scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

scholarly journals Impacts of projected maximum temperature extremes for C21 by an ensemble of regional climate models on cereal cropping systems in the Iberian Peninsula

2011 ◽  
Vol 11 (12) ◽  
pp. 3275-3291 ◽  
Author(s):  
M. Ruiz-Ramos ◽  
E. Sánchez ◽  
C. Gallardo ◽  
M. I. Mínguez
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
High Temperatures ◽  
Climate Models ◽  
Cropping Systems ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Grain Filling ◽  
Maximum Temperature ◽  
Climate Change Scenarios

Abstract. Crops growing in the Iberian Peninsula may be subjected to damagingly high temperatures during the sensitive development periods of flowering and grain filling. Such episodes are considered important hazards and farmers may take insurance to offset their impact. Increases in value and frequency of maximum temperature have been observed in the Iberian Peninsula during the 20th century, and studies on climate change indicate the possibility of further increase by the end of the 21st century. Here, impacts of current and future high temperatures on cereal cropping systems of the Iberian Peninsula are evaluated, focusing on vulnerable development periods of winter and summer crops. Climate change scenarios obtained from an ensemble of ten Regional Climate Models (multimodel ensemble) combined with crop simulation models were used for this purpose and related uncertainty was estimated. Results reveal that higher extremes of maximum temperature represent a threat to summer-grown but not to winter-grown crops in the Iberian Peninsula. The study highlights the different vulnerability of crops in the two growing seasons and the need to account for changes in extreme temperatures in developing adaptations in cereal cropping systems. Finally, this work contributes to clarifying the causes of high-uncertainty impact projections from previous studies.

scholarly journals ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan

2012 ◽  
Vol 370 (1962) ◽  
pp. 1121-1139 ◽  
Author(s):  
Toshichika Iizumi ◽  
Mikhail A. Semenov ◽  
Motoki Nishimori ◽  
Yasushi Ishigooka ◽  
Tsuneo Kuwagata
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Local Scale ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Emission Scenarios ◽  
Model Ensemble ◽  
Daily Weather Data

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981–2000 is assessed using several statistical tests and quantile–quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081–2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.

Downscaling of climate change scenarios for a high resolution, site–specific assessment of drought stress risk for two viticultural regions with heterogeneous landscapes

2021 ◽  
Author(s):  
Marco Hofmann ◽  
Claudia Volosciuk ◽  
Martin Dubrovský ◽  
Douglas Maraun ◽  
Hans R. Schultz
Keyword(s):  
Climate Change ◽  
Drought Stress ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Research Knowledge ◽  
Wine Production ◽  
The Future

Abstract. Extended periods without precipitation observed for example in Central Europe including Germany during the seasons from 2018 to 2020, can lead to water deficit and yield and quality losses for grape and wine production. However, irrigation infrastructure is largely non–existent. Regional climate models project changes of precipitation amounts and patterns, indicating an increase in frequency of occurrence of comparable situations in the future. In order to assess possible impacts of climate change on the water budget of grapevines, a water balance model was developed, which accounts for the large heterogeneity of vineyards with respect to their soil water storage capacity, evapotranspiration as a function of slope and aspect, and viticultural management practices. The model was fed with data from soil maps (soil type and plant available water capacity), a digital elevation model, the European Union (EU) vineyard–register, observed weather data and future weather data provided by regional climate models and a stochastic weather generator. This allowed conducting a risk assessment of the drought stress occurrence for the wine–producing regions Rheingau and Hessische Bergstraße in Germany on the scale of individual vineyard plots. The simulations showed that the risk for drought stress varies substantially between vineyard sites but might increase for steep–slope regions in the future. Possible adaptation measures depend highly on local conditions and to make targeted use of the resource water, an intense interplay of different wine-industry stakeholders, research, knowledge transfer, and local authorities will be required.

scholarly journals An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Dongwoo Jang
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Pearson Correlation ◽  
Regional Climate ◽  
Circulation Model ◽  
Regional Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Precipitation Data ◽  
Simulated Precipitation

Climate change scenarios are used for predicting future precipitation. More detailed regional climate change scenarios are being used through dynamic downscale based on global circulation model results. There is a global tendency to utilize simulated precipitation data from downscaled regional climate models (RCMs) suitable for each country. In Korea, there are studies for improving the accuracy of climate change scenario precipitation forecasts compared with observed precipitation. In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. The ANN ensemble of RCMs simulates the actual observed precipitation more accurately than the individual RCM. In particular, it is more effective inland than in coastal areas, where precipitation patterns are complex. Pearson correlation coefficient of ANN is high as 0.04 compared with MRA. It is expected that more detailed analysis will be possible if it is applied not only to four cities but also to other regions in Korea. If observed precipitation data are collected in sufficient quantity, the applicability of the ANN model will widen.

Surrogate climate-change scenarios for regional climate models

1996 ◽  
Vol 23 (6) ◽  
pp. 669-672 ◽  
Author(s):  
Christoph Schär ◽  
Christoph Frei ◽  
Daniel Lüthi ◽  
Huw C. Davies
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Scenarios

scholarly journals Assessing Regional Climate Models (RCMs) Ensemble-Driven Reference Evapotranspiration over Spain

Water ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 1181 ◽  
Author(s):  
Patricia Giménez ◽  
Sandra García-Galiano
Keyword(s):  
Climate Models ◽  
Hydrological Modeling ◽  
Reference Evapotranspiration ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Scenarios ◽  
Seasonal Temperature ◽  
Time Period ◽  
Negative Impacts

The present work applies a novel methodology of combining multiple Regional Climate Models (RCMs) (or ensemble) that are based on the seasonal and annual variability of temperatures over Spain, which allows for the quantification and reduction of uncertainty in the projections of temperature based-potential evapotranspiration. Reference evapotranspiration (ETo) is one of the most important variables in water budgets. Therefore, the uncertainties in the identification of reliable trends of reference evapotranspiration should be taken into account for water planning and hydrological modeling under climate change scenarios. From the results over Spain, the RCMs ensemble reproduces well the yearly and seasonal temperature observed dataset for the time reference period 1961–1990. An increase in the ensemble-driven ETo for time period 2021–2050 over Spain is expected, which is motivated by an increase in maximum and minimum temperature, with the consequent negative impacts on water availability.

scholarly journals Validating the importance of criteria for assessing climate change scenarios

2018 ◽  
Vol 9 (3) ◽  
pp. 570-583 ◽  
Author(s):  
Bojan Srdjevic ◽  
Zorica Srdjevic ◽  
Milena Lakicevic
Keyword(s):  
Climate Change ◽  
Decision Making ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Impacts ◽  
Borda Count ◽  
Climate Change Scenarios ◽  
Ordinal Information ◽  
Output Information

Abstract While evaluating climate impacts within different climate change scenarios, analysts and stakeholders may have different goals and therefore it is usually difficult to define a common decision-making framework applicable for various practical uses. In this paper, we combine two different group decision-making methodologies to prioritise criteria for assessing output information from regional climate models. The first is based on use of a multi-criteria analytic hierarchy process (AHP) to determine weights of criteria as cardinal information about their importance. The second methodology uses two voting methods, namely Borda count and Approval voting, to generate ordinal information (ranks) for criteria. A set of five criteria is assessed by 16 PhD students from the field of climatology, and generated decisions about their importance in the validation of regional climate models' quality are summarised, compared, and critically discussed. The paper is closed with recommendations for further research.

Sign in / Sign up

Export Citation Format

Share Document