长白山麓夏秋季气态和液态水分布特征

doi:10.3969/j.issn.1673-503X.2024.01.006

Abstract

Abstract:

Utilizing the MWP967KV multi-channel microwave radiometer, ground-based rain gauge, and L-band sounding radar data from the China Meteorological Administration Jilin Cloud Physics Field Experiment Base during June to October from 2019 to 2020, the distribution of gaseous and liquid water in the atmosphere at the foot of Changbai Mountain in summer and autumn and its evolution characteristics before precipitation were analyzed. The results show that there is good correlation between the microwave radiometer retrieved data and sounding radar data, though the retrieved values are generally higher. The atmospheric precipitable water vapor (PWV) and liquid water path (LWP) exhibit the diurnal variation characteristic with the peak at night and the valley in the day. The peak appears between 01:00-03:00 during precipitation, while the valley appears around 11:00. The monthly average maximum values of PWV and LWP appear in August and September respectively, because of the influence of the topography and forest vegetation at Changbai Mountain. The distribution frequency of PWV shows a rising and then a falling trend before and during precipitation, whereas the frequency ratio of LWP in the range of 0.00~0.42 mm is the highest before precipitation. The stronger the precipitation intensity is, the more concentrated the frequency distribution of PWV and LWP is, with a greater likelihood of heavy precipitation for PWV greater than 45 mm and LWP greater than 4.20 mm.A surge in both LWP and PWV occurs within 1 h before precipitation starts, with a more pronounced increase in LWP, indicating that this characteristic can serve as a reference index for the analysis of precipitation approaching forecast and artificial rain enhancement operations.

Key words: Microwave radiometer, Atmospheric precipitable water vapor, Liquid water path

CLC Number:

P426

Qinhong SUN,Hongbo MA,Yanbin QI,Dongjia YU,Jialu FAN. Distribution characteristics of gaseous and liquid water at the foot of Changbai Mountain in summer and autumn[J]. Journal of Meteorology and Environment, 2024, 40(1): 47-53.

Figures/Tables 8

Fig.1

Table 1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

References 28

1	汪宏七, 赵高祥. 云和辐射──(Ⅰ)云气候学和云的辐射作用[J]. 大气科学, 1994, 18 (S1): 910- 932.
2	王婉, 雷恒池, 聂皓浩, 等. 基于机载微波辐射计探测大气水汽通道饱和问题研究[J]. 气象学报, 2021, 79 (3): 509- 520.
3	王志诚, 张雪芬, 茆佳佳, 等. 不同天气条件下地基微波辐射计探测性能比对[J]. 应用气象学报, 2018, 29 (3): 282- 295.
4	邹明龙, 刘黎平, 郑佳锋, 等. 降水条件下的云雷达与微波辐射计反演液态水含量对比分析[J]. 热带气象学报, 2021, 37 (4): 669- 680.
5	陈树成, 李晓波, 崔明, 等. 不同天气条件下微波辐射计和风廓线雷达探测数据误差特征分析[J]. 气象与环境学报, 2021, 37 (1): 67- 72.
6	翟晴飞, 张晋广, 王斌飞, 等. 微波辐射计反演大气温湿度廓线与降水相关性分析[J]. 气象与环境学报, 2020, 36 (6): 98- 107. doi: 10.3969/j.issn.1673-503X.2020.06.012
7	孔凡超, 李江波, 王颖. 北京冬奥会云顶赛场微波辐射计反演大气温湿廓线分析[J]. 气象, 2021, 47 (9): 1062- 1072.
8	李建强, 李新生, 董文晓, 等. RPG-HATPRO微波辐射计反演的温度和湿度数据适用性分析[J]. 气象与环境学报, 2017, 33 (6): 89- 95.
9	樊旭, 黄颖, 冷文楠, 等. 基于径向基神经网络的地基微波辐射计反演算法研究[J]. 气象与环境学报, 2020, 36 (2): 62- 69.
10	陈树成, 史静, 王彦, 等. 基于地基微波辐射计遥感的天津大气水汽和液态水特征[J]. 气象与环境学报, 2019, 35 (6): 38- 45.
11	李军霞, 李培仁, 晋立军, 等. 地基微波辐射计在遥测大气水汽特征及降水分析中的应用[J]. 干旱气象, 2017, 35 (5): 767- 775.
12	刘红燕, 王迎春, 王京丽, 等. 由地基微波辐射计测量得到的北京地区水汽特性的初步分析[J]. 大气科学, 2009, 33 (2): 388- 396.
13	张秋晨, 龚佃利, 王俊, 等. 基于地基微波辐射计反演的济南地区水汽及云液态水特征[J]. 气象与环境学报, 2017, 33 (5): 35- 43.
14	田磊, 桑建人, 姚展予, 等. 六盘山区夏秋季大气水汽和液态水特征初步分析[J]. 气象与环境学报, 2019, 35 (6): 28- 37. doi: 10.3969/j.issn.1673-503X.2019.06.005
15	黄建平, 何敏, 阎虹如, 等. 利用地基微波辐射计反演兰州地区液态云水路径和可降水量的初步研究[J]. 大气科学, 2010, 34 (3): 548- 558.
16	张文刚, 徐桂荣, 万蓉, 等. 基于地基微波辐射计的大气液态水及水汽特征分析[J]. 暴雨灾害, 2015, 34 (4): 367- 374.
17	段英, 吴志会. 利用地基遥感方法监测大气中汽态、液态水含量分布特征的分析[J]. 应用气象学报, 1999, 10 (1): 34- 40.
18	白婷, 丁建芳, 刘艳华, 等. 微波辐射计在监测水汽特征及降水分析中的应用[J]. 气象与环境科学, 2021, 44 (6): 102- 107.
19	唐仁茂, 李德俊, 向玉春, 等. 地基微波辐射计对咸宁一次冰雹天气过程的监测分析[J]. 气象学报, 2012, 70 (4): 806- 813.
20	方莎莎, 陆鹏程, 廖可文, 等. 基于微波辐射计资料对武汉市冬季典型大雾个例的探测分析[J]. 气象与环境科学, 2020, 43 (4): 81- 87.
21	刘艳杰, 王清川, 许敏, 等. 2019年5月北京一次强降水超级单体特征及成因分析[J]. 气象与环境学报, 2021, 37 (4): 9- 17. doi: 10.3969/j.issn.1673-503X.2021.04.002
22	许馨尹, 于军琪, 李红莲, 等. 露点温度计算方法对比研究[J]. 气象与环境学报, 2016, 32 (3): 107- 111.
23	盛裴轩, 毛节泰, 李建国, 等. 大气物理学[M]. 北京: 北京大学出版社, 2013: 18- 22.
24	梅海霞, 梁信忠, 曾明剑, 等. 2015—2017年夏季南京雨滴谱特征[J]. 应用气象学报, 2020, 31 (1): 117- 128.
25	Chen B J , Yang J , Pu J P . Statistical characteristics of raindrop size distribution in the Meiyu season observed in Eastern China[J]. Journal of the Meteorological Society of Japan, 2013, 91 (2): 215- 227.
26	冯印成, 王云琦, 王玉杰, 等. 重庆缙云山针阔混交林水汽通量特征及其影响因子[J]. 植物生态学报, 2022, 46 (8): 890- 903.
27	翁闻畅, 葛继稳, 谌佳伟, 等. 神农架大九湖亚高山泥炭湿地水汽通量特征及其与相关环境因子的关系[J]. 植物科学学报, 2020, 38 (4): 493- 505.
28	白婷, 刘艳华, 杨敏. 微波辐射计观测同降水相关性的研究[J]. 气象与环境科学, 2019, 42 (4): 111- 118.

