The Properties and Formation of Cirrus Clouds over the Tibetan Plateau Based on Summertime Lidar Measurements

Q. S. He * Shanghai Meteorological Service, Shanghai, China

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C. C. Li Laboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China

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J. Z. Ma Chinese Academy of Meteorological Sciences, China Meteorological Administration, Beijing, China

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H. Q. Wang College of Environmental Science and Engineering, Donghua University, Shanghai, China

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G. M. Shi Laboratory for Climate and Ocean–Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, China

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Z. R. Liang * Shanghai Meteorological Service, Shanghai, China

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Q. Luan * Shanghai Meteorological Service, Shanghai, China

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F. H. Geng * Shanghai Meteorological Service, Shanghai, China

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X. W. Zhou * Shanghai Meteorological Service, Shanghai, China

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Abstract

As part of the Tibet Ozone, Aerosol and Radiation (TOAR) project, a micropulse lidar was operated in Naqu (31.5°N, 92.1°E; 4508 m MSL) on the Tibetan Plateau to observe cirrus clouds continuously from 19 July to 26 August 2011. During the experiment, the time coverage of ice clouds only was 15% in the upper troposphere (above 9.5 km MSL). The cirrus top/bottom altitudes (mean values of 15.6/14.7 km) are comparable to those measured previously at tropical sites but relatively higher than those measured at midlatitude sites. The majority of the cloud layers yielded a lidar ratio between 10 and 40 sr, with a mean value of 28 ± 15 sr, characterized by a bimodal frequency distribution. Subvisible, thin, and opaque cirrus formation was observed in 16%, 34%, and 50% of all cirrus cases, respectively. A mean cirrus optical depth of 0.33 was observed over the Tibetan Plateau, slightly higher than those in the subtropics and tropics. With decreasing temperature, the lidar ratio increased slightly, whereas the mean extinction coefficient decreased significantly. The occurrence of clouds is highly correlated with the outgoing longwave radiation and the strong cold perturbations in the upper troposphere. Deep convective activity and Rossby waves are important dynamical processes that control cirrus variations over the Tibetan Plateau, where both anvil cirrus outflowing from convective cumulonimbus clouds and large-scale strong cold perturbations in the upper troposphere should play an important role in cirrus formation.

Corresponding author address: C. C. Li, P. O. Box 100871, Beijing, China. E-mail: ccli@pku.edu.cn

Abstract

As part of the Tibet Ozone, Aerosol and Radiation (TOAR) project, a micropulse lidar was operated in Naqu (31.5°N, 92.1°E; 4508 m MSL) on the Tibetan Plateau to observe cirrus clouds continuously from 19 July to 26 August 2011. During the experiment, the time coverage of ice clouds only was 15% in the upper troposphere (above 9.5 km MSL). The cirrus top/bottom altitudes (mean values of 15.6/14.7 km) are comparable to those measured previously at tropical sites but relatively higher than those measured at midlatitude sites. The majority of the cloud layers yielded a lidar ratio between 10 and 40 sr, with a mean value of 28 ± 15 sr, characterized by a bimodal frequency distribution. Subvisible, thin, and opaque cirrus formation was observed in 16%, 34%, and 50% of all cirrus cases, respectively. A mean cirrus optical depth of 0.33 was observed over the Tibetan Plateau, slightly higher than those in the subtropics and tropics. With decreasing temperature, the lidar ratio increased slightly, whereas the mean extinction coefficient decreased significantly. The occurrence of clouds is highly correlated with the outgoing longwave radiation and the strong cold perturbations in the upper troposphere. Deep convective activity and Rossby waves are important dynamical processes that control cirrus variations over the Tibetan Plateau, where both anvil cirrus outflowing from convective cumulonimbus clouds and large-scale strong cold perturbations in the upper troposphere should play an important role in cirrus formation.

Corresponding author address: C. C. Li, P. O. Box 100871, Beijing, China. E-mail: ccli@pku.edu.cn

1. Introduction

Cirrus clouds are made predominantly or wholly of ice (e.g., Lynch 2002), typically covering 20%–35% of the globe (Liou 1986; Wylie et al. 1994). They affect the earth’s radiation allocation mainly by absorbing outgoing longwave radiation (greenhouse effect) (McFarquhar et al. 2000) and by reflecting solar radiation (albedo effect) (Zerefos et al. 2003). The way by which these two effects interact and, thereby, influence the radiation balance of the atmosphere strongly depends on the optical properties, height, thickness, and temperature of the cirrus layers (Seifert et al. 2007). Thin cirrus clouds usually cause a positive radiative forcing at the top of the atmosphere, whereas thick cirrus clouds may produce cooling (Stephens and Webster 1981; Fu and Liou 1993; Fahey and Schumann 1999; Fu et al. 2002). As cirrus clouds play a significant role in the radiative balance of the earth’s atmospheric system, a clear understanding of their properties, at different geographical locations, is highly essential to climate modeling studies. Although many studies on cirrus clouds have been carried out, significant uncertainties still remain with respect to the radiative and climate effects of cirrus clouds (Solomon et al. 2007). Cirrus clouds in the tropical tropopause layer represent the key to understanding the mechanisms of air entering the stratosphere (Fujiwara et al. 2009). To investigate the formation mechanisms of cirrus is important in understanding well various physical, radiative, dynamical, and chemical processes involved in the coupling between the stratosphere and troposphere.

