本文已被：浏览 1661次 下载 2150次
投稿时间：2014-01-09 修订日期：2014-10-13
投稿时间：2014-01-09 修订日期：2014-10-13
中文摘要: 利用143个国家基准站2002—2010年自动与人工逐日平行观测资料进行对比分析，评估自动观测与人工观测气温的差异，着重分析两者存在的较大差异及其发生原因，并利用惩罚最大t检验（PMT）方法结合台站元数据中自动观测仪器变化信息，客观评价自动观测对气温序列均一性的影响。结果表明：(1) 51.29%、54.14%、67.18%的自动观测日平均、日最高、日最低气温大于人工观测值，差值在±0.2℃之间的百分率分别为78.8%、63.1%、60.9%，平均对比差值分别为0.05、0.09、0.15℃，标准差为0.14、0.22和0.15℃，各气温要素的差值、绝对差值和标准差随自动观测时间的增长并无明显的增大或减小的趋势，且空间分布各有不同；(2)通过对对比差值、绝对差值、标准差的分类比较、逐步筛选发现，少数台站自动与人工观测值差异较大，对于采集自同一传感器的不同气温要素，平均、最高、最低气温的差值表现也不尽一致。经PMT检验，在平均气温、最高气温和最低气温的绝对差值最大的20个站中分别有35%的台站的月平均气温序列、35%的台站的月平均最高气温序列和25%的台站的月平均最低气温序列由于自动观测仪器变化引起序列的非均一；(3) 分析认为：温度传感器检定更换而导致的仪器示值误差变化会造成自动与人工观测对比差值跳变，而温度传感器或数据采集器等电子元器件的零点漂移会导致自动观测气温严重偏离人工观测值，这两种因素会导致自动与人工观测气温差异偏大，也是自动观测仪器变化导致气温序列产生非均一断点的可能原因。建议加强自动观测数据的监测与质量控制，增加观测仪器检定示值误差订正，并采取硬件、软件补偿等方法，实现温度零点补偿，尽可能地减小或消除仪器误差，提高自动观测资料的准确性。
Abstract:Based on the parallel daily air temperature data of automatic and manual observations at 143 national benchmark stations from 2002 to 2010, systematic comparative analysis and objective evaluation of differences are made, especially focusing on the large differences and their causes. The impact of automatic observation on the homogeneity of temperature time series is evaluated using the penalized maximal t test (PMT) combined with the metadata of observation instrument changes. The results show that: (1) 51.29%, 54.14%, and 67.18% of daily average, highest, lowest temperatures obtained by AWS (automatic weather station) are greater than the values by manual observation and the percentage of difference between ±0.2℃ respectively accounts for 78.8%, 63.1%, and 60.9%. Average difference values of daily average, highest, lowest temperature are 0.05℃, 0.09℃ and 0.15℃, and the standard deviations are 0.14℃, 0.22℃ and 0.15℃, respectively. The difference, absolute difference value and standard deviation of all temperature elements have no apparent increasing or decreasing trend along with the observation time of AWS and their spatial distributions are different. (2) By the classification comparison and screening of the difference value, absolute difference value and standard deviation step by step, some differences are found greater at a few stations and the differences of the average, the highest and lowest temperatures collected from the same sensor are different as well. By the check of PMT, the inhomogeneous breakpoints are found in the monthly average temperature time series, monthly average maximum temperature time series of 35% station and monthly average minimum temperature time series of 25% stations among the 20 stations with largest absolute difference values of average, maximum and minimum temperatures. (3) The change of calibration error of temperature sensor is the important reason for difference jump between automatic and manual observations. The instrument failures, such as zero drift of electronic components of temperature sensor or data collector can lead temperature obtained by AWS to deviate greatly from the value of manual observation. The above two facts are the main causes for greater differences in temperature between automatic and manual observations, and also possible reasons for inhomogeneous breakpoints of temperature series because of observational instrument changes. Therefore, we suggest strengthening monitoring and quality control for automatic observation data, increasing the observation instrument calibration error correction and realizing the zero temperature compensation adopting methods of hardware and software compensation to reduce or eliminate the instrument error as much as possible and improve the accuracy of the automatic observation data.
文章编号： 中图分类号： 文献标志码：
基金项目:公益性行业(气象)科研专项(GYHY201106038)和陕西省气象局气象科技创新基金项目(2014M 27)共同资助
| 作者 | 单位 |
| 李亚丽 | 陕西省气象信息中心，西安 710014 |
| 任芝花 | 国家气象信息中心，北京 100081 |
| 陈高峰 | 陕西省渭南市气象局，渭南 714000 |
| 夏巧利 | 陕西省气象信息中心，西安 710014 |
| 贺 音 | 陕西省气象信息中心，西安 710014 |
| 余 鹏 | 陕西省气象信息中心，西安 710014 |
引用文本：
李亚丽,任芝花,陈高峰,夏巧利,贺 音,余 鹏,2015.自动与人工观测气温差异偏大的原因及影响分析——以143个国家基准站为例[J].气象,41(8):1007-1016.
LI Yali,REN Zhihua,CHEN Gaofeng,XIA Qiaoli,HE Yin,YU Peng,2015.Causes and Impact Analysis of Errors Between Temperatures Obtained by Automatic and Manual Observations at 143 National Automatic Benchmark Stations[J].Meteor Mon,41(8):1007-1016.
李亚丽,任芝花,陈高峰,夏巧利,贺 音,余 鹏,2015.自动与人工观测气温差异偏大的原因及影响分析——以143个国家基准站为例[J].气象,41(8):1007-1016.
LI Yali,REN Zhihua,CHEN Gaofeng,XIA Qiaoli,HE Yin,YU Peng,2015.Causes and Impact Analysis of Errors Between Temperatures Obtained by Automatic and Manual Observations at 143 National Automatic Benchmark Stations[J].Meteor Mon,41(8):1007-1016.