Climate change and landscape-use patterns influence recent past distribution of giant pandas

Climate change is one of the most pervasive threats to biodiversity globally, yet the influence of climate relative to other drivers of species depletion and range contraction remain difficult to disentangle. Here, we examine climatic and non-climatic correlates of giant panda ( Ailuropoda melanoleuca ) distribution using a large-scale 30 year dataset to evaluate whether a changing climate has already influenced panda distribution. We document several climatic patterns, including increasing temperatures, and alterations to seasonal temperature and precipitation. We found that while climatic factors were the most influential predictors of panda distribution, their importance diminished over time, while landscape variables have become relatively more influential. We conclude that the panda's distribution has been influenced by changing climate, but conservation intervention to manage habitat is working to increasingly offset these negative consequences.

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Effects of climatic factors on the net primary productivity in the source region of Yangtze River, China

Scientific Reports ◽

10.1038/s41598-020-80494-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Zhe Yuan ◽

Yongqiang Wang ◽

Jijun Xu ◽

Zhiguang Wu

Keyword(s):

Climate Change ◽

Primary Productivity ◽

Yangtze River ◽

Net Primary Productivity ◽

Climatic Factors ◽

Source Region ◽

Primary Reason ◽

Vegetation Types ◽

Temperature And Precipitation ◽

Increasing Trend

AbstractThe ecosystem of the Source Region of Yangtze River (SRYR) is highly susceptible to climate change. In this study, the spatial–temporal variation of NPP from 2000 to 2014 was analyzed, using outputs of Carnegie–Ames–Stanford Approach model. Then the correlation characteristics of NPP and climatic factors were evaluated. The results indicate that: (1) The average NPP in the SRYR is 100.0 gC/m2 from 2000 to 2014, and it shows an increasing trend from northwest to southeast. The responses of NPP to altitude varied among the regions with the altitude below 3500 m, between 3500 to 4500 m and above 4500 m, which could be attributed to the altitude associated variations of climatic factors and vegetation types; (2) The total NPP of SRYR increased by 0.18 TgC per year in the context of the warmer and wetter climate during 2000–2014. The NPP was significantly and positively correlated with annual temperature and precipitation at interannual time scales. Temperature in February, March, May and September make greater contribution to NPP than that in other months. And precipitation in July played a more crucial role in influencing NPP than that in other months; (3) Climatic factors caused the NPP to increase in most of the SRYR. Impacts of human activities were concentrated mainly in downstream region and is the primary reason for declines in NPP.

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Impact of Climate Change on Water Availability and Food Security of Nepal

Hydro Nepal Journal of Water Energy and Environment ◽

10.3126/hn.v11i1.7206 ◽

2012 ◽

pp. 59-63

Author(s):

Roshan Kumar Mehta ◽

Shree Chandra Shah

Keyword(s):

Climate Change ◽

Crop Production ◽

Climatic Factors ◽

Monsoon Season ◽

Groundwater Table ◽

Maximum Temperature ◽

Aquatic Life ◽

Temperature And Precipitation ◽

Average Maximum ◽

Water Scarce

The increase in the concentration of greenhouse gases (GHGs) in the atmosphere is widely believed to be causing climate change. It affects agriculture, forestry, human health, biodiversity, and snow cover and aquatic life. Changes in climatic factors like temperature, solar radiation and precipitation have potential to influence agrobiodiversity and its production. An average of 0.04°C/ year and 0.82 mm/year rise in annual average maximum temperature and precipitation respectively from 1975 to 2006 has been recorded in Nepal. Frequent droughts, rise in temperature, shortening of the monsoon season with high intensity rainfall, severe floods, landslides and mixed effects on agricultural biodiversity have been experienced in Nepal due to climatic changes. A survey done in the Chitwan District reveals that lowering of the groundwater table decreases production and that farmers are attracted to grow less water consuming crops during water scarce season. The groundwater table in the study area has lowered nearly one meter from that of 15 years ago as experienced by the farmers. Traditional varieties of rice have been replaced in the last 10 years by modern varieties, and by agricultural crops which demand more water for cultivation. The application of groundwater for irrigation has increased the cost of production and caused severe negative impacts on marginal crop production and agro-biodiversity. It is timely that suitable adaptive measures are identified in order to make Nepalese agriculture more resistant to the adverse impacts of climate change, especially those caused by erratic weather patterns such as the ones experienced recently.DOI: http://dx.doi.org/10.3126/hn.v11i1.7206 Hydro Nepal Special Issue: Conference Proceedings 2012 pp.59-63

