J. Meteor. Res.  2019, Vol. 33 Issue (3): 375-399   PDF    
The Chinese Meteorological Society

Article Information

ZHAO, Ping, Yueqing LI, Xueliang GUO, et al., 2019.
The Tibetan Plateau Surface–Atmosphere Coupling System and Its Weather and Climate Effects: The Third Tibetan Plateau Atmospheric Science Experiment. 2019.
J. Meteor. Res., 33(3): 375-399

Article History

Received November 14, 2018
in final form March 13, 2019
The Tibetan Plateau Surface–Atmosphere Coupling System and Its Weather and Climate Effects: The Third Tibetan Plateau Atmospheric Science Experiment
Ping ZHAO1, Yueqing LI2, Xueliang GUO1, Xiangde XU1, Yimin LIU3, Shihao TANG4, Wenming XIAO5, Chunxiang SHI5, Yaoming MA6, Xing YU7, Huizhi LIU3, La JIA8, Yun CHEN9, Yanju LIU10, Jian LI1, Dabiao LUO8, Yunchang CAO11, Xiangdong ZHENG1, Junming CHEN1, An XIAO12, Fang YUAN5, Donghui CHEN5, Yang PANG5, Zhiqun HU1, Shengjun ZHANG1, Lixin DONG4, Juyang HU4, Shuai HAN5, Xiuji ZHOU1     
1. State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing 100081;
2. Chengdu Institute of Plateau Meteorology of the China Meteorological Administration, Chengdu 610072;
3. Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029;
4. National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081;
5. National Meteorological Information Center, China Meteorological Administration, Beijing 100081;
6. Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101;
7. Meteorological Institute of Shaanxi Province, Xi’an 710014;
8. Meteorological Observatory of Tibet Autonomous Region, Lhasa 850000;
9. National Meteorological Center, China Meteorological Administration, Beijing 100081;
10. National Climate Center, China Meteorological Administration, Beijing 100081;
11. Meteorological Observation Center, China Meteorological Administration, Beijing 100081;
12. Jiangxi Meteorological Observatory, Nanchang 330096
ABSTRACT: The Tibetan Plateau (TP) is a key area affecting forecasts of weather and climate in China and occurrences of extreme weather and climate events over the world. The China Meteorological Administration, the National Natural Science Foundation of China, and the Chinese Academy of Sciences jointly initiated the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-III) in 2013, with an 8–10-yr implementation plan. Since its preliminary field measurements conducted in 2013, routine automatic sounding systems have been deployed at Shiquanhe, Gaize, and Shenzha stations in western TP, where no routine sounding observations were available previously. The observatio-nal networks for soil temperature and soil moisture in the central and western TP have also been established. Meanwhile, the plateau-scale and regional-scale boundary layer observations, cloud–precipitation microphysical observations with multiple radars and aircraft campaigns, and tropospheric–stratospheric air composition observations at multiple sites, were performed. The results so far show that the turbulent heat exchange coefficient and sensible heat flux are remarkably lower than the earlier estimations at grassland, meadow, and bare soil surfaces of the central and western TP. Climatologically, cumulus clouds over the main body of the TP might develop locally instead of originating from the cumulus clouds that propagate northward from South Asia. The TIPEX-III observations up to now also reveal diurnal variations, macro- and microphysical characteristics, and water-phase transition mechanisms, of cumulus clouds at Naqu station. Moreover, TIPEX-III related studies have proposed a maintenance mechanism responsible for the Asian " atmospheric water tower” and demonstrated the effects of the TP heating anomalies on Afri-can, Asian, and North American climates. Additionally, numerical modeling studies show that the Γ distribution of raindrop size is more suitable for depicting the TP raindrop characteristics compared to the M–P distribution, the overestimation of sensible heat flux can be reduced via modifying the heat transfer parameterization over the TP, and considering climatic signals in some key areas of the TP can improve the skill for rainfall forecast in the central and eastern parts of China. Furthermore, the TIPEX-III has been promoting the technology in processing surface observations, soundings, and radar observations, improving the quality of satellite retrieved soil moisture and atmospheric water vapor content products as well as high-resolution gauge–radar–satellite merged rainfall products, and facilitating the meteorological monitoring, forecasting, and data sharing operations.
Key words: Tibetan Plateau     field observation     data processing     weather and climate     numerical forecasting    
1 Introduction

The Tibetan Plateau (TP) has the highest altitude and the most complex topography in the world, and is one of the key areas affecting extreme weather and climate events in China. It has important impacts on the Asian monsoon and the energy and water cycles in the monsoon region (Ye and Gao, 1979; Luo and Yanai, 1984; Yanai et al., 1992; Wu and Zhang, 1998; Wu et al., 2007; Zhao and Chen, 2001a,b; Xu et al., 2008a; Zhou et al., 2009). The strong ascending motion on the plateau transports water vapor and pollutants upwards, affecting changes in plateau tropospheric–stratospheric ozone and aerosol concentrations (Zhou et al., 1995; Kim et al., 2003; Zheng et al., 2004; Vernier et al., 2015). In addition, the variability of the plateau heat source is closely related to the hemispherical atmospheric circulation system and the Pacific Ocean air–sea interaction (Zhao and Chen, 2000; Liu et al., 2007, 2012; Zhao et al., 2007, 2009; Nan et al., 2009; Wu et al., 2009; Zhou et al., 2009; Duan et al., 2012). Therefore, study of the TP influence on the weather and climate of Asia and even the world is of great scientific significance and has good prospects for applications to improving the ability of wea-ther and climate prediction over the East Asian monsoon region.

The sparse observational network and the complex terrain and underlying surface features on the plateau limit the representation of the observation positions. Meanwhile, the satellite retrieval products have large uncertainties on the plateau. These drawbacks restrict the development of the TP meteorology. In order to make up for the lack of observational data in the TP, Chinese and foreign scientists have carried out many atmospheric science experiments over the TP (Table 1).

Table 1 Information on the previous Tibetan Plateau (TP) atmospheric science experiments
Name Key observational contents Time
The First Qinghai–Xizang Plateau Meteorology
Surface heat and radiation balance observations and intensive
 observations of routine surface and upper-air sounding
 meteorological elements
May–August 1979
China–Japan Cooperative Research on Asian
 Monsoon Mechanisms
Surface heat and radiation balance observations, boundary
 layer observations, and ice/snow/frozen soil observations
The Second TP Atmospheric Science Experiment Surface heat and radiation balance observations, boundary
 layer observations, and intensive observations of routine
 surface and upper-air sounding meteorological elements
May–August 1998
Global Water and Energy Cycle Asian Monsoon
 Experiment: Study on Land Surface Physical
 Process in the TP
Surface heat, radiation, and moisture observations, boundary
 layer observations, intensive observations of routine surface
 and upper-air sounding meteorological elements,
 and observations of cloud and precipitation
May–September 1998
The Global Coordinated Enhanced Observing
 Period (CEOP) Asia–Australia Monsoon
 Project (CAMP) on the TP
Surface heat, radiation, and moisture observations, boundary
 layer observations, intensive observation of routine surface
 and upper-air sounding meteorological elements,
 and observations of cloud and precipitation
A New Integrated Observational System over
 the TP and the Surrounding Areas, supported by
 the Japan International Cooperation Agency
Surface heat balance observations, boundary layer observations,
 and atmospheric heat, energy, and water observations

The first Qinghai–Xizang Plateau Meteorology Experiment (QXPMEX-1979) was conducted by the Chinese Academy of Sciences (CAS) and the Central/China Meteo-rological Administration (CMA) from May to August 1979 (Tao et al., 1986), which has promoted the study of TP meteorology in the 1980s. From March 1993 to March 1999, under the support of the program—China–Japan Cooperative Research on Asian Monsoon Mechanisms, the CMA, together with Chinese and foreign scientists, conducted a field observation experiment on the plateau (Chen, 1999). From May to August 1998, the CMA and the CAS jointly implemented the Second TP Atmosphe-ric Science Experiment (TIPEX-II) (Chen et al., 1999). From May to September 1998, Chinese and Japanese scientists carried out the “Global Water and Energy Cycle Asian Monsoon Experiment: Study on Land Surface Physical Process in the TP” (Wang, 1999) in central plateau. In the 21st century, under the support of “The Glo-bal Coordinated Enhanced Observing Period (CEOP) Asia–Australia Monsoon Project (CAMP) on the TP” and the “China Tibetan Observation and Research Platform (TORP),” the CAS conducted intensive observational experiments in central plateau in 2002–04 (Ma et al., 2006, 2008). Supported by the Japan International Cooperation Agency (JICA) project, Chinese and Japanese scientists implemented “A New Integrated Observational System over the TP and the Surrounding Areas” from 2006 to 2009 (Xu et al., 2008b; Zhang et al., 2012).

Although the past field observation experiments have achieved a series of results with international impacts, the problem of sparse observatories over the plateau (especially the middle and west) is still not well resolved, the western TP still lacks routine sounding observations of atmospheric elements, and there is still a lack of direct observations of tropospheric cloud microphysical features and the tropospheric–stratospheric exchange processes over the TP. At the same time, the atmospheric reanalysis data and the multiple satellite retrieval products are also highly uncertain over the plateau (Li et al., 2012; Zhu et al., 2012; Su et al., 2013; Zeng et al., 2016; Yu et al., 2018). Because the existing reanalysis products have only assimilated limited sounding measurements over the TP, there is a wide divergence in calculating the TP water vapor transport using different reanalysis datasets (Feng and Zhou, 2012). The TP region is one of the regions with the most sparse observation data and there is a great uncertainty in the estimation of the TP heating intensity (Ye and Gao, 1979; Zhao and Chen, 2000; Zhang et al., 2016), which restricts the understanding of the plateau earth–atmosphere physical processes and water cycle, and hinders the understanding of the weather and climate effects of the plateau heating. Besides, there is a lack of objective understanding of the activity of atmospheric circulation systems over the TP. The effects of the plateau tropospheric–stratospheric physical–chemical processes and their influences are still not clear. Thus, the existing numerical models have serious drawbacks in reflecting the plateau earth–atmosphere coupled processes (especially the cloud–precipitation physical processes) and their effects (Zhou et al., 2004; Wu and Zhou, 2011; Qiu et al., 2013; Hu et al., 2014; Zhuo et al., 2016; Wan et al., 2017), and the TP and the surrounding areas are also one of the areas in the world with the lowest numerical prediction level.

In order to further strengthen the research on TP meteorology and related application in the meteorological operation, the CMA, the National Natural Science Foundation of China (NSFC), and the CAS jointly promoted the approval of the Third TP Atmospheric Science experiment (TIPEX-III) in 2013, with an 8–10-yr implementation plan. A preliminary experiment was conducted in 2013 and the TIPEX-III was officially launched in 2014. This paper introduces the TIPEX-III overall objectives, field observation layout, research content, uniqueness, and preliminary achievements.

2 TIPEX-III objectives, tasks, and uniqueness

TIPEX-III aims to construct a comprehensive observation system that includes intensive surface observations and satellite retrievals in the plateau and its surrounding areas, to conduct the ground-based, air-based, and space-based observations of the land surface, boundary layer, tropospheric–stratospheric processes (Fig. 1a), to promote the development of data processing technology, to improve the accuracy of satellite retrieval products and multi-source merged data products, to develop models and parameterization methods of land surface–boundary layer processes, cloud–precipitation physical processes, and tropospheric–stratospheric exchange processes over the complex terrain of TP, and to deepen the understanding of the TP effect on weather and climate in China. TIPEX-III also aims to promote the transformation of research results into meteorological operations and the development of meteorological operation technology.

Figure 1 (a) Schematic diagram of the main physical processes taking place from land surface to the stratosphere over the TP and (b) the general architecture of the Third Tibetan Plateau Atmospheric Science Experiment (TIPEX-III).

In order to achieve the above objectives, TIPEX-III plans to implement targeted intensive field observations based on the routine operation monitoring system, to establish experiment observation networks, and to promote the development of observational data quality control technology, merged technology, and regional reanalysis technology. By using statistical analysis, physical quantity diagnostic analysis, and numerical simulation me-thods, TIPEX-III plans to develop land surface–boundary layer process models, parameterization schemes for cloud–radiation and cloud–precipitation physical processes, and parameterization schemes for stratospheric–tropospheric exchange processes that can accommodate unique plateau attributes, and finally promotes the development of numerical forecasting models. TIPEX-III will also investigate the evolutions of weather and climate over the TP and related mechanisms, the multi-scale interaction mechanisms between the plateau and downstream weather systems, the effects of plateau weather systems on severe weather in China, the application of numerical weather forecast products, and the prediction theories and technology on effects of TP on drought and flood in China, thereby promoting the application of data information in the TP key areas to weather and climate forecast operations (Fig. 1b).

In the past, two TP atmospheric science experiments (QXPMEX-1979 and TIPEX-II) have been carried out. Their field intensive observations were concentrated on the TP land surface and boundary layer, and had short intensive observation periods (usually one year). Based on the experience of the previous two science experiments, the TIPEX-III extends its observations from land surface and boundary layer to the troposphere and stratosphere, so as to provide basic data for in-depth studies of the TP land–atmosphere interaction and for developing land surface–atmosphere coupled model systems.

