The Potential for Long-Range Predictability of Temperature and
Precipitation over Japan
Roland A. Madden and Dennis J. Shea
National Center for Atmospheric Research
P. O. Box 3000
Boulder, CO 80307
Daily temperature and precipitation data from Japanese stations are studied to
estimate 'climate noise', an unpredictable part of long-term variability. The
climate noise is compared to the interannual variance of monthly mean
temperatures and monthly precipitation totals to access the 'potential
predictability'. Potential predictability is that part of the interannual
variance that exceeds climate noise. It is found that potential predictability
of temperature can exceed 40% at some stations primarily during July and
Jannuary. Less potential predictability is present during April and October.
Results are similar for monthly precipitation totals.
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Hongjun Zhang:
zhangho@ucar.edu