The Tibetan Plateau, often called “the roof of the world,” is located southwest of China, with an immense area (about 2.5 million km2) and a mean elevation of more than 4000 m MSL. Therefore, it is one of the most imposing topographic features on the surface of the earth. The Tibetan Plateau plays a key role in Asian climatology and atmospheric circulation. Especially given the elevated heat source in summer, the low pressure over the Plateau induces a supply of moist, warm air from the Indian Ocean to the continent, significantly affecting the general circulation and the Asian summer monsoon circulation (Wu and Chen 1985). Recent studies suggest that the climate over the Tibetan Plateau region is changing (Liu and Chen 2000; Thompson et al. 2003), and the total ozone shows a noticeable decrease during the Asian summer monsoon period over the Tibetan Plateau (so-called ozone valley) (Zhou and Luo 1994; Zou and Gao 1997; Kazimirovsky and Matafonov 1998; Gettelman et al. 2004). Several model simulations and satellite observations have been carried out over the Tibetan Plateau to elucidate the effects of cirrus clouds on regional climate and water cycles. Using water vapor and cirrus cloud data derived from the multichannel imaging data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra spacecraft, Gao et al. (2003) examined the seasonal variations of water vapor and cirrus clouds over the Tibetan Plateau in 2002. They found that the mean high-cloud reflectance over the Plateau reaches its maximum in April and its minimum in November. Chen and Liu (2005) investigated the seasonal migration of cirrus clouds over the Tibetan Plateau using a 4-yr dataset of MODIS and found that large amounts of cirrus clouds, occurring in March–April, were generated by relatively warm and moist air being slowly lifted over a large area by an approaching cold front and topographic lifting. A number of satellite observations have shown that cirrus clouds, associated with deep convection, frequently occur over the Tibetan Plateau (Li et al. 2005; Fu et al. 2006; Jin 2006). Although optical image observations from satellites provide valuable information on cirrus clouds, they have limited temporal and vertical spatial resolution. This limitation stresses the need for local active remote sensing, such as lidar, which, with its capability to detect high and optically thin cirrus clouds, makes it one of the most appropriate instruments for cirrus study (Wang et al. 2005; Noel et al. 2007). Key microphysical parameters of cirrus clouds include the extinction coefficient, extinction-to-backscatter ratio, and cloud-base height, as well as cloud geometric depth (Sunilkumar and Parameswaran 2005). The extinction-to-backscatter ratio, also known as the lidar ratio, is defined for an atmospheric scatterer as the ratio of the volume extinction coefficient (km−1) to the volume backscatter coefficient (km−1 sr−1), which is closely associated with the crystal phase function at 180° (backscattering) and typically varies from about 10 to 60 sr for tropospheric clouds (Del Guasta 2001; Whiteman et al. 2004). Perhaps most importantly, the lidar ratio is also an intermediate variable solved through iterations of the singular lidar equation used in the retrieval of extinction and backscatter coefficients from elastic backscatter lidar data (Fernald et al. 1972). The optical depth of clouds is a key parameter in radiative transfer computations and, therefore, considerable efforts have been undertaken for its retrieval. Several field campaigns have been carried out in various regions of the globe to improve knowledge in cirrus cloud occurrence and formation processes, as well as the climate impact of cirrus clouds (Platt et al. 1998, 2002; Heymsfield et al. 1998; Sassen et al. 2000; Comstock et al. 2002; Pace et al. 2003; Sunilkumar and Parameswaran 2005). Over the Tibetan Plateau, however, vertically and temporally resolved measurements of cirrus cloud properties are still scarce, whereas the cloud-top and tropopause relationships by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; http://www-calipso.larc.nasa.gov/) (Pan and Munchak 2011) and case study of cirrus cloud properties by balloon (Tobo et al. 2007) has been reported recently.

In the present study micropulse lidar (MPL) observations of aerosols and clouds were performed for more than 800 h in Naqu, and about 80 radiosondes were launched. The experiment was carried out from July to August 2011 so that the underlying dataset covers the summer monsoon period of the Tibetan Plateau. We examine the temporal variation and the formation mechanism of cirrus clouds over the Tibetan Plateau using the newly available 2-month lidar cirrus cloud dataset obtained during the Tibet Ozone, Aerosol and Radiation (TOAR) field campaign. Based on the most comprehensive lidar- and radiosonde-based cirrus cloud statistics for the Tibetan region, the obvious optical characteristics of cirrus have been exacted from different formation mechanism. The paper is organized as follows. Section 2 describes the experimental setup and the data analysis methods. Section 3 presents the results of the simultaneous lidar and radiosonde observations. The geometrical and optical properties of the observed cirrus layers are presented and compared with those of the tropical, subtropical, and midlatitude cirrus observed in other studies. In section 4, the cirrus formation process is discussed. Finally, section 5 provides a short summary.

2. Experiment and methods

a. Micropulse lidar

An MPL (MPL-4B, Sigma Space Corporation, United States) was operated at the Naqu Meteorological Bureau (31.5°N, 92.1°E; 4508 m MSL) on the Tibetan Plateau. The location of the Naqu site and the topography of the Tibetan Plateau are plotted in Fig. 1. Naqu is located in the central part of the Tibetan Plateau. During summer, the elevated surface heat and the rising air over the plateau lead to anticyclonic circulation and divergence in the upper troposphere and the lower stratosphere (Yanai et al. 1992). The MPL is a backscatter lidar that uses a neodymium: yttrium lithium fluoride (Nd:YLF) laser with an output power of 12 μJ at 532 nm and 2500-Hz repetition rate. The diameter of the receiving telescope is 20 cm, and the field of view (FOV) is 0.1 mrad. The relatively small FOV reduces background noise and makes the multiple scattered signals from optically thin cirrus clouds negligible. The vertical resolution of the lidar data is 30 m, and the integration time of the data is 30 s.

