
314
A.
J.
SIMMONS
the
0.6
correlation coefficient reached on average about
I
day later in the
forecast period over Europe than over North America. However, the extent
of these differences is not confirmed by examination of another measure of
skill, the standard deviation of forecast error, normalized by persistence, for
the 850-mbar wind.
A
definitive specification of regional differences in fore-
cast accuracy over the extratropical Northern Hemisphere is thus difficult to
give on the basis of such objective verification.
Forecasting for the tropics and immediate subtropics undoubtedly poses
particular problems. There is not only in general a severe deficiency in data
coverage, but also strong sensitivity to aspects of the data assimilation and
parameterization schemes of the forecasting system. In addition, the strong
persistence of some regional circulations emphasizes difficulties.
As
an ex-
ample, the upper panel of Fig.
4
shows the absolute correlation of the 850-
mbar vector wind for a region covering India and part of Southeast Asia for
July 1983. Overall. the numerical forecasts barely improve on a persistence
forecast for the summer monsoon flow, although individual cases of quite
accurate forecasts
of
transient behavior over several days can
be
found. The
verification for Northwest Africa also shown in Fig.
4
indicates a much better
performance relative to persistence, although the absolute correlation of the
forecast evolves similarly for the two regions. Some further discussion of
tropical forecast accuracy is given in Section
6.
The accuracy of forecasts for a given month
or
season can vary substan-
tially from year to year even on a hemispheric domain. Extreme cases for the
extratropical Northern Hemisphere, comparing anomaly correlations for
January 1982 and 1983 and for July 1983 and 1984, are presented in Fig. 5.
Although changes in the forecasting system over the two intervening I-year
periods may have contributed to the differences, particularly between 1983
and 1984, the tests of the various changes that were made indicate that most
of the differences seen in Fig.
5
are not due to development of the model or
data assimilation. Rather, differences
in
predictability of up to
2
days at the
0.6
level of anomaly correlation appear to be mostly a consequence of
differences in the circulation patterns from month to month. The extent to
which this is due to a fundamentally higher predictability, due to a greater
sensitivity to data coverage
or
analysis techniques,
or
due to a greater sensi-
tivity to systematic model deficiencies,
in
certain synoptic situations
is
un-
clear.
The
results shown in Fig. 5 are confirmed by corresponding plots
of
the
standard deviation of forecast error. However, it is also found that standard
deviations for persistence forecasts show some of the same variability. In Fig.
6
we plot a measure of forecast accuracy based on the standard deviation of
the model forecast normafized by the standard deviation of persistence, for
the same months as in Fig. 5.
For
the two Januaries there appears little