Abstract
Objective sensor-placement techniques are applied to the process of selecting locations for a network of ten pyranometers, which will be used to investigate regional patterns of high turbidity across the northeastern United States. The techniques involve adjusting via nonlinear programming methods the values of coefficients in a continuous function that describes correlations between turbidity values separated by temporal and spatial intervals, in order to best describe the structure of turbidity. With the correlation structure function that is found, sensor locations are evaluated by calculating the normalized residual variance obtained from objective analyses performed at gridpoints across the region of interest. Sensor positions are shifted by nonlinear programming methods until residual variance is minimized. A comparison is made between simultaneous and sequential methods of sensorplacement optimization, in which the incremental value of adding sensors is determined objectively.
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