Fig. 1.
Fig. 1.

Location of the MPL observation site and the topography of the Tibetan Plateau.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

We used the cloud mask algorithm of Clothiaux et al. (1998) to identify the cloud boundaries from the lidar backscatter profiles, and then applied the algorithm of Comstock and Sassen (2001) to calculate the optical depth and the lidar ratio of the cirrus. The visible optical depth calculation generally involves integrating the values of the lidar cloud backscatter coefficient β (km−1 sr−1) between the cloud base Hb and top Ht. Comstock and Sassen (2001) reported that estimating the lidar ratio s1 for each profile independently involves the use of the average backscatter coefficient above the cloud. Varying the cirrus lidar ratio yields the most appropriate profile of the cirrus backscatter coefficient; the variation should proceed until the particle backscatter coefficient above the cirrus layer approaches zero again and varies around zero in the stratosphere because of signal noise. The uncertainty in the retrieval products caused by the assumption of particle free air below and above the cirrus clouds is less than 24% (Comstock and Sassen 2001). The effect of forward multiple scattering on the returned energy also contributes to the uncertainty in the optical depth. Because of the narrow FOV of the MPL receiving telescope, the contribution of forward multiple scattering to the total cloud optical depth is assumed to be relatively small. We corrected the multiple scattering effect, following the scheme of Chen et al. (2002), who used a multiple scattering factor η of 0.98–1 for subvisible cirrus, 0.86–0.98 for thin cirrus (optical depth from 0.03 to 0.3), and 0.58–0.86 for opaque cirrus (optical depth from 0.3 to 1). The uncertainty in the optical depth and the column lidar ratio introduced by the multiple scattering correction is estimated to be 10% because of the unknown effective size of cirrus particles.

In the statistics presented in the next section, only clouds above 9.5 km MSL were considered to avoid the possible impact of water clouds on our statistics. This bottom threshold is defined by temperature. Ice clouds exist at temperatures cooler than −40°C, and the altitude corresponding to this temperature is approximately 5 km AGL in the extratropics (Lynch 2002), which refers to 9.5 km MSL over the Tibetan Plateau.

b. Radiosonde observations

During the field campaigns, 76 L-band (GTS1) electronic radiosondes (Nanjing Bridge Machinery Co., Ltd., China) were launched to provide vertical profiles of pressure, temperature, and humidity up to 20–25 km AGL. The radiosondes were released at the lidar field site in Naqu twice a day at 0000 and 1200 UTC (LST − 8 h).

Eleven weather balloons with Vaisala RS92 radiosondes (Vömel et al. 2007) have been launched to provide profiles of air temperature, relative humidity (RH), wind speed, and wind direction usually up to the midstratosphere. The RH can be measured between 0% and 100% with a resolution of 1% and an accuracy of 5% at −50°C (Miloshevich et al. 2006; Währn et al. 2004).

c. Satellite observations

National Oceanic and Atmospheric Administration (NOAA) satellites provide an outgoing longwave radiation (OLR) product for the top of the atmosphere. OLR data are calculated on a daily basis by the Climate Diagnostic Center (CDC), a division of NOAA (Liebmann and Smith 1996). The horizontal resolution is 2.5° × 2.5°. Missing values are computed by applying spatial and temporal interpolations. The OLR in this dataset is calculated by converting 1012-μm channel radiances measured by the Advanced Very High Resolution Radiometer aboard the NOAA operational polar-orbiting satellites. The daily mean is the average of one daytime and one nighttime measurement. The OLR emitted by high, cold, deep convective clouds is much lower than that by warmer low clouds or by the surface. Usually, values of less than 200 W m−2 indicate deep convection (Fujiwara et al. 2009). Deep convection, in turn, indicates regions with extensive lifting of air that may play a role as source regions for cirrus clouds.

3. Results of the simultaneous lidar and radiosonde observations

a. Cirrus clouds observations

The cirrus fraction (CF), defined as the ratio of the number of cirrus cloud events to the total number of soundings during the entire measurement period, is calculated from the MPL data over the Tibetan Plateau to be 14.6%. The data records with water clouds causing the lidar signal saturated were not involved in the statistics. Comstock et al. (2002) studied the optical and geometrical properties of tropical cirrus clouds and found that high clouds occur 44% of the time on average. The yearly averaged CF is 16% between 30° and 60° latitude. Mace et al. (2009) found that CF is approximately 15%, on average, in midlatitudes from the first year of Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) observations for clouds with the tops above 6 km. Sassen et al. (2008) found that CF is about 15% in midlatitudes. The cirrus fractions we observed are similar to those in midlatitudes but much less than tropic region.

Figure 2 shows two cases of cirrus observations during the TOAR campaign. The first case is that on 29 July 2011 (Fig. 2a), which shows the typical situation observed frequently over the Tibetan Plateau. In the afternoon (1530–1900 LST), cirrus clouds were detected at various altitudes from 14.5 to 16.5 km. A Vaisala RS92 radiosonde was launched at 0748 UTC and reached the tropopause at 17 km about 1 h later. Figure 2c presents the temperature and relative humidity above ice (RHi) measured by this sounding along with lidar. These rather thick cirrus clouds had optical depths around 0.3 and occurred in the temperature range of −60° to −70°C. The radiosonde data indicate that the air in the cirrus clouds was relatively wet with RHi of about 120%, which is very similar to the other case measured at 0848 UTC 17 August with maximum RHi of 125%.

