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Results:

• 21. GA_2009_91A_4_Andreassen

  (alb: AWS) MODELLING LONG-TERM SUMMER AND WINTER BALANCES ? The authors 2009 Journal compilation ? 2009 Swedish Society for Anthropology and Geography 241 ed temperatures relative to –20°C to account for de-cay of snow albedo at temperatures below the melt-ing point, following a study by Winther (1993). Wetested both approaches, and chose to use –5°C asthe minimum for the accumulated temperature /media/ces/GA_2009_91A_4_Andreassen.pdf

• 22. 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

• 23. Paper-Olafur-Rognvaldsson_91

  the opportunity to model river runoff and glacier mass balance both in the current climate and also in a hypothetical future climate based on the CE /VO climate change scenarios. The climate of Iceland is largely governed by the interaction of orography and extra-tropical cyclones, both of which can be described quite accurately by present day atmospheric models. As a result, dynamical downscaling /media/ces/Paper-Olafur-Rognvaldsson_91.pdf

• 24. CES_D2.4_VMGO

  the territories of European Russia (ER) and Europe (EU) an ensemble of 9 CMIP3 [1] comprehensive global (coupled atmosphere-ocean) climate models is used in this assessment (Table 1); so called A2 scenario is considered. Both A2 and A1B scenarios are similar in terms of resulting global mean warming up to the mid-21st century IPCC [2]. The projected changes in ER and EU in many cases continue /media/ces/CES_D2.4_VMGO.pdf

• 25. 2013_001_Nawri_et_al

  and a pressure of 1013.25 hPa. In the case of Iceland, the climate deviates significantly from these standard atmospheric conditions. Additionally, terrain elevation varies considerably across the island. Therefore, seasonal and annual differences in air density from the standard value, as well as spatial variability, need to be taken into account. Approximate air density can be calculated by assuming /media/vedurstofan/utgafa/skyrslur/2013/2013_001_Nawri_et_al.pdf

• 26. 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

• 27. vonKorff_etal-2010

  played a role in this first phase as the author tables on decision analysis show. In summary, the comparison resulted in the reconstruction of 10 steps on which there appears to be considerable agreement among the five guides. 1. DA 1: Assemble a team for decision analysis as part of the participation design. Its members should belong to the lead agency, e.g., the water board, but can also /media/loftslag/vonKorff_etal-2010.pdf

• 28. ces-glacier-scaling-memo2009-01

  difference between the band and the maximum altitude of the glaciers ymax Dgi = ri gi ; ri = DSa2 (ymax yi) nj=1(ymax y j)g j : (12) The second step is carried out after the lowest glaciated elevation bands have been altered by the reduction in the glaciated area at the lowest altitudes. This procedure to distribute the reduction in glaciated area with altitude is clearly quite crude /media/ces/ces-glacier-scaling-memo2009-01.pdf

• 29. Huntjens_etal-2010-Climate-change-adaptation-Reg_Env_Change

  can be found in Huntjens et al. (2007), Chapter 4 of NeWater Deliverable 1.7.9a (http://www.newater.info). Climate change adaptation in European river basins 265 123 interactions, by private and public actors, to achieve adaptation and to enhance the capacity of processes, institutional arrangements and actors to adapt to future environmental changes (Huitema et al. 2009). Adaptive governance /media/loftslag/Huntjens_etal-2010-Climate-change-adaptation-Reg_Env_Change.pdf

• 30. 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