of the North Sea. (i) In the southern shallow areas, strong tidal mixing dilutes phytoplankton concentrations and increases turbidity, thus decreasing NPP. (ii) In the frontal regions, tidal mixing infuses nutrients into the surface mixed layer, thus increasing NPP.
Ye Liu, Yongkang Xue, Glen MacDonald, Peter Cox, and Zhengqiu Zhang
Earth Syst. Dynam., 10, 9–29, https://doi.org/10.5194/esd-10-9-2019, https://doi.org/10.5194/esd-10-9-2019, 2019
Short summary
Short summary
Climate regime shift during the 1980s identified by abrupt change in temperature, precipitation, etc. had a substantial impact on the ecosystem at different scales. Our paper identifies the spatial and temporal characteristics of the effects of climate variability, global warming, and eCO2 on ecosystem trends before and after the shift. We found about 15 % (20 %) of the global land area had enhanced positive trend (trend sign reversed) during the 1980s due to climate regime shift.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
Short summary
Short summary
Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Jun Wang, Ning Zeng, Meirong Wang, Fei Jiang, Hengmao Wang, and Ziqiang Jiang
Earth Syst. Dynam., 9, 1–14, https://doi.org/10.5194/esd-9-1-2018, https://doi.org/10.5194/esd-9-1-2018, 2018
Short summary
Short summary
Behaviors of terrestrial ecosystems differ in different El Niños. We analyze terrestrial carbon cycle responses to two extreme El Niños (2015/16 and 1997/98), and find large differences. We find that global land–atmosphere carbon flux anomaly was about 2 times smaller in 2015/16 than in 1997/98 event, without the obvious lagged response. Then we illustrate the climatic and biological mechanisms of the different terrestrial carbon cycle responses in 2015/16 and 1997/98 El Niños regionally.
Ute Daewel and Corinna Schrum
Earth Syst. Dynam., 8, 801–815, https://doi.org/10.5194/esd-8-801-2017, https://doi.org/10.5194/esd-8-801-2017, 2017
Short summary
Short summary
Processes behind observed long-term variations in marine ecosystems are difficult to be deduced from in situ observations only. By statistically analysing a 61-year model simulation for the North Sea and Baltic Sea and additional model scenarios, we identified major modes of variability in the environmental variables and associated those with changes in primary production. We found that the dominant impact on changes in ecosystem productivity was introduced by modulations of the wind fields.
Minchao Wu, Guy Schurgers, Markku Rummukainen, Benjamin Smith, Patrick Samuelsson, Christer Jansson, Joe Siltberg, and Wilhelm May
Earth Syst. Dynam., 7, 627–647, https://doi.org/10.5194/esd-7-627-2016, https://doi.org/10.5194/esd-7-627-2016, 2016
Short summary
Short summary
On Earth, vegetation does not merely adapt to climate but also imposes significant influences on climate with both local and remote effects. In this study we evaluated the role of vegetation in African climate with a regional Earth system model. By the comparison between the experiments with and without dynamic vegetation changes, we found that vegetation can influence climate remotely, resulting in modulating rainfall patterns over Africa.
F. Langerwisch, A. Walz, A. Rammig, B. Tietjen, K. Thonicke, and W. Cramer
Earth Syst. Dynam., 7, 559–582, https://doi.org/10.5194/esd-7-559-2016, https://doi.org/10.5194/esd-7-559-2016, 2016
Short summary
Short summary
In Amazonia, carbon fluxes are considerably influenced by annual flooding. We applied the newly developed model RivCM to several climate change scenarios to estimate potential changes in riverine carbon. We find that climate change causes substantial changes in riverine organic and inorganic carbon, as well as changes in carbon exported to the atmosphere and ocean. Such changes could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean.
Stefan C. Dekker, Margriet Groenendijk, Ben B. B. Booth, Chris Huntingford, and Peter M. Cox
Earth Syst. Dynam., 7, 525–533, https://doi.org/10.5194/esd-7-525-2016, https://doi.org/10.5194/esd-7-525-2016, 2016
Short summary
Short summary
Our analysis allows us to infer maps of changing plant water-use efficiency (WUE) for 1901–2010, using atmospheric observations of temperature, humidity and CO2. Our estimated increase in global WUE is consistent with the tree-ring and eddy covariance data, but much larger than the historical WUE increases simulated by Earth System Models (ESMs). We therefore conclude that the effects of increasing CO2 on plant WUE are significantly underestimated in the latest climate projections.
M. H. Vermeulen, B. J. Kruijt, T. Hickler, and P. Kabat
Earth Syst. Dynam., 6, 485–503, https://doi.org/10.5194/esd-6-485-2015, https://doi.org/10.5194/esd-6-485-2015, 2015
Short summary
Short summary
We compared a process-based ecosystem model (LPJ-GUESS) with EC measurements to test whether observed interannual variability (IAV) in carbon and water fluxes can be reproduced because it is important to understand the driving mechanisms of IAV. We show that the model's mechanistic process representation for photosynthesis at low temperatures and during drought could be improved, but other process representations are still lacking in order to fully reproduce the observed IAV.
S. Missall, M. Welp, N. Thevs, A. Abliz, and Ü. Halik
Earth Syst. Dynam., 6, 359–373, https://doi.org/10.5194/esd-6-359-2015, https://doi.org/10.5194/esd-6-359-2015, 2015
U. Schickhoff, M. Bobrowski, J. Böhner, B. Bürzle, R. P. Chaudhary, L. Gerlitz, H. Heyken, J. Lange, M. Müller, T. Scholten, N. Schwab, and R. Wedegärtner
Earth Syst. Dynam., 6, 245–265, https://doi.org/10.5194/esd-6-245-2015, https://doi.org/10.5194/esd-6-245-2015, 2015
Short summary
Short summary
Near-natural Himalayan treelines are usually krummholz treelines, which are relatively unresponsive to climate change. Intense recruitment of treeline trees suggests a great potential for future treeline advance. Competitive abilities of tree seedlings within krummholz thickets and dwarf scrub heaths will be a major source of variation in treeline dynamics. Tree growth-climate relationships show mature treeline trees to be responsive in particular to high pre-monsoon temperature trends.
