Knowledge of the spatiotemporal coverage of cirrus clouds is
vital in quantifying the radiation budget of the Earth–atmosphere system. In
this paper, we present the diurnal and vertical distributions of the
occurrence of cirrus clouds during different seasons as well as the
interannual variation in the
occurrence of cirrus over Kattankulathur (12.82
Cirrus clouds are the first clouds to interact with solar radiation. They
modify the Earth's radiation budget by reflecting the incoming solar
radiation (albedo effect) and trapping the outgoing longwave radiation
(greenhouse effect). Therefore, the net radiative effects depend on the
macrophysical, microphysical, and optical properties of cirrus clouds
(Lynch, 2002). Tropical deep convective areas are generally capped by cirrus
clouds (Sassen et al., 2009), with the highest fraction of optically thin
cirrus (
Cirrus clouds over tropical latitudes exhibit a variety of natures. Broadly,
cirrus clouds are observed as laminar or horizontally lying (Jensen et al.,
1996), descending, and ascending (Nair et al., 2012). These
clouds can appear as either single-layer or multilayer cirrus (Li et al.,
2011). The laminar cirrus clouds very close to the cold-point tropopause
(CPT) are generally referred to as “tropopause” or “cold-trap” cirrus (Winker
and Trepte, 1998). They occur as thin–subvisible forms under
cold (
Globally, cirrus clouds cover about 50 % of the Earth's surface, with a maximum fraction of
coverage over the tropics (Liou, 1986), mainly within
the TTL (Wang et al., 2012). The TTL is a region between convective outflow
(
The occurrence of cirrus clouds maximizes around regions of intense
convective activities (Spinhirne et al., 2005). Cirrus
clouds frequently occur over the convectively active areas primarily
associated with oceanic convection, such as equatorial Africa, South
America, and southern Asia (Dessler et al., 2006). The cirrus
cloud occurrence over these convective regions shows a large seasonal
variation which is found to be associated with the seasonal shift in the
Intertropical Convergence Zone (ITCZ) and midlatitude storm belts
(Wylie et al., 2005; Nazaryan
et al., 2008). Large-scale circulation patterns, like the El Niño–Southern
Oscillation (ENSO), the quasi-biennial oscillation (QBO), and the Brewer–Dobson
circulation (BDC), also significantly affect the temporal variability in the
occurrence of cirrus clouds (Davis et al., 2013; Tseng and Fu, 2017). For
example, the occurrence of cirrus clouds over a tropical station, Gadanki, was
found to be
The tropical convection or cloudiness shows a diurnal pattern, with a peak in the afternoon to early evening over the continents and midnight to early morning over the oceanic regions (Chen and Houze, 1997; Liu et al., 2008). Recently, Kottayil et al. (2021) also found deep convection peaks in the late evening hours over land. In contrast, it peaks in the afternoon hours over the majority of the oceanic regions. Such a diurnal cycle is attributed to the diurnal cycle of the net radiative forcing due to radiative heating and infrared cooling. In addition, the thermal properties of the land and ocean surfaces also play a significant role in the diurnal cycle of convective activities. Eriksson et al. (2010) observed substantial diurnal variation in the upper-tropospheric humidity and ice water content over tropical land regions. Gupta et al. (2017) investigated the day–night changes in the vertical distribution of tropical clouds. They reported an enhancement in the cloud occurrence during nighttime throughout the middle and upper troposphere.
The diurnal pattern in tropical convection, upper-tropospheric humidity,
and ice water indicates that diurnal variation in cirrus clouds exists.
