To approximate the time series yielding figure 4, 

 sample time series have been generated in which longer 

 sequences of data have been deleted in a random manner 

 during the poor weather months. Then, individual temper- 

 atures are deleted at random from the remaining days until 

 certain arbitrary fractions of missing data are obtained. 

 Table 3 contains the number of longer sequences deleted 

 for three series lengths and for three fractions of missing 

 data. Analysis for 4-year series length was not attempted 

 for the smallest missing fraction. The Monte Carlo technique 

 is applied using 120 independently generated sample time 

 series for each station and each combination of series 

 length and fraction deleted. 



TABLE 3. NUMBER OF LONGER SEQUENCES DELETED 



Total 



Period 



Series Length 



Fraction 



Length 













Missing 



(days) 



4 Years 



7 Years 



12 Years 



0. 16 



28 





1 



2 





6 





4 



5 



0.34 



28 



1 



2 



3 





6 



5 



7 



14 



0.51 



28 



2 



3 



5 





6 



5 



11 



19 



The normalized results are displayed in figure 9. 

 The same theoretical curve has been plotted as in figure 8. 

 The arbitrary dashed curve has twice the ordinate of the 

 solid curve. Because of the much longer sequences deleted, 

 and perhaps because of compromises necessary in con- 

 structing table 3, the scatter of points in figure 9 is 

 greater than in figure 8. 



The dashed curve has been fitted conservatively. It 

 indicates that the fractional increase in the variance of the 



27 



