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The heights of automatic weather station (AWS) sensors over the Antarctic ice sheet are nominal and change with snow accumulation or ablation. Therefore, the measured data may not be used directly. In this study, we analyzed the impact of snow accumulation on AWS observations using continuous measurements from three AWS that were deployed on the traverse route from the Zhongshan Station to Dome A over East Antarctica. We then corrected the measured air temperature to account for changes in the sensor height relative to the snow surface to improve the authenticity and representativeness of the observation data from the AWS. The results show that (i) the annual mean snow accumulations at Dome A, Eagle and LGB69 were approximately 0.11 m, 0.30 m and 0.49 m, respectively, and the corresponding annual mean air temperature differences between the corrected and measured values at 1 m in height were 0.34℃, 0.29℃ and 0.35℃; (ii) the impact on air temperature from accumulation decreases with height from the surface; (iii) the air temperature difference between the corrected and measured values was not directly proportional to the snow accumulation but was related to the seasonal air temperature variations and the intensity of the local surface inversion; and (iv) the averaged corrected air temperature was higher than the measured values except during the summer when there were days without temperature inversion. The magnitude of the temperature difference between the corrected and measured was mainly determined by snow accumulation and the intensity of the local surface inversion. 相似文献
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基于华东地区3 km分辨率WRF (Weather Research and Forecasting) 模式和高密度地面自动气象站(AWS)观测,研究GSI-3DVAR同化系统的RHZSCL对AWS观测的地面温度和风观测同化的敏感性。结果表明:运用GSI-3DVAR同化地面AWS观测时,RHZSCL的取值较为敏感;选取合适的RHZSCL能有效改进地面分析场精度,相较于背景场地面温度和地面矢量风差(VWD) RMSE均可减小35%以上。当RHZSCL过大会导致温度高、低值中心的影响范围过大,风分析场较为平滑,无法反映出中小尺度环流结构。但RHZSCL过小则会使得温度分析场增加误差,并导致风分析场出现虚假大风。观测密度稀疏化的敏感性试验结果表明,地面温度场及风场所适应的最优RHZSCL皆随着观测密度的增大而相应减小。 相似文献
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区域气象站位置信息检验评估 总被引:1,自引:0,他引:1
在全国40872个参加信息质量考核的区域自动气象站(Regional Automatic Weather Station,RAWS)中,由于测站地理位置(Position Of Station,POS)初始信息偏差、POS信息改动、站点拆迁等原因,造成报表POS信息与实际不符,检测并发现这些异动站点,成为提高观测质量且准确应用观测数据的前提。使用SQL数据索引查询优化、汉字正则匹配技术,对全国区域自动气象站站高和站名站址进行检验,评估其POS的准确性。统计分析发现,高程差在20m以内的站数约占总站数的72%,在100m以上的约占7%;匹配距离在1km以内的站数约占总站数的62%,在10km以上或无匹配结果的约占6%。表明,全国区域自动气象站POS数据大部分准确、可用。相关管理部门可以对标注异常的POS进行核实修改,当前业务应用可根据评估结果采用相应的解决方式。 相似文献
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