East Asia and Western Pacific METEOROLOGY AND CLIMATE

444
AM
AM
PO-
N3
A/i + N3'
and
NH--
N2
N\
are evaluated, where Nl, N2 and N3 are the total numbers of stations
corresponding to each class illustrated in Table 1. For example, N3 is the
number of stations where precipitation is observed but not predicted.
Whether 'precipitation' or 'non-precipitation' predicted at the stations is
defined as follows. For every selected station, there are four adjacent
grid points. It is considered that precipitation is predicted at that
station if precipitation is predicted at one or more of the grid points. T
score denotes the rate of the correct forecast. PO denotes the rate of the
observed but not predicted precipitation and NH the rate of the predicted
precipitation which did not occur.
Table 1. Illustration of the number of stations
Observed
Precipitation
Non-Precipitation
Predicted
Precipitation
Nl
N2
Non-Precipitation
Obviously, the closer to 1 T is and the smaller PO and NH are, the
better the forecast is.
The monthly mean values of score T,' PO and NH from July to
November 1984 and 1988 are shown in Table 2.
Table 2. Monthly Mean Values of Scores
Month
JuL
Aug.
Sep.
Oct.
Score
T
0.46
0.51
0.55
0.45
1984
PO
0.46
0.41
0.23
0.17
NH
0.30
0.22
0.33
0.49
1988
Nov. 0.29 0.20 0.69 0.15 .0.75 0.60
It can be seen that the T score is higher in summer than that in
autumn. Obviously.all of the scores are very poor and they are much
different in the different years. We do not think these scores can
express objectively the skill level of precipitation forecast. But,
unfortunely, there is no universally accepted method for use to verify
precipitation forecasts in the world,
IV.
SOME EXPERIMENTS ON PRECIPITATION
T
0.27
0.42
0,34
0.23
PO
0.61
0.43
0.49
0.70
N3
NO
NH
0.51
0.45
0.49
0.29
As one of the attempts to improve the forecast of rainfall amount, we
examined the effects of varying horizontal resolution on precipitation