Geoscience Reference
In-Depth Information
Table 1.
List of atmospheric variables in NCEP re-analysis data.
Variable
Level of measurement
Mean sea level pressure
Surface
Airflow strength
Surface
500 hPa
850 hPa
Zonal velocity
Surface
500 hPa
850 hPa
Meridional velocity
Surface
500 hPa
850 hPa
Vorticity
Surface
500 hPa
850 hPa
Wind direction
Surface
500 hPa
850 hPa
Divergence
Surface
500 hPa
850 hPa
Specific humidity
Near surface
500 hPa
850 hPa
Geopotential height
500 hPa
850 hPa
Canada): Dorval, Drummondville, Maniwaki, and McGill. NCEP re-
analysis data are composed of 24 daily atmospheric variables for the same
period which are selected for the grid box covering each of the stations
considered (see Table 1).
2.2.
Procedures
SDSM uses NCEP reanalysis data as predictors and station data as pre-
dictands, whereas LARS-WG model requires only the station data. Data
for the 1961-1975 period were used for the models' calibration step, and
those of 1976-1990 for the models' validation. After calibration, the cali-
brated models are run with the models' parameters and climate conditions
for the period 1961-1975 to generate 100 series of local weather data, each
series has 15 years of length. At the validation step, the calibrated models
are run with the models' parameters and climate conditions for the period
1976-1990 to generate 100 series of local weather data, each of 15 years
long. The outputs are statistically analyzed and compared to the statistics
of observed data for the same period to evaluate the models' performance.
Table 2 presents the evaluation statistics and indices for comparing the
performance of the SDSM and LARS-WG models. In addition, to compare
the accuracy of the simulation results given by these two models, a scoring
technique is used. In this scoring technique, when comparing the bias of an
evaluation index, score 1 will be given to the model that has larger bias
and score 0 to the one having smaller bias; if the biases of an index of the
two models are the same, score 0 will be given to both models. Finally, the
model with a larger total score implies that it is less accurate than the one
with a smaller total score.