3 Configuration and progress of TIPEX-III field observation

Considering the heterogeneity in terrain elevations and land-cover types, and the logistical challenges of maintaining observation sites, TIPEX-III constructs a TP- and a Naqu regional-scale intensive observation network and uses multiple ground-based radar and aircraft observations to perform intensive observations for the cloud–precipitation physical processes in the TP area where there are frequent activities of cloud and precipitation. Detailed information on the observation data is shown inTable 2. These data are stored under the title—“The Basic Data Service Special Collection for the Tibetan Plateau Atmospheric Scientific Experiment” and have been made available at http://data.cma.cn/tipex.

Table 2 The TIPEX-III observation information
Name Content and time
Plateau-scale soil moisture observation Soil moisture observations at depths of 10, 20, 30, 40, and 50 cm from January 2015 to
 December 2016.
Regional-scale soil temperature and
 humidity observations
The observation network at Ali consists of 17 sites, with operation started from
 December 2016. The observation network at Naqu consists of 33 sites and started
 from August 2015. Both networks observe soil temperature and humidity at
 depths of 2, 5, 10, 20, and 30 cm.
Mobile observations Surface features, vegetation coverage, soil dielectric parameters, emissivity, total atmospheric
 ozone, AOD. Observations made every 50–100 km. Along the Linzhi–Lhasa–Naqu line
 in summer 2014, along the Linzhi–Lhasa–Naqu–Ali line in summer 2015, and
 along the Naqu–Changdu–Bomi-Linzhi–Lhasa line in summer 2016.
Boundary layer observation system Observations of near-ground wind direction and speed, three-dimensional ultrasonic pulsating
 values of wind speed, temperature, water vapor, and CO2, upward and downward longwave
 and shortwave radiation at the surface, soil temperature and humidity at depths of 5, 10, 20,
 50, and 100 cm, soil heat flux at 5 cm, and precipitation. Observation sites and periods:
 Shiquanhe, Namco, Naqu, Ando, Linzhi, Litang, Dali, and Wenjiang during July 2014–
 December 2016; Bange, Biru, Jiali, and Nierong during July 2014–March 2016;
 Linzhou during August 2015–December 2016.
Intensive sounding observation
 (Vaisala portable sounding system)
Observing the tropospheric pressure, temperature, humidity, and wind direction and speed twice
 (at 0800 and 2000 Beijing Time) a day during July–August 2014.
Intensive sounding observation
 (automatic sounding system)
Observing the tropospheric pressure, temperature, humidity, and wind direction and speed twice
 (0800 and 2000 Beijing Time) a day from November 2014, but no observation in winter.
Multiple ground-based radar observations
 for cloud–precipitation physical
Detecting radar echo intensity, cloud echo intensity, radial velocity, velocity spectrum width,
 depolarization factor, correlation coefficient, power spectral density function, temperature and
 water vapor profiles, cloud base height, boundary layer height, raindrop spectrum, rainfall,
 and atmospheric liquid water content. Observation periods: July–August 2014, July–August
 2015, and July–August 2016.
Aircraft equipment observations for cloud–
 precipitation physical characteristics
Detecting air pressure, temperature, humidity, wind direction and speed, vertical velocity,
 ambient temperature; size and concentration of cloud particle, cloud water droplet; ice particle
 size, concentration, and shape; rain drop size, concentration, and image;
 liquid water content, total water content, and ice accretion; in July 2014.
Tropospheric–stratospheric ozone,
 aerosol, and water vapor observations
Detecting air pressure, temperature, humidity, wind, and water vapor profile from land surface to
 28-km altitude, aerosol backscattering coefficient, total atmospheric ozone, and vertical
 distribution of ozone. Observation site and time: Linzhi, June–July 2014; Shiquanhe, May–
 September 2016; Lhasa and Golmud, July–August 2016.
3.1 Observation of land surface–boundary layer features

The existing meteorological operation observation stations for soil moisture are mainly located in the eastern TP and its surrounding areas. To improve the capability of soil moisture monitoring on the TP, TIPEX-III and the Tibet Autonomous Region Meteorological Bureau newly established 46 observation sites in central and western TP (Zhao et al., 2018) in accordance with the CMA operational specifications, which basically constitutes a TP-scale soil moisture observation network. To correct satellite remote sensing products, TIPEX-III designs a number of “multi-level and multi-scale” automatic observation networks (Zhao et al., 2018) for surface and soil temperature and humidity, and have built two regional networks at Naqu and Ali. The data collector suitable to frozen soil environment and the remote management, the real-time analysis system, and the remote mobile monitoring system for the multi-scale network observation data developed by TIPEX-III were applied to solve the problems such as the harsh environment in the alpine region, scattered observation sites, and difficulties in manual maintenance. The collected soil samples at Naqu were also used to calibrate the instrument to ensure the accuracy of the observation. The Naqu regional network (coverage of approximately 50 km) consists of 33 observation sites and started observation in August 2015 (Zhao et al., 2018). The Ali regional network consists of 17 observation sites and launched observation in December 2016. In addition, to provide more detailed information on the TP surface characteristics, TIPEX-III also designs mobile observations for surface features, vegetation coverage, soil dielectric parameters, emissivity, total atmospheric ozone, and atmospheric optical depth (AOD), and collects samples of soil and herbaceous vegetation for different surface types, with distance of 50–100 km between two sites and a total of more than 20 observation sites. TIPEX-III has completed the observation along the Linzhi–Lhasa–Naqu line in summer 2014, with a total length of more than 1000 km; along the Linzhi–Lhasa–Naqu–Ali line in summer 2015, with a total length of more than 5000 km; and along the Naqu–Changdu–Bomi–Linzhi–Lhasa line in summer 2016.

In order to study the heterogeneity of the land–atmosphere interaction, TIPEX-III designs plateau- and Naqu regional-scale boundary layer observation networks. The plateau-scale network consists of 10 multi-layer boundary layer towers at Shiquanhe, Gaize, Naqu, Linzhou, Linzhi, Tuotuohe, Maqu, Litang, Dali, and Wenjiang (Fig. 2), with the horizontal distance between two towers of about 500 km. The observed data are used to analyze differences in the land surface–boundary layer structures between the eastern and western parts of the TP. The regional-scale network was built in an area of 300 km × 200 km near Naqu where cloud and precipitation occur frequently, including seven observation sites at Naqu, Bange, Namucuo, Anduo, Nierong, Jiali, and Biru. This regional network is used to compare the plateau- and regional-scale heterogeneity for understanding high-resolution land surface–boundary layer features and their effects on mesoscale systems in the TP (Zhao et al., 2018). TIPEX-III conducted observations at Shiquanhe, Namu-cuo, Naqu, Anduo, Linzhi, Litang, Dali, and Wenjiang from July 2014 to December 2016, at Bange, Biru, Jiali, and Nierong from July 2014 to March 2016, and at Linzhou from August 2015 to December 2016.

Figure 2 Distribution of planetary boundary layer (PBL) observation sites (purple stars) and atmospheric composition observation sites (blue triangles for TIPEX-III and black triangles for routine meteorological observations), in which the blue solid box is for a regional PBL network near Naqu, black dashed boxes indicate the observation areas for cloud–precipitation properties, and the black long-dashed line indicates the aircraft flight path from Golmud to Naqu. The thin solid curves on the map denote the rivers.
3.2 Intensive tropospheric sounding observation

After low vortex systems in the TP generate, they often move out of the TP and move along the Yangtze River basin (near 30°N), which affects weather and climate in central and eastern China. In order to fill the gap of limited routine operational sounding stations over the western plateau (Fig. 3), TIPEX-III uses the Vaisala portable sounding system to carry out intensive routine sounding observations twice a day [0800 Beijing Time (BT) and 2000 BT] at Shiquanhe, Gaize, and Shenzha stations approximately along 30°N from July to August 2014. With the support of the CMA, TIPEX-III has built new automatic sounding stations at Shiquanhe, Gaize, and Shenzha stations, respectively (Zhao et al., 2018), carried out intensive observations twice a day since November 2014, and established the trial operation. Together with the meteorological operational stations in the eastern TP, these new stations initially constitute a plateau-scale sounding observation network. In addition, in order to analyze the formation and development mechanisms of convective precipitation weather in the TP–Yangtze River basin frequently occurring in the afternoon, TIPEX-III conducted a routine sounding intensive observation at 1400 BT (Fig. 3) at about 39 stations (including Shiquanhe, Gaize, and Shenzha stations) in the TP and its downstream areas to the south of 40°N in summers of 2015 and 2016. To obtain the data in a key area of water vapor channels from the Indian Ocean to East Asia, TIPEX-III also designed the intensive sounding observations at Gongshan, Jinchuan, and Litang (Fig. 3) on the southeastern slope of the TP. Furthermore, to obtain sounding observation data in southwestern China where low vortexs occur frequently, the Chengdu Institute of Plateau Meteorology of the CMA conducted intensive sounding observations with global positioning system (GPS) at Jiulong and Jinchuan of Sichuan Pro-vince in summers of 2014 and 2015.

Figure 3 Distribution of meteorological sounding stations, in which blue triangles are the TIPEX-III intensive observation sites, red and black dotes are routine operational sounding sites, and black dots also indicate intensive sounding observation sites at 1400 BT. The thin so-lid curves on the map denote the rivers.
3.3 Observation of tropospheric cloud–precipitation physical characteristics

Mesoscale low vortices and convective systems frequently occur in the central and eastern parts of the TP; and through the southeastern TP, water vapor from the Bay of Bengal enters the central and eastern parts of China. Therefore, TIPEX-III uses multi-type ground-based special radar, airborne instruments, and the operational Doppler weather radars to carry out intensive observations of cloud–precipitation physical features at Naqu of the central TP, Linzhi of the southeastern TP, and Daocheng of the eastern slope of the TP (Fig. 2). From July to August 2014, the observation of cloud–precipitation microphysical characteristics was carried out in an area of 200 km × 200 km near Naqu with multi-type ground-based radar and airborne equipment (Zhao et al., 2018). Meanwhile, TIPEX-III designed a coordinated observation scheme between aircrafts and ground-based radars to avoid the interference to aircraft signals from the multi-type ground-based radar signals; a coordinated observation scheme between aircrafts and satellites, which carries out aircraft observations along the moving direction of the CloudSAT or A-Train satellite sub astral point; and the flight paths of aircraft inside the cloud, for example, in a spiral descent from the cloud top or in a random fashion, which ensures better observation of the cloud characteristics. From 15 July to 31 August 2015, TIPEX-III and Chengdu University of Information Science and Technology jointly conducted cloud–precipitation physical characteristic observations using multi-type ground-based radars at Naqu and Linzhi. From July to August 2016, TIPEX-III, Chengdu Institute of Plateau Meteorology, Lanzhou Institute of Arid Meteorology, Wuhan Institute of Heavy Rain, Nanjing University of Information Science & Technology, Chengdu University of Information Technology, and Anhui Provincial Office of Weather Modification jointly performed a collaborative intensive observation with multi-type radars and sounding instruments from the eastern slope of the TP to the lower reaches of the Yangtze River, including Dao-cheng, Nanchong, Suining, Jiulong, and Jinchuan of Si-chuan Province; Wuhan, Xianning, Jingmen, Xiantao, and Huangshi of Hubei Province; Nanjing of Jiangsu Province; and Shouxian and Dingyuan of Anhui Province.

3.4 Intensive observation of atmospheric ozone, aerosol, and water vapor vertical profiles

It is known that strong ascending motion occurs in the troposphere over southeastern TP, weakening toward the north and west (Tao et al., 1986; Cong et al., 2002). In order to understand the influence of the TP vertical motion on the spatial distribution of atmospheric ozone, aerosol, and water vapor, TIPEX-III designed the intensive observation for tropospheric–stratospheric aerosols, ozone, and water vapor at Shiquanhe, Lhasa, Linzhi, Tuotuohe, Golmud, Mangya, and Xining meteorological stations (Fig. 2). Using balloon borne package instruments and ground-based remote sensing measurements, TIPEX-III carried out intensive observations for atmospheric ozone, aerosol, and water vapor at Linzhi from June to July 2014 and supported the intensive observations at Shiquanhe (from May to September) and Lhasa and Golmud (from July to August) (Zhao et al., 2018).

4 Progress in TIPEX-III theoretical research 4.1 Land surface–boundary layer characteristics

Based on the TIPEX-III plateau-scale soil moisture observation data, Wang et al. (2016) pointed out that the surface soil moisture generally increases from the western TP to the Sichuan basin, with 0.05 m3 m–3 over the western TP, 0.11–0.46 m3 m–3 over the central TP, 0.32–0.40 m3 m–3 over the southeastern TP, and 0.38 m3 m–3 in the Sichuan basin. In the central TP, the soil moisture in each layer shows a significant seasonal variation, peaks in July and September, and starts to decrease in October. In April, the soil moisture above the depth of 10 cm has an obvious diurnal variation, with the lowest value from 0800 to 1000 BT and the largest value from 1900 to 2000 BT, but the diurnal variation of the soil moisture is relatively small in July. In addition, the relationship between soil moisture and temperature is complex, with a negative correlation in summer and a positive correlation in January, April, and October. The soil moisture above the depth of 20 cm increases with depth in winter and spring, while it decreases with depth in summer and autumn (Li B. et al., 2018).

