The use of a climate-type classification for assessing climate change effects in Europe from an ensemble of nine regional climate models

2007 ◽  
Vol 81 (S1) ◽  
pp. 329-341 ◽  
Author(s):  
M. de Castro ◽  
C. Gallardo ◽  
K. Jylha ◽  
H. Tuomenvirta
2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.


Author(s):  
Camila Billerbeck ◽  
Ligia Monteiro da Silva ◽  
Silvana Susko Marcellini ◽  
Arisvaldo Méllo Junior

Abstract Regional climate models (RCM) are the main tools for climate change impacts assessment in hydrological studies. These models, however, often show biases when compared to historical observations. Bias Correction (BC) are useful techniques to improve climate projection outputs. This study presents a multi-criteria decision analysis (MCDA) framework to compare combinations of RCM with selected BC methods. The comparison was based on the modified Kling-Gupta efficiency (KGE’). The criteria evaluated the general capability of models in reproducing the observed data main statistics. Other criteria evaluated were the relevant aspects for hydrological studies, such as seasonality, dry and wet periods. We applied four BC methods in four RCM monthly rainfall outputs from 1961 to 2005 in the Piracicaba river basin. The Linear Scaling (LS) method showed higher improvements in the general performance of the models. The RCM Eta-HadGEM2-ES, corrected with Standardized Reconstruction (SdRc) method, achieved the best results when compared to the observed precipitation. The bias corrected projected monthly precipitation (2006-2098) preserved the main signal of climate change effects when compared to the original outputs regarding annual rainfall. However, SdRc produced significant decrease in monthly average rainfall, higher than 45% for July, August and September for RCP4.5 and RCP8.5 scenarios.


2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin

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.


2018 ◽  
Vol 22 (1) ◽  
pp. 673-687 ◽  
Author(s):  
Antoine Colmet-Daage ◽  
Emilia Sanchez-Gomez ◽  
Sophie Ricci ◽  
Cécile Llovel ◽  
Valérie Borrell Estupina ◽  
...  

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.


2021 ◽  
Author(s):  
Patrick Nistahl ◽  
Tim Müller ◽  
Gerhard Riedel ◽  
Hannes Müller-Thomy ◽  
Günter Meon

&lt;p&gt;Climate change impact studies performed for Northern Germany indicate a growing demand for water storage capacity to account for flood protection, low flow augmentation, drinking and agricultural water supply. At the same time, larger storage volumes for hydropower plants can be used to cope with the demands of changing energy supply from fossil to renewable energies. To tackle these challenges for the next decades, a novel reservoir system planning instrument is developed, which consists of combined numerical models and evaluation components. It allows to model simultaneously the current interconnected infrastructure of reservoirs as well as additional planning variants (structural and operational) as preparation for climate change. This planning instrument consists of a hydrological model and a detailed reservoir operation model.&lt;/p&gt;&lt;p&gt;As hydrological model, the conceptual, semi-distributed version of PANTA RHEI is applied. &amp;#160;Bias-corrected regional climate models (based on the RCP 8.5 scenario) are used as meteorological input. The hydrological model is coupled with a detailed reservoir operation model that replicates the complex rules of various interconnected reservoirs based on an hourly time step including pumped storage plants, which may have a subsurface reservoir as a lower basin. Downstream of the reservoirs, the hydrological model is used for routing the reservoir outflows and simulating natural side inflows. In areas of particular interest for flood protection, the hydrological routing is substituted with 2D hydraulic models to calculate the flood risk in terms of expected annual flood damage based on resulting inundation areas.&lt;/p&gt;&lt;p&gt;For the performance analysis, the simulation runs for all integrated modeling variants are evaluated for a reference period (1971-2000) and for future periods (2041-2070). Performance criteria involve flood protection, drinking water supply, low flow augmentation and energy production. These performance criteria will be used as stake holder information as well as a base for further optimization and ranking of the planning variants.&lt;/p&gt;&lt;p&gt;The combination of the hydrological model and the reservoir operation model shows a good performance of the existing complex hydraulic infrastructure using observed meteorological forcing as input. The usage of regional climate models as input shows a wide dispersion of several performance criteria, confirming the expected need for an innovative optimization scheme and the communication of the underlying uncertainties.&lt;/p&gt;


2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter

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.


2015 ◽  
Vol 7 (1) ◽  
pp. 16-28 ◽  
Author(s):  
Andrijana Todorovic ◽  
Jasna Plavsic

Assessment of climate change (CC) impact on hydrologic regime requires a calibrated rainfall-runoff model, defined by its structure and parameters. The parameter values depend, inter alia, on the calibration period. This paper investigates influence of the calibration period on parameter values, model efficiency and streamflow projections under CC. To this end, a conceptual HBV-light model of the Kolubara River catchment in Serbia is calibrated against flows observed within 5 consecutive wettest, driest, warmest and coldest years and in the complete record period. The optimised parameters reveal high sensitivity towards calibration period. Hydrologic projections under climate change are developed by employing (1) five hydrologic models with outputs of one GCM–RCM chain (Global and Regional Climate Models) and (2) one hydrologic model with five GCM–RCM outputs. Sign and magnitude of change in projected variables, compared to the corresponding values simulated over the baseline period, vary with the hydrologic model used. This variability is comparable in magnitude to variability stemming from climate models. Models calibrated over periods with similar precipitation as the projected ones may result in less uncertain projections, while warmer climate is not expected to contribute to the uncertainty in flow projections. Simulations over prolonged dry periods are expected to be uncertain.


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