However, the complete diurnal variation in cirrus clouds is not yet known. Thus, in the present study, we aim to make use of the continuous micropulse lidar (MPL) observations over the period from 2016 to 2018 in order to
disentangle the vertical distribution and diurnal variation of cirrus
cloud occurrence during different seasons as well as the interannual
variations in cirrus
cloud occurrence over a tropical coastal region, Kattankulathur (12.82
The MPL is an elastic backscatter, dual-polarization compact lidar system
(miniMPL5231, Sigma Space Corporation, USA) that was installed on the
premises of the SRM Institute of Science and Technology (SRMIST), Kattankulathur
(12.82
A lidar transmits short pulses of laser light into the atmosphere. The
received signals, due to scattering from air molecules and particles as well
as additional signal due to instrumental effects, are expressed as follows:
Dead time correction is applied to remove the saturation effect due to the
high-count rate. After-pulse correction is required to eliminate the signal due
to the internally scattered light that saturates the detector at the beginning
of each sampling interval, creating a blind zone in the near field. The overlap
correction occurs when the receiver field of view is inside the transmitter,
causing an over-attenuated near-field signal. For our MPL system, the
average overlap range is found to be
This study used upper-air data observed with radiosonde from the Indian
Meteorological Department (IMD) Chennai at Meenambakkam (13.0
To investigate the role of deep convection in the diurnal variations of
cirrus clouds, we used globally merged infrared brightness temperature (IRBT) data obtained from the
National Weather Service Climate Prediction Center of the National Oceanic and Atmospheric Administration (NOAA). IRBT data are a
globally merged, full-resolution (up to
NRB profiles from the MPL observations are used to identify cirrus cloud
layers based on the differential zero-crossing method (Pal et al., 1992).
This method is based on the fact that the NRB signal intensity generally
decreases monotonically with altitude until a cloud appears. When the signal
encounters a cloud, the NRB signal level begins to increase significantly
due to the larger droplets in clouds compared with ambient air. As a result, using MPL observations, the
cloud-base height of the lowest cloud is directly identified as the change in the slope or gradient (the first derivative) of the
NRB (i.e.,
We have sampled the NRB profiles at a resolution of 30 m, which includes
several random variations arising due to background noise. These small-scale
fluctuations are smoothed by employing a 10-point (width 300 m) running mean
filter to the first derivative of the NRB signal. The 10-point running mean
filter improves the detection of the robust cloud layer and reduces
computation time. The base, top, and peak of cirrus clouds are
identified from the smoothed NRB
signals by the differential zero-crossing method. The NRB signal starts to increase relative to the threshold value
at the cloud base, whereas the NRB signal comes
down to the threshold level at the apparent cloud top. The cloud-base and cloud-top altitudes are only
identified when the NRB gradient increases or decreases, respectively, relative to the
threshold value for at least three consecutive range bins (90 m). The threshold value is taken as the mean plus 2 standard
deviations of the background NRB signal from ambient air over the altitude from
25 to 30 km (see Fig. S1 in the Supplement). To avoid detecting any spurious
layer, we make sure that the NRB signals possess a good SNR value. The level
up to which the NRB signals are more than the 1 standard deviation of the
column-integrated signal is considered a good SNR. In general, a good SNR is
found up to
The apparent cloud-top height is detected by searching the first level where the NRB value is just less than or equal to the NRB value at the cloud base. In the cases of multiple cirrus clouds, the NRB profile may reveal several peaks. However, each of these peaks may not really be associated with separate cloud layers. The distinct multiple cirrus cloud layers are detected only when they are separated by a clear-air region, i.e., the NRB signal must drop to the background level. Finally, LDR values were checked for each cloud layer identified using the differential zero-crossing method and the criteria that the LDR within the cirrus layer should be at least 0.05 greater than the LDR from the ambient air outside of the cloud boundaries, with a minimum absolute value of 0.08 (Sassen and Cho, 1992; Nair et al., 2012).
Once the cirrus cloud-base and cloud-top altitudes are identified, the cirrus cloud optical thickness is derived using the two-way transmittance method (Young, 1995). The optical thickness is half of the logarithm of the ratio of the NRB signals just below the cloud base to those immediately above the cloud top. Note that the NRB is the range-corrected signal that has passed through the system and overlap corrections. The molecular and aerosol contributions to the altitudinal variation in the NRB are also removed before calculating the optical thickness. Thus, using the transmittance method, optical thickness is obtained without inverting the lidar signals and without the requirement for knowledge of the lidar ratio. We have obtained the altitude profiles of the molecular coefficient using the monthly mean temperature and pressure profiles. For the aerosol contribution to the NRB signal, we used the seasonal mean altitude profiles of the aerosol extinction coefficient derived from MPL observations over the site during the period from 2016 to 2018. The details of deriving the extinction coefficients are provided in Ananthavel et al. (2021a) and Ananthavel et al. (2021b). However, it is to be noted that the molecular and aerosol contributions to the NRB signal are very small compared with cirrus clouds occurring above 8 km (Young, 1995; Nair et al., 2012). We have employed only nighttime profiles with a very good SNR to determine the optical thickness. Whenever a low SNR is observed, time averaging of the NRB signals is done to reduce the noise level and improve the SNR before calculating the optical thickness (Nair et al., 2012).