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Are large scale models useful? A case of nested model domains for assessing current and future stream runoff and sediments

10.5194/egusphere-egu21-8852 ◽

2021 ◽

Author(s):

Alena Bartosova ◽

Berit Arheimer ◽

Alban de Lavenne ◽

René Capell ◽

Johan Strömqvist

Keyword(s):

Climate Change ◽

Spatial Patterns ◽

Large Scale ◽

Aridity Index ◽

Global Climate Models ◽

Hydrological Models ◽

Nested Model ◽

Nested Models ◽

Changing Climate ◽

Scale Models

Continental and global dynamic hydrological models have emerged recently as tools for e.g. flood forecasting, large-scale climate impact analyses, and estimation of time-dynamic water fluxes into sea basins. One such tool is a dynamic process-based rainfall-runoff and water quality model Hydrological Predictions for Environment (HYPE). We present and compare historical simulations of runoff, soil moisture, aridity, and sediment concentrations for three nested model domains using global, continental (Europe), and national (Sweden) catchment-based HYPE applications. Future impacts on hydrological variables from changing climate were then assessed using the global and continental HYPE applications with ensembles based on 3 CMIP5 global climate models (GCMs).Simulated historical sediment concentrations varied considerably among the nested models in spatial patterns while runoff values were more similar. Regardless of the variation, the global model was able to provide information on climate change impacts comparable to those from the continental and national models for hydrological indicators. Output variables that were calibrated, e.g. runoff, were shown to result in more reliable and consistent projected changes among the different model scales than derived variables such as the actual aridity index. The comparison was carried out for ensemble averages as well as individual GCMs to illustrate the variability and the need for robust assessments.Global hydrological models are shown to be valuable tools for e.g. first screenings of climate change effects and detection of spatial patterns and can be useful to provide information on current and future hydrological states at various domains. The challenge is (1) in deciding when we should use the large-scale models and (2) in interpreting the results, considering the uncertainty of the model results and quality of data especially at the global scale. Comparison across nested domains demonstrates the significance of scale which needs to be considered when interpreting the impacts alongside with model performance.Bartosova et al, 2021: Large-scale hydrological and sediment modeling in nested domains under current and changing climate. Accepted to Special Issue Journal of Hydraulic Engineering.

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Prediction of Plant Phenological Shift under Climate Change in South Korea

Sustainability ◽

10.3390/su12219276 ◽

2020 ◽

Vol 12 (21) ◽

pp. 9276

Author(s):

Ha Kyung Lee ◽

So Jeong Lee ◽

Min Kyung Kim ◽

Sang Don Lee

Keyword(s):

Climate Change ◽

Prunus Persica ◽

Climatic Factors ◽

Cherry Tree ◽

Rcp Scenarios ◽

Temperature And Precipitation ◽

Prunus Yedoensis ◽

Forsythia Koreana ◽

The Difference ◽

Phenological Shift

Information on the phenological shift of plants can be used to detect climate change and predict changes in the ecosystem. In this study, the changes in first flowering dates (FFDs) of the plum tree (Prunus mume), Korean forsythia (Forsythia koreana), Korean rosebay (Rhododendron mucronulatum), cherry tree (Prunus yedoensis), and peach tree (Prunus persica) in Korea during 1920–2019 were investigated. In addition, the changes in the climatic factors (temperature and precipitation) and their relationship with the FFDs were analyzed. The changes in the temperature and precipitation during the January–February–March period and the phenological shifts of all research species during 1920–2019 indicate that warm and dry spring weather advances the FFDs. Moreover, the temperature has a greater impact on this phenological shift than precipitation. Earlier flowering species are more likely to advance their FFDs than later flowering species. Hence, the temporal asynchrony among plant species will become worse with climate change. In addition, the FFDs in 2100 were predicted based on representative concentration pathway (RCP) scenarios. The difference between the predicted FFDs of the RCP 4.5 and RCP 6.0 for 2100 was significant; the effectiveness of greenhouse gas policies will presumably determine the degree of the plant phenological shift in the future. Furthermore, we presented the predicted FFDs for 2100.