Fig. 2.
Fig. 2.

(a),(b) Two cases of cirrus observations during the TOAR campaign. Range-corrected 532-nm signals are shown with 30-s and 30-m resolution. (c),(d) Temperature and RHi profiles measured by the RS92 radiosonde. In cases with strongly varying cloud-base (center) and/or cloud-top height, 10-min averages are computed, and the respective mean values are taken as the cloud-base/-top height.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

b. Frequency distribution of cirrus cloud properties

The global distribution of cloud vertical structure is essential to climate studies because of its effect on both the magnitude and the sign of the net cloud radiative forcing and latent heating profiles of the atmosphere, which, in turn, affects both small-scale dynamics and the general atmospheric circulation (Ramaswamy and Ramanathan 1989; Randall et al. 1989; Chang and Li 2005). Figure 3a shows the vertical distribution of the frequency of the top and bottom altitudes of the cirrus cloud measured by MPL over the Tibetan Plateau. Vertical frequency distributions of cirrus bottom/top altitudes were calculated at 1-km altitude intervals. The distribution at 10.5 km, for example, represents the averaged cirrus frequency for altitudes between 10 and 11 km. The vertical frequency distributions of the cirrus bottom/top altitudes over the Tibetan Plateau have a skewed normal distribution, especially for the cloud-top distribution. The maximum frequencies of the cirrus cloud top (17 km) and bottom (15 km) are 27% and 31%, respectively. The bottom altitudes show a broad distribution from 10 to 18 km, with a mean value of 13.7 km. Dominant fractions of cloud tops are vertically distributed between 14.5 and 17.5 km, with a mean value of 15.6 km over the Tibetan Plateau. The cloud tops do not have large fractions above the tropopause (17.5 km). To identify similarities and differences in the cirrus properties of different latitudinal bands, we compared the present results with measurements obtained from the lidar system at other latitudes. Based on the Geoscience Laser Altimeter System (GLAS) data within the period of 1 October–18 November 2003, Eguchi et al. (2007) found the maximum frequencies of the cirrus cloud top (bottom) in the tropics as 13% (8%) at 16.5 (14.5) km, which are lower than observed in the current work. Comparisons of our experimental results with other studies further reveal that the cloud top over the Tibetan Plateau share similarities with those in previous works at the tropical sites—for example, at Nauru (16 km; Comstock et al. 2002) and at the Maldives (around 14–15 km; Seifert et al. 2007). As for most of the midlatitude cirrus clouds, the top altitudes were found most frequently at 11–13-km altitudes (e.g., Ansmann et al. 1993; Sassen and Campbell 2001; Sassen and Comstock 2001; Wang and Sassen 2002). The cirrus top/bottom altitudes over the Tibetan Plateau are relatively higher than those at the midlatitude sites. In fact, the tropopause height over the Plateau during this time is higher than that in the midlatitude region. As presented by Pan and Munchak (2011), the region of the Plateau, about 20°–40°N, is covered under the high tropical-like tropopause in August during the monsoon. As a result, the cloud-top/-bottom distribution is spread out over a large range in the vertical, up to the tropical tropopause altitudes over the Plateau. The distribution also indicates that the convection from the Plateau results in cloud tops below the core of the Asian monsoon anticyclone (~12–14 km) (e.g., Randel and Park 2006).

Fig. 3.
Fig. 3.

(a) Vertical distribution of the frequency of the cloud layer–top altitudes (black bar) and –bottom altitudes (white bar) from the MPL dataset, (b) frequency of cirrus cloud geometric thickness, (c) frequency of cirrus lidar ratio, and (d) frequency of cirrus cloud optical depth.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

Figure 3b displays the distribution of the cirrus cloud mean thickness. The most common cirrus thickness over the Tibetan Plateau is less than 2.5 km, with an occurrence frequency of about 80%. For the midlatitude sites, the mean value of cirrus thickness (1.8 km) was found over Utah (Sassen and Campbell 2001). The mean cirrus depth was 2–2.5 km over Oklahoma (Wang and Sassen 2002). For the tropical latitudes, Seifert et al. (2007), Sivakumar et al. (2003), and Sunilkumar and Parameswaran (2005) showed thickness values of around 0.5–2.5 km (75% of all cases). The observations at Nauru (Comstock et al. 2002) and the Maldives (Seifert et al. 2007) also reveal that the cloud bottom is typically about 2 km below the cloud top at the tropical sites. These observations indicated that the mean cloud thickness (1.7 km) over the Tibetan Plateau is at the lower end of the observed cirrus cloud thicknesses globally.

The lidar ratio is an important parameter for the inversion of lidar signals in instruments that do not have Raman channel. Space-based lidars, such as CALIPSO, depend on a parameterization that may vary with location and cloud type. This function of occurrence frequency of the lidar ratio in the Tibetan Plateau, as shown in Fig. 3c, can be characterized by a bimodal distribution, with a mean value of 28 ± 15 sr. Aside from the main peak at around 10 sr, a second mode occurs at around 35 sr. The majority of the cloud layers yields a lidar ratio between 10 and 50 sr. The bimodal distribution of lidar ratio in the Tibetan Plateau is similar to the observations in The Observing System Research and Predictability Experiment–Pacific (THORPEX; Shapiro and Thorpe 2004). Similar mean lidar ratios were observed in some tropical sites. For example, the mean lidar ratio of 20 ± 8 sr was derived from the lidar observations in Taiwan (25°N, August 1999–July 2000) during the Indian Ocean Experiment (INDOEX), as presented by Chen et al. (2002), and the lidar ratios of 10–40 sr (mean values of 20 ± 8 sr) were observed over the Andros Islands (25°N, August–September 1998), as reported by Whiteman et al. (2004). Our results are significantly larger than the value measured at the midlatitude site of Lindenberg, Germany (16 ± 9 sr) (Immler et al. 2007), indicating that the significantly different meteorological conditions may be responsible for the cirrus formation in the two regions.

