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The purpose of this paper is to present a methodology for
estimating space-time stochastic properties of local climatic
factors reflecting global climate change. Specifically, daily
precipitation amount and daily mean temperature are considered and
illustrated with application to the state of Nebraska, U. S. A.
Furthermore, a drought index with and without global climate change
is examined. The magnitude and consequences of regional response to
anticipated climatic changes are uncertain (Houghton et al., 1990).
Typical questions to be answered are: can time series of
hydrological events or 10cal climatic variables such as daily
temperature be conditioned in scenarios of future climate change
and if so, how can this be utilized ? Can extreme historical
drought events be reproduced by a stochastic hydroc1imatological
model ? Can such a model be used with General Circu1ation Model
(GCM) outputs to evaluate the regional/local effects of climate
change scenarios? The approach presented in this paper is an
extension of the usual analysis of regional hydrometeorological
impacts of climate change: we propose to examine time series of GCM
produced daily atmospheric circulation patterns (CP), thought to be
relatively accurate GCM output to estimate local climatic factors.
The paper is organized as follows. First, daily CPs are classified
and analyzed statistically, first for historical and then for GCM
produced data. Next, the height of the 500 hPa pressure field is
introduced as an additional physically relevant variable
influencing local climatic factors within each CP type."
The purpose of this paper is to present a methodology for
estimating space-time stochastic properties of local climatic
factors reflecting global climate change. Specifically, daily
precipitation amount and daily mean temperature are considered and
illustrated with application to the state of Nebraska, U. S. A.
Furthermore, a drought index with and without global climate change
is examined. The magnitude and consequences of regional response to
anticipated climatic changes are uncertain (Houghton et al., 1990).
Typical questions to be answered are: can time series of
hydrological events or 10cal climatic variables such as daily
temperature be conditioned in scenarios of future climate change
and if so, how can this be utilized ? Can extreme historical
drought events be reproduced by a stochastic hydroc1imatological
model ? Can such a model be used with General Circu1ation Model
(GCM) outputs to evaluate the regional/local effects of climate
change scenarios? The approach presented in this paper is an
extension of the usual analysis of regional hydrometeorological
impacts of climate change: we propose to examine time series of GCM
produced daily atmospheric circulation patterns (CP), thought to be
relatively accurate GCM output to estimate local climatic factors.
The paper is organized as follows. First, daily CPs are classified
and analyzed statistically, first for historical and then for GCM
produced data. Next, the height of the 500 hPa pressure field is
introduced as an additional physically relevant variable
influencing local climatic factors within each CP type."
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