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Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France

Climate of the Past ◽

10.5194/cp-12-635-2016 ◽

2016 ◽

Vol 12 (3) ◽

pp. 635-662 ◽

Cited By ~ 25

Author(s):

Laurie Caillouet ◽

Jean-Philippe Vidal ◽

Eric Sauquet ◽

Benjamin Graff

Keyword(s):

Climate Change ◽

Twentieth Century ◽

High Resolution ◽

Large Scale ◽

Local Scale ◽

Precipitation Forecast ◽

Seasonal Temperature ◽

Downscaling Method ◽

Quantitative Precipitation Forecast ◽

Precipitation And Temperature

Abstract. This work proposes a daily high-resolution probabilistic reconstruction of precipitation and temperature fields in France over the 1871–2012 period built on the NOAA Twentieth Century global extended atmospheric reanalysis (20CR). The objective is to fill in the spatial and temporal data gaps in surface observations in order to improve our knowledge on the local-scale climate variability from the late nineteenth century onwards. The SANDHY (Stepwise ANalogue Downscaling method for HYdrology) statistical downscaling method, initially developed for quantitative precipitation forecast, is used here to bridge the scale gap between large-scale 20CR predictors and local-scale predictands from the Safran high-resolution near-surface reanalysis, available from 1958 onwards only. SANDHY provides a daily ensemble of 125 analogue dates over the 1871–2012 period for 608 climatically homogeneous zones paving France. Large precipitation biases in intermediary seasons are shown to occur in regions with high seasonal asymmetry like the Mediterranean. Moreover, winter and summer temperatures are respectively over- and under-estimated over the whole of France. Two analogue subselection methods are therefore developed with the aim of keeping the structure of the SANDHY method unchanged while reducing those seasonal biases. The calendar selection keeps the analogues closest to the target calendar day. The stepwise selection applies two new analogy steps based on similarity of the sea surface temperature (SST) and the large-scale 2 m temperature (T). Comparisons to the Safran reanalysis over 1959–2007 and to homogenized series over the whole twentieth century show that biases in the interannual cycle of precipitation and temperature are reduced with both methods. The stepwise subselection moreover leads to a large improvement of interannual correlation and reduction of errors in seasonal temperature time series. When the calendar subselection is an easily applicable method suitable in a quantitative precipitation forecast context, the stepwise subselection method allows for potential season shifts and SST trends and is therefore better suited for climate reconstructions and climate change studies. The probabilistic downscaling of 20CR over the period 1871–2012 with the SANDHY probabilistic downscaling method combined with the stepwise subselection thus constitutes a perfect framework for assessing the recent observed meteorological events but also future events projected by climate change impact studies and putting them in a historical perspective.

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Analyses of temperature and precipitation in the Indian Jammu and Kashmir region for the 1980–2016 period: implications for remote influence and extreme events

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-15-2019 ◽

2019 ◽

Vol 19 (1) ◽

pp. 15-37 ◽

Cited By ~ 17

Author(s):

Sumira Nazir Zaz ◽

Shakil Ahmad Romshoo ◽

Ramkumar Thokuluwa Krishnamoorthy ◽

Yesubabu Viswanadhapalli

Keyword(s):

Climate Change ◽

Statistical Tests ◽

Wrf Model ◽

Annual Rainfall ◽

Maximum Temperature ◽

Seasonal Temperature ◽

Western Himalayas ◽

Jammu And Kashmir ◽

Temperature And Precipitation ◽

Average Annual Temperature

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.

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The impact of climate change on cocoa production in West Africa

International Journal of Climate Change Strategies and Management ◽

10.1108/ijccsm-01-2013-0007 ◽

2014 ◽

Vol 6 (3) ◽

pp. 296-314 ◽

Cited By ~ 3

Author(s):

Kenneth Ofori-Boateng ◽

Baba Insah

Keyword(s):