Once the cirrus cloud-base and cloud-top altitudes are identified, the height and time functions of the monthly percentage occurrence (POC) of cirrus clouds are calculated. For this, we have segregated the total hours of MPL and cirrus cloud observations between 14:00 IST on the first day and 11:00 IST on the second day for each month during 2016–2018. We obtained 665 d of MPL data that were continuously measured for 1 h, i.e., 11 778 h of MPL observations were collected in total. Of the abovementioned 665 d of data, 496 d contained observed cirrus cloud durations longer than 30 min, i.e., 5002 h of cirrus cloud observations are found in total. The POC is the ratio of the total hours of cirrus cloud to the total hours of MPL operation multiplied by 100. We have counted the total hours of cirrus clouds in 30 m altitude bins from cloud base to cloud top that occur between 8 and 20 km at a 5 min time interval between 14:00 IST on the first day and 11:00 IST on the second day.
The tropopause parameters, such as the CPT, convective tropopause (COT), and TTL, are obtained using radiosonde temperature profiles at 05:30 and 17:30 IST over the period from 2016 to 2018. The CPT is defined as the minimum temperature level in the troposphere (Selkirk et al., 1993), and the COT is defined as the minimum potential temperature gradient (Mehta et al., 2011). The region between the COT and CPT levels is called the tropical tropopause layer (TTL).
Figure 1 shows the monthly mean variation in the temperature, relative
humidity (RH), zonal wind, meridional wind, potential temperature gradient
from the surface to an altitude of 25 km, rainfall, outgoing longwave
radiation (OLR), and the CPT and COT altitudes over IMD Chennai. The monthly mean
CPT and COT altitudes are obtained by averaging the daily data.
Kattankulathur (Chennai) is a coastal station that experiences rainfall
both from the southwest (SW) monsoon during June–July–August–September (JJAS) and the
northeast (NE) monsoon during October–November–December (OND). Thus, the
influence of both of the monsoons results in an abundant supply of moisture
into the upper troposphere, which is favorable for cirrus cloud formation. The
study region is also influenced by the sea breeze that triggers local
convective rainfall (Reddy et al., 2020; Simpson et al., 2007) over Kattankulathur.
The temperature shows substantial seasonal variation at the surface,
within the atmospheric boundary layer (ABL
Time–height sections of the composite monthly mean
The identification of cirrus cloud layers is illustrated for different
types of cirrus cloud cases, such as laminar cirrus, descending
cirrus, broad cirrus, and multilayer cirrus, observed on 12 February 2018,
27 May 2016, 3 August 2017, and 26 July 2016, respectively, as shown in
Fig. 2. Figure 2 presents the time–height section of the NRB signals over the
altitude from 0.3 to 22 km observed on 14:00 IST on the first day to 11:00 IST on
the second day; vertical profiles of the NRB signal,
Time–height sections of the normalized backscatter (NRB) signals
over the altitude from 0.3 to 22 km observed from 15:00 IST on the first day to 11:00 IST on the second day. The panels show the vertical profiles of the NRB; the gradient of NRB
and SNR signals at 01:30 IST using MPL over Kattankulathur; and the
daily mean temperature, potential temperature, and potential temperature
gradient using radiosonde observation over Meenambakkam for different types
of cirrus cloud cases:
On 12 February 2018 (Fig. 2a), we observed a laminar cirrus cloud
layer between the altitudes of
On 27 May 2016 (Fig. 2b), we observed the descending type of cirrus cloud
layer, which descended from an altitude with a cloud base at
On 3 August 2017 (Fig. 2c), a broad layer of cirrus clouds was observed
with a cloud base at
On 26 July 2016 (Fig. 2d), multiple cirrus layers were observed from
22:00 to 06:00 IST. In this case, the cirrus layers appear to present
before 15:00 IST on the first day and after 11:00 IST on the second day;
however, the lidar was switched off due to high solar radiation, missing the
complete diurnal feature. The cirrus cloud-base and cloud-top heights are at