M.-H. Cho, K.-O. Boo, G. M. Martin, J. Lee, and G.-H. Lim
Earth Syst. Dynam., 6, 147–160, https://doi.org/10.5194/esd-6-147-2015, https://doi.org/10.5194/esd-6-147-2015, 2015
Z. Yin, S. C. Dekker, B. J. J. M. van den Hurk, and H. A. Dijkstra
Earth Syst. Dynam., 5, 257–270, https://doi.org/10.5194/esd-5-257-2014, https://doi.org/10.5194/esd-5-257-2014, 2014
S. Ostberg, W. Lucht, S. Schaphoff, and D. Gerten
Earth Syst. Dynam., 4, 347–357, https://doi.org/10.5194/esd-4-347-2013, https://doi.org/10.5194/esd-4-347-2013, 2013
U. Port, V. Brovkin, and M. Claussen
Earth Syst. Dynam., 3, 233–243, https://doi.org/10.5194/esd-3-233-2012, https://doi.org/10.5194/esd-3-233-2012, 2012
N. A. Brunsell, S. J. Schymanski, and A. Kleidon
Earth Syst. Dynam., 2, 87–103, https://doi.org/10.5194/esd-2-87-2011, https://doi.org/10.5194/esd-2-87-2011, 2011
Cited articles
Ainsworth, E. A. and Rogers, A.: The response of photosynthesis and stomatal conductance to rising [CO2]: mechanisms and environmental interactions, Plant Cell Environ., 30, 258–270,
https://doi.org/10.1111/j.1365-3040.2007.01641.x, 2007.
Allen, R. G.: Skin layer evaporation to account for small precipitation
events – An enhancement to the FAO-56 evaporation model, Agr. Water Manage., 99, 8–18, https://doi.org/10.1016/j.agwat.2011.08.008, 2011.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration – Guidelines for computing crop water requirements, FAO
Irrigation and drainage paper 56, FAO – Food and Agriculture Organization of the United Nations, Rome, ISBN 92-5-104219-5, 1998.
Allen, R. G., Walter, I. A., Elliot, R., Howell, T., Itenfisu, D., and Jensen, M.: The ASCE Standardized Reference Evapotranspiration Equation, ASCE-EWRI Task Committee Report, https://doi.org/10.1061/9780784408056, 2005.
Berthold, G., Meilinger, F., Dettweiler, I., and Muskat, S.: Die Umsetzung
der Wasserrahmenrichtlinie in Hessen – Ausblick und Rückblick, in:
Umweltschonender Weinbau – das solidarische Ziel, Hessisches Ministerium
für Umwelt, Klimaschutz, Landwirtschaft und Verbraucherschutz, https://www.rheingau.com/fileadmin/user_upload/Wein/Wein/Ressourcenschutz_im_Weinbau_Das_solidarische_Ziel_Broschu%CC%88re_Web.pdf
(last access: 27 July 2018), 2016.
Bindi, M., Fibbi, L., and Miglietta, F.: Free Air CO2 Enrichment (FACE) of grapevine (Vitis vinifera L.): II. Growth and quality of grape and wine in response to elevated CO2 concentrations, Eur. J. Agron., 14, 145–155, https://doi.org/10.1016/S1161-0301(00)00093-9, 2001.
Böhm, P., Friedrich, K., and Sabel, K.-J.: Die Weinbergsböden von
Hessen, Hessisches Landesamt für Umwelt und Geologie, Wiesbaden, https://www.hlnug.de/fileadmin/dokumente/boden/heft7.pdf (last access: 20 September 2019), 2007.
Bormann, H.: Sensitivity analysis of 18 different potential evapotranspiration models to observed climatic change at German climate
stations, Climatic Change, 104, 729–753, https://doi.org/10.1007/s10584-010-9869-7, 2011.
Bota, J., Tomás, M., Flexas, J., Medrano, H., and Escalona, J. M.:
Differences among grapevine cultivars in their stomatal behavior and water
use efficiency under progressive water stress, Agr. Water Manage., 164, 91–99, https://doi.org/10.1016/j.agwat.2015.07.016, 2016.
Bülow, K., Huebener, H., Keuler, K., Menz, C., Pfeifer, S., Ramthun, H.,
Spekat, A., Steger, C., Teichmann, C., and Warrach-Sagi, K.: User tailored
results of a regional climate model ensemble to plan adaption to the changing climate in Germany, Adv. Sci. Res., 16, 241–249, https://doi.org/10.5194/asr-16-241-2019, 2019.
Cook, B. I. and Wolkovich, E. M.: Climate change decouples drought from early wine grape harvests in France, Nat. Clim. Change, 6, 715–719, https://doi.org/10.1038/nclimate2960, 2016.
Costa, J. M., Ortuño, M. F., Lopes, C. M., and Chaves, M. M.: Grapevine
varieties exhibiting differences in stomatal response to water deficit, Funct. Plant Biol., 39, 179–189, https://doi.org/10.1071/FP11156, 2012.
Coumou, D. and Robinson, A.: Historic and future increase in the global land area affected by monthly heat extremes, Environ. Res. Lett., 8, 034018, https://doi.org/10.1088/1748-9326/8/3/034018, 2013.
Cronshey, R., McCuen, R. H., Miller, N., Rawls, W., Robbins, S., and Woodward, D.: Urban Hydrology for Small Watersheds TR-55, United States
Department of Agriculture, NRCS, https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/stelprdb1044171.pdf
(last access: 13 February 2021), 1986.
Destatis: Landwirtschaftliche Bodennutzung – Rebflächen, Statistisches
Bundesamt, Wiesbaden, https://www.statistischebibliothek.de/mir/receive/DEHeft_mods_00076093
(last access: 20 February 2019), 2018.
