Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data, with the  focus on improving data management and have shared data curation for future use. The  issue was tackled with help from the MACSUR central hub coordination in the form of Jason  Jargenson from University of Reading. The data management as proposed and  implemented in this deliverable is very much a bottom up process, in which partners in a  meeting in Spring 2013 in Aarhus investigated the best way forward for data management  across activities in CropM.As a follow up to this, the work was mainly divided in three  parts:  1. The  Open  Data  Journal  for  Agricultural  Research,  mainly  focused  on  long  term  data  archival  and  citation  of  data  sets,  as  input  and  outputs  to  the  modelling  work,  as  part  of  MACSUR,  lead  by  Wageningen  UR  2. The  Geonetwork  data  catalog  hosted  at  Aarhus  Universitet,  that  allows  for  operational  access  and  storage  of  data  sets  as  part  of  the  ongoing  work,  also  for  restricted  access  of  the  consortium,  and  as  a  first  step  to  visualization,  lead  by  Aarhus  Universitet.  3. The  work  on  rating  data  sets,  that  provides  a  tool  for  improving  data  set  access  in  an  early  phase  for  connecting  them  to  models,  lead  by  Reading  University.  At the end of the deliverable some next steps are giving for data activities in the context  of AgMIP and beyond. No Label

Abstract: This deliverable lays out the work as done as part of MACSUR CropM on data publishing, with the focus on improving data sharing and discovery and have shared data curation for future use. As part of the first phase MACSUR, The Open Data Journal for Agricultural Research (www.odjar.org) was started and documented in Deliverable C2.2 as part of Crop M. Odjar.org mainly focuses on long term data archival and citation of data sets, as input and outputs to the modelling work, as part of MACSUR, lead by Wageningen UR This deliverable is a short update on the process of creating such a data journal by demonstrating a set of articles published through the journal, some of which are based on MACSUR results, as well as related networks. The deliverable does not further explain what the journal is, as this is part of the previous deliverable.

Abstract: The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. No Label