of lower threshold values (which provide greater probability of eliminating all cloud 

 contaminated points), and the improved coverage when higher values are established. 

 These results are in agreement with the findings of an earlier study by Wexler. 

 Using the early orbits of TIROS III data, Wexler found an uncorrected average 

 Channel 5 albedo of 15 % for the range of concurrent Channel 2 temperatures from 

 242 to 268 K (clear conditions were assumed for temperatures greater than 268 K, 

 and an overcast was assumed for temperatures less than 242 K). Using the sensor 

 deterioration information presented in the TIROS III and TIROS VII Radiation Cat- 

 alogues ' , this was found to be equivalent, during the early life of TIROS VII, 

 to a 24 % average albedo for approximately 50 % cloudiness. Thus, the 10-20 % 

 threshold values employed for individual data points should eliminate a very large 

 proportion of the seriously cloud contaminated data points. 



4. 2. 2 Nighttime Cases 



During nighttime passes , no meaningful measurements are available from 

 either Channel 3 or Channel 5. An investigation was made of the difference between 

 Channel 4 and Channel 2 measurements as a cloud detection mechanism. This 

 difference is relatively constant at a given temperature, but should decrease in the 

 presence of high water vapor amounts. Daylight cases were used to attempt to 

 correlate these differences with the presence or absence of clouds. Unfortunately, 

 but not totally unexpectedly, the measured differences showed no detectable changes 

 in the transition from clear to overcast conditions. This seemed due primarily to 

 the high noise level of the Channel 2 minus Channel 4 difference, relative to the 

 peak to peak range of this difference. The estimated short term relative accuracy 

 of these differences was — 3 K, while the entire range of the difference values 

 rarely exceeded 9 K. The failure of this approach may, however, also be due to 

 the lack of sufficient or sufficiently abrupt humidity variations over a partially cloudy 

 area or at a cloud boundary. 



Figure 4-1 shows data from a typical daytime swath across a cloud boundary. 

 Channel 5 shows an abrupt change, while the Channel 2 minus Channel 4 difference 

 reveals no obvious breaking point. 



It was consequently concluded that the use of nightime IR measurements to 

 eliminate cloud contaminated points from SST data is impractical at the present time. 

 Unfortunately, this result approximately halves the number of usable cases over a 

 given area. There is no reason for believing the Nimbus MRIR data will be sig- 

 nificantly better in this regard. 



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