We applied the abovementioned zero-crossing method to detect the cirrus cloud layers for all of the observations over the period from 2016 to 2018. Figure 3 shows the day-to-day variation in the total duration of the first-layer or single-layer cirrus cloud observations and the total duration of the MPL observations during 2016–2018. The MPL is operated between 14:00 IST on the first day and 11:00 IST on the second day under clear-sky conditions. The maximum duration of MPL operation is 20 h; however, on several occasions, MPL operation was stopped due to technical issues or bad weather conditions. The major data gaps are during February, June, and December 2016; July, October, and November 2017; and April and September 2018. Note that we have plotted only those days with more than 1 h of lidar operation and more than 30 min of cirrus cloud observations. Some noticeable differences can be seen in cirrus cloud occurrence among 2016, 2017, and 2018, indicating robust interannual variation. Cirrus clouds frequently occur during January–February of 2016 and 2018 compared with 2017. While cirrus cloud occurrence and duration is higher during March–April in 2016 and 2017 compared with 2018. During May–June, all of the years show a relatively long duration of cirrus cloud occurrence. We also checked the occurrence of cirrus clouds persisting for more than 1 d. In total, cirrus clouds were observed on 665 d during 2016–2018. Of these 665 d, cirrus clouds persist for more than 1 d on 93 of the observed days (i.e., 14 %). The persistence of cirrus clouds for longer than 1 d frequently occurs from May to August (covering the SW monsoon) and from October to November (covering the NE monsoon). It is to be noted that cirrus persistence for a longer duration may have large implications for the TTL region; this will likely be explored in a future study.
The day-to-day total duration of cirrus cloud (single-layer)
occurrence and the total duration of MPL observations during
Figure 4 shows the timing of the occurrence of single and multiple layers of cirrus cloud as well as the day-to-day variations in cirrus cloud during 2016–2018. We use the term “single” for single-layer clouds and the first layer in the case of multilayer cirrus clouds. At the same time, “multi” is used to refer to the second layer of cirrus clouds in the case of multilayer cirrus. The occurrence of a third layer was rare and is not considered in this study. The purpose of showing different colors on the left side of the panels in Fig. 4 is to distinguish the day-to-day occurrence of cirrus clouds. Single-layer cirrus clouds appear to occur throughout the year. However, multilayer cirrus clouds occur mainly from May to August, followed by occurrence in October–November. It can be seen that cirrus clouds sometimes occur throughout the night and sometimes during the early evening and the early morning. To understand the overall occurrence frequency, we have calculated the percentage of occurrence between 14:00 IST on the first day and 12:00 IST on the second day at a 2 h interval. On the right side in the panels of Fig. 4, the occurrence frequency is displayed at 15:00, 17:00, 19:00 IST, and so on. It should be noted that the occurrence of cirrus clouds during the daytime is affected by the high solar noise, which significantly reduces the MPL detection capability with respect to cirrus clouds, especially the thin and subvisible types. Thus, the occurrence of cirrus clouds presented from sunrise to 11:00 IST and from 15:00 IST to sunset may not represent accurate statistics. The overall occurrence of single-layer cirrus clouds reveals that they occur more frequently during the evening hours (18:00–20:00 IST). At the same time, multilayer cirrus clouds occur more frequently during the early morning hours (04:00–06:00 IST). The diurnal occurrence of cirrus clouds shows variation in terms of the amount and pattern among the years (2016–2018). The occurrence of both single- and multilayer cirrus clouds was higher during 2016 compared with 2017 and 2018. It should be noted that, to our best knowledge, the diurnal structure of single- and multilayer cirrus cloud occurrence is being reported here for the first time: we have not come across any such existing work. Earlier studies have reported the diurnal cycle of the total cloud fractions using spaceborne observations, which do not provide information on multilayer cirrus clouds (Noel et al., 2018; Feofilov Stubenrauch, 2019).
