THE PERFORMANCE EVALUATION AND DATA CORRECTION OF THE FORWARD SCATTERING VISIBILITY SENSOR
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This paper introduces different sorts of automated visibility metrical instruments and the measurement theory.The original signals of the forward-scattering visibility sensor in the Pearl River Delta network and the main factors that have impacts on the measurement are analyzed.It shows that the emitting intensity is negatively correlated with air temperature,and its impact on data results can be reduced by using the normalized process;background noise has obvious diurnal variation owing to background radiation.Therefore,special attention must be paid to its orientation and position with regard to visibility sensors that are already set up to minimize the background noise and increase the signal/noise ratio.The measured values of the visibility sensor are compared with false observations and the results are as follows.The changes are basically consistent.When visibility is less than 15km,the measurements and false observations are very close.Nevertheless,when visibility is larger than 15km,the former is obviously larger than the latter.Using statistics method to revise the metrical value of the visibility sensor helps reduce the metrical error of high visibility effectively.A lidar is used to retrieve the visibility and to make a contrastive comparison of the inverse value and the value of the visibility sensor.The two detection methods are coherent,as shown in comparisons of the results of the two types of measurements.