Figure 3d shows the relative frequency of occurrence of the cirrus optical depth (COD) over the Tibetan Plateau. COD ranges from 3.0 × 10−4 to 2.6, with a mean value of 0.33 ± 0.29, around the visibility threshold. According to the classification scheme of cloud types by Sassen and Cho (1992), who divided cirrus clouds by optical depth τ, with τ < 0.03 as subvisible cirrus, 0.03 < τ < 0.3 as thin cirrus, and τ > 0.3 as opaque cirrus, 16% of all analyzed cirrus cases are subvisible cirrus, 34% thin cirrus, and about 50% opaque cirrus. The COD shape of the distribution suggests a discrimination between the two types of cirrus clouds over the Tibetan Plateau: thin cirrus and opaque cirrus; the latter are usually visible to the naked eye. Sassen and Campbell (2001) presented a midlatitude climatology showing that COD is greater than 0.3 in 50% of detected cases. Goldfarb et al. (2001) found that 20% of total cirrus cloud occurrences are subvisible in a midlatitude lidar station in France. Some other midlatitude observations reveal that subvisible, thin, and opaque cirrus clouds occurred at about 10%, 60%–65%, and 25%–30% of all cases over central Europe (Reichardt 1999) and Oklahoma (Wang and Sassen 2002), and roughly 10%, 30%, and 60% over Utah (Sassen and Comstock 2001). In the tropical site, the Nauru observations (0°S, 166°W, April–November 1999) revealed more subvisible cirrus (20%–25%) and more thin cirrus (60%–70%). Compared to the cirrus statistics at the tropical site of Nauru, the frequency of subvisible cirrus over the Tibetan Plateau is remarkably similar; for the midlatitude, the frequency of opaque cirrus over the Tibetan Plateau is similar to that found in Utah but higher than that in central Europe and Oklahoma. Based on some midlatitude observations, the mean COD was 0.58 in Oklahoma and 0.75 in Utah (Sassen and Comstock 2001), and about 0.25–0.3 in northern Germany (Ansmann et al. 1993; Reichardt 1999). The geometrical and optical properties of cirrus observed on the Tibetan Plateau are summarized in Table 1, which also lists the results from other locations in the world for comparison. It must be borne in mind that the observations from the other sites in Table 1 are multiyear observations, but the current study was done for less than 2 months during the summer. By comparing the mean COD results obtained in different campaigns, the probability of encountering opaque cirrus in the upper troposphere over the Tibetan Plateau, as well as in other midlatitudes, was clearly enhanced relative to those in the subtropics and tropics. This result may be explained by the enhanced lifetime of this opaque midlatitude cirrus, compared with its subtropical and tropical counterparts.

Table 1.

Mean values and standard deviations (in parentheses) of the geometrical and optical cirrus properties in different locations around the world.

Table 1.

c. Dependence of cirrus optical properties on temperature

Various studies (Heymsfield and Platt 1984; Platt and Harshvardhan 1988; Sassen and Comstock 2001) have shown that temperature is an important factor in determining cirrus cloud properties because of the strength of the adiabatic process. Figure 4 shows a steady increase of lidar ratio from about 15–21 ± 10 sr at −50°C to 40 ± 10 sr at temperatures around −80°C. Interestingly, Whiteman et al. (2004) found a similar behavior in lidar ratio at Andros Islands, Bahamas. Excluding the hurricane-influenced observations, they found a steady increase from about 22 ± 8 sr at −50°C to 28–33 ± 12 sr at temperatures around −70°C. Similar lidar ratios observed during INDOEX were also derived from the lidar observations in Taiwan, as presented by Chen et al. (2002). In the height range of 12–15 km (−50° to −70°C), they found single-scattering-related lidar ratios of about 35 ± 15 sr. The lidar ratio over the Tibetan Plateau shows larger values in temperatures around −80°C compared with the subtropical observations.

Fig. 4.
Fig. 4.

Lidar ratio as a function of midcloud temperature. The error bars represent the standard deviations of the lidar ratio of the whole continuous cirrus around the sounding launch time.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

