Geoscience Reference
In-Depth Information
ON THE LINKAGE OF LARGE-SCALE CLIMATE
VARIABILITY WITH LOCAL CHARACTERISTICS OF
DAILY PRECIPITATION AND TEMPERATURE
EXTREMES: AN EVALUATION OF STATISTICAL
DOWNSCALING METHODS
VAN-THANH-VAN NGUYEN
∗,§
, TAN-DANH NGUYEN
∗
and PHILIPPE GACHON
†
∗
Department of Civil Engineering and Applied Mechanics
McGill University, Montreal, Quebec, Canada H3A 2K6
§
van.tv.nguyen@mcgill.ca
†
Environment Canada and OURANOS Consortium
Montreal, Quebec, Canada
This paper provides an overview of various downscaling methods that could be
used for assessing the potential impacts of climate change and variability on
hydrological regime. In general, two broad categories of the downscaling tech-
niques currently exist: dynamical downscaling (DD) and statistical downscaling
(SD) procedures. While neither DD methods nor SD methods were found to
outperform the other, the SD techniques have several practical advantages.
Hence, two popular SD methods based on the statistical downscaling model
(SDSM) and the stochastic weather generator (LARS-WG) were selected for
testing their feasibility in the simulation of two fundamental hydrologic pro-
cesses: daily precipitation time series and daily temperature extremes. Results
of the evaluation using available climate data in the Montreal region (Quebec,
Canada) have indicated that both models were able to describe accurately the
basic statistical properties of daily maximum and minimum temperatures at
local sites. However, none of these models appears to be able to simulate well
the statistical properties of the daily precipitation processes.
1. Introduction
General circulation models (GCMs) have been recognized to be able to
represent reasonably well the main features of the global atmospheric cir-
culation, but these models so far could not reproduce well details of regional
climate conditions at temporal and spatial scales of relevance to hydrologi-
cal impact studies. Hence, there is a need to develop tools for downscaling
GCM predictions of climate change to regional scales. Of particular impor-
tance for the management of water resources systems are those tools deal-
ing with the linkage of the large-scale climate variability to the historical
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