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  • 21. vanRoosmalen_etal-2009-WRR_2007WR006760

    and Irrigationa Scenario Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Current 101 85 59 13 6 4 1 6 39 79 84 97 A2 145 132 73 10 10 7 6 8 4 75 92 123 B2 137 119 75 16 6 6 6 5 21 74 110 141 aValues are in millimeters. 10 of 18 W00A15 VAN ROOSMALEN ET AL.: CLIMATE AND LAND USE CHANGE W00A15 time and larger area where groundwater levels rise above the drain levels. Table 6 shows the mean discharges /media/loftslag/vanRoosmalen_etal-2009-WRR_2007WR006760.pdf
  • 22. 2010_005_

    Century control runs, as well as 21st Century forecast runs, submitted by various institutions to the Intergovernmental Panel on Climate Change (IPCC) for their Forth 11 Table 1. General circulation and regional climate models that were considered in this study. Model Version Model Name, Institute BCCR BCM 2.0 Bergen Climate Model, Bjerknes Centre for Climate Research, Bergen, Norway CCCMA CGCM 3.1 /media/ces/2010_005_.pdf
  • 23. 2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343

    e in relatio n to climat echang eadapt ation .X ,X X ,XX X is a ge n era lguid eo n th e relativ e imp ortanc e leve lo fth e sourc es , alth oug h it mus tb e em phasise d tha tth e imp ortanc e o fth e indi vidua lsou rce s o fun certaint y is co n tex tspe cifi c St ep si n cl im at e ch an ge ad ap tat io n an al ys es (ch ain in u n ce rta in ty ca sc ad e, Fi g. 2) So ur ce s o fu n ce rta /media/loftslag/2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343.pdf
  • 24. Kok_et_al._TFSC_published_2011

    ]. There is ample experience with backcasting, and consequently much has been said about the underlying principles (e.g. [20]), the methodological 838 K. Kok et al. / Technological Forecasting & Social Change 78 (2011) 835851 Author's personal copy framework (e.g. [8,30–32]), and practical applications (e.g. [33–35]). Also the combination between backcasting and other types of scenarios has been /media/loftslag/Kok_et_al._TFSC_published_2011.pdf
  • 25. Refsgaard_etal-2007-Uncertainty-EMS

    The advantage of Monte Carlo analysis is its general appli- cability and that it does not impose many assumptions on prob- ability distributions and correlations and that it can be linked to any model code. The key limitation is the large run times for computationally intensive models and the huge amount of outputs that are not always straightforward to analyse. 4.8. Multiple model simulation Multiple model /media/loftslag/Refsgaard_etal-2007-Uncertainty-EMS.pdf
  • 26. 2010_003rs

    ................ 91 Figure B.5. Rake distribution for mapped faults/clusters in boxes E and F, Brennisteinsfjöll-Bláfjöll. ................................................................................. 92 Figure B.6. Rake distribution for mapped faults/clusters in box G, Ölfus. ......................... 93 Figure B.7. Rake distribution for mapped faults/clusters in box H, Hengill, active between January /media/vedurstofan/utgafa/skyrslur/2010/2010_003rs.pdf
  • 27. ces-oslo2010_proceedings

    change over the North Atlantic and in some simulations also for Iceland. In all areas, including the North Atlantic and Iceland, a clear climate change signal compared to the spread between the simulations is seen. The standard deviation calculated from 17 of the simulations are less than 1°C in all areas apart from Iceland where it reaches between 1 and 2°C and in parts of the Barents Sea where /media/ces/ces-oslo2010_proceedings.pdf
  • 28. VI_2009_006_tt

    lake in a volcanic caldera in the interior of the Vatnajökull ice cap (Björns- son, 1988). Jökulhlaups from Grímsvötn have been known since at least the fourteenth century (Þórarinsson, 1939, 1974). In the beginning of the twentieth century there were about ten years between outbursts but the floods diminished with time and became more frequent. After a catastrophic, rapidly rising flood caused /media/vedurstofan/utgafa/skyrslur/2009/VI_2009_006_tt.pdf
  • 29. D2.3_CES_Prob_fcsts_GCMs_and_RCMs

    Institution BCCR-BCM2.0 Bjerknes Centre for Climate Research, Norway CGCM3.1 (T47) Canadian Centre for Climate Modelling and Analysis CGCM3.1 (T63) same as previous CNRM-CM3 Météo-France CSIRO-MK3.0 CSIRO Atmospheric Research, Australia ECHAM5/MPI-OM Max Planck Institute (MPI) for Meteorology, Germany ECHO-G University of Bonn and Model & Data Group, Germany; Korean Meteorological Agency GFDL /media/ces/D2.3_CES_Prob_fcsts_GCMs_and_RCMs.pdf
  • 30. Gudmundsson-etal-2011-PR-7282-26519-1-PB

    are currently melting at a fast rate. Over recent decades, annual mass balance field observations on the three largest ice caps in Iceland* Langjo¨kull (ca. 900 km2), Hofsjo¨kull (ca. 890 km2) and Vatnajo¨kull (ca. 8100 km2)*show a declining specific mass balance from about 0 m yr1 w. eq. on average from 1980 to 1994 to 1 to 1.3 m yr1 w. eq. on average after 1995 (Bjo¨rnsson et al. 2002 /media/ces/Gudmundsson-etal-2011-PR-7282-26519-1-PB.pdf

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