Climate Change ◽

West Africa ◽

Climatic Factors ◽

Extreme Temperature ◽

Yield Response ◽

Content Type ◽

Impact Of Climate Change ◽

Temperature And Precipitation ◽

Cocoa Production ◽

The Impact

Purpose – The study aimed at examining the current and future impact of climate change on cocoa production in West Africa. Design/methodology/approach – A translog production function based on crop yield response framework was used. A panel model was estimated using data drawn from cocoa-producing countries in West Africa. An in-sample simulation was used to determine the predictive power of the model. In addition, an out-sample simulation revealed the effect of future trends of temperature and precipitation on cocoa output. Findings – Temperature and precipitation play a considerable role in cocoa production in West Africa. It was established that extreme temperature adversely affected cocoa output in the sub-region. Furthermore, increasing temperature and declining precipitation trends will reduce cocoa output in the future. Practical implications – An important implication of this study is the recognition that lagging effects are the determinants of cocoa output and not coincident effects. This finds support from the agronomic point of view considering the gestation period of the cocoa crop. Originality/value – Although several studies have been carried out in this area, this study modeled and estimated the interacting effects of factors that influence cocoa production. This is closer to reality, as climatic factors and agricultural inputs combine to yield output.

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Locomotion of Slope Geohazards Responding to Climate Change in the Qinghai-Tibetan Plateau and Its Adjacent Regions

Sustainability ◽

10.3390/su131910488 ◽

2021 ◽

Vol 13 (19) ◽

pp. 10488

Author(s):

Yiru Jia ◽

Jifu Liu ◽

Lanlan Guo ◽

Zhifei Deng ◽

Jiaoyang Li ◽

...

Keyword(s):

Climate Change ◽

Climatic Factors ◽

High Sensitivity ◽

Spatial Location ◽

Future Climate ◽

Tibet Plateau ◽

The South ◽

Climate Conditions ◽

Temperature And Precipitation ◽

Qinghai Tibet Plateau

Slope geohazards, which cause significant social, economic and environmental losses, have been increasing worldwide over the last few decades. Climate change-induced higher temperatures and shifted precipitation patterns enhance the slope geohazard risks. This study traced the spatial transference of slope geohazards in the Qinghai-Tibet Plateau (QTP) and investigated the potential climatic factors. The results show that 93% of slope geohazards occurred in seasonally frozen regions, 2.6% of which were located in permafrost regions, with an average altitude of 3818 m. The slope geohazards are mainly concentrated at 1493–1988 m. Over time, the altitude of the slope geohazards was gradually increased, and the mean altitude tended to spread from 1984 m to 2562 m by 2009, while the slope gradient varied only slightly. The number of slope geohazards increased with time and was most obvious in spring, especially in the areas above an altitude of 3000 m. The increase in temperature and precipitation in spring may be an important reason for this phenomenon, because the results suggest that the rate of air warming and precipitation at geohazard sites increased gradually. Based on the observation of the spatial location, altitude and temperature growth rate of slope geohazards, it is noted that new geohazard clusters (NGCs) appear in the study area, and there is still a possibility of migration under the future climate conditions. Based on future climate forecast data, we estimate that the low-, moderate- and high-sensitivity areas of the QTP will be mainly south of 30° N in 2030, will extend to the south of 33° N in 2060 and will continue to expand to the south of 35° N in 2099; we also estimate that the proportion of high-sensitivity areas will increase from 10.93% in 2030 to 14.17% in 2060 and 17.48% in 2099.

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Calculating groundwater stress and climate change-induced vulnerability of karst aquifers on a global scale

10.5194/egusphere-egu21-929 ◽

2021 ◽

Author(s):

Philipp Nußbaum ◽

Márk Somogyvári ◽

Christopher Conrad ◽

Martin Sauter ◽

Irina Engelhardt

Keyword(s):

