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This paper presents a numerical technique for short-term aviation
climate forecast. The forecast period covers 30 days from the initial time; the
main frame of the forecast system is composed of a fine-grid regional climate
model (RCM) and coarse-grid global circulation model (GCM)(Fig 1). Besides the conventional nesting techniques, the present system
also involves some new approaches to raise the prediction accuracy, which
include the weekly SST updating, the latest LULC fed from the satellite
observation, downscaling interpretation to the interesting routes or flight
zones, as well as the integrating technique with the popular statistical
models.
The GCM used in the system is known as T63L16 that is used as the
operational model by National Climate Center of China while the RCM is a
modified version of the meso-scale model MM5(V3). The 30-day short-term
prediction products includes the main weather procedures that might affect the
aviation activities within the 30-day forecast period, the average, maximum, and
minimum temperature, and precipitation of each 10-day period.
The system was run since July 1, 2001 and has performed very well.
The system validation was carried on according to the four critical parameters
that are commonly used in short-term climate validations; these are prediction
score (P), climate skill-scores of forecast (SS1), random skill-scores of
forecast (SS2) and the abnormal correlation coefficient (ACC) with respect to
monthly averaged temperature, precipitation as well as 500hpa potential heights
at each grid within the domain of RCM that covers an area of 14.1°ã-- 49.6°ãN, 84.6°ã --140.5°ãE. The preliminary results are listed in Table 1 in comparison with
the operational forecasts issued by National Climate Center of China during a
period from 1971 to 1995, we satisfy with the significant accuracy
improvement.
References
1.
Barnston A and G. Linear 1994.
Statistical shore-term climate predictive skill in the Northern Hemisphere. J.
Climate, 7:1513-1564
2.
Wang Shaowu, 1984. The rhythm in the
atmosphere and oceans in application to long-range weather forecasting. Advance
in Atmospheric Science, 1(1):7-18.
3.
Monin A S and LI Piterbarg ,
Forecasting weather and climate. in Limits of Predictability Yurii A
Kravtsov(Ed), Springer-Verlag, Berlin Heidelberg,1993:7-44. Table 1 The preliminary results of the
short-term aviation climate numerical prediction system in comparison with
operational forecast of National Climate Center of China
P SS1 SS2 ACC Averaged monthly temperature of NCC's
forecast 64.6 0.03 -0.06 0.004 Averaged monthly temperature of
Present system 75.6 0.23 0.16 0.63 Averaged monthly precipitation of
NCC's forecast 60.6 0.009 0.16 0.013 Averaged monthly precipitation of
Present system 85.5 0.61 0.67 0.14
Fig. 1 The Configuration of short-term
aviation climate numerical prediction system
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