By combining the theoretical formula with the observations on ice/snow and gravel surfaces at the Rongbu Temple in the north slope of the Mount Everest, Ye and Gao (1979) proposed that the turbulent heat exchange coefficient (Ch) be of (6–10) × 10–3 at the surface of the TP, and an average value of 8 × 10–3 was used to estimate the surface sensible heat flux (SH) over the TP. Later, Yang and Guo (2011) re-estimated the TP SH using a Ch value of (4–5) × 10–3 and obtained a lower value of SH in the central (mainly with grassland and meadow surfaces) and western (mainly with a bare soil surface) parts of the TP, compared to Ye and Gao (1979). Recently, Wang et al. (2016) used the TIPEX-III ultrasonic pulsating observations in summer 2014 and obtained a new Ch estimate. It is found that Ch is mainly (2–4) × 10–3 at each station of the central and western TP, and has a smaller varying range compared to the momentum exchange coefficient (Cd) of (3–11) × 10–3 (Table 3). SH is generally 5–40 W m–2 at each station of the central TP in August, with an average of 18 W m–2, and it is 40–70 W m–2 in the western TP, with an average of 56 W m–2 (Zhao et al., 2018). The new estimates are smaller than before. In addition, TIPEX-III analyzes the characteristics of effective aerodynamic roughness length and zero plane displacement height using the wind profile data and the GPS sounding data at the Mount Everest, Shiquanhe, and Litang. It is also pointed out that the effective aerodynamic roughness in the TP region is 1–2 orders larger compared to the local scale (Han et al., 2015), and the difference in surface sensible heat inside the regional network in the central TP is significantly smaller compared to that be-tween the eastern and western TP (Zhao et al., 2018), which may be related to a greater difference in climatic conditions between the eastern and western TP.

Table 3 Turbulent exchange coefficients for surface momentum (Cd; ×10–3) and heat (Ch; ×10–3) observed during TIPEX-III (Wang et al., 2016)
Station name Underlying surface condition Ch Cd
Shiquanhe Relatively flat bare soil 2.4 9.6
Anduo Alpine grassland 2.4 2.9
Bange Alpine grassland 2.7 3.4
Biru Alpine grassland 3.4 10.1
Namucuo Alpine grassland 2.2 3.8
Naqu Alpine grassland 2.8 4.4
Bierong Alpine grassland 3.2 3.8
Jiali Relatively flat alpine meadow 3.8 10.5
Linzhi Alpine meadows with rare shrubs and trees 6.0 8.0
Dali Relatively flat farmland 4.5 11.6
Wenjiang Flat farmland 4.7 12.6

The TP SH shows a significant diurnal variation, and the peak value of the diurnal variation appears at 1300 local time (LT) and decreases from west to east, with a peak of 200 W m–2 in the west, a peak of 70–130 W m–2 in the middle, and a peak of < 70 W m –2 in the Sichuan basin. For the surface latent heat flux (LE), the peak value of the diurnal variation is only 20 W m–2 in the western TP, while it is 150–250 W m–2 in central and southeastern TP and the Sichuan basin (Wang et al., 2016). The diurnal variations of the TP surface heat fluxes are closely related to weather conditions. On sunny days, the SH diurnal variation is obvious and greater compared to LE. On rainy days, their diurnal variations are small and the diurnal variation of LE is greater than that of SH. The activities of the South Asian monsoon can adjust the diurnal variation of surface heat fluxes by affecting the TP weather conditions. When warm and moist southerly flows in front of the South Asian monsoon trough prevail over the southeastern TP, the diurnal variations of the local SH and shortwave radiation are small (Li et al., 2016). In addition, before the onset of the South Asian monsoon, SH plays a dominant role, increases rapidly, and shows an eastward decreasing feature, while LE intensity is smaller. After the monsoon onset, the TP SH weakens and the TP LE increases rapidly and shows an eastward increasing feature. After the monsoon retreat, the SH and LE values are equivalent (Han et al., 2019).

In order to estimate surface heat fluxes in the whole plateau region, TIPEX-III estimated the components of surface heat balance in the TP during 2001–12 through combining the intensive and routine meteorological observation data with satellite remote sensing data and the boundary layer model. The new estimates are very close to the observed, with a relative error of less than 10%, which suggests that the new method is reliable.Figure 4 shows the linear trends of the components of surface heat balance in the TP. It is seen that SH generally weakens and surface net radiation, LE, and soil heat flux exhibit increasing trends (Han et al., 2017).

Figure 4 Variation trends categorized in four significance groups as indicated by the bottom color bar at the 90% confidence level for the annual mean (a) net radiation flux, (b) soil heat flux, (c) sensible heat flux, and (d) latent heat flux over the TP during 2001–12 (Han et al., 2017).

TIPEX-III compares the observed surface heat fluxes with those from the large-aperture scintillometer (LAS) and eddy correlation meter (EC). It is found that the LAS SH and LE values have a strong correlation with those of EC, with correlation coefficient of 0.85 and 0.90, respectively. However, there are some differences between these two observational results. For example, the LAS SH (LE) is smaller (larger) than EC SH (LE) during the daytime but the case is opposite at night. The LAS SH is smaller than that of EC in the wet season (May–August, October) and the LAS LE is smaller than that of EC in the dry season (April). In other months, the LAS SH and LE are larger than those of EC (Xu et al., 2017). Moreover, TIPEX-III also evaluated the performance of the TP SH and LE of the NCEP-Climate Forecast System Reanalysis (CFSR), ECMWF Interim Re-Analysis (ERA-Interim), Japanese 55-yr Reanalysis (JRA55), NCEP–NCAR reanalysis (NCEP1), and NCEP–U.S. Department of Energy reanalysis (NCEP2) datasets. The results show that root mean square errors (RMSE) of the ERA-Interim SH and LE are smallest and the errors of the other four reanalysis datasets are generally comparative. In the western TP, these reanalysis SH RMSE is 53 W m–2 on average, with the maximum of about 60 W m–2. In the central TP, the ERA-Interim SH RMSE is 9 W m–2. In the whole TP, the atmospheric reanalysis LE values have a larger error in general, compared to SH (Fig. 5).

Figure 5 Root mean square error (RMSE) of surface (a) sensible and (b) latent heat fluxes between observation and reanalysis (ERA-Interim with a horizontal resolution of 0.75° × 0.75°, NCEP1 with a horizontal resolution of 1.875° × 1.905°, NCEP2 with a horizontal resolution of 1.875° × 1.905°, CFSR with a horizontal resolution of 1.875° × 1.905°, and JRA55 with a horizontal resolution of 1.25° × 1.25°) averaged from 1 to 31 August 2014.
4.2 Cloud–precipitation processes over the TP and sub-regional atmospheric water cycle characteristics

Li et al. (2019) showed the occurrence frequency (number of convection occurrences divided by the total sample number) of convective activity (defined as black-body brightness temperature TBB < –32°C) over the TP. The TP convective activity mainly occurs in July and August, occupying more than 21% of the time in July. It mainly appears in central TP (from Shenzha to Naqu), with the convection center obviously independent of that in the South Asian monsoon region. On a climatic average, the center of the Fengyun (FY)-2E geostationary meteorological satellite TBB lower than –15°C does not show a remarkable stretch from the south Asian monsoon region to the central and western TP. On the contrary, the low TBB center in the eastern TP propagates southward. These results imply that the TP convective activity is not originated from the northward movement of the South Asian convection, indicating the independence of the TP convection. This is different from the result of Dong et al. (2016), who reported that the South Asian convective storm may frequently move into the southwestern TP.

The occurrence and development of convective clouds and precipitation over the TP are closely related to the local heating. Analysis of cloud radar data shows that the strong heating at Naqu in the afternoon promotes the lo-cal convection development (Fig. 6a). Convection reaches the strongest at 1700–1800 LT. At night, precipitation begins to weaken, lasts until 0600 LT, and then gradually dissipates. There is less convective activity in the morning. The cloud appears mainly in two layers from the ground surface to the height of 4 km and above 6 km, and the lowest frequency of cloud activity occurs near 5 km above the ground (Fig. 6b). Most of the convective cloud tops reach up to the height of 15 km above sea level (ASL), and the deep convective cloud top is above 16.5 km ASL (Liu L. P. et al., 2015; Chang and Guo, 2016; Tang et al., 2019). From the South Asian Plain to the TP, the average heights of cloud top and base generally show an increasing trend (Chen Y. L. et al., 2017). The macro- and microphysical features of the convective clouds from the SNPP/VIIRS (Suomi National Polar-orbiting Partnership satellite/Visible Infrared Imaging Radiometer Suite) satellite data further shows a convective cloud base temperature of about –5°C, a base height of 1.8–2.2 km above the ground, and a convective cloud top height of 10–13 km ASL over the TP. The mean could top height is 10.58 km ASL at Naqu ( Yue et al., 2019). The convective cloud top height from the TIPEX-III ground-based radar observations (Liu L. P. et al., 2015) is obviously higher than that from the SNPP/VIIRS satellite data, also higher than the cloud top height (with a mean value of 14–15 km ASL) from theCloudSat/CALIPSO satellite data (Luo et al., 2011), and is equivalent to the deep convective cloud top height over South Asia (about 16.3 km ASL) (Luo et al., 2011).

Figure 6 (a) Height–time cross-section of diurnal C-band continuous wave radar echo averaged from July to August 2014, in which the ordinate is for the altitude (km) above sea level and the abscissa is for local time (LT) (Chang et al., 2016). (b) Diurnal variation of cloud top (open circle) and base (triangle) averaged from 5 July to 4 August 2014, in which the ordinate is for the altitude (km) away from the land surface and the abscissa is for Beijing Time (BT) (Liu L. P. et al., 2015).

The TIPEX-III studies show that the cloud–precipitation microphysical processes over the TP are different from those in the plain area. For example, the cloud particle data observed by aircraft show that the large supercooled cloud droplets are rich in the cloud region with a negative temperature at Naqu in summer, which is beneficial to the formation of precipitation particles in the cloud. In the low-level cloud, there are a large number of supercooled water droplets that are of raindrop size (Zhao et al., 2018) and in the upper layer, there are a large number of graupel particles (Fig. 7). The concentration of cloud droplets with a diameter of about 10 μm is generally < 10 2 L–1, which is significantly lower than the cloud droplet concentration over the clean (104 L–1) or lightly polluted (105 L–1) ocean environment (Zhao et al., 2018). Analysis of the SNPP/VIIRS satellite retrieval product shows that the water content in the TP convective cloud is only about 1/3 of that in the plain area. The condensation nucleus concentration at the cloud base is low (only 200–400 mg–1) but with large supersaturation (obviously higher than that of the surrounding plains), which implies a faster growth rate of cloud droplets over the plateau. Meanwhile, the starting height of precipitation (namely the height at which raindrops are formed) over the TP is low (1500–2000 m above the ground), while it is 4000–5000 m in the plain areas. Therefore, precipitation is easier to form over the plateau. Because ice is more likely to form in the convective cloud over the TP than over plain areas, the ice phase dominates the precipitation particles in the cloud (Yue et al., 2019). Numerical simulation studies further exhibit that the supercooled water content is rich in the TP cloud, mainly appearing in the layer between 0 and –20°C. The ice crystal content mainly appears above the height with temperature of –20°C, and it also appears above the height with temperature of –40°C in the strong convective cloud. In this case, rainfall depends mainly on the melting processes of ice particles ( Tang et al., 2019). As a result of these microphysical processes, precipitation in the TP is of the characteristics of frequent occurrence, short duration, small amount, and large droplet.

Figure 7 Cloud particle characteristics at a high level with temperature of –17.9℃, sampled by aircraft flight on 21 July 2014.

In the TP region, although the direct contribution of warm rain processes to precipitation is small, the heterogeneous freezing of supercooled raindrops formed in the warm rain processes is very important to the formation of graupel embryos in the cloud, which suggests that the warm rain microphysical processes play an important role in the weak convective cloud induced precipitation over the TP (Gao et al., 2016, 2018; Tang et al., 2019). During the period of weak convective precipitation, cloud water and rainwater amounts may double when ice cloud microphysical processes are considered and precipitation reaching the ground surface is most sensitive to condensation processes of cloud droplets (Gao et al., 2016, 2018). Rich supercooled water in the cold zone plays an important role in convective precipitation, in which the cloud–precipitation microphysical processes are featured with water vapor condensation and attaching of snow and graupel particles to the supercooled cloud water, while the ice crystal microphysical processes are featured with ice crystal deposition and automatic conversion between ice and snow. This phenome-non is different from that in the plain areas where the supercooled water in the convective cloud is mainly related to upward transport of the lower-layer water vapor. Moreover, the water vapor from evaporation on the ground surface is also important to the earlier convective precipitation on the TP, which leads to a phenomenon of water vapor self-cycling process. During the period of convective precipitation, the peak time of water vapor transport lags behind that of deposition and condensation in the cloud, which reflects that local cloud microphysical processes are likely initiated prior to large-scale advection processes (Gao et al., 2016, 2018).