Dubrovský, M., Žalud, Z., and Šťastná, M.: Sensitivity of Ceres-Maize Yields to Statistical Structure of Daily Weather Series, Climatic Change, 46, 447–472, https://doi.org/10.1023/A:1005681809065, 2000.
Dubrovský, M., Buchtele, J., and Žalud, Z.: High-Frequency and Low-Frequency Variability in Stochastic Daily Weather Generator and Its
Effect on Agricultural and Hydrologic Modelling, Climatic Change, 63, 145–179, https://doi.org/10.1023/b:clim.0000018504.99914.60, 2004.
DWD Climate Data Center (CDC): Historical daily station observations (temperature, pressure, precipitation, sunshine duration, etc.) for Germany,
version v006, DWD Climate Data Center (CDC) [data set], https://opendata.dwd.de, last access: 4 December 2018.
DWD Climate Data Center (CDC): Multi-annual station means for the climate
normal reference period 1971–2000, for current station location and for
reference station location, Version V0.x, https://opendata.dwd.de (last access: 20 February 2019), 2020.
Ebrahimian, M., Nuruddin, A. A. B., Soom, M., Sood, A. M., and Neng, L. J.:
Runoff Estimation in Steep Slope Watershed with Standard and Slope-Adjusted
Curve Number Methods, Pol. J. Environ. Stud., 21, 1191–1202, 2012.
Emde, K.: Experimentelle Untersuchungen zu Oberflächenabfluß und
Bodenaustrag in Verbindung mit Starkregen bei verschiedenen Bewirtschaftungssystemen in Weinbergsarealen des oberen Rheingaus, Geisenheimer Berichte 12, Gesellschaft zur Förderung der Forschungsanstalt Geisenheim, Geisenheim, ISBN 3-9802964-1-5, 1992.
Erfurt, M., Skiadaresis, G., Tijdeman, E., Blauhut, V., Bauhus, J., Glaser, R., Schwarz, J., Tegel, W., and Stahl, K.: A multidisciplinary drought
catalogue for southwestern Germany dating back to 1801, Nat. Hazards Earth
Syst. Sci., 20, 2979–2995, https://doi.org/10.5194/nhess-20-2979-2020, 2020.
Esri: “Topographic” [base map], Scale not specified, “Worldwide Topographic Map”, 19 February 2012,
http://www.arcgis.com/home/item.html?id=30e5fe3149c34df1ba922e6f5bbf808f
(last access: 25 May 2017), 2012.
Everard, J. E., Dale, U., Rachel, K., and Michael, T.: Multi-seasonal effects of warming and elevated CO2 on the physiology, growth and production of mature, field grown, Shiraz grapevines, OENO One, 51, 127–132,
https://doi.org/10.20870/oeno-one.2017.51.2.1586, 2017.
Feldmann, H., Schädler, G., Panitz, H.-J., and Kottmeier, C.: Near future changes of extreme precipitation over complex terrain in Central Europe derived from high resolution RCM ensemble simulations, Int. J. Climatol., 33, 1964–1977, https://doi.org/10.1002/joc.3564, 2013.
Flato, G., Marotzke, J., Abiodun, B., Braconnot, P., Chou, S. C., Collins, W., Cox, P., Driouech, F., Emori, S., Eyring, V., Forest, C., Gleckler, P.,
Guilyardi, E., Jakob, C., Kattsov, V., Reason, C., and Rummukainen, M.: Evaluation of Climate Models, in: Climate Change 2013: The Physical Science
Basis, Contribution of Working Group I to the Fifth Assessment Report of the
Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin,
D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A.,
Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge,
United Kingdom and New York, NY, USA, 741–866, https://doi.org/10.1017/CBO9781107415324.020, 2013.
Fraga, H., Malheiro, A. C., Moutinho-Pereira, J., and Santos, J. A.: Future
scenarios for viticultural zoning in Europe: ensemble projections and
uncertainties, Inte. J. Biometeorol., 57, 909–925, https://doi.org/10.1007/s00484-012-0617-8, 2013.
Frei, C., Christensen, J. H., Déqué, M., Jacob, D., Jones, R. G., and Vidale, P. L.: Daily precipitation statistics in regional climate models: Evaluation and intercomparison for the European Alps, J. Geophys. Res.-Atmos., 108, 1–19, https://doi.org/10.1029/2002JD002287, 2003.
Garofalo, P., Ventrella, D., Kersebaum, K. C., Gobin, A., Trnka, M., Giglio,
L., Dubrovský, M., and Castellini, M.: Water footprint of winter wheat
under climate change: Trends and uncertainties associated to the ensemble of
crop models, Sci. Total Environ., 658, 1186–1208, https://doi.org/10.1016/j.scitotenv.2018.12.279, 2019.
Gaudillère, J. P., Van Leeuwen, C., and Ollat, N.: Carbon isotope
composition of sugars in grapevine, an integrated indicator of vineyard water status, J. Exp. Bot., 53, 757–763, https://doi.org/10.1093/jexbot/53.369.757, 2002.
Gaudin, R., Celette, F., and Gary, C.: Contribution of runoff to incomplete
off season soil water refilling in a Mediterranean vineyard, Agr. Water Manage., 97, 1534–1540, https://doi.org/10.1016/j.agwat.2010.05.007, 2010.
Gruber, B.: Untersuchungen zur Bodenfeuchtedynamik und zum Pflanzenwasserhaushalt bei verschiedenen Bodenmanagement- und
Laubwandsystemen von Vitis vinifera L. (cv. Riesling) im Steilhang – ein Ansatz zur bedarfsgerechten Steuerung von Tröpfchenbewässerungsanlagen, Geisenheimer Berichte 71, Gesellschaft zur Förderung der Hochschule Geisenheim e.V., 235 pp., ISBN 13 978-3-934-742-60-4, 2012.
Gruber, B. R. and Schultz, H. R.: Coupling of plant to soil water status at
different vineyard sites, Acta Hort. (ISHS), 689, 381–390, 2005.
