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Automated quality control of meteorological observations
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Automated quality control of meteorological observations : ウィキペディア英語版
Automated quality control of meteorological observations
A meteorological observation at a given place can be inaccurate for a variety of reasons, such as a hardware defect. Quality control can help spot which meteorological observations are inaccurate.
One of the main automated quality control programs used today in the area of meteorological observations is the ''meteorological assimilation data ingest system'' (MADIS).〔(Meteorological assimilation data ingest system (MADIS) )〕
==History==
Weather observation quality control systems verify probability, history, and trends. One of the main and simplest forms of quality control is the check of probability.〔Gandin, L., 1988: Complex Quality Control of Meteorological Observations. Monthly Weather Review, 116, 1137–1156.〕 This check throws out impossible observations, such as the dew point being higher than the temperature or data outside acceptable ranges, such as temperatures over 200 degrees Fahrenheit. Another basic quality control check is to have the data compared to preset geographic extremes,〔DeGaetano, A., 1997: A Quality-Control Routine for Hourly Wind Observations. Journal of Atmospheric and Oceanic Technology, 14, 308–317.〕 perhaps combined with diurnal variations. However this only flags the data as uncertain because the station could be reporting correctly but there is no way to know. A better way is to correlate with previous observations as well as the other simple checks.〔Miller, P. and S. Benjamin, 1992: A System for the Hourly Assimilation of Surface Observations in Mountainous and Flat Terrain. Monthly Weather Review, 120, 2342–2359.〕 This method uses one hour persistence to check the quality of the current observation. This method makes continuity of observations better since the system is able to make better judgments on whether the current observations are bad or not.

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
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