| 雨滴谱式降水现象仪与人工观测结果的一致性分析 |
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| 引用本文： | 吴宜,刘西川,孙宇,张军.雨滴谱式降水现象仪与人工观测结果的一致性分析[J].气象科技,2021,49(1):32-39. |
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| 作者姓名： | 吴宜 刘西川 孙宇 张军 |
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| 作者单位： | 南京市气象探测中心,南京 210009;国防科技大学气象海洋学院,长沙 410073;北京航天飞行控制中心,北京 100094 |
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| 基金项目： | 国家自然科学基金项目（41975030、41327003）和南京市气象局自立科研项目（NJ201907）共同资助 |
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| 摘 要： | 为验证雨滴谱式降水现象仪的测量性能,利用南京市气象局在江宁布设的PARSIVEL型雨滴谱式降水现象仪2018年1—11月期间的天气现象观测资料,重点分析了雨滴谱式降水现象仪对不同类型降水的测量性能。结果表明:①总体而言,雨滴谱式降水现象仪与人工观测具有良好的一致性,但是在降水时间、降水类型方面存在一定差异。②白天,人工观测的总降水时间明显高于仪器观测结果,主要原因在于人工观测有时会忽略降水间隙,而仪器可能会漏掉极微量降雨;人工观测的降水现象分类较粗,有时会忽略降水的精细变化,而仪器能够灵敏检测到降雨的短时变化、毛毛雨和雨的转换、降雨和降雪的转换等。③夜间,人工观测有时会忽略个别时次的毛毛雨或雨,而仪器容易漏测微量降水,大雨强条件下有时会把降雨误判为霰或雪,降水现象的判别算法仍需改进。
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| 关 键 词： | 雨滴谱式降水现象仪 天气现象 人工观测 对比 |
| 收稿时间： | 2020/3/3 0:00:00 |
| 修稿时间： | 2020/11/18 0:00:00 |
Consistency Analysis of Raindrop-Spectrum Precipitation Phenomenon Sensor and Manual Observation Results |
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| WU Yi,LIU Xichuan,SUN Yu,ZHANG Jun.Consistency Analysis of Raindrop-Spectrum Precipitation Phenomenon Sensor and Manual Observation Results[J].Meteorological Science and Technology,2021,49(1):32-39. |
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| Authors: | WU Yi LIU Xichuan SUN Yu ZHANG Jun |
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| Institution: | (Nanjing Meteorological Observation Center,Nanjing 210009;College of Meteorology and Oceanography,National University of Defense Technology,Changsha 410073;Beijing Aerospace Control Center,Beijing 100094) |
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| Abstract: | In order to verify the performance of the raindrop spectrum precipitation phenomenon sensor, the PARSIVEL raindrop spectrum precipitation phenomenon sensor deployed at Jiangning by the Nanjing Meteorological Service is used to collate the observation data of weather phenomena from January to November 2018, and the performance of the sensor for different types of precipitation is analyzed. The conclusions are as follows: (1) The raindrop spectrum precipitation phenomenon sensor has good consistency with manual observations in general, but there are some differences in precipitation duration and precipitation types. (2) In the daytime, the total precipitation duration of manual observation is obviously higher than that of the sensor, and the main reason is that manual observation might ignore the time between precipitation events, while the sensor might miss very light precipitation; the precipitation classification of manual observation is rough, and the fine changes of precipitation may be neglected, while the sensor is able to detect the short term changes in rainfall, the conversion of drizzle and rainfall, the conversion of rainfall and snow, etc. (3) At night, the manual observation may ignore a certain drizzle or rainfall, whereas the sensor tends to miss the light rainfall, and rains might be misjudged as graupels or snowfall. Therefore, the algorithm for classifying precipitation still needs to be improved. |
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| Keywords: | raindrop-spectrum precipitation phenomenon sensor weather phenomenon manual observation comparison |
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