The cloud–precipitation microphysical characteristics over the TP are closely related to meteorological conditions. For example, in the earlier stage of the low vortex precipitation at Naqu on 14 July 2014, the ascending motion in front of the vortex was deep; the convection developed vigorously; and the raindrops could well deve-lop, with a wide raindrop spectrum distribution (0.3–4.9 mm). The small raindrops (< 1 mm) accounted for 87% of the total raindrops, and the large raindrops (> 2 mm) accounted for 0.35% of the total raindrops, with the large raindrop concentration of 65.27 mm–1 m–3 (Fig. 8a). In the later stage of the low vortex precipitation, convection significantly weakened and the cloud top height increased, with a bright zone of 0°C around 1.1 km above the ground (Fig. 8b), which indicates a feature of stratiform cloud precipitation. The precipitation in the cloud is likely dominated by ice phase (liquid phase) above (below) the bright zone of 0°C. Then, in the stage of the topographic cloud precipitation, it is also mainly featured by stratiform cloud precipitation: the raindrop spectrum distribution is narrow (0.3–2.1 mm); small raindrops account for a large proportion of total raindrops (92%), while large raindrops account for a small proportion, with a very low concentration (only 0.69 mm–1 m–3; Fig. 8a) (Zhao and Yuan, 2017). Compared to the plains, there are more big raindrops (> 3 mm) in the convective precipitation in the TP. The TP raindrop spectrum distribution observed by TIPEX-III is quite different from that of the M–P distribution that is often used in the numeri-cal models, which implies that the M–P distribution may not be suitable for the TP case. The Γ distribution could better reflect the characteristics of the TP raindrop spectrum distribution when the raindrop diameter is < 2 mm. In addition, precipitation at Naqu is mainly of the features of short-term and showery precipitation in summer. Most of the precipitation processes last for less than 1 h and have a small precipitation intensity (mainly below 5 mm h–1), with a mean hourly precipitation of 1.16 mm (Chang and Guo, 2016). The intensity of precipitation in the TP shows a large spatial difference (Li, 2018). There are more occurrences of hourly heavy precipitation and weak precipitation in the southeastern TP, and there are more hourly heavy precipitation and less hourly weak precipitation in the northeastern TP and the Yarlung Zangbo River valley. In the western and northern TP, occurrences of both the heavy and weak precipitation are less.

Figure 8 (a) Raindrop size distributions at earlier (blue) and later (green) stages of the Naqu low-vortex rainfall case and during the topographic cloud induced rainfall stage (pink) on 14 July 2014 (Zhao et al., 2017). (b) Time–height cross-section of the C-band continuous wave radar echo (dBZ) during 1400–2400 BT 14 July 2014 (Zhao and Yuan, 2017).

Numerical simulations show that the conversion efficiency from water vapor to precipitation in the Naqu area is 20.8%, higher than that in North and Northwest China and close to that in the lower reaches of the Yangtze River (Tang et al., 2018). In addition, the recycling rate of precipitation at Naqu is 10.9%. This result shows that although water vapor from the local evaporation contributes to precipitation, the externally imported water vapor still plays a major role. This recycling rate of precipitation is lower in the central TP than in the western TP, as pointed out by the previous studies (Guo, 2013).

Yan Y. F. et al. (2016, 2018) analyzed the CloudSat/CALIPSO and TRMM satellite products. They found that the topographic effects and the insufficient low-layer water vapor may reduce the thickness and number of cloud layers over the TP in summer, and the variations of the TP cloud thickness and top height are obviously smaller than those in the adjacent land and sea. The net radiation effect of the TP cloud forms a strong radiative cooling layer with a thickness of about 1 km at the height of 8 km above the ground, and a strong radiative heating layer of 7 km above the ground surface. Under the background of global warming, the changes of cloud, radiation, and water vapor content in the TP can result in a smaller diurnal temperature range. In this process, cloud–radiation and water vapor play the most important role and the effect of latent heat release is secondary. This is different from that in the eastern plains of China (Yang and Ren, 2017).

4.3 Characteristics of tropospheric–stratospheric atmospheric vertical profiles in summer

TIPEX-III shows (figure omitted) that the tropopause height is about 17 km ASL, with the lowest temperature near 17–19 km ASL and the average temperature of –76.7°C (Zhao et al., 2018). Water vapor content decreases rapidly from greater than 1000 × 10–6 ppm in the lower troposphere to (3–4) × 10–6 ppm near the tropopause, and then it changes little with height. Ozone concentration is relatively large in the near-ground layer, decreases upwards, and then shows a small change near 13–17 km ASL. In the lower stratosphere, it shows a remarkable increasing trend. This vertical distribution of ozone in the TP is different from that in the South Asian monsoon region. Ozone concentration is generally lower in Linzhi than in India’s New Delhi (28.3°N, 77.07°E), with an average difference of 3.1 hPa between these two regions near 16–22 km (Zhao et al., 2018). On a clima-tic average, ozone concentration in the middle and lower troposphere increases from the tropical ocean to the midlatitudes of the Northern Hemisphere. Because Linzhi’s latitude is roughly equivalent to that of New Delhi, the lower ozone concentration in the lower troposphere over the TP is possibly related to the fact that pollutant produced by human activities is less in the TP than in New Delhi, and less pollutant does not favor the rise in ozone concentration due to photochemical reactions. At Waliguan of the northeastern TP, the lower tropospheric ozone concentration changes in summer are mainly affected by two processes (Zhu et al., 2016). One is the local photochemical process and the other is the long-distance transport from East Asia, Europe, and Africa. Especially in June, the contribution of local photochemistry processes over the TP is equivalent to almost half of the remote transport.

The strong vertical ascending motion generated by the TP heating affects the tropospheric–stratospheric transport of ozone in summer. The observations show that the average temperature in the upper troposphere and the lower stratosphere (UTLS) over the southeastern TP is higher than –78.15°C (the highest critical temperature for formation of the polar stratospheric cloud) in summer, with a relatively low water vapor concentration (Zhao et al., 2018). Under such an atmospheric temperature condition, the stratospheric cloud similar to that in the polar region is unlikely to occur over the plateau, that is, the heterogeneous chemical reaction for ozone depletion is likely weak over the TP. Therefore, the heterogeneous chemical process near the tropopause may not be a main mechanism for the formation of the TP UTLS low ozone in summer (Zhao et al., 2018). The upward transport of the observed lower-tropospheric low ozone concentration (Zheng et al., 2004) may play a more important role.

The tropopause fold is a favorable structure that facilitates stratospheric–tropospheric exchange and is accompanied by two tropopause heights. One is the polar tropopause height and the other is the tropical tropopause height. The TIPEX-III intensive sounding data exhibit that in the western TP, the polar tropopause height appears throughout the rainy season, showing a downward trend from the early to late rainy season (Hong et al., 2016). In the late rainy season, the tropopause fold frequently occurs and also accompanies the frequent occurrence of the tropical tropopause height. This result suggests that the late rainy season is an important time window for stratospheric–tropospheric exchanges in the western TP.

Using the TIPEX-III observation data, Yan X. L. et al. (2016) evaluated the reliability of water vapor and ozone products from the earth observation system satellite MLS (Microwave Limb Sounder). They pointed out that the MLS water vapor content is generally lower below 100 hPa compared to the TIPEX-III data, with relative deviation of –43% ± 20%, and it is higher above 83 hPa, with relative deviation of 5.3% ± 4.1%. The MLS product overestimates ozone concentration in the middle troposphere–stratosphere, with relative deviation of 43.5% ± 21.2% below 100 hPa and 16.4% ± 9.7% above 100 hPa. These results show that the parameters of the algorithm used to retrieve the MLS products have shortcomings and need to be corrected and verified against the observational data.

4.4 TP and anomalies of East Asian and global weather and climate

The TP is a key area of “strong signal” that affects the downstream precipitation weather. The occurrence, development, and eastward migration of the TP vortices and convective systems forced by local heating exert important impacts on the local and surrounding precipitation weathers. The TIPEX-III studies show that when the TP surface gives more heat to the atmosphere, the lower-tropospheric flow convergence strengthens, the TP vortex is active, and the low vortex precipitation increases. In summer, the precipitation caused by the TP vortex accounts for 30%–80% of the local total precipitation (Lin Z. X. et al., 2019; personal communication) and the TP convective systems may contribute more than 70% to the local precipitation (Hu et al., 2016, 2017). In addition, the vertical structure of the atmospheric heat source over the TP affects the intensity and moving direction of the plateau vortices. The strong precipitation caused by the eastward-moving TP low vortices appears in the TP and near the Sichuan basin along 28°–35°N, with zonally-oriented precipitation centers. The precipitation caused by the dying-out vortex on the TP occurs locally and is also weak (Li et al., 2014). Statistical analysis shows that in summer, the occurrence frequency of convective systems in central and eastern TP is significantly negatively correlated with precipitation in South, Northwest, and North China, and has a significant positive correlation with precipitation in the Yangtze River basin and Northeast China. The TP convective systems contribute 30%–70% of precipitation in the Sichuan basin and the middle–upper reaches of the Yangtze River (Hu et al., 2016, 2017).

In addition to the effects of the TP weather systems, low vortices often form and develop in the Sichuan basin, the south part of the Ganshu Province, and northern Sichuan to the east of the TP, and they move eastwards, which usually lead to precipitation weather in eastern China (Ye and Gao, 1979). TIPEX-III establishes a multi-scale conceptual model of rainstorm in the Sichuan basin caused by the southwestern low vortices in summer (Yang et al., 2016). A main feature presented in this model includes: the large-scale South Asian high in the upper troposphere over the TP, the upper troposphe-ric divergence center over the Sichuan basin caused by the combined effect of the South Asian high and the upper tropospheric jet stream, the middle tropospheric trough behind the Northeast China cold vortex system, and an eastward retreat of the western Pacific subtropi-cal high (with slightly weakened intensity). In the lower troposphere, the synoptic-scale east–west shear line appears at 700 hPa, and the mesoscale southwestern vortex generates and develops, with strengthened low-level jet stream and water vapor convergence over the Sichuan basin. These multi-scale circulation systems provide favorable dynamic and water vapor conditions for the precipitation occurrence in the Sichuan basin. Meanwhile, the easterly flow to the north of the vortex meets the topography to the west of the Sichuan basin, which forms southeastward moving mesoscale convective systems. At this time, the northern cold air masses invade into the Sichuan basin, meeting the northward warm and moist flows, which provides a favorable atmospheric instability condition for the precipitation occurrence. Moreover, in summer, the development and eastward migration of the low vortices to the northeast of the TP also affect the downstream heavy rainstorm weathers. For example, in the heavy rainfall process occurring in Beijing on 21 July 2012, with the development and eastward migration of a low-level vortex to the northeast of the TP, the southeasterly warm and moist flow to the east of the low vortex center formed a mesoscale convergence center under the effect of topography in western Beijing, with strong but relatively shallow ascending motion, which resulted in occurrence of warm-sector heavy precipitation different from that in southern China. When the low vortex moved eastward to the vicinity of the Beijing city, the ascending motion near the center of the vortex was strong and deep, forming deep convective and heavy rainfall weather (Zhong et al., 2015). In winter, when the anomalous signal in the TP propagates eastward, a cyclonic circulation appear in the downstream areas, which enhances water vapor transport and ascending motion in southern China and thus produces the lo-cal rainfall and snow (Ma et al., 2019). Xu et al. (2015) found that when the midlatitude westerly wind climbing across the TP sinks on the leeward slope, it forms a weak wind zone in the near-ground layer in the downstream area, which may contribute to the accumulation of local air pollutants and the occurrence of extreme fog and haze events and forms a frequently occurring area of fog and haze events in central and eastern China. Moreover, the interannual variation of the TP heat source is significantly positively correlated with the occurrence of winter haze in central and eastern China (Xu et al., 2016). Under the influence of the TP heat source, the East Asian winter monsoon weakens, low-level southerly flow strengthens, and the atmosphe-ric stability strengthens, which leads to frequent occurrences of haze events. Therefore, it is necessary to consider the impacts of the TP topography on the environment and climate change when formulating the China’s air pollution mitigation policies.

The climate signals in the key areas of the TP have important indications for climate anomalies in the local and surrounding areas. For example, the plateau surface heating intensity is 1–3 months ahead the TP monsoon index. When the heating is strong in February, the TP summer monsoon breakouts earlier, with a strong monsoon intensity at the initial stage (Bai and Hu, 2016). The study shows that the atmospheric apparent heat source in the eastern TP in winter has a significant positive correlation to the beginning of the pre-flood season in South China next year. That is, when the winter atmospheric apparent heat source in the eastern TP is weak, the pre-flood season in South China next year comes earlier, and vice versa. In addition, the TP surface sensible heat in spring is significantly correlated with summer precipitation in central and eastern China (Li X. Z. et al., 2018). When the spring sensible heat is strong, summer precipitation increases in the Yangtze River valley and decreases in South China. When the spring TP sensible heat factor was added into the prediction model that originally included only sea temperature forcing, the correlation coefficient of the model increased from 0.63 to 0.75 in South China and from 0.52 to 0.65 in the middle and lower reaches of the Yangtze River. Therefore, considering the climate anomaly signals in the key areas of the TP can raise the prediction skill for precipitation in central and eastern China.