要素	检验物理量	降水样本	无降水样本	总体样本
气温/℃	平均误差	1.93	1.30	1.36
	均方根误差	3.50	3.03	3.08
	相关系数	0.93	0.90	0.91
相对湿度/ (%)	平均误差	16.70	11.50	11.90
	均方根误差	30.50	32.90	32.80
	相关系数	0.52	0.31	0.39
水汽密度/ (g·m^-3)	平均误差	0.68	0.33	0.36
	均方根误差	1.03	0.89	0.90
	相关系数	0.83	0.62	0.71

[1]	Weidong JIANG,Rongzhi ZHANG,Bo CHEN,Tianqi ZHANG,Hailing HUANG,Lin ZHOU. Experimental study on thunderstorm forecast of ground-based microwave radiometer based on BP neural network [J]. Journal of Meteorology and Environment, 2023, 39(5): 106-112.
[2]	Shu-cheng CHEN,Xiao-bo LI,Ming CUI,Yan WANG. Error analysis of detection data of microwave radiometer and wind profiler radar under different weather conditions [J]. Journal of Meteorology and Environment, 2021, 37(1): 67-72.
[3]	Qing-fei ZHAI,Jin-guang ZHANG,Bin-fei WANG,Jian YUAN,Yao LI,Ming-yu LI. Correlation analysis of atmospheric temperature and humidity profiles retrieved from microwave radiometer with precipitation [J]. Journal of Meteorology and Environment, 2020, 36(6): 98-107.
[4]	Xu FAN,Ying HUANG,Wen-nan LENG,Bei-dou ZHANG,Wen-yu ZHANG,Guo-yin WANG. Inversion of ground-based microwave radiometer measurements using radial basis function neural network [J]. Journal of Meteorology and Environment, 2020, 36(2): 62-69.
[5]	TIAN Lei, SANG Jian-ren, YAO Zhan-yu, CHANG Zhuo-lin, DAN Xin-lan, CAO Ning, SUN Yan-qiao. Characteristics of atmospheric water vapor and liquid water in Liupan Mountain area in summer and autumn [J]. Journal of Meteorology and Environment, 2019, 35(6): 28-37.
[6]	CHEN Shu-cheng, SHI Jing, WANG Yan, LI Xiao-bo, CUI Ming. Characteristics of atmospheric water vapor and liquid water over Tianjin identified by remote sensing data from ground-based microwave radiometer [J]. Journal of Meteorology and Environment, 2019, 35(6): 38-45.
[7]	ZHANG Qiu-chen, GONG Dian-li, WANG Jun, ZHANG Hong-sheng. Characteristics of water vapor and liquid water content retrieved by ground-based microwave radiometer in Ji'nan [J]. Journal of Meteorology and Environment, 2017, 33(5): 35-43.
[8]	WANG Ying, LI Guo-chun, GAO Yang-hua, DU Qin, ZHAO Zi-qi. Polarization-difference parameterization in estimating liquid water path based on AMSR-E data [J]. Journal of Meteorology and Environment, 2016, 32(2): 59-65.

Distribution characteristics of gaseous and liquid water at the foot of Changbai Mountain in summer and autumn

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 28

Related Articles 8

Metrics

Comments

Recommended 10