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Results:

• 21. CES_BioFuels_Flyer_new

  ) and changing climate (CC:CC) 1. Current climate (CU) - varying thinning regimes (0%, 15%, 30%,45%) 2. Changing climate (CC) - varying thinning regimes (0%, 15%, 30%,45%) 3. Current (CU) & changing climate (CC) - current thinning regime 4. Current (CU) & changing climate (CC) - changed thinning regimes C l i m a t e s c e n a r i o s M ea s u r e m en t s o f c l i m a t e p /media/ces/CES_BioFuels_Flyer_new.pdf

• 22. VI_2014_005

  in an overall cold bias, compared with station measurements. To test, whether this is due to the HARMONIE model core or the external surface scheme, biases of 2-m temperature from SURFEX are com- pared with biases of temperature projected from the lowest two model levels to 2 mAGL. It is found that the negative temperature biases are due to shallow inversion layers near the ground, which are introduced /media/vedurstofan/utgafa/skyrslur/2014/VI_2014_005.pdf

• 23. 2010_005_

  which are significantly lower com- pared with similar beginning and end years. Consequently, for the 2004–50 period, the average RCM warming rates of 0.29 K per decade over the ocean, and 0.35 K per decade over the land are somewhat larger than for the reduced IPCC ensemble mean. Additionally, the tabulated values of SAT differences between the 1961–90 control period and either the 2021–50 /media/ces/2010_005_.pdf

• 24. Outline_for_the_case_Road_maintenance_in_a_changing_climate

  course – Adaptive management in relation to climate change – Copenhagen 21-26/8/2011 …………………………………………………………………………………………………………………………………………………………………… 6 Figure 1. Flow chart summarizing information and decision flows of an adaptive management inspired adaptation planning cycle for road transport (at national strategic / tactical level) M a n d a t e f r o m g o v e r n m e n t + p r /media/loftslag/Outline_for_the_case_Road_maintenance_in_a_changing_climate.pdf

• 25. VI_2020_005

  /media/vedurstofan-utgafa-2020/VI_2020_005.pdf

• 26. VI_2015_009

  by rescaling a dimensionless regional flood frequency distribution or growth curve, qR(D;T ), com- mon to all sites of the homogeneous region, with the so-called index flood, µi(D), of the target site: bQi(D;T ) = µi(D)qR(D;T ); (1) where bQi(D;T ) is the estimated flood quantile, i.e. the T -year flood peak discharge averaged over duration D, at site i. The regional growth curve, qR(D;T /media/vedurstofan/utgafa/skyrslur/2015/VI_2015_009.pdf

• 27. Observations - Reykjavik area - Overview stations

  | Seltjarnarnes - Suðurnes | Skrauthólar | Straumsvík Mon 1.05 14 GMT Arnarnesvegur 5.9° E 5 Max wind : 5 / 8 Garðabær - Urriðaholt 7.5° ENE 2 Max wind : 4 / 7Precip.: 0.0 mm / 1 h Geldinganes 8.3° E 5 Max wind : 5 / 8 Hólmsheiði 6.9° E 6 Max wind : 6 / 10Precip.: 0.0 mm / 1 h Kjalarnes 6.2° WSW 2 Max wind : 4 / 7Road temp. : 16.7° Korpa 7.7° E 5 Max /m/observations/areas

• 28. 2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343

  ORIGINAL ARTICLE The role of uncertainty in climate change adaptation strategies—A Danish water management example J. C. Refsgaard & K. Arnbjerg-Nielsen & M. Drews & K. Halsnæs & E. Jeppesen & H. Madsen & A. Markandya & J. E. Olesen & J. R. Porter & J. H. Christensen Received: 10 November 2011 /Accepted: 4 February 2012 # The Author(s) 2012. This article is published with open access /media/loftslag/2012-Refsgaard_etal-uncertainty_climate-change-adaptation-MITI343.pdf

• 29. esa_flyer_new

  EA Analyse A/S and Optensys Energianalys will forecast energy system variables, while SINTEF Energy Research will make assumptions for the energy system in different cases, include new inputs in the EMPS model and carry out simulations. Cl i ma t e Sc e nar i os G ro u p R i s ø St o c h as t i c v a r i a b l e s Clima t e s c e n a r i o NV E S M H I FE I N o r w a y S w e d e n F inla n /media/ces/esa_flyer_new.pdf

• 30. 2013_001_Nawri_et_al

  is then proportional to the mean cube of wind speed, E = 1 2 r¯ A3G(1+3=k) ; (3) where r¯ is average air density. Wind power density only depends on atmospheric variables, and is therefore most appropriate for turbine-independent evaluations of wind energy potential, such as for wind atlases. To be able to determine the actual power or energy, which can be extracted from the atmosphere, specific information /media/vedurstofan/utgafa/skyrslur/2013/2013_001_Nawri_et_al.pdf