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MNFT : Robust detection of slow nonstationarity in LIGO Science data

MNFT : Robust detection of slow nonstationarity in LIGO Science data. Soma Mukherjee Max Planck Institut fuer Gravitationsphysik Germany. LSC Meeting, Livingston, LA, March 17-20, 2003

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319 views • 19 slides

Case stud y based on one dimensional model with Kain-Fritsch convection parameterization scheme

Case stud y based on one dimensional model with Kain-Fritsch convection parameterization scheme Paulius Jalinskas Tartu, Estonia, 24-26 January 2005. LITHUANIAN HYDROMETEOROGICAL SERVICE under the Ministry of Environment VILNIUS UNIVERSITY Division of Hydrology & Climatology. Downdraft effect.

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227 views • 11 slides

Add weather file (/Training/NamSVMod/rain_Phen.txd)

Add weather file (/Training/NamSVMod/rain_Phen.txd) Edit weather data interpolation change 0.002-> 0 Change initial state (/Training/NamSVMod/ns_training_init.vms). Change pet calculation method to pan evaporation Add timeseries point (Nam Oon Dam)

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274 views • 10 slides

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MNFT : Robust detection of slow nonstationarity in LIGO Science data

Case stud y based on one dimensional model with Kain-Fritsch convection parameterization scheme

Add weather file (/Training/NamSVMod/rain_Phen.txd)