Abstract: This document is intended to aid in the development of regional Representative Agricultural Pathways in Europe for use in MACSUR case studies, especially the regional pilot studies. We present overviews of existing characterisations of RCPs, SSPs, SPAs, RAPs and more detailed descriptions of the scenarios and assumptions relevant for MACSUR. No Label

Abstract: The workshop was called to define an overarching question to be answered by all Regional  Pilot Studies and to select from the existing studies those that fit best to the aims of  MACSUR. The question that evolved from the discussions is “What would be the different  contributions of different European adaptation strategies to ensure global food security  until 2050 at different scales (farm to EU) while keeping the GHG targets?” Workshop  participants agreed to use the newest climate simulations related to Representative  Concentration Pathways that were also used by the AgMIP and ISI-MIP projects. There was  also agreement to use a subset of the AgMIP scenarios (S2-S6) for impact assessments, with  AgMIP scenario S1 as the reference scenario, for details see Table 3 below. The selection  of Regional Pilot Studies was discussed separately for European Grand Regions, but there  was no concluding decision taken. The Project Steering Committee will finally decide on  showcase studies at a meeting in the first week of July based on characterisations sent in  by interested members. Questionnaires for characterising the Regional Pilot Studies will be  sent by the Hub to the regional contact persons mentioned in Table 2 to fill in. The  characterization list can be extended. The questionnaires should be filled in by the end of  June. Stakeholder meetings are planned for October 2013 in each region where  preliminary/sample outputs of the regional pilot studies should be presented. Results will  be presented at the mid-term meeting in April 2014. The last year of MACSUR is then  available to improve the studies.The geographic extent of the Regional Pilot Studies is  approximately county level – representing the area of the studies they are based on. The  Regional Pilot Studies will be linked within the grand regions (northern, central, southern  Europe) by consistent regional and continental Representative Agricultural Pathways (RAP).  These regional RAPs will feed into the RAP process underway at AgMIP. Through the  common RAPs the Regional Pilot Studies will reflect the common challenges of the greater  region and by having several Regional Pilot Studies the diversity of the environment,  farming systems, and political systems is represented. The workshop was a first step into  further planning and performing the Regional Pilot Studies that will fine-tune the results of  the workshop. No Label

Abstract: Crop growth simulation models are increasingly used for regionally assessing the effects of climate change and variability on crop yields. These models require spatially and temporally detailed, location-specific, environmental (weather and soil) and management data as inputs, which are often difficult to obtain consistently for larger regions. Aggregating the resolution of input data for crop model applications may increase the uncertainty of simulations to an extent that is not well understood. The present study aims to systematically analyse the effect of changes in the spatial resolution of weather input data on yields simulated by four crop models (LINTUL-SLIM, DSSAT-CSM, EPIC and WOFOST) which were utilized to test possible interactions between weather input data resolution and specific modelling approaches representing different degrees of complexity. The models were applied to simulate grain yield of spring barley in Finland for 12 years between 1994 and 2005 considering five spatial resolutions of daily weather data: weather station (point) and grid-based interpolated data at resolutions of 10 km x 10 km; 20 km x 20 km; 50 km x 50 km and 100 km x 100 km. Our results show that the differences between models were larger than the effect of the chosen spatial resolution of weather data for the considered years and region. When displaying model results graphically, each model exhibits a characteristic ‘fingerprint’ of simulated yield frequency distributions. These characteristic distributions in response to the inter-annual weather variability were independent of the spatial resolution of weather input data. Using one model (LINTUL-SLIM), we analysed how the aggregation strategy, i.e. aggregating model input versus model output data, influences the simulated yield frequency distribution. Results show that aggregating weather data has a smaller effect on the yield distribution than aggregating simulated yields which causes a deformation of the model fingerprint. We conclude that changes in the spatial resolution of weather input data introduce less uncertainty to the simulations than the use of different crop models but that more evaluation is required for other regions with a higher spatial heterogeneity in weather conditions, and for other input data related to soil and crop management to substantiate our findings. Our results provide further evidence to support other studies stressing the importance of using not just one, but different crop models in climate assessment studies. (C) 2013 Elsevier B.V. All rights reserved.