Development of methodology and tools for determining the impact of cloud-cover on satellite sensors
Luke McGuire, Univ. of Oklahoma, Lewisburg, PA; and H. E. Snell and T. S. Zaccheo
Several studies have addressed the problem of optimizing field of view (FOV) size and sampling area of infrared sensors with the goal of achieving a higher percentage of cloud-free measurements. This study focuses on developing a tool to use global cloud analysis data in order to better understand the effects that different FOV sizes and satellite tracks have on the percentage of cloud-free measurements and the expected altitude of clouds that distort the signal of interest. This paper specifically discusses the situation of a satellite taking nadir measurements with a square FOV. The probability of a cloud contaminated measurement is estimated within 12-km grid boxes, making up a domain centered over the continental United States, using cloud fraction, cloud top altitude, and cloud base altitude values. The data confirms that the probability of a cloud contaminated FOV increases with an increase in FOV size. Compared to seasonal and diurnal variations, data suggests that FOV size has a relatively small effect on the expected value of cloud top and base altitudes. Increased understanding of factors effecting cloud contamination can improve scanning strategies and future satellite-based sensor designs.
Poster Session 1, Student Conference General Poster Session
Sunday, 20 January 2008, 5:30 PM-7:00 PM, Exhibit Hall B
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