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 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.

A Bayesian Hierarchical Model for Heterogeneous RCM–GCM Multimodel Ensembles*

2015 ◽  
Vol 28 (15) ◽  
pp. 6249-6266 ◽  
Author(s):  
Christian Kerkhoff ◽  
Hans R. Künsch ◽  
Christoph Schär
Keyword(s):  
Hierarchical Model ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Bayesian Hierarchical Model ◽  
Global Climate Models ◽  
Seasonal Temperature ◽  
Bayesian Hierarchical ◽  
Multimodel Ensembles

Abstract A Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to regional and seasonal temperature averages from the ENSEMBLES project, probabilistic projections of future climate are derived. Intermodel correlations that are particularly strong between regional climate models and their driving global climate models are explicitly accounted for. Instead of working with time slices, a data archive is investigated in a transient setting. This enables a coherent treatment of internal variability on multidecadal time scales. Results are presented for four European regions to highlight the feasibility of the approach. In particular, the methodology is able to objectively identify patterns of variability changes, in ways that previously required subjective expert knowledge. Furthermore, this study underlines that assumptions about bias changes have an effect on the projected warming. It is also shown that validating the out-of-sample predictive performance is possible on short-term prediction horizons and that the hierarchical model herein is competitive. Additionally, the findings indicate that instead of running a large suite of regional climate models all forced by the same driver, priority should be given to a rich diversity of global climate models that force a number of regional climate models in the experimental design of future multimodel ensembles.

scholarly journals Regional climate models downscaling in the Alpine area with multimodel superensemble

2013 ◽  
Vol 17 (5) ◽  
pp. 2017-2028 ◽  
Author(s):  
D. Cane ◽  
S. Barbarino ◽  
L. A. Renier ◽  
C. Ronchi
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Temperature Fields ◽  
Optimal Interpolation ◽  
Climate Change Scenarios ◽  
Alpine Area ◽  
Ensembles Project

Abstract. The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control period.

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.

Temperature and precipitation verification over Pannonian Basin in EURO-CORDEX simulations during summer season

2020 ◽  
Author(s):  
Irida Lazic ◽  
Vladimir Djurdjevic
Keyword(s):  
Climate Models ◽  
Pannonian Basin ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Summer Season ◽  
Data Set ◽  
Sea Level Pressure ◽  
Temperature And Precipitation ◽  
Time Period ◽  
Precipitation Bias

&lt;p&gt;In previous studies, it was noticed that many Regional Climate Models (RCMs) tend to overestimate mean near surface air temperature and underestimate precipitation in the Pannonian Basin during summer, leading to so-called summer drying problem [1]. Our intention for this study was to analyze temperature and precipitation biases in the state of the art EURO-CORDEX multi-model ensemble results in the summer season. Models&amp;#8217; results from the historical runs, and over time period 1971-2000, for temperature, precipitation and sea level pressure were verified against gridded E-OBS data set. In total there were 30 selected integrations, with different combinations of RCMs and Global Climate Models (GCMs). In order to assess the impact of the different lateral boundary conditions on the results from RCMs simulations, emphasizing the errors of the corresponding driving models used in 30 RCMs simulations, results from driving GCMs are also verified.&lt;/p&gt;&lt;p&gt;Verification results for selected time period was expressed in term of four verification scores: bias, root mean square error (RMSE), spatial correlation coefficient and standard deviations. Verification scores were evaluated within a sub-domain in the center of the region bounded by longitudes, 14E and 27E, and latitudes, 43.5N and 50N, in which topography elevation is below 200 m. This sub-domain was selected to eliminate the influence of results over the surrounding mountains on spatially averaged scores [2], because previous studies indicated a pronounced summer drying problem in low lying areas. Our analysis showed that 17 RCMs tend to overestimate the temperature, 8 RCMs tend to underestimate the temperature and 5 RCMs tend to estimate temperature around E-OBS gridded data set. On the other hand, most of the RCMs that overestimate the temperature, underestimate the precipitation. According to the results, temperature bias was in the range from -1.9&amp;#176;C to +4.4&amp;#176;C , while precipitation bias was in the range from 42% to -70%. For some models the positive temperature and negative precipitation bias were even more pronounced, leading to the conclusion, that the problem is still present in the majority of analyzed simulations. Analysis of the sea level pressure was conducted as an indirect indicator of errors in advection processes in RCMs, which was indicated, beside others, as a potential precursor of temperature and precipitation biases [3]. To better understand the sources and reasons for summer drying problem further research is needed.&lt;/p&gt;&lt;p&gt;[1] Kotlarski S. et al., (2014): Regional climate modelling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble. Geoscientific Model Development 7:1297&amp;#8211;1333, doi: 10.5194/gmd-7-1297-2014&lt;/p&gt;&lt;p&gt;[2] Lazic I., Djurdjevic V., (2019): EURO-CORDEX regional climate models&amp;#8217; performances in representing temperature and precipitation over Pannonian Basin, Book of abstracts, 5th PannEx Workshop, 3-5 June 2019, Novi Sad, Serbia.&lt;/p&gt;&lt;p&gt;[3] Sz&amp;#233;psz&amp;#243; G., (2006): Adaptation of the REMO model at the Hungarian Meteorological Service (in Hungarian). Proceedings of the 31st Scientific Days for Meteorology, 125&amp;#8211;135.&lt;/p&gt;&lt;p&gt;&lt;em&gt;Keywords&lt;/em&gt;: summer drying problem, verification, EURO-CORDEX, Pannonian Basin&lt;/p&gt;&lt;p&gt;Acknowledgement: This study was supported by the Serbian Ministry of Science and Education, under grant no. 176013.&lt;/p&gt;