Because the abundant water resources in glaciers, snow cover, lakes, and rivers in the TP provide water for the Asian water cycle, especially the major rivers in Asia, the TP is also known as the Asian “water tower.” TIPEX-III proposes a mechanism for maintenance of the atmospheric “water tower” and a water cycle model on the TP. It is found that the “tropospheric atmospheric heat island” over the TP drives water vapor from tropical oceans to climb the southern slope of the TP (Xu et al., 2014). In this process, the warm and moist flow reaches the TP through a relay of two “ladders,” and both “ladders” exhibit a dynamic structure with low-level convergence and high-level divergence, which matches the vertical structure of the atmospheric apparent heat source of the two “ladders.” In this way, the TP atmospheric “water tower” is maintained.

In recent years, there is controversy about the TP thermal effects on the surrounding climate. For example, Boos and Kuang (2010) believed that the dynamic functions of the Himalayas and the orographic lifting of the southern slopes lead to the formation of the present South Asian monsoon characteristics while the TP heating possibly has a weak impact on the formation of the South Asian monsoon. In fact, however, their view ignores the role of “heat pump” on the southern slope of the TP and the fact that the region to the north of South Asia receives more solar radiation and there is no cold advection over there (Wu et al., 2007, 2012; He et al., 2015). Then, what is the impact of the variability of the TP heating on the present climate? TIPEX-III deeply studies the influences of the TP thermal forcing on the climate near the TP and a wider area. It is pointed out that for the present climate, the summer TP thermal forcing modifies the Eurasian–Pacific extratropical atmospheric zonal circulation, the TP–Indian Ocean atmospheric meridio-nal circulation (Zhao et al., 2019), and climates in East Asia, South Asia, and a larger region. Wu et al. (2016) pointed out that the TP heating in summer enhances the meridional circulation in the Asian monsoon region and produces the eastward-propagating Rossby wave along the extratropical westerly jet stream, which regulates the large-scale climate variability in the Northern Hemisphere. Liu G. et al. (2015, 2017) discovered that the TP heating anomalies can trigger an extratropical teleconnection in the Northern Hemisphere similar to the Asian–Pacific Oscillation (APO), which has been confirmed by numerical prediction models (Chen et al., 2013). Through this oscillation, the TP thermal functions may regulate the low-pressure systems in the Asian and African monsoon regions and the subtropical anticyclones in North Pacific and Atlantic Ocean, thus resulting in temperature and precipitation anomalies in Africa, South Asia, East Asia, and extratropical North America (Zhao et al., 2018). Nan et al. (2019) addressed that when the TP heating strengthens in summer, the uplift flow in the TP strengthens, moving westward and sinking near the Mediterranean Sea. It also induces anomalous upward flow in Africa and strengthens the low-pressure system in the African continent, with strengthened westerly wind in the lower troposphere from eastern Atlantic to African continent, which affects precipitation in Africa. In summer, there is an interaction between the TP and Iranian thermal effects, which affects the convergence of water vapor flux in the Asian subtropical monsoon region and the formation of the cold center in the tropopause and lower stratosphere over the Eurasian continent (Wu et al., 2016; Liu Y. M. et al., 2017).

5 Progress in TIPEX-III application research

TIPEX-III has made noticeable progress in the construction of observation station networks, data treatment technologies, and weather and climate forecast technologies. In particular, the setup of intensive observations and advances in data treatment technologies provide a more reliable data support to investigations of weather and climate effects of the TP.

5.1 Construction of intensive meteorological observation station networks on the TP

The Meteorological Observation Center (MOC) of the CMA established automatic sounding observation systems at Shiquanhe, Gaize, and Shenzha stations of the western TP in 2014, solving some technical problems of the automatic sounding systems when they were operated in harsh environments of the TP. The hardware systems, the algorithms emulation, and the balloon-releasing system software, were upgraded; the data from the automatic sounding systems were formatted to meet the operational standards; and the technical manuals for operational application of the automatic sounding systems were compiled. Evaluation shows that these automatic sounding observation systems have met the operational needs and their trial operation has been successfully realized, which significantly alleviates the dilemma in lack of routine sounding observations in the western TP, provides basic data for analyzing the characteristics and evolution of weather systems in the central and western TP, and promotes the integrated reform of the surface and upper air observations of the CMA in entire China.

The National Satellite Meteorological Center of China (NSMC) has designed and built a “multi-level and multi-scale” automatic observation station network for checking and correcting satellite products of soil temperature and soil moisture in the TP, as well as a data collecting system suitable to the TP frozen soil environment, thus solving the problem in remote transmission of observation data from scattered meteorological stations in the frozen soil environment. The network also promotes the observation technology advancement in the alpine region. The associated technologies have obtained a China national invention patent (i.e., Network Observation Me-thods for Geoscience Variables), a China national utility model patent (i.e., Data Collector in Frozen Soil Environment), and a software copyright (i.e., Automatic Collec-ting and Analyzing System for Multi-Scale Network Observation Data and Associated Mobile Monitoring).

5.2 Development of meteorological monitoring technology and data product

The TIPEX-III observation data are applied in the evaluation, calibration, and correction of the China national-level meteorological monitoring operational products. The NSMC has improved the retrieval method for FY-3 soil moisture product using “multi-level and multi-scale” automatic observation network data, which further improves the quality of the retrieval product, with a reduction of RMSE in soil moisture by 29.2% and an increase of correlation coefficient from 0.86 to 0.92. Based on the sounding data, the NSMC has also evaluated and modified the algorithm for retrieving atmospheric precipitable water from the Fengyun meteorological satellites. The new algorithm has significantly improved the accuracy of the precipitable water product in the TP and adjacent areas, with a decrease of RMSE from 39.4 to 4.5 mm and an increase of correlation coefficient from 0.23 to 0.97, and has been approved for operational application.

The MOC uses the sounding data at Gaize, Shenzha, and other stations to calculate the atmospheric precipitable water, and evaluate the same product from the Glo-bal Navigation Satellite System (GNSS), the Moderate Resolution Imaging Spectroradiometer (MODIS), and the FY-3 (Hu et al., 2018). The results show that variation of the atmospheric precipitable water from the sounding data is highly consistent with that of GNSS. Based on this relationship, TIPEX-III improves the quality control algorithm for the GPS atmospheric precipitable water retrieval, the sliding window treatment me-thod for the GNSS meteorological observation, and the assessment system for total zenith delay and total water vapor. These improvements have been put into effect in a national-level operational data processing platform of China. The upgraded platform achieves obviously better quality in the atmospheric precipitable water product. The retrieval accuracies for the water vapor and zenith delay are raised from 2.2 and 13.9 mm to 1.4 and 8.1 mm, respectively.

The National Meteorological Information Center of China (NMIC) has developed a quality control algorithm for the TP surface and sounding data. The new sounding data algorithm is better in identifying erroneous observation data in the TP region and reduces the data misjudgment. Based on the new algorithm, the automatic quality control process for the sounding data has been established and the quasi real-time quality control of the sounding data has been realized. “The sounding experimental observation dataset in the TP region,” after quality control, has been produced and provided to users through the Chinese meteorological data network platform under the entry—“Basic Data Service Special Collection for the TP Atmospheric Science Experiment.”

The MOC/CMA has improved the quality of operational weather radar data in the weather radar quality control operational system by introducing a radial velocity defuzzying algorithm. The accuracy for identifying ground object/super refraction echoes increases from 93.25% to 95.03%, the accuracy for fully identifying faulty images increases from 36.62% to 88.57%, and the accuracy for identifying radial interference echoes increases from 83.07% to 96. 66%. In addition, a new wind profile radar quality control algorithm, the quality control subsystem, and the quality evaluation subsystem have been developed by combining the observation data from millimeter wave radars, surface routine observation data, and wind profile radars. After the quality control, data reliability is about 30% higher than before. The quality control for the entire observation network data as well as the real-time output of the new products has been realized. All these have provided more reliable radar products for the TP meteorological research.

TIPEX-III promotes the merging technology for multi-source precipitation data and land surface and atmosphe-ric reanalysis techniques in the East Asian region. The NMIC has developed a merging method for gauge– satellite–radar precipitation data using the probability density function matching, Bayesian model averaging, and optimal interpolation, and produced precipitation products with high temporal/spatial resolutions of 1 h/0.05°. In the area with sparse stations, quality of the precipitation data from this method is better compared to that of the single-source precipitation data, with an increase of correlation coefficient from 0.30–0.40 (for single-source product) to 0.5 (for the three-source merged product) and a decrease of RMSE from 0.85–1.00 to 0.80 mm h–1 (Pan et al., 2018). This new method has been applied to the China national precipitation merged analysis system and employed in the trial operation. The NMIC has also applied the TP observation data in testing and evaluating soil temperature, soil moisture, and sensible and latent heat fluxes products from the CMA Land Surface Data Assimilation System (CLDAS), analyzed the quality of the CLDAS products in the TP region, and carried out experiments to improve the CLDAS product quality. At the same time, based on the CLDAS system, the 2008–17 “Reanalysis Dataset for East Asian Regio-nal Atmospheric Forcing Fields” and “Reanalysis Dataset for East Asian Regional Soil Moisture” have been deve-loped and shared at the website http://data.cma.cn/tipex under the title of “Basic Data Service Special Collection for the TP Atmospheric Science Experiment.” Based on the WRFv3 mesoscale model and the Gridpoint Statisti-cal Interpolation (GSI) assimilation system, our team has developed a prototype system for the High East Asian Regional Reanalysis (HEAR) and generated the 2015–16 reanalysis products with a horizontal resolution of 12 km, in which the TIPEX-III intensive and operational routine observation data, the Doppler radar reflectivity data in China, and the NOAA satellite products were assimilated. A preliminary assessment for the reanalysis temperature at 500 hPa shows that RMSE of summer 500-hPa temperature with observation is generally between 1 and 1.6°C in China, with a larger RMSE in the TP (Fig. 9a). The difference between the HEAR and ERA-Interim (horizontal resolution of 0.75°) RMSEs is generally small (between –0.5 and 0.5°C) ( Fig. 9b), which indicates that the product quality of the HEAR reanalysis prototype system is comparative to the ECMWF level. In the TP region, RMSE of the HEAR product is generally smaller than that of the ERA-Interim reanalysis, which is likely attributed to the assimilation of more intensive sounding data in the HEAR prototype system.

Figure 9 Distributions of RMSE of 500-hPa temperature (°C) between the HEAR reanalysis product and observation from 1 to 31 July 2016, in which black circles denote sounding observation stations. (b) As in (a), but for the RMSE difference (°C) of 500-hPa temperature between the HEAR and ERA-Interim (with a horizontal resolution of 0.75°) reanalysis datasets.

In order to promote sharing and application of the TIPEX-III data and products, the NMIC has built a sharing platform and a service system for the TIPEX-III data, with the latter including functions of data submission, management, and directory navigation, realizing the unified data management. The TIPEX-III data storage system with real-time access, a cloud infrastructure, and a nimble support platform has been built, which provides one-stop online data service, convenient data search, enquiry, and downloading, and a capability to assess the benefit of the service. Moreover, the NMIC also built the website http://data.cma.cn/tipex as an official way for downloading the TIPEX-III data.

5.3 Application to operational weather forecast and climate prediction

The TIPEX-III intensive observation data have been applied to operational weather forecast to help forecasters better understand the characteristics and evolution of weather systems. The Meteorological Observatory of Tibet Autonomous Region has employed the intensive sounding observation data at Shiquanhe, Gaize, and Shenzha of western Tibet in its operational forecast. Evaluation of such an operational application during more than three years shows that these intensive observation data are conducive to analyzing and predicting weather systems in the TP region, such as the short-term strong convective weather in northern Tibet in flood season and the windy and cold weather in northern Tibet during winter. For example, based on the intensive sounding observation data (with a northerly wind at Gaize), a warm low vortex was observed over the central TP (around 31°N, 85°–88°E) (Fig. 10a). However, the low vortex could not be identified without the intensive station data, and this vortex appeared to the west of 85°E (with a southeasterly wind near Gaize) even with the most advanced reanalysis data in the world (without including the intensive data) (Fig. 10b). Missing the low vortex in local operational weather forecast directly affects forecast of the related rainfall area. In addition, the Sichuan Regional Meteorological Center has introduced the TIPEX-III intensive observation data into its real-time operational platform, helping forecasters finely analyze and predict the evolutions of weather systems such as low vortices, shear lines, and low pressure troughs, which in the end improves the capability of short-term weather forecast operations.