Climate Change ◽

Water Stress ◽

Climatic Factors ◽

Karst Aquifer ◽

Global Scale ◽

Stress Index ◽

Karst Aquifers ◽

Climate Zones ◽

Climate Conditions ◽

Temperature And Precipitation

Approximately 10% of the global population rely on groundwater from karst aquifers. Due to complex karst structures, these aquifers have high infiltration capacities and hydraulic conductivities, which makes them vulnerable to pollution and, as prediction and management are complicated, overexploitation. As populations are growing and demand rises, we assess the current level of groundwater stress in karst aquifers with Mediterranean climates and their vulnerability (defined as the change in groundwater stress) to expected changes in temperature and precipitation on the global scale.Our approach is based on a Groundwater Stress Index (GSI), which is calculated for 356 karst aquifers (as identified in the World Karst Aquifer Map) that have some of their area located in Mediterranean climate zones (Csa, Csb, and Csc after K&#246;ppen/Geiger). GSI are calculated from seven indicators: groundwater recharge, storage, and abstractions, surface runoff, climatic water balance, water-intensity of crops, and groundwater-dependent ecosystems. Each indicator is spatially and temporally averaged to describe a recent trend on aquifer level, resulting in one complex attribute table for the 356 aquifers. GSI is calculated as the average of the normalized indicators for each aquifer, ranging from 0 (no water stress) to 1 (extreme water stress).Aquifers are then grouped based on similarities in two classification parameters &#8211; degree of karstification (P1) and land cover (P2). Comparison of aquifers with similar classification parameters allows to focus more directly on the relationship between groundwater stress and climate, disregarding relatively constant influences. For each group (e.g., well-developed karst, primarily agriculturally used), we plot calculated GSI values with current temperature and precipitation data. By investigating four Shared Socioeconomic Pathways (SSPs) until 2100, we identify aquifers that mimic future climate conditions for others with similar P1 and P2. We then measure the difference in groundwater stress accompanied by altered climatic factors. This change is interpreted as vulnerability to climate change.This approach, which relies on present-day observed conditions, allows us to predict the effect of a changing climate without the need to develop a complex numerical model, which requires large amounts of data and functional understanding of aquifer behavior. While analysis is currently ongoing, we expect both groundwater stress and vulnerabilities to be high. Predicted climate zone shifts by Beck et al. (2018) indicate that, out of 356 karst aquifers with Mediterranean climates, 52 could move to more extreme arid climate zones by 2100.Results will be visualized in the form of vulnerability maps that may serve as an &#8220;early-warning system&#8221;. For particularly threatened aquifers, we will derive recommendations for more sustainable management by suggesting strategies to lower groundwater stress. This is done by taking a closer look at the aquifer&#8217;s indicator values and identifying factors that currently contribute the most to groundwater stress.

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Large-scale atmospheric circulation biases and changes in global climate model simulations and their importance for climate change in Central Europe

Atmospheric Chemistry and Physics ◽

10.5194/acp-6-863-2006 ◽

2006 ◽

Vol 6 (4) ◽

pp. 863-881 ◽

Cited By ~ 140

Author(s):

A. P. van Ulden ◽

G. J. van Oldenborgh

Keyword(s):

Climate Change ◽

Central Europe ◽

Large Scale ◽

Global Climate Model ◽

Late Summer ◽

Geostrophic Flow ◽

Temperature And Precipitation ◽

Mean Temperature ◽

Precipitation Changes ◽

Circulation Changes

Abstract. The quality of global sea level pressure patterns has been assessed for simulations by 23 coupled climate models. Most models showed high pattern correlations. With respect to the explained spatial variance, many models showed serious large-scale deficiencies, especially at mid-latitudes. Five models performed well at all latitudes and for each month of the year. Three models had a reasonable skill. We selected the five models with the best pressure patterns for a more detailed assessment of their simulations of the climate in Central Europe. We analysed observations and simulations of monthly mean geostrophic flow indices and of monthly mean temperature and precipitation. We used three geostrophic flow indices: the west component and south component of the geostrophic wind at the surface and the geostrophic vorticity. We found that circulation biases were important, and affected precipitation in particular. Apart from these circulation biases, the models showed other biases in temperature and precipitation, which were for some models larger than the circulation induced biases. For the 21st century the five models simulated quite different changes in circulation, precipitation and temperature. Precipitation changes appear to be primarily caused by circulation changes. Since the models show widely different circulation changes, especially in late summer, precipitation changes vary widely between the models as well. Some models simulate severe drying in late summer, while one model simulates significant precipitation increases in late summer. With respect to the mean temperature the circulation changes were important, but not dominant. However, changes in the distribution of monthly mean temperatures, do show large indirect influences of circulation changes. Especially in late summer, two models simulate very strong warming of warm months, which can be attributed to severe summer drying in the simulations by these models. The models differ also significantly in the simulated warming of cold winter months. Finally, the models simulate rather different changes in North Atlantic sea surface temperature, which is likely to impact on changes in temperature and precipitation. These results imply that several important aspects of climate change in Central Europe are highly uncertain. Other aspects of the simulated climate change appear to be more robust. All models simulate significant warming all year round and an increase in precipitation in the winter half-year.

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