For prediction of the extreme significant wave height in the ocean areas wh
ere long term wave data are not available, the empirical method of extrapol
ating short term data (1 similar to3 years) is used in design practice. In
this paper two methods are proposed to predict extreme significant wave hei
ght based on short-term daily maxima. According to the daa recorded by the
Oceanographic Station of Liaodong Bay at the Bohai Sea, it is supposed that
daily maximum wave heights are statistically independent. The data show th
at daily maximum wave heights obey log-normal distribution, and that the nu
mbers of daily maxima vary from year to year, obeying binomial distribution
. Based on these statistical characteristics, the binomial-log-normal compo
und extremum distribution is derived for prediction of extreme significant
wave heights (50 similar to 100 years). For examination of its accuracy and
validity, the prediction of extreme wave heights is based on 12 years' dat
a at this station, and based on each 3 years' data respectively. The result
s show that with consideration of confidence intervals, the predicted wave
heights based on 3 years' data are very close to those based on 12 years' d
ata. The observed data in some ocean areas in the Atlantic Ocean and the No
rth Sea show it is not correct to assume that daily maximum wave heights ar
e statistically independent; they are subject to Markov chain condition, ob
eying log-normal distribution. In this paper an analytical method is derive
d to predict extreme wave heights in these cases. A comparison of the compu
tations shows that the difference between the extreme wave heights based on
the assumption that daily maxima are statistically independent and that th
ey are subject to Markov Chain condition is smaller than 10%.