The day-to-day occurrence of cirrus clouds from 14:00 IST on
the first day to 11:00 IST on the second day as well as the overall percentage occurrence for
As mentioned in Sect. 1, cirrus clouds are either
convectively generated or formed in situ. Convectively generated cirrus
develops mainly due to the remnants of anvil clouds following deep
convection, whereas cirrus formed in situ originates due to an extremely cold TTL
temperature. In this section, we examine the possible roles of
convection and TTL temperatures on the diurnal variation in cirrus
cloud occurrence during different seasons. The diurnal variation in the
occurrence of single- and multilayer cirrus clouds, the occurrence of an
IRBT of less than 240 and 220 K during different seasons, and the monthly
occurrence of a CPT temperature less than 191 K at 05:30 and 17:30 IST
(evening) are calculated, as shown in Fig. 5. During the winter and SW
monsoon seasons, cirrus clouds occur more frequently in the late evening
(
Diurnal variation in the percentage occurrence of
To understand the role of convection in the occurrence of cirrus
clouds, we obtained the occurrence of an IRBT of less than 240 K,
representing convective clouds with a cloud top above 8 km, and an IRBT of less
than 220 K, representing deep convection with a cloud top above 12 km (Ali
et al., 2020). Convective clouds and deep convection frequently occur
during the SW monsoon season, followed by the NE monsoon and pre-monsoon
seasons. During the winter seasons, convection is rare. During the SW and NE
monsoon seasons, the diurnal pattern of convection is similar. In these
seasons, convection frequently starts in the late morning and remains prevalent
until midnight, with the maximum occurrence from late evening to midnight. Daytime convection during the SW and NE monsoons can be related to the
higher occurrence of cirrus clouds in the late evening hours. At the same
time, the maximum occurrence of deep convection at midnight may be
related to the cirrus occurrence during the early morning hours. During the
pre-monsoon season, convection mainly occurs in the daytime, resulting in
uniform cirrus occurrence throughout the night. However, although there is no
convection during the winter season, cirrus clouds frequently occur during
the late evening, similar to the SW and NE monsoon seasons. To understand
this, we examined the role of freeze-drying processes in the formation of cirrus clouds formed in situ by calculating the occurrence frequency of
a cold-point tropopause (CPT) temperature less than 191 K during the morning
and evening hours. This CPT temperature (
To understand the altitudinal distribution of the diurnal variation in
cirrus cloud occurrence during different seasons, we calculated its
percentage occurrence for each month from January to December over the
period from 2016 to 2018, as shown in Fig. 6. We calculated the monthly
POC from 14:00 IST on the first day to 11:00 IST on the second day, covering the entire
night above 8 km. Note that we have shown the plot from 5 to 20 km (Fig. 6). Monthly mean CPT and COT heights and standard deviations obtained using
daily average IMD radiosonde data are also embedded in Fig. 6. As mentioned
earlier, the vertical and diurnal structure of the occurrence is calculated
by taking the ratio of the total number of cirrus clouds observed to the
total number of observations for every 5 min at 30 m altitude intervals in
a given month for the period from 2016 to 2018. Note that the occurrence is only
calculated for MPL operational periods longer than 1 h and cirrus presence
longer than 30 min. The POC shows high temporal and vertical structures of occurrence
during each month. In general, it is found to be between
Monthly occurrence of cirrus clouds as a function of time and altitude from 2016 to 2018. The mean CPT (red line) and COT (white line) altitudes for the corresponding months are also embedded. The standard deviation of the CPT altitude at 17:30 and 05:30 IST is also shown. Vertical dashed lines indicate the sunset and sunrise times.
During the winter season (December–February, DJF), the POC is observed from the evening (
The POC during March is minimal (10 %–15 %); however, it extends from 8 to 16 km, similar to all of the other months. The POC during March shows two distinct layers: the first one within the TTL and the second one just below the TTL base. As mentioned earlier, the second peak in the occurrence of cirrus clouds could be remnants of the deep convective outflows. Compared with previous months, the POC significantly improved from April to May, with the maximum occurrence confined within the TTL.
