80 results were found for WA 0821 7001 0763 (MEVVAH) model marmer dinding P. Haruku Kabupaten Maluku Tengah Maluku.

Results:

• 21. norsem_buhcheva

  located events to invert for a new 1D minimum velocity model for both P- and S-waves using VELEST. A depth region of a lower vpvs ratio down to 20 km depth is revealed. We perform relocation of the whole dataset using the new velocity model and the double-difference relocation technique. We look into details of the depth distribution of the events and how the relocation procedure affects /media/norsem/norsem_buhcheva.pdf

• 22. Group5-Stakeholders_involvement

  /EPP 2 Stakeholders analysis 26 August 2011 PM/YZ/EPP 3 Stake h o l d e r s P u b l i c / p r i v at e P o w e r l e v e l (“ n u i s an ce” ca p a c i t y ) O r i e n tat i o n H or s t e n s m uni c ipal i t y ( c o m pe t e n t a u t h ori t y ) P u b l i c S t ron g Go v ernanc e N eighbour mun i c i p ali t y P u b l i c S t ron g Go v ernanc e Poli c y /media/loftslag/Group5-Stakeholders_involvement.pdf

• 23. Publications

  [Extended abstract] Graham, L. P., Andréasson, J., & Carlsson, B. (Submitted). Assessing Climate Change Impacts on Hydrology from an Ensemble of Regional Climate Models, Model Scales and Linking Methods - a Case Study on the Lule River Basin. Climatic Change (PRUDENCE special issue). Harby, A., Finstad, A. G., Fiske, P., Forseth, T., Hvidsten, N. A., Jensen, A. J., Tøfte, L. S., & Ugedal, O. (2006 /climatology/research/ce/publications/

• 24. Lettenmaier_Dennis_CES_2010pdf

  interpolated to VIC scale Regional Bias: spatial example GSM: NCEP Global Spectral Model obs prcp GSM prcp obs temp GSM temp JULY Verification using NCEP Global Spectral Model (GSM) output Process into the daily VIC-scale input time series Force hydrology model to produce streamflow Ohio R. flow @ Metropolis, IL Start with GSM-scale monthly observed T & P (“unbiased”) time series /media/ces/Lettenmaier_Dennis_CES_2010pdf.pdf

• 25. VI_2009_013

  (above) and vertical cross section viewed from south (below). The SIL-velocity model (black) and P23-velocity model (green) are also shown for both P- and S-waves. 17 Figure 5. Selected relocated events with low relative error (within 100 m in latitude and longitude and 300 m in depth). We examined the spatial/temporal evolution of the activity (Figure 6–Figure 8) in order to find changes /media/vedurstofan/utgafa/skyrslur/2009/VI_2009_013.pdf

• 26. Lawrence_Deborah_CES_2010

  and northern areas • Western Norway dominated by uncertainty from HBV and methods for adjusting P, T Uncertainty source with largest magnitude: GCM/RCM EA/DC HBV parameter Uncertainty from flood frequency analysis relative to model uncertainty Viksvatn - 83.2 A1B HadCM3Qref/HIRHAM (25 x 25 km) 'Empirical Adjustment' til 1 x 1 km 100 150 200 250 300 350 400 450 500 550 600 650 700 750 800 850 900 /media/ces/Lawrence_Deborah_CES_2010.pdf

• 27. Climate and Modeling Scenarios

  A. (2010b). 21st century changes in the European climate: uncertainties derived from an ensemble of regional climate model simulations. Tellus, published online. DOI: 10.1111/j.1600-0870.2010.00475. Ólafsson H, & Rögnvaldsson Ó. (2010). Regional and Seasonal Variability in Precipitation Scenarios For Iceland. Hydrology Research, in revision. Peltonen-Sainio, P., Hakala, K., Jauhiainen, L /ces/publications/nr/1680

• 28. VI_2009_006_tt

  –conduit model for subglacial water flow was used to simulate the jökulhlaup. The model was forced with the estimated outflow from the subglacial lake. The simulations were not successful as a realistic subglacial pressure field could not be obtained for a reasonable fit of the jökulhlaup discharge at the glacier terminus. This indicates that the physical basis of the model is insufficient to provide /media/vedurstofan/utgafa/skyrslur/2009/VI_2009_006_tt.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. programme2---PhD-Workshop-preceding-Adaptation-Research-Conference

  C l i m a t e C h a n g e : S y n e r g i e s , C o n f l i c t s , a n d T r a d e - o f f s Economic analysis f extreme weather events and climate change Assessing climate predictions in a multi-model framework d i ss e r t a t i o n t i t l e R u r a l h o u s e h o l d s ’ a d a p ta ti o n to f u tu r e c l i ma te r i s k s T h e s i g n i f i c a n c e o f /media/loftslag/programme2---PhD-Workshop-preceding-Adaptation-Research-Conference.pdf