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.

scholarly journals Zustand und Entwicklung der Trockenheit in Schweizer Wäldern

2015 ◽  
Vol 166 (6) ◽  
pp. 352-360 ◽  
Author(s):  
Jan Remund ◽  
Sabine Augustin
Keyword(s):  
Regional Differences ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Regional Climate ◽  
Regional Scale ◽  
Climate Scenario ◽  
Regional Climate Models ◽  
Weather Extremes ◽  
Climatic Regions ◽  
Site Water

State and development of drought in Swiss forests Climate scenarios for the 21st century for Switzerland show increasing temperatures and more frequent weather extremes and the risk of drought will become more important. The objective of the study was the calculation of indicators which allow the estimation and evaluation of drought risks on a regional scale. The site water balance and the ratio between actual and potential evapotranspiration (ETa/ETp) were used as indicators. They are closely related to vitality parameters of trees. For projections in the future were used the A1B climate scenario, which assumes a warming of 2.7 to 4.1°C in Switzerland, and three regional climate models (CLM, RCA, REGCM3), which predict different developments regarding precipitation and temperature. Historical time series between 1951 and 2012 and scenarios up to 2100 for different climatic regions were calculated. The indicators reproduce well the measured trends and the regional differences. In all regions there was in the past a trend to increased drought. The Geneva/ Vaud region as well as the western midlands and north Switzerland show the most pronounced changes. Projections with the CLM model (which reproduced best the historic trend 1981–2010 for Switzerland) show increasing drought and, in general, an increasing variability of the climate for the mid-century.

scholarly journals Geographical distribution of the incubation period of coffee leaf rust in climate change scenarios

2019 ◽  
Vol 54 ◽  
Author(s):  
Waldenilza Monteiro Vital Alfonsi ◽  
Priscila Pereira Coltri ◽  
Jurandir Zullo Júnior ◽  
Flávia Rodrigues Alves Patrício ◽  
Renata Ribeiro do Valle Gonçalves ◽  
...  
Keyword(s):  
Leaf Rust ◽  
Incubation Period ◽  
Geographical Distribution ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Change Scenarios ◽  
Regression Equations ◽  
Coffee Leaf Rust

Abstract: The objective of this work was to simulate the geographical distribution of the incubation period of coffee leaf rust in Coffea arabica, using data of two regional climate models, Eta-HadGEM2-ES and Eta-MIROC5. The scenario of high greenhouse gas emission (RCP 8.5 W m-2) was used for the states of Minas Gerais and São Paulo, Brazil, for current and future climate scenarios. The behavior of six different regression equations for incubation period (IP), available in the literature, was also analyzed as affected by data from the regional climate models. The results indicate the possibility of an increase in the affected area in the studied region, when the IP is less than 19 days, from 0.5% for Eta-MIROC5 to 14.2% for Eta-HadGEM2-ES. The severity of coffee leaf rust in future scenarios should increase in the hottest and wettest months of the year, extending to the driest and coldest months. The potential of rust infection is estimated differently by the studied equations. In higher temperature scenarios, the Kushalappa & Martins equation indicates a very high severity potential.

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.

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