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Reference quality upper-air measurements: GRUAN data processing for the Vaisala RS92 radiosonde

机译:参考质量上空测量:GAISALA RS92无线电探空仪的GUAR数据处理

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The GCOS (Global Climate Observing System) Reference Upper-Air Network (GRUAN) data processing for the Vaisala RS92 radiosonde was developed to meet the criteria for reference measurements. These criteria stipulate the collection of metadata, the use of well-documented correction algorithms, and estimates of the measurement uncertainty. An important and novel aspect of the GRUAN processing is that the uncertainty estimates are vertically resolved. This paper describes the algorithms that are applied in version 2 of the GRUAN processing to correct for systematic errors in radiosonde measurements of pressure, temperature, humidity, and wind, as well as how the uncertainties related to these error sources are derived. Currently, the RS92 is launched on a regular basis at 13 out of 15 GRUAN sites. An additional GRUAN requirement for performing reference measurements with the RS92 is that the manufacturer-prescribed procedure for the radiosonde's preparation, i.e. heated reconditioning of the sensors and recalibration during ground check, is followed. In the GRUAN processing however, the recalibration of the humidity sensors that is applied during ground check is removed. For the dominant error source, solar radiation, laboratory experiments were performed to investigate and model its effect on the RS92's temperature and humidity measurements. GRUAN uncertainty estimates are 0.15 K for night-time temperature measurements and approximately 0.6 K at 25 km during daytime. The other uncertainty estimates are up to 6% relative humidity for humidity, 10–50 m for geopotential height, 0.6 hPa for pressure, 0.4–1 m s1 for wind speed, and 1° for wind direction. Daytime temperature profiles for GRUAN and Vaisala processing are comparable and consistent within the estimated uncertainty. GRUAN daytime humidity profiles are up to 15% moister than Vaisala processed profiles, of which two-thirds is due to the radiation dry bias correction and one-third is due to an additional calibration correction. Redundant measurements with frost point hygrometers (CFH and NOAA FPH) show that GRUAN-processed RS92 humidity profiles and frost point data agree within 15% in the troposphere. No systematic biases occur, apart from a 5% dry bias for GRUAN data around ?40 °C at night.
机译:观测系统(全球气候观测系统),用于维萨拉RS92探空参考高空网(GRUAN)数据处理的开发,以满足标准的参考测量。这些标准规定的元数据的集合,利用证据充分的校正算法,并测量不确定性的估计。的GRUAN处理的一个重要的和新颖的方面是,不确定性估算垂直解决。本文描述了在GRUAN处理的版本2适用于校正系统误差在压力,温度,湿度,风和无线电探空仪的测量,以及如何与这些误差源的不确定性所来源的算法。目前,RS92是在13的15个GRUAN网站定期推出。用于与RS92执行基准测量的附加GRUAN要求是用于无线电探空仪的制备制造商规定的程序,即,加热地面检查期间的传感器和重新校准的整修,接着。在GRUAN然而处理,即地面检查期间所施加的湿度传感器的校准被去除。为主要的误差源,太阳辐射,进行实验室试验以调查和模拟其对RS92的温度和湿度的测量的影响。 GRUAN不确定性估计是0.15 K代表夜间温度测量并有25公里白天约0.6ķ。其他的不确定性的估计是高达6%的相对湿度湿度,10-50米为位势高度,0.6百帕用于压力,0.4-1米S1为风速,以及1°为风向。白天温度分布GRUAN和维萨拉处理是所估计的不确定度范围内可比和一致的。 GRUAN白天湿度分布是高达15%的湿润比维萨拉加工轮廓,其中三分之二是由于辐射干燥偏差校正和三分之一是由于附加的校准校正。与霜点湿度计(CFH和NOAA FPH)冗余测量显示GRUAN处理RS92湿度分布和霜点数据在对流层中的15%内一致。没有系统偏差发生,除了5%的干偏压GRUAN数据周围?40℃,晚上。

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