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  • 21. raisanen_ruosteenoja_CES_D2.2

    ............................................................................................................ 4 3. Best estimates of temperature and precipitation change................................................ 7 4. How certainly will temperature and precipitation increase? ....................................... 10 5. Uncertainty ranges and quantiles of temperature and precipitation change .............. 12 6. Hindcast verification of the resampling ensemble /media/ces/raisanen_ruosteenoja_CES_D2.2.pdf
  • 22. Journal_of_Hydrology_Veijalainen_etal

    at 67 sites: (a) 100-year floods with the Gumbel distribution and (b) average discharge. −6 0 −4 0 −2 0 0 20 40 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Scenario number Change in 100a Flood (% ) Fig. 5. Box plot (median, 25 and 75 percentiles, average [diamond], max and min) of changes in 100-year floods in 2070–2099 at the 67 sites with different scenarios. Numbering of the scenarios /media/ces/Journal_of_Hydrology_Veijalainen_etal.pdf
  • 23. CES_D2.4_task1

    about 20-25% in 2010 to about 50% in 2050. Perhaps surprisingly, a particularly high probability is found in Iceland, most likely as a result of the small 12 interannual variability there. As expected, the probability of very warn years rises even faster than that of warm months – in northern Europe from typically 30-40% in 2010 to about 60- 80% in 2030 and to 85-95% or even more in 2050 /media/ces/CES_D2.4_task1.pdf
  • 24. Lorenzoni_Pidgeon_2006

    affecting climate change; increased skin cancers resulting from climate change), while mitigation measures proposed by the interviewees typically focused on general pollution control. These researchers (Read et al., 1994; Kempton, 1997) point out that not all misconceptions matter for 80 I. LORENZONI AND N. F. PIDGEON communicating risks to lay publics. Rather, policy makers should concentrate upon /media/loftslag/Lorenzoni_Pidgeon_2006.pdf
  • 25. Reykholt-abstracts

    ............................................................................................................... 33 Lidar measurements of the cryosphere Reykholt, Iceland, June 20–21, 2013 3 CryoSat-2 Arctic sea-ice freeboard and thickness data product and its validation Ciaran Robb, Ian Willis and Neil Arnold ............................................................................ 34 Using airborne remote /media/vatnafar/joklar/Reykholt-abstracts.pdf
  • 26. The weather in Iceland 2014

    prec.days >=1.0 mm Reykjavík 963.1 121 112 37.6 223 160 Stafholtsey 829.4 97 28.0 182 144 Bláfeldur 1460.7 97 32.0 272 195 Stykkishólmur 678.8 96 87 20.0 218 136 Litla-Ávík 835.0 96 34.1 267 164 Bergstaðir 458.2 98 22.6 177 92 Sauðanesviti 1017.5 115 28.2 239 158 Akureyri 743.7 152 133 23.0 225 133 Grímsstaðir 514.8 /about-imo/news/nr/3082
  • 27. ved-eng-2014

    24-hr mm prec.days >=1.0 mm Reykjavík 963.1 121 112 37.6 223 160 Stafholtsey 829.4 97 28.0 182 144 Bláfeldur 1460.7 97 32.0 272 195 Stykkishólmur 678.8 96 87 20.0 218 136 Litla-Ávík 835.0 96 34.1 267 164 Bergstaðir 458.2 98 22.6 177 92 Sauðanesviti 1017.5 115 28.2 239 158 Akureyri 743.7 152 133 23.0 225 133 Grímsstaðir 514.8 146 128 22.5 228 133 Miðfjarðarnes 765.0 120 36.4 233 /media/vedurstofan/utgafa/skylduskil/ved-eng-2014.pdf
  • 28. VI_2019_009

    a71 a71 a71 a71 a71 a71 a71 a71 0 10 20 21 23 24 30 51 52 53 61 62 64 67 71 72 73 81 85 87 1 2 3 10 11 14 15 16 20 21 22 23 25 26 36 40 41 46 50 51 52 53 54 58 60 61 62 63 64 65 68 70 71 72 73 74 80 81 83 84 85 86 87 92 Present weather (Manual) Present weather ( Automatic ) Number of records a71 a71 a71 a71 5 10 15 20 5 10 15 20 Number of records Figure 16. Automatic records as a function of manual /media/vedurstofan-utgafa-2019/VI_2019_009.pdf
  • 29. VI_Arsskyrsla_2018_vef

    Nesjum 0-5 5-10 10 15 20-15 2008-2018 1979-1989 Dæmi um ólíkt rennslismynstur. 100 90 80 70 60 50 40 30 20 10 0 Júní mánaðarmeðaltal Ársmeðaltal Rennsli m 3 /s Sigurvegarinn í getraun Veðurstofunnar á Vísindavöku Rannís hlaut heimsókn á Veðurstofuna að launum. Salka Elín Sæþórsdóttir ásamt vinum sínum, Ými og Bjarti. Með þeim á myndinni er Ragnar Heiðar Þrastarson, fagstjóri landfræðilegra /media/vedurstofan/utgafa/arsskyrslur/VI_Arsskyrsla_2018_vef.pdf
  • 30. Huntjens_etal-2010-Climate-change-adaptation-Reg_Env_Change

    part of Upper Tisza. Based on data from EM-DAT: The OFDA/CRED International Disaster Database 2008 1 For a disaster to be entered into the Emergency Events Database (EM-DAT) at least one of the following criteria must be fulfilled: (1) Ten or more people reported killed; (2) Hundred people reported affected; (3) Declaration of a state of emergency; (4) Call for international assistance (From: EM /media/loftslag/Huntjens_etal-2010-Climate-change-adaptation-Reg_Env_Change.pdf

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