Low Cost Instrument for Automatic Determination of Cloud Cover

There is a continuing need for reliable cloud observations to drive climatic UV-B prediction models. Traditionally, observations such as cloud cover are made by human observers, and thus often suffer from uncertainties due to the subjectivity of the observer. Cloud cover data is especially important in UV-B hazard prediction, as well as storm prediction. It is generally accepted that UV-B doses should be predicted, rather than just reported, in order to minimize public health impact. These UV-B forecast models rely heavily on consistent and accurate cloud cover data. We propose to investigate several novel ideas for inexpensive, autonomous, electro-optic sensors that can determine cloud cover conditions automatically. We believe that with proper design, these sensors can produce repeatable and consistent data that should reduce the measurement uncertainty and operational costs associated with human observers.