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Author Calanca, P.; Semenov, M.A. url  doi
openurl 
  Title Local-scale climate scenarios for impact studies and risk assessments: integration of early 21st century ENSEMBLES projections into the ELPIS database Type Journal Article
  Year 2013 Publication Theoretical and Applied Climatology Abbreviated Journal Theor. Appl. Climatol.  
  Volume (up) 113 Issue 3-4 Pages 445-455  
  Keywords stochastic weather generators; regional climate; lars-wg; daily; precipitation; models; simulation; europe; temperature; variability; heatwaves  
  Abstract We present the integration of early 21st century climate projections for Europe based on simulations carried out within the EU-FP6 ENSEMBLES project with the LARS-WG stochastic weather generator. The aim was to upgrade ELPIS, a repository of local-scale climate scenarios for use in impact studies and risk assessments that already included global projections from the CMIP3 ensemble and regional scenarios for Japan. To obtain a more reliable simulation of daily rainfall and extremes, changes in wet and dry series derived from daily ENSEMBLES outputs were taken into account. Kernel average smoothers were used to reduce noise arising from sampling artefacts. Examples of risk analyses based on 25-km climate projections from the ENSEMBLES ensemble of regional climate models illustrate the possibilities offered by the updated version of ELPIS. The results stress the importance of tailored information for local-scale impact assessments at the European level.  
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  Language English Summary Language Original Title  
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  ISSN 0177-798x 1434-4483 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4484  
Permanent link to this record
 

 
Author Lardy, R.; Bellocchi, G.; Martin, R. url  doi
openurl 
  Title Vuln-Indices: Software to assess vulnerability to climate change Type Journal Article
  Year 2015 Publication Computers and Electronics in Agriculture Abbreviated Journal Computers and Electronics in Agriculture  
  Volume (up) 114 Issue Pages 53-57  
  Keywords climate change; Java; vulnerability indices; pasture simulation-model; integrated assessment; environmental-change; change impacts; system  
  Abstract Vuln-Indices Java-based software was developed on concepts of vulnerability to climate change of agro-ecological systems. It implements the calculation of vulnerability indices on series of state variables for assessments at both site and region levels. The tool is useful because synthetic indices help capturing complex processes and prove effective to identify the factors responsible for vulnerability and their relative importance. It is suggested that the tool may be plausible for use with stakeholders to disseminate information of climate change impacts. (C) 2015 Elsevier B.V. All rights reserved.  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0168-1699 ISBN Medium Article  
  Area Expedition Conference  
  Notes LiveM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4648  
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Author Balkovič, J.; van der Velde, M.; Schmid, E.; Skalský, R.; Khabarov, N.; Obersteiner, M.; Stürmer, B.; Xiong, W. url  doi
openurl 
  Title Pan-European crop modelling with EPIC: Implementation, up-scaling and regional crop yield validation Type Journal Article
  Year 2013 Publication Agricultural Systems Abbreviated Journal Agricultural Systems  
  Volume (up) 120 Issue Pages 61-75  
  Keywords EPIC; large-scale crop modelling; model performance testing; EU; climate-change; high-resolution; organic-carbon; growth-model; wheat yield; water; calibration; impacts; productivity; simulations  
  Abstract Justifiable usage of large-scale crop model simulations requires transparent, comprehensive and spatially extensive evaluations of their performance and associated accuracy. Simulated crop yields of a Pan-European implementation of the Environmental Policy Integrated Climate (EPIC) crop model were satisfactorily evaluated with reported regional yield data from EUROSTAT for four major crops, including winter wheat, rainfed and irrigated maize, spring barley and winter rye. European-wide land use, elevation, soil and daily meteorological gridded data were integrated in GIS and coupled with EPIC. Default EPIC crop and biophysical process parameter values were used with some minor adjustments according to suggestions from scientific literature. The model performance was improved by spatial calculations of crop sowing densities, potential heat units, operation schedules, and nutrient application rates. EPIC performed reasonable in the simulation of regional crop yields, with long-term averages predicted better than inter-annual variability: linear regression R-2 ranged from 0.58 (maize) to 0.91 (spring barley) and relative estimation errors were between +/- 30% for most of the European regions. The modelled and reported crop yields demonstrated similar responses to driving meteorological variables. However, EPIC performed better in dry compared to wet years. A yield sensitivity analysis of crop nutrient and irrigation management factors and cultivar specific characteristics for contrasting regions in Europe revealed a range in model response and attainable yields. We also show that modelled crop yield is strongly dependent on the chosen PET method. The simulated crop yield variability was lower compared to reported crop yields. This assessment should contribute to the availability of harmonised and transparently evaluated agricultural modelling tools in the EU as well as the establishment of modelling benchmarks as a requirement for sound and ongoing policy evaluations in the agricultural and environmental domains. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved.  