Gutiérrez, J. M., Maraun, D., Widmann, M., Huth, R., Hertig, E., Benestad, R., Roessler, O., Wibig, J., Wilcke, R., Kotlarski, S., San Martín, D., Herrera, S., Bedia, J., Casanueva, A., Manzanas, R.,
Iturbide, M., Vrac, M., Dubrovsky, M., Ribalaygua, J., Pórtoles, J.,
Räty, O., Räisänen, J., Hingray, B., Raynaud, D., Casado, M. J.,
Ramos, P., Zerenner, T., Turco, M., Bosshard, T., Štěpánek, P.,
Bartholy, J., Pongracz, R., Keller, D. E., Fischer, A. M., Cardoso, R. M.,
Soares, P. M. M., Czernecki, B., and Pagé, C.: An intercomparison of a
large ensemble of statistical downscaling methods over Europe: Results from
the VALUE perfect predictor cross-validation experiment, Int. J. Climatol., 39, 3750–3785, https://doi.org/10.1002/joc.5462, 2019.
Hanel, M., Rakovec, O., Markonis, Y., Máca, P., Samaniego, L., Kyselý, J., and Kumar, R.: Revisiting the recent European droughts from a long-term perspective, Scient. Rep., 8, 9499, https://doi.org/10.1038/s41598-018-27464-4, 2018.
Hartmann, D. L., Klein Tank, A. M. G., Rusticucci, M., Alexander, L. V.,
Brönnimann, S., Charabi, Y., Dentener, F. J., Dlugokencky, E. J., Easterling, D. R., Kaplan, A., Soden, B. J., Thorne, P. W., Wild, M., and
Zhai, P. M.: Observations: Atmosphere and Surface, in: Climate Change 2013:
The Physical Science Basis, Contribution of Working Group I to the Fifth
Assessement Report of the Intergovernmental Panel on Climate Change,
Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.3390/atmos11121364, 2013.
Hartmann, E., Schulz, J.-P., Seibert, R., Schmidt, M., Zhang, M., Luterbacher, J., and Tölle, M. H.: Impact of Environmental Conditions on
Grass Phenology in the Regional Climate Model COSMO-CLM, Atmosphere, 11, 1364, https://doi.org/10.1017/CBO9781107415324.008, 2020.
Hausfather, Z. and Peters, G. P.: Emissions – the `business as usual' story is misleading, Nature, 577, 618–620, 2020.
Hertig, E., Maraun, D., Bartholy, J., Pongracz, R., Vrac, M., Mares, I.,
Gutiérrez, J. M., Wibig, J., Casanueva, A., and Soares, P. M. M.: Comparison of statistical downscaling methods with respect to extreme events
over Europe: Validation results from the perfect predictor experiment of the
COST Action VALUE, Int. J. Climatol., 39, 3846–3867, https://doi.org/10.1002/joc.5469, 2019.
Hlavinka, P., Kersebaum, K. C., Dubrovský, M., Fischer, M., Pohanková, E., Balek, J., Žalud, Z., and Trnka, M.: Water balance,
drought stress and yields for rainfed field crop rotations under present and
future conditions in the Czech Republic, Clim. Res., 65, 175–192,
https://doi.org/10.3354/cr01339, 2015.
HLNUG: Bodenflächendaten weinbauliche Nutzfläche 1:5000 BFD5W,
Hessisches Landesamt für Naturschutz, Umwelt und Geologie, Wiesbaden,
https://www.hlnug.de/?id=7664 (last access: 8 October 2019), 2008.
Hochschule Geisenheim University: Tagesauswertungen der Wetterstationen, http://rebschutz.hs-geisenheim.de/wetterstationen/tagesauswertung.php, last access: 14 December 2018.
Hofmann, M. and Schultz, H. R.: Warum es seit 1989 wieder heller wird, Der
Deutsche Weinbau, 16–17, 32–34, 2010.
Hofmann, M. and Schultz, H. R.: Modeling the water balance of sloped vineyards under various climate change scenarios, BIO Web Conf., 5, 01026, https://doi.org/10.1051/bioconf/20150501026, 2015.
Hofmann, M., Lux, R., and Schultz, H. R.: Constructing a framework for risk
analyses of climate change effects on the water budget of differently sloped
vineyards with a numeric simulation using the Monte Carlo method coupled to
a water balance model, Front. Plant Sci., 5, 1–22, https://doi.org/10.3389/fpls.2014.00645, 2014.
Hoppmann, D., Schaller, K., and Stoll, M.: Terroir, Ulmer Verlag, Stuttgart,
372 pp., ISBN 978-3-8001-0350-8, 2017.
Huang, M., Gallichand, J., Wang, Z., and Goulet, M.: A modification to the
Soil Conservation Service curve number method for steep slopes in the Loess
Plateau of China, Hydrol. Process., 20, 579–589, https://doi.org/10.1002/hyp.5925,
2006.
Hübener, H., Bülow, K., Fooken, C., Früh, B., Hoffmann, P., Höpp, S., Keuler, K., Menz, C., Mohr, V., Radtke, K., Ramthun, H.,
Spekat, A., Steger, C., Toussaint, F., Warrach-Sagi, K., and Woldt, M.:
ReKliEs-De Ergebnisbericht, DKRZ, https://doi.org/10.2312/WDCC/ReKliEsDe_Ergebnisbericht, 2017.
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O., Bouwer, L.,
Braun, A., Colette, A., Déqué, M., Georgievski, G., Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A., Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski, S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S., Preuschmann, S.,
Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M., Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R., Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution climate change projections for European impact research, Reg. Environ. Change, 14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014.
Jäger, L. and Porten, M.: Biodiversität in Weinbausteillagen, Die
Winzer-Zeitschrift, 3, 26–28, 2018.
Jones, G. V. and Schultz, H. R.: Climate change and emerging cool climate
wine regions, Wine & Viticulture Journal, November/December, 51–53, 2016.