Figure 10 (a) The 500-hPa weather map at 0800 BT 27 July 2017 (provided by the Meteorological Observatory of Tibetan Autonomous Region), in which “+” symbols denote new sounding stations. (b) Distribution of geopotential height (black solid lines), temperature (color shading), and wind (arrows) at 500 hPa on 27 July 2017 from the ERA-Interim reanalysis, in which black dots denote new sounding stations.

Understanding the initiation and development of wea-ther systems and their physical connection can help forecasters better capture/predict these weather systems and associated precipitation, and better correct systematic deviations in the numerical forecast products. For example, the National Meteorological Center of China (NMC) has applied the multi-scale conceptual model of rainstorm in the Sichuan basin associated with the southwestern low vortices in summer (Yang et al., 2016) to the operational forecast in flood season. Evaluation of such operational applications shows that, by referring to this conceptual model, the rainfall areas and intensity forecast from the numerical model can be adjusted, leading to improved operational forecast. Based on an objective identification method for the TP low vortices, TIPEX-III also corrected the low vortex intensity and position and established a prediction method for the position and intensity of heavy precipitation caused by the low vortices, which has been applied to the weather forecast operation in the Meteorological Observatory of Tibet Autonomous Region.

Statistical forecast methods play important roles in climatic predictions of China. In view of the important influence of the TP on East Asian climate, the National Climate Center of China (NCC) has established an operational monitoring system for the TP atmospheric heat source and a statistical forecast model for the beginning date of the pre-flood season in South China using the previous winter TP atmospheric apparent heat source and tropical Pacific sea surface temperature. This model has been employed in national-level forecast operations in China and successfully predicted the beginning date of pre-flood season of 2015–18. In addition, adding the spring TP surface sensible heat in the summer precipitation forecast model over the middle–lower reaches of the Yangtze River and South China leads to improved prediction of summer precipitation, with an increase of the explained variance from 40% to 56% in South China and from 27% to 42% in the middle–lower reaches of the Yangtze River (Li X. Z. et al., 2018). This result indicates that the use of the climatic signal in key areas of the TP can significantly improve the prediction of summer precipitation in South China and the middle–lower reaches of the Yangtze River.

How to correctly describe the physical processes in the numerical forecast models under the complex terrain of the TP has always been a problem in scientific research and routine operation work. TIPEX-III uses the experimental observation data to evaluate the boundary layer parameterization scheme of the weather research and forecasting (WRF) model. It is found that the boundary layer scheme has an obvious cold bias in simulating the TP surface temperature (Xu et al., 2018). This also occurs in the models of the fifth phase of the Coupled Mo-del Intercomparison Project (CMIP5) (Chen X. L. et al., 2017). Zhuo et al. (2016) documented that an improvement in the parameterization of surface heat transfer process in the TP region may significantly reduce the overestimated surface heating and underestimated surface temperature in the model, raising the model performance in simulating rainfall in central and eastern China. The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics (LASG) of Institute of Atmospheric Physics (IAP) of the CAS has developed a new convective scheme in the Finite-volume Atmospheric Model of IAP/LASG (FAMIL). The scheme called “Atmospheric Circulation Model FAMIL Explicit Convective Precipitation System” has obtained a software registration right from the National Copyright Administration of China and has also been coded into the high-resolution FAMIL-2 model as well as the flexible global sea–land–air coupled system grid version 2 (FGOALS-f2).Li et al. (2017) evaluated the computational performance of the improved FAMIL-2. Moreover, the TIPEX-III aircraft observation data have also been used to improve the parameterization of cloud entrainment–mixing processes in the FGOALS-f2 model.

Studies have shown that a higher horizontal resolution of the numerical prediction model can enhance stationary meridional eddy flow and water vapor transport in the model, thus improving the skill in simulating the East Asian monsoon rainbelt (Yao et al., 2017). Therefore, the TP precipitation characteristics simulated by the improved FGOALS-f2 model with a horizontal resolution of 25 km are more consistent with those of the high-resolution satellite products (Fig. 11), the simulated fake precipitation on the southern slope of the TP has been basically eliminated, and the tropical convergence zones and tropical low-frequency oscillations are better simulated (Fig. 12). The FGOALS-f2 prediction system is also incorporated into the “Ensemble Climate Prediction System” of the Marine Environmental Prediction Center of China National Oceanic Administration and the “China Multi-model Ensemble Prediction System” of the NCC, which has promoted the development of numeri-cal forecast technology.

Figure 11 (a) Summer rainfall (mm day-1) retrieved by TRMM satellite and (b) as in (a) but for the FGOALS-f2 coupled model with a resolution of 25 km.
Figure 12 (a) Annual mean rainfall (mm day–1) simulated by the FGOALS-f2 coupled model with a resolution of 25 km; (b) time–longitude cross-section of the regressed rainfall against the 20–100-day filtered regional mean rainfall over 5°S–5°N, 130°–150°E; (c) as in (a) but for TRMM rainfall; and (d) as in (b) but for TRMM rainfall.

Considering the impacts of TP weather systems on the downstream weather and the importance of topography on the eastern slope of the TP to mesoscale heavy rainfall forecast, the NMC has established a mesoscale forecast system that can optimize the initial field in the key areas of the TP through introducing the altitude of meteorological stations on the eastern slope of the TP into the mesoscale numerical model and assimilating surface and sounding observation data in areas with frequent occurrences of the TP weather systems. This system has been operated in real time. It is shown that for stormy weather associated with the TP weather systems, the heavy precipitation centers predicted by this mesoscale forecast system is closer to the observation. The forecast products have been applied in national-level forecast operations in China and have improved the forecast of mesoscale heavy rainfall to the east of the TP. With assimilation of the sounding data at Shiquanhe, Gaize, and Shenzha stations into the WRF model, rainfall forecast in the middle–lower reaches of the Yangtze River has been significantly improved (Fig. 13). An evaluation of the forecasts from June to August 2015 shows that when assimilating the intensive sounding data at the three stations, RMSE of 48- and 72-h forecast precipitation in the middle–lower reaches of the Yangtze River decreases, especially with a RMSE reduction of 24-h forecast precipitation by about 11% in the TP and adjacent areas (Zhao et al., 2018). In addition, the Chengdu Institute of Plateau Meteorology of the CMA has applied the experimental intensive sounding observation data to its regio-nal numerical weather forecast system. It is found that assimilating the intensive sounding data can raise the TS score for regional mean 0–48-h forecast precipitation in Southwest China, in particular for the 24-h forecast precipitation in Sichuan Province and the Tibet Automatic Region. This has facilitated the numerical weather forecast operations of the Southwest Regional Meteorologi-cal Center of China (Li and Xu, 2016).

Figure 13 Distributions of 24-h accumulated rainfall (mm) on 8 June 2015 from (a) observation and (b, c) WRF model forecasts. The assimilation of the intensive sounding data at Shiquanhe, Gaize, and Shenzha stations is switched off in (b), but is on in (c).
6 Conclusions and prospects

Since the beginning of the preliminary experiment in 2013, TIPEX-III has implemented a comprehensive observational experiment for land surface–boundary layer and cloud–precipitation physical processes and troposphere–stratospheric atmospheric composition exchanges that occur mainly over the central and western TP, by making full use of the TP meteorological observation operational systems, rationally designed observation networks, and coordinated instruments and field compaigns. TIPEX-III has also deeply investigated the TP land–air coupled system and its impacts on weather and climate, and has achieved significant progress in the research to application in weather and climate forecasts. The achieve-ments are concluded as follows.

(1) New automatic sounding systems have been built at Shiquanhe, Gaize, and Shenzha stations and their trial operation has been realized, which fills the gap of lacking routine sounding operational stations in the western TP. The new sounding observation data are obviously conducive to analyzing and predicting weather systems, such as strong convective and high wind, cold weathers in the TP region. The assimilation of the new sounding observation data can significantly improve the ability of mesoscale models in forecasting rainbelts in the TP and the middle–lower reaches of the Yangtze River, reducing RMSE of 24-h forecast precipitation in the TP and its adjacent areas. The application of these sounding data can also significantly improve the product quality of satellite retrieved atmospheric precipitable water, GPS total water vapor, and the East Asian regional reanalysis in the TP region.

(2) TIPEX-III has created a soil temperature and soil moisture data collecting system suitable to the frozen soil environment with independent intellectual property rights. In addition, a “multi-level and multi-scale” automatic observation network for soil temperature and soil moisture was built in the central and western TP, which has obtained a national invention patent, a national new utility patent, and a software copyright of China, which promotes the related automatic observation technology in alpine regions. The application of these experimental data in the evaluation, calibration, and correction of FY-3 inversion products has significantly improved the quality of satellite products.

(3) The TP boundary layer ultrasonic pulsation observations show that surface turbulent heat exchange coefficient (Ch) under the grassland, meadow, and bare soil surfaces in the central and western TP is (2–4) ×10–3, significantly lower than the previous estimates based on theoretical calculations and observations on ice, snow, and gravel surfaces at the Rongbu Temple in the north slope of the Mount Everest. Surface sensible heat flux is also significantly smaller than previous estimates. For the numerical prediction model, improving the parameterization scheme of heat transfer processes in the TP region can significantly reduce the overestimated TP surface sensible heat flux and raise the model ability in simulating precipitation in central and eastern China.

(4) Direct observations and theoretical studies of the cloud–precipitation physical characteristics over the TP reveal the diurnal variations of convective clouds, the unique cloud macro- and micro-features, the characteristics of raindrop spectrum distribution, and the transition mechanism between different phases of water in the cloud at Naqu. The M–P raindrop spectrum distribution commonly used in the numerical models is not suitable to the characteristics of the TP clouds, while the Γ distribution is better in the TP. On the climatological average, the convective cloud in the TP may develop mainly locally, rather than from a northward propagation of convective cloud in the South Asian monsoon region. Application of the intensive observation data can help improve the parameterization of cloud entrainment–mixing processes. Compared to the model results with a lower horizontal resolution, the FAMIL model with a horizon-tal resolution of 25 km has improved simulations of the precipitation over the southern slope of the TP, the tropical convergence zones, and the tropical low-frequency oscillations.

(5) Impacts of the initiation and eastward movement of the TP low-pressure systems on the downstream heavy rainfall in summer, the mechanism responsible for the TP heating to maintaining the Asian “water tower” in summer, and the regulations of the TP heating on Asian, African, and North American climates are further understood. The multi-scale conceptual model for rainstorm processes in the Sichuan basin caused by the southwestern low vortex in summer and the objective identification method for the TP vortices, developed by TIPEX-III, have improved the operational ability in forecasting low vortices and precipitation in Southwest China. Considering the heating signals in the key areas of TP can significantly improve the prediction accuracy for the beginning date of the pre-flood season in South China and summer precipitation in central and eastern China.

In summary, TIPEX-III has greatly improved the observation capability of both the meteorological sounding station network in the western TP and the plateau- and regional-scale soil temperature and soil moisture observation station networks in the TP, through implementing a land surface–boundary layer–troposphere–stratosphere comprehensive observation experiment over the TP. The physical characteristics of the TP land surface–boundary layer–troposphere–stratosphere processes, the characteristics of regional atmospheric water cycles in the TP, and their relationships with the atmospheric circulation systems have been revealed. The influences of the TP land–air physics processes on atmospheric circulation, weather, and climate in the East Asian region and even larger regions are further understood. TIPEX-III promotes the development of the national-level quality control technologies of routine surface and sounding observation data and operational weather radar and wind profile radar data, improves the quality of both national-level satellite and GPS remote sensing atmospheric water vapor products and high-resolution radar–satellite–gauge rainfall merged products, facilitates the development of meteorological operations in monitoring, forecast, and data sharing, and provides new insight into upgrading numerical forecast models and weather and climate forecast techniques. TIPEX-III also contributes to the construction in surface observation station networks and satellite remote sensing monitoring for meteorologi-cal environments under the background of the warming and humidification in the TP. It provides a new data support to the NSFC major research program “The earth–atmosphere coupled system over the TP and its global climate effects” and to understanding the future trends and attributions of the TP warming and humidification climate and its effects on the regional ecological environment and water resources.

The subsequent experiments of TIPEX-III will conduct the land surface–boundary layer–tropospheric–stratospheric comprehensive observations mainly in the central–eastern, northeastern, and southeastern TP, develop new treatment techniques for multi-source observation data, promote the application of experimental data in developing numerical forecast models, and improve the ability of numerical forecast models in the TP region. We will investigate in-depth the mechanisms for earth–atmosphere interactions in the TP and surrounding regions and their influences on convective organization, and the impacts of climate signals in key areas of the TP on weather and climate forecasts in China. We will also promote the sharing of the TIPEX-III data. In the future, TIPEX-III will enhance construction of integrated monitoring systems for meteorology, hydrology, ecology, and environment in the TP, and data sharing platforms, and facilitate multidisciplinary studies.

Acknowledgment. We thank the CMA, the NSFC, the CAS, and the TIPEX-III lead group, expert group, participating institutes for their support to the TIPEX-III. We also thank the TIPEX-III implementation group, participants, and management office for their hard work.