During June–September, cirrus clouds frequently occur between 14:00 IST
on the first day and 11:00 IST on the second day compared with the rest of the months. The
POC varies between 10 % and 30 % during June, with the highest occurrence
observed at night. The POC is limited to a height of 8–14 km during the
daytime; however, it is in the altitude range of 8–17 km during nighttime.
Note that cirrus clouds at higher altitudes (generally the thin
and subvisible types) may remain undetected due to high solar noise during
daytime. The POC during June–July–August (JJA) over Kattankulathur is found to be consistent
with CATS observations over the NH tropical region (Noel et al., 2018); however, the
magnitude differs, as mentioned earlier (Fig. S2b and d in the Supplement) The
diurnal variation in the temperature in the upper troposphere (Mushin et
al., 2017) seems to be the controlling factor of the higher occurrence and
greater extent of cirrus clouds during nighttime compared with daytime.
The limited vertical extent of the daytime cirrus cloud occurrence could be
due to the limitation of the lidar with respect to detecting cirrus (due to high solar
noise). Note that, during the SW monsoon season, deep convective clouds such
as cumulonimbus clouds frequently occur at the same height (
In contrast, the lower layer of cirrus clouds occurs even before sunset and after sunrise. This indicates that the upper layer of cirrus clouds or multiple cirrus clouds would have disappeared after sunrise due to dissipation by solar heating or would have remained undetected due to high solar noise. However, the lower-layer cirrus clouds occur throughout the day and night, indicating the role of high moisture availability during the SW monsoon season. Compared with the rest of the seasons, the higher POC during the SW monsoon season mainly appears due to large-scale convection and the upper-tropospheric anticyclonic circulation (Parameswaran et al., 2003; Satheesan and Murthy, 2002).
The vertical structure of the POC has a lesser extent during the transition (October) from the SW monsoon season to the NE monsoon season. It is generally confined within the TTL, with fewer or no cirrus clouds above the CPT. During October, zonal wind in the upper troposphere changes to weak easterlies (Sunilkumar et al., 2010), decreasing the moisture due to horizontal transport from the Bay of Bengal and, thus, significantly reducing the POC. The inadequate supply of moisture due to the weakening of local convection reduces the sustenance of cirrus clouds. However, a relatively higher POC during November appears due to the prevalence of the NE monsoon over Kattankulathur. The convection during the NE monsoon is not as strong as during the SW monsoon, leading to the formation of cirrus clouds at relatively lower heights during November.
Overall, the POC varies from 20 % to 40 %, except during the March and
October months with low occurrence. It is worth mentioning here that the
lower POC value is found during the months when the zonal wind
pattern transits from westerly to easterly (easterly to westerly) in the
upper troposphere during March (October) over the Indian monsoon region
(Goswami, 2005). It is well known that the zonal wind shear significantly
changes the TTL temperature and, hence, cirrus cloud occurrence
(Randel et al., 2002) by uplifting the
humidity to the upper troposphere, which provides favorable conditions for
the in situ formation of cirrus clouds (Das
et al., 2011). We also examined the zonal wind shear using radiosonde
observations at IMD Chennai (13.0
The top of cirrus clouds is observed at and above the CPT, especially
during July and August. The occurrence of cirrus in the vicinity of and
above the CPT has significant implications for the vertical and poleward transport of water vapor, resulting in a change in stratospheric ozone
chemistry. Thus, we have segregated cirrus clouds occurring above the
CPT and their corresponding altitude. It is observed that cirrus clouds
frequently occur above the CPT during May (
Figure 7 shows the vertical extent of cirrus occurrence; the monthly means and standard deviations of the altitudes of the cloud base, cloud top, CPT and COT; monthly total observations of the MPL; and the occurrence of single- and multilayer cirrus clouds. It can be seen that the POC has a greater vertical extent during January, February, March, June–September, and December, whereas it had a relatively lesser vertical extent during April–May and October–November. The POC is lower from December to March and higher from April–November. The peak of the POC varies during different months. The monthly variation in the altitude of the POC peak shows a strong seasonal variation, with higher altitude during the winter season and lower altitude during the SW monsoon season.
