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Results:

• 31. 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

• 32. 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

• 33. Daniell_etal-2010

  and evaluating impacts (see also Swallow et al. 2001, van Ast and Boot 2003). METHODS AND DATA This article is based on empirical data that originated from the analysis of the participatory exercise in the Dhuenn basin. The strong involvement of researchers from two research projects (NeWater[1] and ACER[2]) linked by a joint case study led to the variety of sources available for exploration, including /media/loftslag/Daniell_etal-2010.pdf

• 34. VI_2014_005

  lines). Additionally, the aver- age profiles for offshore distances to the coast of up to 30 km are shown by the black lines. For temperature, the dashed lines indicate linear projection from the two lowest model levels to 2 m above ground. A comparison of monthly averages of simulated 2-m temperature with station measurements, both for SURFEX and projected values, is shown in Figure 8. On average /media/vedurstofan/utgafa/skyrslur/2014/VI_2014_005.pdf

• 35. Henriksen_Barlebo-2008-AWM_BBN-Journ_Env_Management

  the body of knowledge in any given area by mapping out cause-and-effect relationships among key variables and encoding them with numbers that represent the extent to which one variable is likely to affect another (Jensen, 2002). Factors, associations and probabilities can be adjusted and validated and BNs are powerful for integrating data and knowledge from different sources and domains, e.g /media/loftslag/Henriksen_Barlebo-2008-AWM_BBN-Journ_Env_Management.pdf

• 36. VI_2017_009

  we take the corresponding data from the CMIP5 project. Table 1. All GCMs and RCMs used in this study. If a model is available for any of the domains Arctic-44, EURO-44, or EURO-11, it is marked with a v, but with an x if it is unavailable. Model name Type EURO-11 EURO-44 Arctic-44 CCCma-CanESM2 GCM x v v COSMO-CLM4-8-17 RCM v v x CNRM-CERFACS-CNRM-CM5 GCM v v x IHCEC-EC-Earth GCM v v v /media/vedurstofan-utgafa-2017/VI_2017_009.pdf

• 37. VI_2020_005

  and CNES, n.d.; National Center for Atmospheric Research Staff, 2016; Quante and Colijn, 2016). Now, additional altimeters at different orbits perform slightly less accurate measurements up to 82 N and S (Rhein et al., 2013). These records are used to estimate sea surface changes and calculate global mean sea level, a temporal average sea level averaged over the oceans (Church, Clark, et al., 2013 /media/vedurstofan-utgafa-2020/VI_2020_005.pdf

• 38. Kok_and_Veldkamp_editorial_ES-2011-4160

  agreement on use of terminology. Third, all scoping papers stress that there is no silver bullet solution, with a different view on both scale and governance being appropriate depending on the specific case. Buizer et al. (2011) are strongest on this view by presenting and discussing a framework. Termeer et al. (2010) confirm that there is no best governance approach, drawing an analogue /media/loftslag/Kok_and_Veldkamp_editorial_ES-2011-4160.pdf

• 39. Refsgaard_2-uncertainty

  Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec ARPEGE-CNRM ARPEGE-DMI BCM-DMI BCM-SMHI ECHAM-DMI ECHAM-ICPT ECHAM-KNMI ECHAM-SMHI Lauren P Seaby PhD project www.hyacints.dk Preliminary results Data from 8 climate models in the ENSEMBLES project (A1B) Future climate Down scaling Bias correction Global 100-250 km Scale Regional 10-25 km Hydrological 50-500 m Present climate Climate change /media/loftslag/Refsgaard_2-uncertainty.pdf

• 40. Adalgeirsdottir-etal-tc-5-961-2011

  Korona et al., 2009) and 2010 (airborne LiDAR in autumn). The Cryosphere, 5, 961–975, 2011 www.the-cryosphere.net/5/961/2011/ G. Aðalgeirsdóttir et al.: 20th and 21st century evolution of Hoffellsjökull glacier 963 Fig. 2. (A) Measured bedrock topography of Hoffellsjökull (2001). Blue colours indicate elevation below sea level. (B–E) Surface to- pography at different times, showing retreat /media/ces/Adalgeirsdottir-etal-tc-5-961-2011.pdf