Bai, B. R., and Z. Y. Hu, 2016: Significance of the thermal effects of the Qinghai–Xizang Plateau to the onset of plateau summer monsoon. Plateau Meteor., 35, 329–336.
Boos, W. R., and Z. M. Kuang, 2010: Dominant control of the South Asian monsoon by orographic insulation versus plateau heating. Nature, 463, 218–222. DOI:10.1038/nature08707
Chang, Y., and X. L. Guo, 2016: Characteristics of convective cloud and precipitation during summer time at Naqu over Tibetan Plateau. Chinese Sci. Bull., 61, 1706–1720. DOI:10.1360/N972015-01292
Chen, L. S., X. D. Xu, and S. Q. Yu, 1999: The second Tibetan Plateau field experiment: Air–land process and planetary boundary layer observational study. Ann. Rep. Chinese Acad. Meteor. Sci., 15–16.
Chen, L. X., 1999: China–Japan cooperative research on Asian monsoon mechanisms. Ann. Rep. Chinese Acad. Meteor. Sci., 26–26.
Chen, X. L., T. J. Zhou, and L. W. Zou, 2013: Variation characteristics of the Asian–Pacific Oscillation in boreal summer as simulated by the LASG/IAP climate system model FGOALS_gl. Acta Meteor. Sinica, 71, 23–37. DOI:10.11676/qxxb2013.002
Chen, X. L., Y. M. Liu, and G. X. Wu, 2017: Understanding the surface temperature cold bias in CMIP5 AGCMs over the Tibetan Plateau. Adv. Atmos. Sci., 34, 1447–1460. DOI:10.1007/s00376-017-6326-9
Chen, Y. L., Y. F. Fu, T. Xian, et al., 2017: Characteristics of cloud cluster over the steep southern slopes of the Himalayas observed by CloudSat. Int. J. Climatol., 37, 4043–4052. DOI:10.1002/joc.4992
Cong, C., W. L. Li, and X. J. Zhou, 2002: Mass exchange between the stratosphere and troposphere over the Tibetan Plateau and its adjacent region. Chinese Sci. Bull., 46, 1914–1918.
Dong, W. H., Y. L. Lin, J. S. Wright, et al., 2016: Summer rainfall over the southwestern Tibetan Plateau controlled by deep convection over the Indian subcontinent. Nat. Commun., 7, 10,925. DOI:10.1038/ncomms10925
Duan, A. M., G. X. Wu, Y. M. Liu, et al., 2012: Weather and climate effects of the Tibetan Plateau. Adv. Atmos. Sci., 29, 978–992. DOI:10.1007/s00376-012-1220-y
Feng, L., and T. J. Zhou, 2012: Water vapor transport for summer precipitation over the Tibetan Plateau: Multidata set analysis. J. Geophys. Res. Atmos., 117, D20114. DOI:10.1029/2011JD017012
Gao, W. H., C. H. Sui, J. W. Fan, et al., 2016: A study of cloud microphysics and precipitation over the Tibetan Plateau by radar observations and cloud-resolving model simulations. J. Geophys. Res. Atmos., 121, 13735–13752. DOI:10.1002/2015JD024196
Gao, W. H., L. P. Liu, J. Li, et al., 2018: The microphysical properties of convective precipitation over the Tibetan Plateau by a subkilometer resolution cloud-resolving simulation. J. Geophys. Res. Atmos., 123, 3212–3227. DOI:10.1002/2017JD027812
Guo, Y. P., 2013: The changing characteristics of water cycle over the Qinghai–Xizang Plateau in last 40 years. Master dissertation, Lanzhou University, Lanzhou, China, 77 pp. (in Chinese)
Han, C. B., Y. M. Ma, Z. B. Su, et al., 2015: Estimates of effective aerodynamic roughness length over mountainous areas of the Tibetan Plateau. Quart. J. Roy. Meteor. Soc., 141, 1457–1465. DOI:10.1002/qj.2462
Han, C. B., Y. M. Ma, X. L. Chen, et al., 2017: Trends of land surface heat fluxes on the Tibetan Plateau from 2001 to 2012. Int. J. Climatol., 37, 4757–4767. DOI:10.1002/joc.5119
Han, Y. Z., W. Q. Ma, Y. M. Ma, et al., 2019: Variations of surface heat fluxes over the Tibetan Plateaubefore and after the onset of the South Asian summer monsoon during 1979–2016. J. Meteor. Res., 33, 491–500. DOI:10.1007/s13351-019-8616-x
He, B., G. X. Wu, Y. M. Liu, et al., 2015: Astronomical and hydrological perspective of mountain impacts on the Asian summer monsoon. Sci. Rep., 5, 17586. DOI:10.1038/srep17586
Hong, J. C., J. P. Guo, J. Du, et al., 2016: An observational study on the vertical structure of the upper troposphere and lower stratosphere in Gaize of Tibet during the rainy season. Acta Meteor. Sinica, 74, 827–836. DOI:10.11676/qxxb2016.055
Hu, H., Y. C. Cao, C. Yin, et al., 2018: A comparative analysis of precipitable water vapor in the Tibetan Plateau. Acta Meteor. Sinica, 76, 1029–1039. DOI:10.11676/qxxb2018.055
Hu, L., D. F. Deng, S. T. Gao, et al., 2016: The seasonal variation of Tibetan Convective Systems: Satellite observation. J. Geophys. Res. Atmos., 121, 5512–5525. DOI:10.1002/2015JD024390
Hu, L., D. F. Deng, X. D. Xu, et al., 2017: The regional differences of Tibetan Convective Systems in boreal summer. J. Geophys. Res. Atmos., 122, 7289–7299. DOI:10.1002/2017JD026681
Hu, Q., D. B. Jiang, and G. Z. Fan, 2014: Evaluation of CMIP5 models over the Qinghai–Tibetan Plateau. Chinese J. Atmos. Sci., 38, 924–938. DOI:10.3878/j.issn.1006-9895.2013.13197
Kim, Y. S., T. Shibata, Y. Iwasaka, et al., 2003: Enhancement of aerosols near the cold tropopause in summer over Tibetan Plateau: Lidar and balloonborne measurements in 1999 at Lhasa, Tibet, China. Proceedings of SPIE 4893, Lidar Remote Sensing for Industry and Environment Monitoring III, SPIE, Hangzhou, China, 496–503, doi: 10.1117/12.466090.
Li, B., M. Zhang, S. H. Tang, et al., 2018a: Variations of soil moisture over Nagqu at different time scales based on network observations. Acta Meteor. Sinica, 76, 1040–1052. DOI:10.11676/qxxb2018.057
Li, B., L. Yang, and S. H. Tang, 2019: Intraseasonal variations of summer convection over the Tibetan Plateau revealed by geostationary satellite FY-2E in 2010–14 . J. Meteor. Res., 33, 478–490. DOI:10.1007/s13351-019-8610-3
Li, J., 2018: Hourly station-based precipitation characteristics over the Tibetan Plateau. Int. J. Climatol., 38, 1560–1570. DOI:10.1002/joc.5281
Li, J., Y. Q. Li, X. W. Jiang, et al., 2016: Characteristics of land–atmosphere energy exchanges over complex terrain area of southeastern Tibetan Plateau under different synoptic conditions. Chinese J. Atmos. Sci., 40, 777–791. DOI:10.3878/j.issn.1006-9895.1509.15197
Li, J. X., Q. Bao, Y. M. Liu, et al., 2017: Evaluation of the computational performance of the finite-volume atmospheric model of the IAP/LASG (FAMIL) on a high-performance computer. Atmos. Ocean. Sci. Lett., 10, 329–336. DOI:10.1080/16742834.2017.1331111
Li, L., R. H. Zhang, M. Wen, et al., 2014: Effect of the atmosphe-ric heat source on the development and eastward movement of the Tibetan Plateau vortices. Tellus A, 66, 24451. DOI:10.3402/tellusa.v66.24451
Li, R. Q., S. H. Lyu, B. Han, et al., 2012: Preliminary comparison and analyses of air temperature at 2-m height between three reanalysis datasets and observation in the east of Qinghai–Xiang Plateau. Plateau Meteor., 31, 1488–1502.
Li, X. Z., X. Z. Tang, S. H. Li, et al., 2018: Impact of the spring sensible heat flux over the Tibetan Plateau on summer rainfall over East China and its role in rainfall prediction. Acta Meteor. Sinica, 76, 930–943. DOI:10.11676/qxxb2018.061
Li, Y. Q., and X. D. Xu, 2016: A review of the research and observing experiment on Southwest China vortex. Adv. Meteor. Sci. Technol., 6, 134–140.
Liu, G., P. Zhao, J. M. Chen, et al., 2015: Preceding factors of summer Asian–Pacific Oscillation and the physical mechanism for their potential influences. J. Climate, 28, 2531–2543. DOI:10.1175/JCLI-D-14-00327.1
Liu, G., P. Zhao, and J. M. Chen, 2017: Possible effect of the thermal condition of the Tibetan Plateau on the interannual variability of the summer Asian–Pacific Oscillation. J. Climate, 30, 9965–9977. DOI:10.1175/JCLI-D-17-0079.1
Liu, L. P., J. F. Zheng, Z. Ruan, et al., 2015: Comprehensive radar observations of clouds and precipitation over the Tibetan Plateau and preliminary analysis of cloud properties. J. Meteor. Res., 29, 546–561. DOI:10.1007/s13351-015-4208-6
Liu, Y. M., B. Hoskins, and M. Blackburn, 2007: Impact of Tibetan orography and heating on the summer flow over Asia. J. Meteor. Soc. Japan Ser. Ⅱ, 85B, 1–19. DOI:10.2151/jmsj.85.1
Liu, Y. M., G. X. Wu, J. L. Hong, et al., 2012: Revisiting Asian monsoon formation and change associated with Tibetan Plateau forcing: Ⅱ. Change. Climate Dyn., 39, 1183–1195. DOI:10.1007/s00382-012-1335-y
Liu, Y. M., Z. Q. Wang, H. F. Zhuo, et al., 2017: Two types of summertime heating over Asian large-scale orography and excitation of potential-vorticity forcing Ⅱ. Sensible heating over Tibetan–Iranian Plateau. Sci. China Earth Sci., 60, 733–744. DOI:10.1007/s11430-016-9016-3
Luo, H. B., and M. Yanai, 1984: The large-scale circulation and heat sources over the Tibetan Plateau and surrounding areas during the early summer of 1979. Part Ⅱ: Heat and moisture budgets. Mon. Wea. Rev., 112, 966–989. DOI:10.1175/1520-0493(1984)112<0966:TLSCAH>2.0.CO;2
Luo, Y. L., R. H. Zhang, W. M. Qian, et al., 2011: Intercompari-son of deep convection over the Tibetan Plateau–Asian monsoon region and subtropical North America in boreal summer usingCloudSat/CALIPSO data . J. Climate, 24, 2164–2177. DOI:10.1175/2010JCLI4032.1
Ma, T. T., G. X. Wu, Y. M. Liu, et al., 2019: Impact of surface potential vorticity density forcing over theTibetan Plateau on the South China extreme precipitation in January 2008. Part I: Data analysis. J. Meteor. Res., 33, 400–415. DOI:10.1007/s13351-019-8604-1
Ma, Y. M., T. D. Yao, and J. M. Wang, 2006: Experimental study of energy and water cycle in Tibetan Plateau—The progress on the study of GAME/Tibet and CAMP/Tibet. Plateau Meteor., 25, 344–351. DOI:10.3321/j.issn:1000-0534.2006.02.023
Ma, Y. M., S. C. Kang, L. P. Zhu, et al., 2008: Tibetan observation and research platform (TORP): Atmosphere–land interaction over a heterogeneous landscape. Bull. Amer. Meteor. Soc., 89, 1487–1492. DOI:10.1175/1520-0477-89.10.1469
Nan, S. L., P. Zhao, S. Yang, et al., 2009: Springtime troposphe-ric temperature over the Tibetan Plateau and evolutions of the tropical Pacific SST. J. Geophys. Res. Atmos., 114, D10104. DOI:10.1029/2008JD011559
Nan, S. L., P. Zhao, and J. M. Chen, 2019: Variability of summertime Tibetan tropospheric temperature and associated precipitation anomalies over the central–eastern Sahel. Climate Dyn., 52, 1819–1835. DOI:10.1007/s00382-018-4246-8
Pan, Y., J. X. Gu, J. J. Yu, et al., 2018: Test of merging methods for multi-source observed precipitation products at high resolution over China. Acta Meteor. Sinica, 76, 755–766. DOI:10.11676/qxxb2018.034
Qiu, G. Q., H. Li, Y. Zhang, et al., 2013: Applicability research of planetary boundary layer parameterization scheme in WRF model over the Alpine Grassland Area. Plateau Meteor., 32, 46–55.
Su, Z., P. de Rosnay, J. Wen, et al., 2013: Evaluation of ECMWF’s soil moisture analyses using observations on the Tibetan Plateau. J. Geophys. Res. Atmos., 118, 5304–5318. DOI:10.1002/jgrd.50468
