School of Atmospheric Sciences, Chengdu University of Information Technology and Plateau Atmosphere and Environment Key Laboratory of Sichuan Province, Chengdu 610225, China Manuscript received: 2019-01-11 Manuscript revised: 2019-03-29 Manuscript accepted: 2019-05-13 Abstract:Deep convection systems (DCSs) can rapidly lift water vapor and other pollutants from the lower troposphere to the upper troposphere and lower stratosphere. The main detrainment height determines the level to which the air parcel is lifted. We analyzed the main detrainment height over the Tibetan Plateau and its southern slope based on the CloudSat Cloud Profiling Radar 2B_GEOPROF dataset and the Aura Microwave Limb Sounder Level 2 cloud ice product onboard the A-train constellation of Earth-observing satellites. It was found that the DCSs over the Tibetan Plateau and its southern slope have a higher main detrainment height (about 10?16 km) than other regions in the same latitude. The mean main detrainment heights are 12.9 and 13.3 km over the Tibetan Plateau and its southern slope, respectively. The cloud ice water path decreases by 16.8% after excluding the influences of DCSs, and the height with the maximum increase in cloud ice water content is located at 178 hPa (about 13 km). The main detrainment height and outflow horizontal range are higher and larger over the central and eastern Tibetan Plateau, the west of the southern slope, and the southeastern edge of the Tibetan Plateau than that over the northwestern Tibetan Plateau. The main detrainment height and outflow horizontal range are lower and broader at nighttime than during daytime. Keywords: main detrainment height, deep convection systems, Tibetan Plateau and its southern slope, A-train 摘要:深对流系统能够快速的将对流层下层的水汽和污染物输送到对流层上层和平流层下层,其主要溢出高度则决定了气块被深对流抬升后影响环境场的高度。基于A-train卫星编队中的CloudSat和Aura两颗卫星对青藏高原及其南坡深对流的联合观测,本文对深对流在青藏高原及其南坡的主要溢出高度以及出流对环境场冰水含量的影响进行了综合的分析研究。主要的结论如下:通过CloudSat CPR对云雷达回波的观测发现青藏高原及其南坡的深对流相比同纬度的其他地区有较高的主要溢出高度,深对流出流云砧分布在10-16 km。平均的主要溢出高度在青藏高原及其南坡分别为12.9和13.3 km。具有较高出流高度和较大出流范围的深对流则主要分布在青藏高原的中东部以及高原南坡。夜间发生的深对流相比白天出流高度较低但是出流范围更大。结合Aura MLS对冰水含量的观测也表明在深对流出流过程中环境场冰水含量的最大增加层也发生在178 hPa (约13 km)。深对流对气候态的平均冰水路径有显著影响,去除深对流的影响后,夏季平均冰水路径将减少16.8%。 关键词:主要溢出高度, 深对流系统, 青藏高原及其南坡, A-train
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2.1. Datasets
We used CloudSat and MLS data for June?August 2006?16, except for the year 2011 when a battery anomaly caused the CloudSat satellite to stop collecting data and to lose formation with the A-train. The datasets include 2B-GEOPROF_R04 (http://cloudsat.atmos.colostate.edu/data) and MLS-L2GP-IWC_v04 (https://daac.gsfc.nasa.gov/datasets/ML2IWC_V004). CloudSat, which forms part of the Afternoon Constellation or A-train of Earth-observing satellites, carries the CPR instrument, which has a high sensitivity toward smaller cloud droplets (Stephens et al., 2008). According to the CloudSat data, an accurate detrainment height and the anvil of DCSs can be obtained and detected. The CPR instrument can therefore directly observe the detrained anvil to obtain the main detrainment height. The Aura MLS, which follows about 15 minutes behind CloudSat, can detect changes in the atmospheric components when the detrainment caused by a DCS is recognized by the CPR (Livesey et al., 2006). Such dual observations are beneficial in obtaining a comprehensive view of the outflow process. The A-train includes several Earth-observing satellites that follow the close orbital track within minutes of each other. They provide comprehensive information about a wide variety of climate parameters (Savtchenko et al., 2008; L'Ecuyer and Jiang, 2011). CloudSat launched on 28 April 2006. It successfully joined the A-train alignment on 1 June 2006 and exited the A-train on 26 February 2018. The CPR carried onboard the CloudSat platform was designed to have a strong cloud detection sensitivity for precipitation and cloud particles, with an along-track resolution of 1.9 km and a vertical resolution of 240 m (Stephens et al., 2002, 2008). The Aura satellite was successfully launched on 25 July 2004 and follows about 15 minutes behind CloudSat in the A-train satellite formation. The MLS instrument onboard the Aura satellite uses microwave emissions to measure trace amounts of gases, volcanic eruptions, cloud ice, temperature and geopotential height in the upper troposphere and stratosphere (Waters et al., 2006; Wu et al., 2008).
2 2.2. Methods -->
2.2. Methods
The radar echo from the backscattering of cloud and rain droplets can be used to recognize DCSs, including the DCC, stratiform precipitation and the anvil. The CloudSat CPR has been used to study deep convection (Chung et al., 2008; Iwasaki et al., 2010; Luo et al., 2011), overshooting (Luo et al., 2008; Bedka et al., 2012; Iwasaki et al., 2012; Takahashi and Luo, 2012), detrained anvils (Takahashi and Luo, 2012) and aerological cirrus clouds (Sassen et al., 2009). We detected DCSs over the Tibetan Plateau and its southern slope using the following methods. We used a cloud mask of > 30 to obtain high-quality data (Mace, 2007). Radar echo data were used to detect the DCC and the cloud-top height of the DCC (DCC_CTH) required to ensure that the DCS could lift an air parcel to > 14 km, the height at which the UTLS is affected (Highwood and Hoskins, 1998; Folkins et al., 1999). The distance between the cloud base and the surface was < 3 km and the maximum echo value was > 10 dBZ to exclude clouds from non-DCSs. We looked for the detrained anvil near the DCC. The anvil should be a 4?5 km thick heterogeneous layer (Cetrone and Houze, 2009; Yuan and Houze, 2010; Yuan et al., 2011) and the cloud base height of the anvil (anvil_CBH) should be > 9 km to preclude radar echoes from stratiform precipitation. The height of maximum echo inside the anvil is the height of the maximum mass detrainment (anvil_maxMass), which means that the largest amount of air is detrained in this layer (Takahashi and Luo, 2012). We obtained data for 1241 DCSs over a 10-year period. A total of 669 DCSs showed clear detrainment, which requires a horizontal scale of the anvil > 20 km (see Fig. 2). Figure2. An example of a DCS that generated on 21 August 2008. The gray shadow represents the topography, and the red lettering annotates the cloud top of the DCC and the anvil maximum mass detrainment.
The Aura satellite follows CloudSat on an adjacent track. The Aura MLS measures the change in the ambient IWC after the CloudSat CPR has probed the DCSs. The IWC detrained by the DCSs has a short life cycle of about 1?2 days (Luo and Rossow, 2004). The distribution of the IWC is more directly affected by the DCS than other gaseous pollutants (e.g., CO, HCN, CH3Cl and chlorofluorocarbons) with a longer life cycle.