Estimating Cloud Type from Pyranometer Observations

Abstract

In this paper the authors evaluate an inexpensive and automatable method to estimate cloud type at a given location during daylight hours using the time series of irradiance from a pyranometer. The motivation for this investigation is to provide ground-based estimates of cloud type at locations where there are no human observations of sky condition. A pyranometer naturally measures the effect of intervening clouds along the solar beam path to the sensor. Because a daily time series of irradiance is nonstationary, it is appropriately scaled to yield a stationary time series. From the latter, the standard deviation and ratio of observed irradiance to clear-sky irradiance derived from a 21-min moving window are related to one of the following cloud types or conditions: cirrus, cumulus, cirrus and cumulus, stratus, precipitation or fog, no clouds, and other clouds. Comparisons with human observations at the Department of Energy Atmospheric Radiation Measurement Calibration and Radiation Testbed site in northern Oklahoma show that the pyranometer method and human observations are in agreement about 45% of the time. Many of the differences can be attributed to two factors: 1) the pyranometer method is weighted toward clouds crossing the sun's path, while the human observer can view clouds over the entire sky, and 2) the presence of aerosols causes the pyranometer to overestimate the occurrence of cirrus and cirrus plus cumulus. When attenuation of the solar beam by aerosols is negligible or can be accounted for, the pyranometer method should be especially useful for cloud-type assessment where no other sky observations are available.