  Address 2016-06-01  
  Corporate Author Thesis  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0308-521x ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial 4737  
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Author Refsgaard, J.C.; Madsen, H.; Andréassian, V.; Arnbjerg-Nielsen, K.; Davidson, T.A.; Drews, M.; Hamilton, D.P.; Jeppesen, E.; Kjellström, E.; Olesen, J.E.; Sonnenborg, T.O.; Trolle, D.; Willems, P.; Christensen, J.H. url  doi
openurl 
  Title A framework for testing the ability of models to project climate change and its impacts Type Journal Article
  Year 2014 Publication Climatic Change Abbreviated Journal Clim. Change  
  Volume (up) 122 Issue 1-2 Pages 271-282  
  Keywords simulation-models; shallow lakes; predictions; calibration; ensembles; terminology; uncertainty; temperature; adaptation; validation  
  Abstract Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data in order to build further confidence in model projections.  
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  Series Volume Series Issue Edition  
  ISSN 0165-0009 1573-1480 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial 4688  
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Author Rötter, R.P.; Palosuo, T.; Kersebaum, K.C.; Angulo, C.; Bindi, M.; Ewert, F.; Ferrise, R.; Hlavinka, P.; Moriondo, M.; Nendel, C.; Olesen, J.E.; Patil, R.H.; Ruget, F.; Takác, J.; Trnka, M. url  doi
openurl 
  Title Simulation of spring barley yield in different climatic zones of Northern and Central Europe: A comparison of nine crop models Type Journal Article
  Year 2012 Publication Field Crops Research Abbreviated Journal Field Crops Research  
  Volume (up) 133 Issue Pages 23-36  
  Keywords climate; crop growth simulation; model comparison; spring barley; yield variability; uncertainty; change impacts; nitrogen dynamics; high-temperature; soil-moisture; elevated co2; ceres-wheat; data set; growth; drought; sensitivity  
  Abstract In this study, the performance of nine widely used and accessible crop growth simulation models (APES-ACE, CROPSYST, DAISY, DSSAT-CERES, FASSET, HERMES, MONICA, STICS and WOFOST) was compared during 44 growing seasons of spring barley (Hordeum vulgare L) at seven sites in Northern and Central Europe. The aims of this model comparison were to examine how different process-based crop models perform at multiple sites across Europe when applied with minimal information for model calibration of spring barley at field scale, whether individual models perform better than the multi-model mean, and what the uncertainty ranges are in simulated grain yields. The reasons for differences among the models and how results for barley compare to winter wheat are discussed. Regarding yield estimation, best performing based on the root mean square error (RMSE) were models HERMES, MONICA and WOFOST with lowest values of 1124, 1282 and 1325 (kg ha(-1)), respectively. Applying the index of agreement (IA), models WOFOST, DAISY and HERMES scored best having highest values (0.632, 0.631 and 0.585, respectively). Most models systematically underestimated yields, whereby CROPSYST showed the highest deviation as indicated by the mean bias error (MBE) (-1159 kg ha(-1)). While the wide range of simulated yields across all sites and years shows the high uncertainties in model estimates with only restricted calibration, mean predictions from the nine models agreed well with observations. Results of this paper also show that models that were more accurate in predicting phenology were not necessarily the ones better estimating grain yields. Total above-ground biomass estimates often did not follow the patterns of grain yield estimates and, thus, harvest indices were also different. Estimates of soil moisture dynamics varied greatly. In comparison, even though the growing cycle for winter wheat is several months longer than for spring barley, using RMSE and IA as indicators, models performed slightly, but not significantly, better in predicting wheat yields. Errors in reproducing crop phenology were similar, which in conjunction with the shorter growth cycle of barley has higher effects on accuracy in yield prediction. (C) 2012 Elsevier B.V. All rights reserved.  
  Address 2016-10-31  
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  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0378-4290 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ftnotmacsur Approved no  
  Call Number MA @ admin @ Serial 4803  
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