Both experiments (Sassen 1978) and theory (Takano and Liou 1995) have indicated that LR is controlled by the complexity of ice crystal shape and aspect ratio. According to the model calculations of the optical properties of ice crystals with weak shape distortion (slight deviations from the regular hexagonal structure and rough surface) (Seifert et al. 2007), columnlike crystals mostly produce lidar ratios on the order of 5–20 sr, whereas platelike crystals lead to lidar ratios in the range predominately from 15 to 35 sr. The model study further shows that lidar ratio is rather sensitive to crystal shape, especially to deviations from the ideal hexagonal structure (pristine particles). With increasing distortion (irregularity), the lidar ratios increase. Lidar ratios for larger, more complex crystals that are assumed to show a higher degree of distortion than small crystals are considerably larger than 30 sr (Seifert et al. 2007). According to these simulations, we conclude that extremely low temperatures at the tropopause layer (−65° to −80°C) with strong stability may initiate the formation of crystals with large mean sizes and more complex forms with irregular structures compared with the warmer layer (−50° to −65°C) over the Tibetan Plateau. However, the translation of the crystal optical properties into actual shapes and sizes of the cirrus particles is not straight forward (Reichardt et al. 2002). Composite particles have been shown to scatter similarly to the ensemble of basic crystals that formed it (Yang and Liou 1998). So a small ice particle consisting of one or more relatively large ice crystals may still have a higher lidar ratio than a large ice particle formed from relatively small crystals (Reichardt et al. 2002). The ice particles become larger and more irregular at lower levels (higher temperatures) because of collisions and stronger impact of turbulence. We propose that the crystals that form the particles in the two different layers are formed with very different formation mechanisms (see section 4). To determine the radiative properties of clouds accurately, a basic requirement is improving knowledge on cirrus extinction coefficient δ as a function of temperature T (Heymsfield and McFarquhar 2002). Parameterization functions, determined from the distributions of the extinction coefficient dependency on temperature, are useful to improve cirrus modeling. The parameterization function derived from the TOAR dataset is shown in Fig. 5 (solid line). The fitted equation is δ = 0.568 + 6.0 × 10−3T. The mean extinction coefficient decreases with decreasing temperature for typical cirrus temperatures less than −50°C. For comparison, additional fit functions are presented for the tropical region of the Maldives [dashed line (Seifert et al. 2007)] and for the midlatitudinal region of Oklahoma [dotted line (Wang and Sassen 2002)]. Wang and Sassen (2002) presented a relatively stronger, almost exponential increase in the extinction coefficient with increasing temperature for the Oklahoma dataset, whereas the polynomial function for the Maldives data greatly deviated from the TOAR polynomial function. Obviously, a weaker increase in the trend of the extinction coefficient with increasing temperature was observed in Maldives, compared to the TOAR function.

Fig. 5.
Fig. 5.

Mean extinction coefficient vs temperature. The solid curve shows the fitting line of the mean cloud extinction coefficient for the Tibetan Plateau dataset. The dashed curve is the polynomial fit function of the Maldives distribution, and the dotted curve shows the polynomial fit function of the midlatitude cirrus clouds observed over Oklahoma. The error bars represent the standard deviations of the extinction coefficients of the entire continuous cirrus around the sounding launch time.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

4. Cirrus formation process and maintenance mechanism

According to current understanding, the primary formation mechanisms of cirrus clouds in the midlatitude region are the outflow from deep convection (Li et al. 2005; Fu et al. 2006; Jin 2006), the large-scale uplift of humid layers induced by the Asian monsoon (Chen and Liu 2005), and the cooling due to the wave activity in the upper troposphere (Spichtinger et al. 2003).

The low OLR (<200 W m−2) has been treated as an indicator of organized deep convective activity in the troposphere (Fujiwara et al. 2009). Figure 6 shows the OLR calculated from the CDC OLR dataset for the Naqu observation site. The occurrence of cirrus clouds was strongly correlated with deep convection. From the graph, a strong convective activity over the site is obvious, especially in two stages (between 26 and 30 July and between 15 and 18 August). In addition, as with the Ice, Cloud, and Land Elevation Satellite (ICESat)/GLAS, cirrus statistics based on satelliteborne lidar measurements reveal an increase in the frequency of the occurrence of cirrus clouds with decreasing OLR (Dessler et al. 2006). However, OLR was high (more than 200 W m−2 on some days) on 23, 24, and 31 July and on 19 and 20 August 2011, despite occurrence of cirrus clouds. The relationship between the occurrence of cirrus clouds and OLR indicates that cirrus formation is not always connected with the deep convective activity over the Tibetan Plateau during the observation period. Some other mechanism may contribute to the cirrus formation and maintenance.

Fig. 6.
Fig. 6.

Daily mean OLR calculated from the CDC OLR dataset over the lidar observation site. The white bars represent the occurrence of cirrus clouds in the specified days.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

According to the period of occurrence of cirrus clouds, the continuous lidar observation can be split into four stages: 19–31 July and 15–21 August 2011 for the cirrus maintenance stages, and 2–14 August and 22–26 August 2011 for the cirrus blank stages. Figure 7 shows the spatial distributions of OLR, averaged over the four stages, which is an indicator of the organized convective activity over the Tibetan Plateau. The location of the lidar site is also shown in Fig. 7, denoted by the star symbol. The prominent feature over the Tibetan Plateau is the occurrence of cirrus clouds, associated with the deep convection (OLR < 200 W m−2) in the troposphere. Therefore, more than half of the Tibetan Plateau cirrus clouds we observed had been significantly affected by the deep convective activity. Convective cumulonimbus clouds are the primary source of outflow cirrus, which would form when upper-tropospheric winds blow ice particles away from their convective cores. This cirrus is usually called anvil cirrus. In addition, the anvil clouds that remain in the troposphere after the deep convective cloud has dissipated are counted as outflow cirrus.

Fig. 7.
Fig. 7.