Jones, G. V., Duchène, E., Tomasi, D., Yuste, J., Bratislavska, O.,
Schultz, H. R., Martinez, C., Boso, S., Langellier, F., Perruchot, C., and
Guimberteau, G.: Changes in European Winegrape Phenology and Relationships
with Climate, in: XIV International GESCO-Viticulture-Congress, 23–27 August 2005, Geisenheim, 55–61, ISBN 3-93472-19-X, 2005a.
Jones, G. V., White, M., Cooper, O., and Storchmann, K.: Climate Change and
Global Wine Quality, Climatic Change, 73, 319–343, https://doi.org/10.1007/s10584-005-4704-2, 2005b.
Karim, J. R., Burr, W. S., and Thomson, D. J.: Appendix A: Multitaper R Package, in: Applications of Multitaper Spectral Analysis to Nonstationary
Data, PhD diss., Queen's University, 149–183, http://hdl.handle.net/1974/12584 (last access: 11 September 2021), 2014.
Keller, M.: Deficit Irrigation and Vine Mineral Nutrition, Am. J. Enol. Viticult., 56, 267–283, 2005.
Kenny, G. J. and Harrison, H. A.: The Effects of Climate Variability and
Change on Grape Suitability in Europe, J. Wine Res., 3, 163–183, 1992.
Kirtman, B., Power, S. B., Adedoyin, J. A., Boer, G. J., Bojariu, R.,
Camilloni, I., Doblas-Reyes, F. J., Fiore, A. M., Kimoto, M., Meehl, G. A.,
Prather, M., Sarr, A., Schär, C., Sutton, R., van Oldenborgh, G. J., Vecchi, G., and Wang, H. J.: Near-term Climate Change: Projections and Predictability, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 953–1028, https://doi.org/10.1017/CBO9781107415324.023, 2013.
Kjellström, E., Boberg, F., Castro, M., Christensen, J. H., Nikulin, G.,
and Sánchez, E.: Daily and monthly temperature and precipitation statistics as performance indicators for regional climate models, Clim. Res., 44, 135–150, https://doi.org/10.3354/cr00932, 2010.
Kjellström, E., Nikulin, G., Hansson, U., Strandberg, G., and Ullerstig,
A.: 21st century changes in the European climate: uncertainties derived from
an ensemble of regional climate model simulations, Tellus A, 63, 24–40, https://doi.org/10.1111/j.1600-0870.2010.00475.x, 2011.
Kornhuber, K., Osprey, S., Coumou, D., Petri, S., Petoukhov, V., Rahmstorf,
S., and Gray, L.: Extreme weather events in early summer 2018 connected by a
recurrent hemispheric wave-7 pattern, Environ. Res. Lett., 14, 054002, https://doi.org/10.1088/1748-9326/ab13bf, 2019.
Kotlarski, S., Keuler, K., Christensen, O. B., Colette, A., Déqué,
M., Gobiet, A., Goergen, K., Jacob, D., Lüthi, D., van Meijgaard, E.,
Nikulin, G., Schär, C., Teichmann, C., Vautard, R., Warrach-Sagi, K., and Wulfmeyer, V.: Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble, Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, 2014.
Kreienkamp, F., Huebener, H., Linke, C., and Spekat, A.: Good practice for
the usage of climate model simulation results – a discussion paper, Environ. Syst. Res. 1, 1–13, https://doi.org/10.1186/2193-2697-1-9, 2012.
Lebon, E., Dumas, V., Pieri, P., and Schultz, H. R.: Modelling the seasonal
dynamics of the soil water balance of vineyards, Funct. Plant Biol., 30, 699–710, https://doi.org/10.1071/FP02222, 2003.
Le Roux, R., de Rességuier, L., Corpetti, T., Jégou, N., Madelin, M., van Leeuwen, C., and Quénol, H.: Comparison of two fine scale spatial models for mapping temperatures inside winegrowing areas, Agr. Forest Meteorol., 247, 159–169, https://doi.org/10.1016/j.agrformet.2017.07.020, 2017.
Löhnertz, O., Hoppmann, D., Emde, K., Friedrich, K., Schmanke, M., and
Zimmer, T.: Die Standortkartierung der hessischen Weinbaugebiete, in: Geologische Abhandlungen Hessen 114, edited by: Becker, R. E., Hessisches
Landesamt für Umwelt und Geologie, Wiesbaden, https://www.hlnug.de/static/medien/boden/fisbo/wbsa/start.htm
(last access: 28 May 2019), 2004.
Lovelli, S., Perniola, M., Di Tommaso, T., Ventrella, D., Moriondo, M., and
Amato, M.: Effects of rising atmospheric CO2 on crop evapotranspiration in a Mediterranean area, Agr. Water Manage., 97, 1287–1292, https://doi.org/10.1016/j.agwat.2010.03.005, 2010.
Malheiro, A. C., Santos, J. A., Fraga, H., and Pinto, J. G.: Climate change
scenarios applied to viticultural zoning in Europe, Clim. Res., 43, 163–177, https://doi.org/10.3354/cr00918, 2010.
Manabe, S., and Wetherald, R. T.: Thermal Equilibrium of the Atmosphere with
a Given Distribution of Relative Humidity, J. Atmos. Sci., 24, 241–259, https://doi.org/10.1175/1520-0469(1967)024<0241:teotaw>2.0.co;2, 1967.
Maniak, U.: Hydrologie und Wasserwirtschaft, Springer-Verlag, Berlin, Heidelberg, https://doi.org/10.1007/978-3-642-05396-2, 2010.
Maraun, D., Wetterhall, F., Ireson, A. M., Chandler, R. E., Kendon, E. J., Widmann, M., Brienen, S., Rust, H. W., Sauter, T., Themeßl, M., Venema,
V. K. C., Chun, K. P., Goodess, C. M., Jones, R. G., Onof, C., Vrac, M., and
Thiele-Eich, I.: Precipitation downscaling under climate change: Recent
developments to bridge the gap between dynamical models and the end user,
Rev. Geophys., 48, RG3003, https://doi.org/10.1029/2009rg000314, 2010.
