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Jorgenson, J. |
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Title |
Review of Cloud Computing Opportunities |
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Report |
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2013 |
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FACCE MACSUR Reports |
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1 |
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D-H1.1 |
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This paper will begin by defining some of the challenges that we face on the MACSUR project in terms of evaluating model uncertainty and carrying out model integration. I will briefly review what cloud technologies are available, followed with some suggestions about how those cloud technologies can be used in order to contribute to meeting the challenges set out in the first part of the paper.’Month 12’ deliverable for WP1 is a review of the opportunities for using cloud computing to develop the potential for model inter-comparison and interlinking in MACSUR. A challenging aspect of compiling this review is that before an ‘opportunity’ for any kind of model linking/comparison can be identified, a lot of information about the specifics of extant models and workflows must be gathered from each of the three themes (TradeM, CropM, and LiveM).This deliverable must, however, be more than just saying ‘these are the computing tools that we can use to.’. There are a number of different challenges at different levels; a hierarchy of challenges, if you like. For example, in order to get models ‘talking’ to one another, adequate protocols for the transference of data and scaleability will need to be established, and then things like uncertainty analysis for these integrated models will need to be addressed. Further issues exist relating to human behaviour and logistics (e.g. MACSUR is a large project with many members from all over Europe, with substantial distances between many of it’s members).The term “Cloud” is very ambiguous, and Cloud Computing covers a huge range of services, and a number of innovative tools exist which can make international collaborative research more effective. Two examples (already implemented on the MACSUR website) are: a discussion forum (where project members can create topics, make or reply to posts, and upload documents) and a complete surveying platform (to provide an un-restricted and fully featured survey platform for MACSUR members’ information gathering needs.) No Label |
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MA @ admin @ |
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2247 |
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Zimmermann, A.; Witzke, H.-P.; Heckelei, T. |
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Title |
Filling gaps: AgMIP scenario results from CAPRI |
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2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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2 |
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D-T1.4 |
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Climate change impacts on food production, socioeconomic changes (population and income growth in large parts of the world) and biofuel policies affecting demand quantities have risen scientific, political and public interest in long-term forecasts on food security. Whereas first quantitative analyses from global economic models are starting to appear (e.g. (von Lampe et al., under review)), similar studies on smaller regional scales are not yet available. However, acknowledging that climate change affects crop yields differently across scales and regions (e.g. (Reidsma et al., 2007)) and considering the specific political setting given through the Common Agricultural Policy (CAP) in Europe, the MACSUR project focuses on the impact of climate change and socioeconomic changes on European agriculture and its contribution to global food security. We present a Europe-wide analysis of the effect of selected climate and socioeconomic scenarios on food security in terms of food prices using the Common Agricultural Policy Regionalised Impact modelling system (CAPRI). No Label |
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MA @ admin @ |
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2246 |
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Palosuo, T. |
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Data format for model in- and output |
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2013 |
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FACCE MACSUR Reports |
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2 |
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D-C1.3 |
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A common format for model input variables and model output variables has been defined to be distributed to modellers participating in the model inter-comparison and improvement. The aim of common formats is to support the communication between the modellers, those providing empirical data of the experiments and those analysing the simulation results. The input format facilitates the model application in a way that each cropping-system to be modelled will be defined in the same way. Data will be delivered in EXCEL sheets with sub-tables for each block of inputs. Tables are mostly organized in a way that allows export and sequential read-in by the models. The common output format enables effective processing of results estimating model performance indicators. No Label |
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MA @ admin @ |
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2239 |
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Köchy, M.; Zimmermann, A. |
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Workshop on Regional Pilot Studies, 5-7 June 2013, Braunschweig |
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2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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2 |
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R-H1.2.1 |
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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 |
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MA @ admin @ |
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2237 |
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Author |
Kipling, R.; Topp, K.; Don, A. |
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Title |
Appropriate meta-data for modellers |
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Report |
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2014 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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3 |
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D-L1.4.1 |
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Report D-L1.4.1 provided an overview of the data and related resources available online and through EU funded projects, relating to soil organic carbon (SOC), and carbon sequestration in grasslands in particular. Building on D-L1.4.1, the report presented here discusses how meta-data describing these types of data (and experimental data more generally) can best be presented in an online resource useful to grassland modellers requiring data to use in their modelling work. Identifying the useful categories of meta-data is a necessary precursor to providing such a resource, which could facilitate better communication between modelling and experimental research groups, allowing researchers to more efficiently locate relevant data and to link up with other scientists working on similar topics. A survey among grassland modelling teams and an assessment of online meta-data resources was used to produce recommendations about the meta-data categories that should be included in an online resource. The categories are generic, so that the recommendations can be followed in the design of meta-data resources for the more general agricultural modelling community. No Label |
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MA @ admin @ |
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2235 |
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