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Ruiz-Ramos, M.; Ferrise, R.; Rodríguez, A.; Lorite, I.J.; Pirttioja, N.; Fronzek, S.; Palosuo, T.; Carter, T.R.; Bindi, M.; Höhn, J.G.; Baranowski, P.; Buis, S.; Cammarano, D.; Claas, N.; Deligios, P.; Havlinka, P.; Hoffmann, H.; Jurecka, F.; Kersebaum, K.C.; Krzyszczak, J.; Lana, M.; Mechiche-Alami, A.; Minet, J.; Montesino, M.; Porter, J.; Recio, J.; Ruget, F.; Sanz, A.; Steinmetz, Z.; Stratonovitch, P.; Supit, I.; Tao, F.; Trnka, M.; Ventrella, D.; de Wit, A.; Rötter, R.P. |
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Title |
Adaptation response surfaces from an ensemble of wheat projections under climate change in Europe |
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2016 |
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Vienna (Austria) |
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Geophysical Research Abstracts |
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European GeoSciences Union (EGU), General Assembly 2016, 2016-04-17 to 2016-04-22, Vienna, Austria |
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MA @ admin @ |
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4887 |
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Piccard, I.; Gobin, A.; Curnel, Y.; Goffart, J.-P.; Planchon, V.; Wellens, J.; Tychon, B.; Cattoor, N.; Cools, R. |
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Title |
iPot: Improved potato monitoring in Belgium using remote sensing and crop growth modelling |
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2016 |
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Vienna (Austria) |
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European GeoSciences Union (EGU), General Assembly 2016 |
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18 |
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Geophysical Research Abstracts, 2016-04-17 to 2016-04-22, Vienna |
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MA @ admin @ |
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4890 |
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Pulina, A.; Bellocchi, G.; Seddaiu, G.; Roggero, P.P. |
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Scenario analysis of alternative management options on the forage production and greenhouse gas emissions in Mediterranean grasslands |
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2016 |
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116 |
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263-266 |
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LiveM; MACSUR_ACK |
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TI @ martin.koechy @ |
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2940 |
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Heinschink, K.; Lembacher, F.; Sinabell, F.; Trible, C. |
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Title |
Crop production costs in Austria: Comparison of simulated results and farm observations |
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Conference Article |
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2016 |
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Jahrbuch der ÖGA |
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26 |
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33-34 |
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26. Jahrestagung der Österreichischen Gesellschaft für Agrarökonomie, 2016-09-15 to 2016-09-16, Vienna, Austria |
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MA @ admin @ |
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5025 |
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Author |
Semenov, M.A.; Stratonovitch, P. |
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Title |
Local-scale CMIP5-based climate scenarios for MACSUR2 |
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Report |
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2016 |
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FACCE MACSUR Reports |
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8 |
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C2.2-D |
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CropM |
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Climate sensitivity of GCMs was used to select 5 GCMs from the CMIP5 ensemble for impact studies in MACSUR2. Selected GCMs for MACSUR2 are EC-EARTH (7), GFDL-CM3 (8) HadGEM2-ES (10), MIROC5 (13), and MPI-ESM-MR (15). These GCMs are evenly distributed among CMIP5 (Fig 1) and should capture, in principal, climate uncertainty of the CMIP5 ensemble. Using 5 GCMs will enable us to assess uncertainties in impacts related to uncertainty in climate projections. The selection of GCMs in MACSUR2 has a good overlap with selections of GCMs used in CORDEX and AgMIP projects. We used the LARS-WG generator to construct local-scale CMIP5-based climate scenarios for Europe (Semenov & Stratonovitch, 2015). Fifteen sites were selected in Europe for MACSUR2. For each site and each selected GCM, 100 yrs climate daily data were generated by LARS-WG for RCP4.5 and RCP8.5 emission scenarios and for baseline and 3 future periods: near-term (2021-2040), mid-term (2041-2060) and long-term (2081-2100). |
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MA @ admin @ |
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2270 |
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