Geoscience Reference
In-Depth Information
In this study, the feasibility of two popular downscaling methods, namely
the statistical downscaling model (SDSM) and the stochastic weather gen-
erator (LARS-WG) model, were assessed using daily precipitation and tem-
perature extreme data available in the southern Quebec region in Canada
for the 1961-1990 period. In general, it was found that both models were
able to describe accurately the basic statistical properties of daily tem-
perature extremes at local sites. However, none of these models appears
to be able to simulate well the statistical properties of daily precipitation
processes.
2. Evaluation of Statistical Downscaling Methods
As mentioned above, because of various practical advantages of SD methods
over DD procedures, two popular SD techniques based on the SDSM
6
and
the LARS-WG
7
model have been selected in this study for testing their
feasibility in the simulation of daily precipitation and extreme temperature
processes for the Montreal region in Quebec, Canada.
The SDSM is best described as a hybrid of the stochastic weather
generator and regression-based methods. The model permits the spatial
downscaling of daily predictor-predictand relationships using multiple lin-
ear regression techniques and generates “synthetic predictand” that repre-
sents the generated local weather. Further details of SDSM are provided by
Wilby
et al
.
6
The LARS-WG model
7
produces synthetic daily time series of
maximum and minimum temperatures, precipitation, and solar radiation.
The model uses input observed daily weather for a given site to determine
the parameters of specifying probability distributions for weather variables
as well as the correlations between these variables. As mentioned above,
LARS-WG utilizes semi-empirical distributions for the lengths of wet and
dry day series, daily precipitation and daily solar radiation. The generation
procedure to produce synthetic weather data is then based on selecting
values from the appropriate distributions using a pseudo-random number
generator.
2.1.
Data
Two data sets are used: station data and NCEP re-analysis data. Sta-
tion data include observed daily precipitation, daily maximum temperature
(
t
max
), and daily minimum temperature (
t
min
) for the period 1961-1990
recorded at four stations in the greater region of Montreal (Quebec,
