List:
I am interested in doing some geostatistical simulations using GSTAT and
have some theoretical questions.
I am attempting to model hourly rainfall accumulations over a large
region, so there will almost always be zero rainfall somewhere. I can
generate random fields of precipitation, using both conditional and
unconditional simulations using GSTAT. However, I get negative values as
well as (mostly) positive values. The simulated fields otherwise look
very reasonable. The data I used (and must use) to estimate my variogram
has zero values where no rainfall occurs. What does this suggest to you?
I am using gaussian simulation.
I have seen some references to more exotic geostatistcal simulation
methods using bayesian or some other methods. Is this what I need?
From reading the literature, I have seen that some researchers have
successfully used indicator kriging and simulation. With GSTAT I can
successfully do simulations using 'method : is' rather than 'method :
gs', how using GSTAT do I model a continuous (non-binary) variable
using the GSTAT syntax?
Regards to all,
Tom
--
Thomas E Adams
National Weather Service
Ohio River Forecast Center
1901 South State Route 134
Wilmington, OH 45177
EMAIL: [EMAIL PROTECTED]
VOICE: 937-383-0528
FAX: 937-383-0033
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