... Home

MACSUR Literature Database

Home |  Show All |  Simple Search |  Advanced Search
Quick Search:
1–5 of 19 records found matching your query (RSS):
toggle visibility Search & Display Options
Select All    Deselect All << 1 2 3 4 >>
List View
 | 
Citations
 | 
Details
   print
  Records Links
Author Liu, B.; Asseng, S.; Müller, C.; Ewert, F.; Elliott, J.; Lobell, D. B.; Martre, P.; Ruane, A. C.; Wallach, D.; Jones, J. W.; Rosenzweig, C.; Aggarwal, P. K.; Alderman, P. D.; Anothai, J.; Basso, B.; Biernath, C.; Cammarano, D.; Challinor, A.; Deryng, D.; Sanctis, G. D.; Doltra, J.; Fereres, E.; Folberth, C.; Garcia-Vila, M.; Gayler, S.; Hoogenboom, G.; Hunt, L. A.; Izaurralde, R. C.; Jabloun, M.; Jones, C. D.; Kersebaum, K. C.; Kimball, B. A.; Koehler, A.-K.; Kumar, S. N.; Nendel, C.; O’Leary, G. J.; Olesen, J. E.; Ottman, M. J.; Palosuo, T.; Prasad, P. V. V.; Priesack, E.; Pugh, T. A. M.; Reynolds, M.; Rezaei, E. E.; Rötter, R. P.; Schmid, E.; Semenov, M. A.; Shcherbak, I.; Stehfest, E.; Stöckle, C. O.; Stratonovitch, P.; Streck, T.; Supit, I.; Tao, F.; Thorburn, P.; Waha, K.; Wall, G. W.; Wang, E.; White, J. W.; Wolf, J.; Zhao, Z.; Zhu, Y. url  doi
openurl 
  Title Similar estimates of temperature impacts on global wheat yield by three independent methods Type Journal Article
  Year 2016 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change  
  Volume 6 Issue 12 Pages 1130-1136  
  Keywords  
  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1758-678x ISBN Medium article  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial (down) 4965  
Permanent link to this record
 
 
Author Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. doi  openurl
  Title Lessons from climate modeling on the design and use of ensembles for crop modeling Type Journal Article
  Year 2016 Publication Climatic Change Abbreviated Journal Clim. Change  
  Volume 139 Issue 3-4 Pages 551-564  
  Keywords change projections; elevated CO2; uncertainty; wheat; water; soil; simulations; yield; rice; 21st-century; Model ensembles; Crop models; Climate models; Model weighting; Super ensembles  
  Abstract Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.  
  Address 2017-01-06  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0165-0009 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_MACSUR Approved no  
  Call Number MA @ admin @ Serial (down) 4933  
Permanent link to this record
 
 
Author Thornton, P.; Ewert, F. openurl 
  Title Making the most of climate impacts ensembles (vol 4, pg 77, 2014) – Correction Type Journal Article
  Year 2014 Publication Nature Climate Change Abbreviated Journal Nat. Clim. Change  
  Volume 4 Issue 3 Pages 166-166  
  Keywords  
  Abstract  
  Address 2016-10-31  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1758-678x ISBN Medium Letter  
  Area Expedition Conference  
  Notes CropM Approved no  
  Call Number MA @ admin @ Serial (down) 4817  
Permanent link to this record
 
 
Author Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E. url  doi
openurl 
  Title Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century Type Journal Article
  Year 2016 Publication Climatic Change Abbreviated Journal Clim. Change  
  Volume 134 Issue 1-2 Pages 283-297  
  Keywords regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes  
  Abstract Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management.  
  Address 2016-10-31  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0165-0009 ISBN Medium Article  
  Area Expedition Conference  
  Notes CropM, ft_macsur Approved no  
  Call Number MA @ admin @ Serial (down) 4805  
Permanent link to this record
 
 
Author Wallach, D.; Mearns, L.O.; Ruane, A.C.; Rötter, R.P.; Asseng, S. url  doi
openurl 
  Title Lessons from climate modeling on the design and use of ensembles for crop modeling Type Journal Article
  Year 2016 Publication Climatic Change Abbreviated Journal Clim. Change  
  Volume Issue Pages  
  Keywords Model ensembles; Crop models; Climate models; Model weighting; Super ensembles  
  Abstract Working with ensembles of crop models is a recent but important development in crop modeling which promises to lead to better uncertainty estimates for model projections and predictions, better predictions using the ensemble mean or median, and closer collaboration within the modeling community. There are numerous open questions about the best way to create and analyze such ensembles. Much can be learned from the field of climate modeling, given its much longer experience with ensembles. We draw on that experience to identify questions and make propositions that should help make ensemble modeling with crop models more rigorous and informative. The propositions include defining criteria for acceptance of models in a crop MME, exploring criteria for evaluating the degree of relatedness of models in a MME, studying the effect of number of models in the ensemble, development of a statistical model of model sampling, creation of a repository for MME results, studies of possible differential weighting of models in an ensemble, creation of single model ensembles based on sampling from the uncertainty distribution of parameter values or inputs specifically oriented toward uncertainty estimation, the creation of super ensembles that sample more than one source of uncertainty, the analysis of super ensemble results to obtain information on total uncertainty and the separate contributions of different sources of uncertainty and finally further investigation of the use of the multi-model mean or median as a predictor.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0165-0009 1573-1480 ISBN Medium Review  
  Area CropM Expedition Conference  
  Notes CropM; wos; ft=macsur; wsnotyet; Approved no  
  Call Number MA @ admin @ Serial (down) 4781  
Permanent link to this record
Select All    Deselect All << 1 2 3 4 >>
List View
 | 
Citations
 | 
Details
   print
toggle visibility
Save Citations:
Export Records:
Home CQL Search  |  Library Search  |  Show Record  |  Extract Citations Help