Identification on Cloud Macroscopic Physical Characteristics Based upon Multi-source Observations in Beijing

Zhou Qing; Li Bai; Zhang Yong; Tao Fa; Hu Shuzhen; Li Ruiyi; Yang Rongkang

doi:10.11898/1001-7313.20230207

Vol.34, NO.2, 2023

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Article Navigation > Journal of Applied Meteorological Science > 2023 > 34(2): 206-219

Zhou Qing, Li Bai, Zhang Yong, et al. Identification on cloud macroscopic physical characteristics based upon multi-source observations in Beijing. J Appl Meteor Sci, 2023, 34(2): 206-219. DOI: 10.11898/1001-7313.20230207.

Citation:

Zhou Qing, Li Bai, Zhang Yong, et al. Identification on cloud macroscopic physical characteristics based upon multi-source observations in Beijing. J Appl Meteor Sci, 2023, 34(2): 206-219. DOI: 10.11898/1001-7313.20230207.

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Identification on Cloud Macroscopic Physical Characteristics Based upon Multi-source Observations in Beijing

DOI: 10.11898/1001-7313.20230207

Meteorological Observation Center, China Meteorological Administration, Beijing 100081

Received Date: 2022-08-04
Rev Recd Date: 2023-01-11
Publish Date: 2023-03-31

Abstract

Abstract

The knowledge of accurate cloud heights (including cloud base height and cloud top height) information and its variation is of great importance to elucidating synoptic variation and improving climate model and prediction precision. Utilizing the theory of variation continuity and first-order discontinuity of meteorological element in frontal zone, cloud front zone is defined as transitional zone between the cloud cluster and its adjacent area in vertical direction in order to solve the problem of cloud heights uncertainties observed by different equipments. According to the humidity, scattering and turbulence properties of cloud, using observation from L-band sounding, Ka-band millimeter wave cloud radar (MMCR) and the wind profiler, the variation characteristics of temperature, humidity, radar reflectivity and signal noise ratio (SNR) as well as their differences from the ambient atmosphere are studied. In addition, the differences between convective clouds and stratified clouds are studied in terms of the characteristics of element gradient variation inside and outside clouds. Finally, the identification for cloud front zone is verified by case study and the reasonable scope and identification criterion for cloud base height and cloud top height are concluded. The results show that the first-order and second-order derivative of temperature, humidity, and radar reflectivity are discontinuous in cloud front zone (they are not equal inside and outside the cloud front region), and the vertical gradient of SNR retrieved by wind profiler is also instable, which shows that the cloud boundary range with better spatial consistency can be obtained by different devices, based on the frontal theory. In addition, there are two indicators that can be utilized to distinguish the stratiform clouds from convective clouds. The first is the difference between the vertical gradient of temperature and humidity in clouds and that in ambient atmosphere, which is larger in convective clouds than that in stratiform clouds. The second is the fluctuation amplitude of the second-order derivative of reflectivity in clouds, which is also larger in convective clouds than that in stratiform clouds. The concept of cloud front zone can be used to comprehensively identify the common range of cloud height detected by different devices, indicating that there are consistent variation characteristics in a certain area near the cloud front zone for different devices. The similarity of cloud vertical structures retrieved by multi-source equipment observation are elucidated through the characteristics of cloud front zone, which is worth applying for collaborative observation of different devices.
- cloud front zone;
- second-order derivative;
- discontinuous variation;
- identification method

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References(32)

Figures and Tables

Fig. 1 MMCR-observed radar reflectivity from 0000 BT to 2359 BT(a) and from 1800 BT to 2100 BT(b) on 28 Aug 2017

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Fig. 2 Profiles of MMCR-observed reflectivity(a) and its first-order derivative(b), second-order derivative(c) at 1940 BT 28 Aug 2017

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Fig. 3 Profiles of radiosonde-observed temperature, relative humidity, relative humidity below 0℃, judgment entry cloud relative humidity threshold(a) and temperature, relative humidity first-order derivative(b), second-order derivative(c) at 2000 BT 28 Aug 2017

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Fig. 4 SNR(a) and its first-order derivative(b) from 0000 BT to 2359 BT, with SNR(c) and its first-order derivative(d) from 1800 BT to 2100 BT observed by WPR on 28 Aug 2017

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Fig. 5 Profiles of WPR-observed SNR(a) and its first-order derivative(b) at 1940 BT 28 Aug 2017

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Fig. 6 The same as in Fig. 1,but on 30 Jun 2018

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Fig. 7 The same as in Fig. 2,but at 1930 BT 30 Jun 2018

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Fig. 8 The same as in Fig. 3,but at 2000 BT 30 Jun 2018

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Fig. 9 The same as in Fig. 4,but on 30 Jun 2018

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Table 1 Identification criterion for cloud frontal zone on 28 Aug 2017 and 27 Jul 2017

	探测设备	云锋区范围	判识条件
云底高度	毫米波雷达	7.08~7.32 km(个例1) 5.76~6.00 km(个例2)	取极大值，从极大值迅速降为极小值的区域
	探空	7.25~7.34 km(个例1) 5.80~6.00 km(个例2)	取极大值，且R_H达饱和阈值，且
	风廓线雷达	7.00~7.47 km(个例1) 4.83~5.07 km(个例2)	信噪比的一阶导数取极大值
云顶高度	毫米波雷达	11.28~11.40 km(个例1) 10.32~11.16 km(个例2)	取极小值，从极小值迅速增为极大值的区域
云顶高度	探空	11.18~12.78 km(个例1) 11.05~11.77 km(个例2)	R_H接近未饱和阈值，且≤0，≥0

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Table 2 Identification criterion for cloud frontal zone on 30 Jun 2018 and 18 Aug 2017

	探测设备	云锋区范围	判识条件
云底高度	毫米波雷达	4.20~4.32 km(个例3) 5.04~5.16 km(个例4)	取极大值，或从极大值迅速降为极小值的区域
云底高度	探空	4.28~5.03 km(个例3) 4.93~5.12 km(个例4)	R_H达饱和阈值，且≤0，≥0
云顶高度	毫米波雷达	12.60~12.72 km(个例3) 9.12~9.84 km(个例4)	取极小值，或从极小值迅速增为极大值的区域
云顶高度	探空	12.50~13.50 km(个例3) 9.70~10.21km(个例4)	R_H低于饱和阈值，且≤0，≥0

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