Tang, J., X. L. Guo, and Y. Chang, 2018: Cloud microphysics and regional water budget of a summer precipitation process at Naqu over the Tibetan Plateau. Chinese J. Atmos. Sci., 42, 1327–1343. DOI:10.3878/j.issn.1006-9895.1801.17202
Tang, J., X. L. Guo, and Y. Chang, 2019: A numerical investigation on microphysical properties of cloudsand precipitation over the Tibetan Plateau in summer 2014. J. Meteor. Res., 33, 463–477. DOI:10.1007/s13351-019-8614-z
Tao, S. Y., S. W. Luo, and H. C. Zhang, 1986: The Qinghai–Xizang Plateau meteorological experiment (QXPMEX) in May–August 1979. Proc. International Symposium on the Qinghai–Xizang Plateau and Mountain Meteorology, American Meteorological Society, Boston, MA, 3–13, doi: 10.1007/978-1-935704-19-5_1.
Vernier, J. P., T. D. Fairlie, M. Natarajan, et al., 2015: Increase in upper tropospheric and lower stratospheric aerosol levels and its potential connection with Asian pollution. J. Geophys. Res. Atmos., 120, 1608–1619. DOI:10.1002/2014JD022372
Wan, L. F., D. Guo, R. Q. Liu, et al., 2017: Evaluation of WACCM3 performance in simulation of the double-core ozone valley over the Qinghai–Xizang in summer. Plateau Meteor., 36, 57–66.
Wang, J. M., 1999: Land surface process experiments and interaction study in China—From HEIFE to IMGRASS and GAME-Tibet/TIPEX. Plateau Meteor., 18, 280–294. DOI:10.3321/j.issn:1000-0534.1999.03.005
Wang, Y. J., X. D. Xu, H. Z. Liu, et al., 2016: Analysis of land surface parameters and turbulence characteristics over the Tibetan Plateau and surrounding region. J. Geophys. Res. Atmos., 121, 9540–9560. DOI:10.1002/2016JD025401
Wu, C. Q., and T. J. Zhou, 2011: Characteristics of cloud radiative forcings over East Asia as simulated by the AGCMs in the CFMIP. Acta Meteor. Sinica, 69, 381–399. DOI:10.11676/qxxb2011.033
Wu, G. X., and Y. S. Zhang, 1998: Tibetan Plateau forcing and the timing of the monsoon onset over South Asia and the South China Sea. Mon. Wea. Rev., 126, 913–927. DOI:10.1175/1520-0493(1998)126<0913:TPFATT>2.0.CO;2
Wu, G. X., Y. M. Liu, Q. Zhang, et al., 2007: The influence of mechanical and thermal forcing by the Tibetan Plateau on Asian climate. J. Hydrometeorol., 8, 770–789. DOI:10.1175/JHM609.1
Wu, G. X., Y. M. Liu, X. Zhu, et al., 2009: Multi-scale forcing and the formation of subtropical desert and monsoon. Ann. Geophys., 27, 3631–3644. DOI:10.5194/angeo-27-3631-2009
Wu, G. X., Y. M. Liu, B. He, et al., 2012: Thermal controls on the Asian summer monsoon. Sci. Rep., 2, 404. DOI:10.1038/srep00404
Wu, G. X., H. F. Zhuo, Z. Q. Wang, et al., 2016: Two types of summertime heating over the Asian large-scale orography and excitation of potential-vorticity forcing I. Over Tibetan Plateau. Sci. China Earth Sci., 59, 1996–2008. DOI:10.1007/s11430-016-5328-2
Xu, A. L., J. Li, H. Peng, et al., 2017: Comparison of sensible and latent heat fluxes over farmland underlying surface of Erhai lakeside region measured from large aperture scintillometer and eddy-covariance system. Plateau Meteor., 36, 98–106.
Xu, L. J., H. Z. Liu, X. D. Xu, et al., 2018: Evaluation of the WRF model in simulating atmospheric boundary layer over Nagqu area in the Tibetan Plateau. Acta Meteor. Sinica, 76, 955–967. DOI:10.11676/qxxb2018.059
Xu, X. D., C. G. Lu, X. H. Shi, et al., 2008a: World water tower: An atmospheric perspective. Geophys. Res. Lett., 35, L20815. DOI:10.1029/2008GL035867
Xu, X. D., R. H. Zhang, T. Koike, et al., 2008b: A new integrated observational system over the Tibetan Plateau. Bull. Amer. Me-teor. Soc., 89, 1492–1496. DOI:10.1175/2008BAMS2557.1
Xu, X. D., T. L. Zhao, C. G. Lu, et al., 2014: An important mechanism sustaining the atmospheric " water tower” over the Tibetan Plateau. Atmos. Chem. Phys., 14, 11287–11295. DOI:10.5194/acp-14-11287-2014
Xu, X. D., Y. J. Wang, T. L. Zhao, et al., 2015: " Harbor” effect of large topography on haze distribution in eastern China and its climate modulation on decadal variations of haze in China. Chinese Sci. Bull., 60, 1132–1143. DOI:10.1360/N972014-00101
Xu, X. D., T. L. Zhao, F. Liu, et al., 2016: Climate modulation of the Tibetan Plateau on haze in China. Atmos. Chem. Phys., 16, 1365–1375. DOI:10.5194/acp-16-1365-2016
Yan, X. L., J. S. Wright, X. D. Zheng, et al., 2016: Validation of Aura MLS retrievals of temperature, water vapour and ozone in the upper troposphere and lower–middle stratosphere over the Tibetan Plateau during boreal summer. Atmos. Meas. Tech., 9, 3547–3566. DOI:10.5194/amt-9-3547-2016
Yan, Y. F., Y. M. Liu, and J. H. Lu, 2016: Cloud vertical structure, precipitation, and cloud radiative effects over Tibetan Plateau and its neighboring regions. J. Geophys. Res. Atmos., 121, 5864–5877. DOI:10.1002/2015JD024591
Yan, Y. F., X. C. Wang, and Y. M. Liu, 2018: Cloud vertical structures associated with precipitation magnitudes over the Tibetan Plateau and its neighboring regions. Atmos. Ocean. Sci. Lett., 11, 44–53. DOI:10.1080/16742834.2018.1395680
Yanai, M., C. F. Li, and Z. S. Song, 1992: Seasonal heating of the Tibetan Plateau and its effects on the evolution of the Asian summer monsoon. J. Meteor. Soc. Japan Ser. II, 70, 319–351. DOI:10.2151/jmsj1965.70.1B_319
Yang, K., and X. F. Guo, 2011: On the climatology and trend of the atmospheric heat source over the Tibetan Plateau: An experiments-supported revisit. J. Climate, 24, 1525–1541. DOI:10.1175/2010JCLI3848.1
Yang, S. N., F. H. Zhang, J. Xu, et al., 2016: Mesoscale convective systems and characteristics of environment field during a heavy rainfall process in Sichuan basin. Plateau Meteor., 35, 1476–1486.
Yang, Y., and R. C. Ren, 2017: On the contrasting decadal changes of diurnal surface temperature range between the Tibetan Plateau and southeastern China during the 1980s–2000s. Adv. Atmos. Sci., 34, 181–198. DOI:10.1007/s00376-016-6077-z
Yao, J. C., T. J. Zhou, Z. Guo, et al., 2017: Improved performance of high-resolution atmospheric models in simulating the East Asian summer monsoon rain belt. J. Climate, 30, 8825–8840. DOI:10.1175/JCLI-D-16-0372.1
Ye, D. Z., and Y. X. Gao, 1979: Meteorology of the Qinghai–Xizang Plateau. Science Press, Beijing, 278 pp. (in Chinese)
Yu, W., Y. M. Liu, X. Q. Yang, et al., 2018: The interannual and decadal variation characteristics of the surface sensible heating at different elevations over the Qinghai–Tibetan Plateau and attribution analysis. Plateau Meteor., 37, 1161–1176.
Yue, Z. G., X. Yu, G. H. Liu, et al., 2019: Microphysical properties of convective clouds in summer overthe Tibetan Plateau from SNPP/VIIRS satellite data . J. Meteor. Res., 33, 433–445. DOI:10.1007/s13351-019-8608-x
Zeng, Y. J., Z. B. Su, R. van der Velde, et al., 2016: Blending satellite observed, model simulated, and in situ measured soil moisture over Tibetan Plateau . Remote Sens., 8, 268. DOI:10.3390/rs8030268
Zhang, G., F. Chen, and Y. J. Gao, 2016: Assessing uncertainties in the Noah-MP ensemble simulations of a cropland site during the Tibet Joint International Cooperation program field campaign. J. Geophys. Res. Atmos., 121, 9576–9596. DOI:10.1002/2016JD024928
Zhang, R. H., T. Koike, X. D. Xu, et al., 2012: A China–Japan cooperative JICA atmospheric observing network over the Tibetan Plateau (JICA/Tibet Project): An overview. J. Meteor. Soc. Japan Ser. II, 90C, 1–16. DOI:10.2151/jmsj.2012-C01
Zhao, P., and L. X. Chen, 2000: Study on climatic features of surface turbulent heat exchange coefficients and surface thermal sources over the Qinghai–Xizang Plateau. Acta Meteor. Sinica, 14, 13–29.
Zhao, P., and L. X. Chen, 2001a: Climatic features of atmosphe-ric heat source/sink over the Qinghai–Xizang Plateau in 35 years and its relation to rainfall in China. Sci. China Earth Sci., 44, 858–864. DOI:10.1007/BF02907098
Zhao, P., and L. X. Chen, 2001b: Role of atmospheric heat source/sink over the Qinghai–Xizang Plateau in quasi-4-year oscillation of atmosphere–land–ocean interaction. Chinese Sci. Bull., 46, 241–245. DOI:10.1007/BF03187178
Zhao, P., and Y. Yuan, 2017: Characteristics of a plateau vortex precipitation event on 14 July 2014. J. Appl. Meteor. Sci., 28, 532–543. DOI:10.11898/1001-7313.20170502
Zhao, P., Z. J. Zhou, and J. P. Liu, 2007: Variability of Tibetan spring snow and its associations with the hemispheric extratropical circulation and East Asian summer monsoon rainfall: An observational investigation. J. Climate, 20, 3942–3955. DOI:10.1175/JCLI4205.1
Zhao, P., X. D. Zhang, Y. F. Li, et al., 2009: Remotely modulated tropical–North Pacific ocean–atmosphere interactions by the South Asian high. Atmos. Res., 94, 45–60. DOI:10.1016/j.atmosres.2009.01.018
Zhao, P., X. D. Xu, F. Chen, et al., 2018: The Third Atmospheric Scientific Experiment for understanding the earth–atmosphere coupled system over the Tibetan Plateau and its effects. Bull. Amer. Meteor. Soc., 99, 757–776. DOI:10.1175/BAMS-D-16-0050.1
Zhao, P., X. J. Zhou, J. M. Chen, et al., 2019: Global climate effects of summer Tibetan Plateau. Sci. Bull., 64, 1–3. DOI:10.1016/J.scib.2018.11.019
Zheng, X. D., X. J. Zhou, J. Tang, et al., 2004: A meteorological analysis on a low tropospheric ozone event over Xining, northwestern China on 26–27 July 1996. Atmos. Environ., 38, 261–271. DOI:10.1016/j.atmosenv.2003.09.063
Zhong, L. Z., R. Mu, D. L. Zhang, et al., 2015: An observational analysis of warm-sector rainfall characteristics associated with the 21 July 2012 Beijing extreme rainfall event. J. Geophys. Res. Atmos., 120, 3274–3291. DOI:10.1002/2014JD022686
Zhou, X. J., C. Luo, W. L. Li, et al., 1995: Variations of total ozone amount in China and the ozone low center over Tibetan Plateau. Chinese Sci. Bull., 40, 1396–1398.
Zhou, X. J., W. L. Li, L. X. Chen, et al., 2004: Study of ozone change over Tibetan Plateau. Acta Meteor. Sinica, 62, 513–527. DOI:10.11676/qxxb2004.053
Zhou, X. J., P. Zhao, J. M. Chen, et al., 2009: Impacts of thermodynamic processes over the Tibetan Plateau on the Northern Hemispheric climate. Sci. China Earth Sci., 52, 1679–1693. DOI:10.1007/s11430-009-0194-9
Zhu, B., X. W. Hou, and H. Q. Kang, 2016: Analysis of the seasonal ozone budget and the impact of the summer monsoon on the northeastern Qinghai–Tibetan Plateau. J. Geophys. Res. Atmos., 121, 2029–2042. DOI:10.1002/2015JD023857
Zhu, X. Y., Y. M. Liu, and G. X. Wu, 2012: An assessment of summer sensible heat flux on the Tibetan Plateau from eight data sets. Sci. China Earth Sci., 55, 779–786. DOI:10.1007/s11430-012-4379-2
Zhuo, H. F., Y. M. Liu, and J. M. Jin, 2016: Improvement of land surface temperature simulation over the Tibetan Plateau and the associated impact on circulation in East Asia. Atmos. Sci. Lett., 17, 162–168. DOI:10.1002/asl.638