Maraun, D., Widmann, M., Gutiérrez, J. M., Kotlarski, S., Chandler, R. E., Hertig, E., Wibig, J., Huth, R., and Wilcke, R. A. I.: VALUE: A framework to validate downscaling approaches for climate change studies, Earth's Future, 3, 1–14, https://doi.org/10.1002/2014EF000259, 2015.
Maraun, D., Huth, R., Gutiérrez, J. M., Martín, D. S., Dubrovsky,
M., Fischer, A., Hertig, E., Soares, P. M. M., Bartholy, J., Pongrácz,
R., Widmann, M., Casado, M. J., Ramos, P., and Bedia, J.: The VALUE perfect
predictor experiment: Evaluation of temporal variability, Int. J. Climatol., 39, 3786–3818, https://doi.org/10.1002/joc.5222, 2019.
Maraun, D., Truhetz, H., and Schaffer, A.: Regional Climate Model Biases, Their Dependence on Synoptic Circulation Biases and the Potential for Bias
Adjustment: A Process-Oriented Evaluation of the Austrian Regional Climate
Projections, J. Geophys. Res.-Atmos., 126, e2020JD032824, https://doi.org/10.1029/2020JD032824, 2021.
Matthews, M. A., Anderson, M. M., and Schultz, H. R.: Phenologic and growth
responses to early and late season water deficits in Cabernet franc, Vitis,
26, 147–160, 1987.
Maule, C. F., Thejll, P., Christensen, J. H., Svendsen, S. H., and Hannaford, J.: Improved confidence in regional climate model simulations of precipitation evaluated using drought statistics from the ENSEMBLES models,
Clim. Dynam., 40, 155–173, https://doi.org/10.1007/s00382-012-1355-7, 2013.
McLeod, A. I.: Kendall: Kendall rank correlation and Mann–Kendall trend test, R package version 2.2, CRAN, http://CRAN.R-project.org/package=Kendall (last access: 2 May 2019), 2011.
Meinshausen, M., Raper, S. C. B., and Wigley, T. M. L.: Emulating coupled
atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 –
Part 1: Model description and calibration, Atmos. Chem. Phys., 11, 1417–1456, https://doi.org/10.5194/acp-11-1417-2011, 2011.
Monteith, J. L. and Unsworth, M. H.: Chapter 13 – Steady-State Heat Balance: (i) Water Surfaces, Soil, and Vegetation, in: Principles of Environmental Physics (Fourth Edition), edited by: Monteith, J. L. and Unsworth, M. H., Academic Press, Boston, 217–247, https://doi.org/10.1016/B978-0-12-386910-4.00013-5, 2013.
Moriondo, M., Bindi, M., Fagarazzi, C., Ferrise, R., and Trombi, G.: Framework for high-resolution climate change impact assessment on grapevines at a regional scale, Reg. Environ. Change, 11, 553–567, https://doi.org/10.1007/s10113-010-0171-z, 2010.
Moriondo, M., Jones, G. V., Bois, B., Dibari, C., Ferrise, R., Trombi, G., and Bindi, M.: Projected shifts of wine regions in response to climate change, Climatic Change, 119, 825–839, https://doi.org/10.1007/s10584-013-0739-y, 2013.
Morlat, R., Penavayre, M., Jacquet, A., Asselin, C., and Lemaitre, C.:
Influence des terroirs sur le fonctionnement hydrique et la photosynthèse de la vigne en millessime exceptionnellement sec (1990), Conséquence sur la maturation du raisin, Int. J. Vine Wine Sci., 26, 197–218, 1992.
Moutinho-Pereira, J., Goncalves, B., Bacelar, E., Boaventura Cunha, J., Coutinho, J., and Correira, C. M.: Effects of elevated CO2 on grapevine (Vitis vinifera L.): Physiological an yield attributes, Vitis, 48, 159–165, 2009.
Neethling, E., Barbeau, G., Coulon-Leroy, C., and Quénol, H.: Spatial
complexity and temporal dynamics in viticulture: A review of climate-driven
scales, Agr. Forest Meteorol., 276–277, 107618, https://doi.org/10.1016/j.agrformet.2019.107618, 2019.
Ojeda, H., Deloire, A., and Carbonneau, A.: Influence of water deficits on grape berry growth, Vitis, 40, 141–145, 2001.
Ollat, N., Bordenave, L., Tandonnet, J. P., Boursiquot, J. M., and Marguerit, E.: Grapevine rootstocks: origins and perspectives, Acta Hortic., 1136, 11–22, https://doi.org/10.17660/ActaHortic.2016.1136.2, 2016.
Pellegrino, A., Gozé, E., Lebon, E., and Wery, J.: A model-based diagnosis tool to evaluate the water stress experienced by grapevine in field sites, Eur. J. Agron., 25, 49–59, https://doi.org/10.1016/j.eja.2006.03.003, 2006.
Petermann, J., Petersen, B., and Gnittke, I.: Hotspots im Bundesprogramm
biologische Vielfalt, Referat Öffentlichkeitsarbeit, BMU – Bundesministerium für Umwelt, Naturschutz und Reaktorsicherheit, https://biologischevielfalt.bfn.de/ (last access: 13 February 2021), 2012.
Prein, A. F., Langhans, W., Fosser, G., Ferrone, A., Ban, N., Goergen, K.,
Keller, M., Tölle, M., Gutjahr, O., Feser, F., Brisson, E., Kollet, S.,
Schmidli, J., van Lipzig, N. P., and Leung, R.: A review on regional
convection-permitting climate modeling: Demonstrations, prospects, and
challenges, Rev. Geophys., 53, 323–361, https://doi.org/10.1002/2014RG000475, 2015.
Quénol, H., Grosset, M., Barbeau, G., van Leeuwen, C., Hofmann, M., Foss, C., Irimia, L., Rochard, J., Boulanger, J.-P., Tissot, C., and Miranda, C.: Adaptation of Viticulture to Climate Change: High Resolution Observations of Adaptation scenario for Viticulture: The ADVICLIM European Project, Bulletin de l'OIV, 87, 395–406, 2014.
