79 results were found for JZMOR contro la truffa: strategie efficaci per proteggere i tuoi fondi.

Results:

• 41. 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

• 42. Awards and press

  wanted to drop you guys a line and say thank you. I was in Iceland for 16 days in September surfing, and your web site was so crucial to the trip on knowing when to move and where to go. Keep up the great work. Thanks again.Preparing a visit to Iceland Elizabeth wrote in August 2015: "I just wanted to thank you so much for your wonderful website, which is truly one of the most comprehensive /about-imo/the-web/awards_and_press/

• 43. VI_2015_005

  time-series of to- tal accumulation from the start time of each successive forecast run. To reduce spin-up effects, the first 12 forecast hours are ignored. Six-hourly precipitation on day D0 is then calculated by differentiating the forecast run starting at 12 UTC on day D0 1. Units of 6-hourly precipitation are kilograms per square metre. This is approximately equivalent to millimetres of liquid /media/vedurstofan/utgafa/skyrslur/2015/VI_2015_005.pdf

• 44. TietavainenHanna_CES_2010

  the observed data sets are smaller in SW than in NE • MMM overestimates precipitation, but is closer to observations in SW than NE barb2right Better observational coverage in SW SW NE p r e c i p i t a t i o n s u m ( m m ) CES Conference, Oslo 31.5.-2.6.2010 SWNE • Precipitation trends (mm / 10 yr) in 1961-2000 according to observations and model simulations (MMM) • Including the range /media/ces/TietavainenHanna_CES_2010.pdf

• 45. Alam_Ashraful_CES_2010

  FOREST BIOMASS FOR ENERGY PRODUCTION – POTENTIALS, MANAGEMENT AND RISKS UNDER CLIMATE CHANGE Ashraful Alam, Antti Kilpeläinen, Seppo Kellomäki School of Forest Sciences, University of Eastern Finland, Joensuu F t Cli t d R bl E I t Ri k d Ad t tiu ure Cl ma e an enewa e nergy – mpac s, s s an ap a on Oslo, Norway 2 June, 2010 Contents • Forestry in Finland • Challenges • Objectives /media/ces/Alam_Ashraful_CES_2010.pdf

• 46. i-frame services

  i-frame services i-frame services Other web-sites can be configured to display information automatically from vedur.is /about-imo/the-web/iframes/

• 47. Cradden_Lucy_CES_2010

  2050s 2080s C h a n g e i n r a t i n g ( % ) 10% 50% 90% C h a n g e i n r a t i n g ( % ) C h a n g e i n r a t i n g ( % ) Each bar shows range over whole UK spatial area June 2010 13 Is the impact similar over the whole UK? • Changes in the summer minimum rating, i.e. worst-case conditions – max temperature: Rating at baseline period 1961 /media/ces/Cradden_Lucy_CES_2010.pdf

• 48. Lorenzoni_Pidgeon_2006

  from various datasets and research studies across nations, supplemented with in-depth data collected in the UK. These findings are not always directly comparable, as this depends on (i) the nature of the issue being investigated and (ii) practical/technical characteristics of data collection. Firstly, climate change is a very complex, per- vasive and uncertain phenomenon, generally difficult /media/loftslag/Lorenzoni_Pidgeon_2006.pdf

• 49. ces-glacier-scaling-memo2009-01

  glacier inventories, aerial photographs and expert judgement must be used to complete the curve down to the origin of the figure. The volume distribution may then be computed by transforming the glacier area on the y-axis of the area distribution curve in Figure 3 to volume using Equation (5) resulting in V (vn) = n i=1 csgi ; (6) in case the cumulative area distribution function V (v /media/ces/ces-glacier-scaling-memo2009-01.pdf

• 50. Dyrrdal_Anita_CES_2010

  Permanent snow cover Snow depth Aug Jun Maximum snow depth Accumulative winter precipitation Number of snow days (snow depth > 0) Snow season duration Introduction Data & Methods Results Norwegian Meteorological Institute met.no Simulated temperature & precipitation Observed snow depth Time series • Period I: 1931-60 – 55 stations • Period II: 1961-90 – 298 stations • Period III: 1979 /media/ces/Dyrrdal_Anita_CES_2010.pdf