ESSAY: Model interpretation of climate signals: an application to the Asian monsoon climate - The Global Climate System: Patterns, Processes, and Teleconnections - page 297

Figure 9.4 Downscaling
global climate signals for
regional and subregional
scale applications.

Outputs from long runs of low-
resolution coupled GCM

Statistical
downscaling

Nested regional
climate model

Time-sliced
method

Variable-grid
GCM

Land hydrological
models

Regional climate
assessment

Water resource management
(river basin catchment scale)

produced remarkable improvement in short-term weather forecasting and is
promising as a tool in multi-model climate projections.

9.2.5 Climate downscaling
To produce multiple realizations of climate variability and to obtain robust
statistics, climate models have to be run in the fully coupled ocean-atmo-
sphere-land mode for many simulated years. For seasonal-to-interannual
time scales, typically 40-50 simulated years are needed. For decadal scales
and climate change scenarios, several hundred or even thousands of simu-
lated years have to be carried out (cf. IPCC reports). Because of the enormous
computation resources required for such long-term integrations, coupled
models are typically run in the low-resolution mode to capture only the
slow physics of the system, which is deemed to be important for long-term
climate change. As a result, regional and subregional scale processes are
unresolved. To obtain regional and local climate information from the long-
term integrations, climate downscaling is necessary.
Climate downscaling is the procedure by which climate signals at the scale
of GCM grid size are translated into regional and subregional scales, which
are unresolved by GCMs (Giorgi and Mearns 1991 ; Hewitson and Crane
1996 ). Downscaling is usually applied to a pre-selected region, in which
climate and/or water resource assessment need to be estimated. As shown in
Figure 9.4 , downscaling may take place in single or multiple stages. At