Richardson, C. W.: Stochastic simulation of daily precipitation, temperature, and solar radiation, Water Resour. Res., 17, 182–190, https://doi.org/10.1029/WR017i001p00182, 1981.
Rötter, R. P., Palosuo, T., Pirttioja, N. K., Dubrovsky, M., Salo, T.,
Fronzek, S., Aikasalo, R., Trnka, M., Ristolainen, A., and Carter, T. R.:
What would happen to barley production in Finland if global warming exceeded
4 ∘C? A model-based assessment, Eur. J. Agron., 35, 205–214, https://doi.org/10.1016/j.eja.2011.06.003, 2011.
RPDA: Die Weinbaukartei des Landes Hessen – Stand 2012, Regierungspräsidium Darmstadt, Dezernat Weinbau, Eltville, Darmstadt, 2012.
Sadras, V. O., Montoro, A., Moran, M. A., and Aphalo, P. J.: Elevated temperature altered the reaction norms of stomatal conductance in field-grown grapevine, Agr. Forest Meteorol., 165, 35–42, https://doi.org/10.1016/j.agrformet.2012.06.005, 2012a.
Sadras, V. O., Schultz, H. R., Girona, J., and Marsal, J.: Grapevine, in:
Crop yield response to water, FAO irrigation and drainage paper 66, edited
by: Steduto, P., Hsiao, T. C., Fereres, E., and Raes, D., Food and Agriculture Organization of the United Nations, Rome, 460–485, ISBN 978-92-5-107274-5, 2012b.
Santos, J. A., Malheiro, A. C., Pinto, J. G., and Jones, G. V.: Macroclimate
and viticultural zoning in Europe: observed trends and atmospheric forcing,
Clim. Res., 51, 89–103, https://doi.org/10.3354/cr01056, 2012.
Santos, J. A., Grätsch, S. D., Karremann, M. K., Jones, G. V., and Pinto, J. G.: Ensemble projections for wine production in the Douro Valley of Portugal, Climatic Change, 117, 211–225, https://doi.org/10.1007/s10584-012-0538-x, 2013.
Santos, J. A., Fraga, H., Malheiro, A. C., Moutinho-Pereira, J., Dinis, L.-T., Correia, C., Moriondo, M., Leolini, L., Dibari, C., Costafreda-Aumedes, S., Kartschall, T., Menz, C., Molitor, D., Junk, J., Beyer, M., and Schultz, H. R.: A Review of the Potential Climate Change
Impacts and Adaptation Options for European Viticulture, Appl. Sci., 10, 3092, https://doi.org/10.3390/app10093092, 2020.
Savoi, S., Wong, D. C. J., Arapitsas, P., Miculan, M., Bucchetti, B.,
Peterlunger, E., Fait, A., Mattivi, F., and Castellarin, S. D.: Transcriptome and metabolite profiling reveals that prolonged drought modulates the phenylpropanoid and terpenoid pathway in white grapes (Vitis vinifera L.), BMC Plant Biol., 16, 67, https://doi.org/10.1186/s12870-016-0760-1, 2016.
Schär, C., Vidale, P. L., Luthi, D., Frei, C., Haberli, C., Liniger, M.
A., and Appenzeller, C.: The role of increasing temperature variability in
European summer heatwaves, Nature, 427, 332–336, https://doi.org/10.1038/nature02300, 2004.
Schultz, H. R.: Water relations and photosynthetic responses of two grapevine cultivars of different geographical origin during water stress, Acta Horticult., 427, 251–266, 1996.
Schultz, H. R.: Climate Change and viticulture: A European perspective on
climatology, carbon dioxide and UV-B effects, Aust. J. Grape Wine Res., 6, 2–12, 2000.
Schultz, H. R.: Differences in hydraulic architecture account for near-isohydric and anisohydric behaviour of two field-grown Vitis vinifera L. cultivars during drought, Plant Cell Environ., 26, 1393–1405,
https://doi.org/10.1046/j.1365-3040.2003.01064.x, 2003.
Schultz, H. R.: Issues to be considered for strategic adaptation to climate
evolution – is atmospheric evaporative demand changing?, OENO One, 51,
109–114, https://doi.org/10.20870/oeno-one.2017.51.2.1619, 2017.
Schultz, H. R. and Hofmann, M.: The ups and downs of environmental impact
on grapevines: future challenges in temperate viticulture, in: Grapevine in
a Changing Environment: A Molecular and Ecophysiological Perspective, edited
by: Gerós, H., Chaves, M. M., Medrano, H., and Delrot, S.,
Wiley-Blackwell, https://doi.org/10.1002/9781118735985.ch2, 2015.
Schultz, H. R. and Jones, G. V.: Climate Induced Historic and Future Changes in Viticulture, J. Wine Res., 21, 137–145, 2010.
Schultz, H. R. and Lebon, E.: Modelling the effect of climate change on
grapevine water relations, Acta Hort. (ISHS), 689, 71–78, 2005.
Smart, D. R., Schwass, E., Lakso, A., and Morano, L.: Grapevine Rooting
Patterns: A Comprehensive Analysis and a Review, Am. J. Enol. Viticult., 57,
89–104, 2006.
Strub, L. and Loose, S.: The cost disadvantage of steep slope viticulture and strategies for its preservation, OENO One, 55, 49–68, https://doi.org/10.20870/oeno-one.2021.55.1.4494, 2021.
Sturman, A., Zawar-Reza, P., Soltanzadeh, I., Katurji, M., Bonnardot, V.,
Parker, A. K., Trought, M. C. T., Quénol, H., Le Roux, R., Gendig, E., and Schulmann, T.: The application of high-resolution atmospheric modelling to weather and climate variability in vineyard regions, OENO One, 51, 99–105, https://doi.org/10.20870/oeno-one.2016.0.0.1538, 2017.