Temporal mean OLR distribution over the four time periods: (a) 19–31 Jul, (b) 2–14 Aug, (c) 15–21 Aug, and (d) 22–26 Aug 2011. The mean wind fields at 200 hPa (white arrow) from the National Centers for Environmental Prediction (NCEP) reanalysis data for the same time periods are also shown. The location of the lidar site is denoted by the star symbol.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

Figure 8 shows the deviation field from the average temperature of the radiosondes in July and August 2011. The blue and green dots vertically distributed on the plot correspond to the observed bottom and top of cirrus clouds, respectively. The red areas correspond to a positive deviation of 6 K, and the dark blue areas correspond to a negative deviation of 8 K from the average temperature. In two stages, from 19 July to 1 August 2011 and from 15 to 21 August 2011, the cold perturbation can be found at an altitude of about 15 km. During these time periods, the highest frequency of cirrus clouds was observed. During warmer periods, such as that between 2 and 14 August 2011, almost no cirrus cloud was detected, despite continuous lidar observations. The Rossby waves can best be recognized at altitudes above 17 km in the tropopause layer. They show a duration cycle of about 12 days with amplitude of more than 5 K.

Fig. 8.
Fig. 8.

Deviation field from the average temperature of the radiosondes in the summer of 2011. The blue and green dots are the observed bottom and top of cirrus clouds, respectively.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

Figure 8 suggests that cirrus occurrence generally increases when strong cold perturbations occur in the tropopause layer and upper troposphere. This should be a frequently observed phenomenon in the midlatitude, but for Tibet, during such perturbation events, convective activity also increases, possibly because of the strengthened atmospheric instability by the cold perturbation in the upper troposphere and a daily strong warming at the surface. This is the difficulty to distinguish the cirrus from the two formation mechanisms over the region. Comstock and Jakob (2004) suggested the two kinds of cirrus can be distinguished from their optical properties with tropical observations. Those observed near convection (anvils) are usually physically and optically thinker than those observed detached from convection near the tropopause layer have a lower cloud base height and have more visible structure within the cloud. Figure 9 presents our observations on the daily mean COD data depending on the corresponding lidar ratios. The dots represents those data in the days with daily mean OLR > 200 W m−2 and the crosses for those daily mean OLR < 200 W m−2 indicating deep convection occurring. Almost all daily mean measurements near convection have a larger mean COD (larger or near 0.3, except one sample). Comparing the results with the lidar ratio distribution depending on temperature (or altitude) on Fig. 4, we concluded that the value 0.3 of COD can be treated as the COD threshold to distinguish the cirrus from convection outflow (anvils) and that from large-scale cold perturbations or vertical ascent over the Tibet Plateau.

Fig. 9.
Fig. 9.

Daily mean COD vs lidar ratio. The dots represents those data in the days with daily mean OLR > 200 W m−2 and the crosses for those with daily mean OLR < 200 W m−2, indicating deep convection.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

Recent studies reveal a strong connection between cirrus clouds and atmospheric waves that causes in situ cooling on a synoptic scale. Massie et al. (2002) noted that, 50% of the time, subvisible cirrus clouds are associated with regions of the tropics near the tropopause, for which backward trajectories are not associated with deep convection. These observations are consistent with the formation of cirrus clouds due to in situ cooling of the humid layers. In the middle latitudes, the most striking cirrus cloud features are produced by upper-air disturbances associated with Rossby waves. Because of the high altitude of the tropopause, the cold temperatures in that area may enable cirrus cloud formation (e.g., Spichtinger et al. 2003). Immler et al. (2008) studied the formation and occurrence of thin cirrus and contrails on the basis of lidar and radiosonde observations over eastern Germany during the heat wave in the summer of 2003. In particular, cirrus clouds were found to occur ubiquitously in high pressure systems, where their coverage was 67% on average. A midlatitude cirrus cloud climatology over Utah through lidar measurements from 1986 to 1996 was used to establish a regional subset of cloud heights combined with radiosondes (Sassen and Campbell 2001). They provided a classification of different weather regimes by visual inspection, and the classification showed the link of high cirrus clouds in cold anticyclones. Spichtinger et al. (2005) discussed the evolution of inertia–gravity wave–inducing cirrus cloud formation by mesoscale updrafts during a late phase of a Rossby wave–breaking event. According to their study, negative temperature deviations from the average temperature in the upper troposphere are directly related to the occurrence of cirrus clouds. Our Tibetan Plateau radiosonde/lidar dataset validates the similar behavior of correlation between tropospheric Rossby waves and the occurrence of cirrus clouds.

Boehm et al. (1999) examined the mechanisms that maintain these clouds using a two-dimensional numerical cloud-resolving model. They concluded that large-scale upward motion is needed to maintain the clouds. Chen and Liu (2005) considered that the strong convective activity within the monsoon system and the highest mountains in the world surrounding the Tibetan Plateau, such as the Himalayas, Pamir, and Kunlun Shan, possibly make the Asian monsoon regions and the Tibetan Plateau favorable for the occurrence of cirrus clouds, and thus plenty of cirrus clouds may exist over these regions. According to Chen and Liu (2005), the formation of cirrus clouds in the midlatitude is possibly induced by the large-scale uplift of humid layers during the Asian monsoon. Figure 10 shows the daily variation in plateau monsoon index (PMI) and the 7-day-averaged PMI time series from 1 July to 31 August 2011, with an overlap of cirrus occurrence. PMI is an indicator of the daily mean intensity of the Tibetan Plateau monsoon. A large PMI value indicates stronger monsoon in summer, which can be determined as follows (Tang et al. 1984):
eq1
where H is the daily deviation from the monthly mean geopotential height at 600 hPa. The subscript numbers 0–4 indicate the location of the center (32.5°N, 90°E), west (32.5°N, 80°E), south (25°N, 90°E), east (32.5°N, 100°E), and north (40°N, 90°E) of the Plateau, respectively.
Fig. 10.
Fig. 10.

