Automatic Instrument Systems for Determining Cloud Amount

R. O. Duda Stanford Research Institute, Menlo Park, Calif. 94025

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R. L. Mancuso Stanford Research Institute, Menlo Park, Calif. 94025

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S. M. Serebreny Stanford Research Institute, Menlo Park, Calif. 94025

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Abstract

A computer simulation program was used to investigate the sampling problems that are associated with using automated instrument systems to determine cloud amount. The simulated cloud conditions were generated in the computer by specifying different values for parameters such as cloud amount and mean cloud length. The simulated instrument responses, which indicate the presence or absence of a cloud overhead, were used to make estimates of the cloud amount. The accuracy of these estimates was determined as a function of the number of instruments, area size, cloud size, sampling rate and averaging time. Conventional vertically pointing ceilometer instruments were found to be capable of producing cloud-amount estimates more accurate than those of human observers if four instruments are used and if the data are properly averaged. The results of this study can be used as a guide for designing instrument systems and data processing procedures.

Abstract

A computer simulation program was used to investigate the sampling problems that are associated with using automated instrument systems to determine cloud amount. The simulated cloud conditions were generated in the computer by specifying different values for parameters such as cloud amount and mean cloud length. The simulated instrument responses, which indicate the presence or absence of a cloud overhead, were used to make estimates of the cloud amount. The accuracy of these estimates was determined as a function of the number of instruments, area size, cloud size, sampling rate and averaging time. Conventional vertically pointing ceilometer instruments were found to be capable of producing cloud-amount estimates more accurate than those of human observers if four instruments are used and if the data are properly averaged. The results of this study can be used as a guide for designing instrument systems and data processing procedures.

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