Suklitsch, M., Gobiet, A., Truhetz, H., Awan, N. K., Göttel, H., and Jacob, D.: Error characteristics of high resolution regional climate models
over the Alpine area, Clim. Dynam., 37, 377–390, https://doi.org/10.1007/s00382-010-0848-5, 2011.
Tölle, M. H., Gutjahr, O., Busch, G., and Thiele, J. C.: Increasing
bioenergy production on arable land: Does the regional and local climate
respond? Germany as a case study, J. Geophys. Res.-Atmos., 119, 2711–2724, https://doi.org/10.1002/2013jd020877, 2014.
Trömel, S. and Schönwiese, C. D.: Probability change of extreme
precipitation observed from 1901 to 2000 in Germany, Theor. Appl. Climatol., 87, 29–39, https://doi.org/10.1007/s00704-005-0230-4, 2007.
Umweltbundesamt: Schwefeldioxid-Emissionen nach Quellkategorien, Nationale
Trendtabellen für die deutsche Berichterstattung atmosphärischer
Emissionen seit 1990, Emissionsentwicklung 1990 bis 2019 (Stand 01/2021),
https://www.umweltbundesamt.de/daten/luft/luftschadstoff-emissionen-in-deutschland/schwefeldioxid-emissionen#entwicklung-seit-1990, last access: 17 December 2021.
van der Linden, P. and Mitchell, J. F. B.: ENSEMBLES: Climate Change and its Impacts: Summary of research and results from the ENSEMBLES project, Met Office Hadley Centre, Exeter, UK, 160 pp., http://ensembles-eu.metoffice.com/docs/Ensembles_final_report_Nov09.pdf
(last access: 28 May 2021), 2009.
Van Leeuwen, C. and Destrac-Irvine, A.: Modified grape composition under
climate change conditions requires adaptations in the vineyard, OENO One, 51, 147–154, https://doi.org/10.20870/oeno-one.2016.0.0.1647, 2017.
Van Leeuwen, C. and Seguin, G.: Incidences de l'alimentation en eau de la vigne, appreciée per l'etat hydrique du feuillage, sur le developpement de l'appareil végétatif et la maturation du raisin, J. Vine Wine Sci., 28, 81–110, 1994.
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Climatic Change, 109, 5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011.
Vorderbrügge, T., Friedrich, K., Sauer, S., Peter, M., and Miller, R.:
Ableitung der FK für Acker aus dem Klassenzeichen der Bodenschätzung, Hesssisches Landesamt für Naturschutz, Umwelt und Geologie, Wiesbaden, https://www.hlnug.de/static/medien/boden/fisbo/bs/doku/zwischenbericht2005/CD Zwischenbericht 2005/methode_FK_al_20060329.pdf (last access: 26 April 2019), 2006.
Webb, L. B., Whetton, P. H., and Barlow, E. W. R.: Modelled impact of future
climate change on the phenology of winegrapes in Australia, Aust. J. Grape Wine Res., 13, 165–175, https://doi.org/10.1111/j.1755-0238.2007.tb00247.x, 2007.
Webb, L. B., Whetton, P. H., and Barlow, E. W. R.: Observed trends in winegrape maturity in Australia, Global Change Biol., 17, 2707–2719,
https://doi.org/10.1111/j.1365-2486.2011.02434.x, 2011.
Wild, M.: Global dimming and brightening: A review, J. Geophys. Res., 114,
1–31, https://doi.org/10.1029/2008jd011470, 2009.
Wild, M.: Enlightening Global Dimming and Brightening, B. Am. Meteorol. Soc., 93, 27–37, https://doi.org/10.1175/bams-d-11-00074.1, 2012.
Wilks, D. S.: Adapting stochastic weather generation algorithms for climate
change studies, Climatic Change, 22, 67–84, https://doi.org/10.1007/BF00143344, 1992.
Williams, L. E. and Matthews, M. A.: Grapevine, in: Irrigation of Agricultural Crops, edited by: Stewart, B. A. and Nielsen, D. R., ASA-CSSA-SSSA, Madison, WI, 1019–1055, ISBN 0-89118-102-4, 1990.
WMO: WMO Statement on the State of the Global Climate in 2019, WMO – World
Meteorological Organization, https://library.wmo.int/index.php?lvl=notice_display&id=21700#.X80KANhKiUk
(last access: 18 March 2022), 2020.
Wohlfahrt, Y., Smith, J. P., Tittmann, S., Honermeier, B., and Stoll, M.:
Primary productivity and physiological responses of Vitis vinifera L. cvs. under Free Air Carbon dioxide Enrichment (FACE), Eur. J. Agron., 101, 149–162, https://doi.org/10.1016/j.eja.2018.09.005, 2018.
Woodward, D. E., Hawkins, R. H., Jiang, R., Hjelmfelt, A. T., and Van Mullem, J. A.: Runoff Curve Number Method: Examination of the Initial Abstraction Ratio, in: World Water Environmental Resources Congress 2003, 23–26 June 2003, Philadelphia, Pennsylvania, USA, 1–10,
https://doi.org/10.1061/40685(2003)308, 2003.
Xu, Z., Jiang, Y., Jia, B., and Zhou, G.: Elevated-CO2 Response of
Stomata and Its Dependence on Environmental Factors, Front. Plant Sci., 7, 657, https://doi.org/10.3389/fpls.2016.00657, 2016.
Zimmer, T.: Untersuchungen zum Wasserhaushalt von Weinbergsböden im Rheingau, Geisenheimer Berichte 35, Gesellschaft zur Förderung der Forschungsanstalt Geisenheim, Geisenheim, 232 pp., ISBN 3-9805265-5-0, 1999.
Short summary
We modelled water budget developments of viticultural growing regions on the spatial scale of individual vineyard plots with respect to landscape features like the available water capacity of the soils, slope, and aspect of the sites. We used an ensemble of climate simulations and focused on the occurrence of drought stress. The results show a high bandwidth of projected changes where the risk of potential drought stress becomes more apparent in steep-slope regions.
We modelled water budget developments of viticultural growing regions on the spatial scale of...
Altmetrics
Final-revised paper
Preprint