Daily variation of PMI and the 7-day-averaged PMI time series from 1 Jul to 31 Aug 2011. The days with cirrus occurrence are shaded.

Citation: Journal of the Atmospheric Sciences 70, 3; 10.1175/JAS-D-12-0171.1

Many research efforts have adopted the PMI to analyze the Tibetan Plateau monsoon variation. It is concluded that the index can reasonably describe the main characteristics of the Tibetan Plateau monsoon (e.g., Bai et al. 2001, 2005; Xun et al. 2011). During the first stage (from 19 July to 1 August 2011), when the highest frequency of cirrus clouds was observed, the values of PMI were high (more than 70 for most of the time). The values sharply decreased to below −20 in the second stage of the high frequency of cirrus clouds from 15 to 21 August 2011. No obvious correlation was observed between the cirrus occurrence and the intensity of the Asian monsoon over the Tibetan Plateau during the campaign period, especially for the duration of 22 July and 12 August, when air mass with relatively less humidity in the lower troposphere (RH ~ 15%) may be responsible for unformed cirrus clouds, even under conditions of remarkable topographic uplift.

5. Conclusions

During the TOAR field campaign, a high-performance MPL was successfully deployed at a Tibetan Plateau site. Measurements were continuously performed from 19 July to 26 August 2011. Radiosondes were launched twice daily to supply the temperature, RH, and wind profiles. The occurrence of cirrus clouds was about 15% during the measurement. The cirrus top/bottom altitudes (with mean value of 15.6/13.7 km) over the Tibetan Plateau site showed similarities to the results of previous work for midlatitude sites, but were relatively lower than those of tropical sites. COD ranged from 3 × 10−4 to 2.6. We showed that the lidar ratio of the Tibetan Plateau cirrus clouds has a mean value of 28 sr, which is significantly higher than that of the midlatitude cirrus clouds observed in Germany (16 sr). This result implies that the microphysical properties of the Tibetan Plateau cirrus clouds are different from those of other midlatitude and tropical cirrus clouds. Subvisible, thin, and opaque cirrus clouds were observed in 16%, 34%, and 50% of all cirrus cases, respectively. By comparing the mean optical depth over the Tibetan Plateau (0.33) with the results obtained during the previous campaigns, the probability of encountering opaque cirrus in the upper troposphere over the Tibetan Plateau, as well as at other midlatitudes, was clearly enhanced, relative to those in the subtropics and tropics. This result may be explained by the frequently occurring opaque cirrus clouds from convection outflow, compared to their subtropical and tropical counterparts. The lidar ratio over the Tibetan Plateau showed larger values in temperatures around −80°C in the tropopause layer, compared to the subtropical observations, which may initiate the formation of crystals with large mean sizes, more complex forms, and irregular structures over the Tibetan Plateau. We also detected that the lidar ratio slightly increased with decreasing temperature, whereas the mean extinction coefficient significantly decreased with decreasing temperature or increasing height. These observed trends in optical properties, as functions of temperature, should help improve current parameterizations of extinction-to-backscatter ratio which, in turn, should yield increased accuracy in cloud optical depth and radiative forcing estimates.

We used the satellite-derived OLR data, together with lidar observations, to investigate the cirrus formation and its maintenance mechanism. The relatively close connection between the occurrence of cirrus and the low OLR (<200 W m−2) in the troposphere indicates that more than half of the cirrus clouds observed at Naqu had been significantly caused by deep convective activity. The other origin and maintenance mechanism of cirrus clouds were also investigated using lidar observations and temperature deviations, calculated from the averaged temperature profile in 2 months. The results suggest that large-scale cold perturbations or vertical ascent is responsible for the formation and evolution of cirrus clouds, which is mostly associated with in situ nucleation and freezing to ice crystals. Because the anvil cirrus is usually physically and optically thicker, the thresholds of COD ~ 0.3 and corresponding appropriate temperature, cloud height, and lidar ratio data can be used to differentiate whether the formation is near or detached from convection over Tibet Plateau.

In the present study, we only have 2 months of data, and we simply speculate the mechanism responsible for these observed phenomena. More extended meteorological observations and optical measurements such as depolarization ratio from Raman lidar are needed to obtain a better understanding of the formation and the variations of cirrus clouds over the Tibetan Plateau. This study is the first to provide measurements of lidar ratio over the Tibetan Plateau and should be of particular interest in space-based lidar missions that rely on parameterization for the lidar ratio to determine the optical depths of cirrus clouds. Moreover, climate modelers pay attention to cirrus clouds because of the lack of observations and the large uncertainty in their parameterization. We expect that our understanding of high clouds over the Tibetan Plateau and nearby areas will be further improved in the future, with more atmospheric information being obtained from observations, such as MODIS, and will ultimately help improve climate modeling.

Acknowledgments

This study is partially supported by the research grants from the China Meteorological Administration Public Welfare Special Funds (Grants GYHY201106023 and GYHY201006047), the National Natural Science Foundation of China (NSFC, Grants 40705013, 40975012, and 41175020), and the Shanghai Science and Technology Committee Research Special Funds (Grant 10JC1401600). We thank all TOAR team members and the staff from the Tibet Meteorological Service for assisting our experiment work. The authors gratefully acknowledge the NOAA/OAR/ESRL PSD, Boulder, Colorado, for providing the interpolated OLR data on their website http://www.cdc.noaa.gov/.

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