Cirrus clouds occur at higher altitudes from January to April, during
which time the dry season prevails over Kattankulathur. During this time, the
cloud-base and cloud-top altitudes (referred to as CBH and CTH, respectively, in Fig. 7b)
show nearly in-phase variation with the COT altitude. This indicates that the main
convective outflow provides a conducive mechanism for the formation of
cirrus clouds. However, from May to November, Kattankulathur remains wet due
to the frequent rainfall from the SW and NE monsoons. The strong convection
during the SW and NE monsoons pushes the COT to a relatively higher
altitude (Mehta et al., 2011). During this time, the mean cloud base
occurs
We also obtained the vertical distribution of the POC during different
seasons, such as DJF, MAM, JJA, and SON, as shown in the Supplement (Fig. S6). It can be seen that the detailed vertical structure of the POC observed
during different months, as shown in Fig. 7, is absent when the POC is
calculated with respect to season. The overall POC profile shows that cirrus clouds
occur within the 8–17 km range, with a maximum POC of about 25 % in the altitude
range of 13–15 km (a broad peak). It is observed that the POC gradually
increases from 8.0 km to about
The vertical distribution of the POC during different seasons shows unique characteristics. First of all, the POC varies significantly among the seasons, with the minimum occurrence during the winter season and the maximum occurrence during the other seasons. The maximum POC is found to be about 19 %, 29 %, 25 %, and 26 % during DJF, MAM, JJA, and SON, respectively. Second, the peak of the POC occurs at different altitudes during different seasons. The altitude of the maximum POC is at 15.5 km during DJF, 15.0 km during MAM, 12.0 and 15.0 km during JJA, and 13.0 km during SON. Thus, the peak POC is at a higher altitude during the winter and pre-monsoon seasons and at a lower altitude during the SW and NE monsoon seasons. Finally, the vertical structures of the POC are unique during different seasons.
During the winter season, the vertical profile of the POC shows a gradual increase from 8 to 15.5 km, a drastic decrease up to 17 km, and a few occurrences above it. The vertical profile of the POC during the pre-monsoon season shows that the occurrence increases gradually from the altitude above 8 to 15 km and gradually decreases up to 18 km. Unlike the winter season, the maximum POC during the pre-monsoon season has a relatively sharper peak that is confined to a narrow altitude region between 13 and 15 km. Although frequent convection does not occur during the pre-monsoon season, deep or very deep convection even penetrates the lower stratosphere, especially during the month of May (Devasthale et al., 2010). The POC at relatively higher altitudes during the pre-monsoon season could be due to the occurrence of very deep convection. The vertical distribution of the POC during the SW monsoon season shows double peaks at altitudes of about 12 and 15 km, unlike the other seasons. Generally, frequent convection, ranging from shallow to deep convection, occurs during the SW monsoon season and spurs a large amount of water vapor into the upper troposphere, causing the frequent occurrence of multiple cirrus clouds in the altitude range between 12 and 15 km. Such multiple layers of cirrus clouds could also be due to vertically propagating gravity waves (Tsuda et al., 1994; Murthy et al., 2002). In this season, the POC gradually increases from 8 to 12 km, shows a broad maximum characterizing a double peak at 12 and 15 km, and then gradually decreases above this altitude.
The vertical profile of the POC during the post-monsoon (NE) season shows a gradual increase from 8 to 13 km (peak altitude cirrus clouds) and then a gradual decrease to about 17 km. It is interesting to find that the POC shows a substantial interannual variation, with a higher POC during the year 2016 when compared with 2017–2018. This higher occurrence of the POC during 2016 is mainly due to the higher POC observed in the winter and SW monsoon seasons in 2016. The POC during the pre-monsoon and NE monsoon seasons does not show intraseasonal variation as large as that observed during the winter and SW monsoon seasons.
As mentioned earlier, the seasonal variation in the POC, with maxima during
the SW monsoon season and minima during the winter season, is well known over
the Asian monsoon region. The SW monsoon, which provides an enormous amount
of water vapor to the upper troposphere, mainly dominates the seasonal
feature of the POC. Here, we have obtained the annual cycles of the POC,
the monthly duration of total hours of lidar observations and cirrus
observations, and the annual cycles of the CPT and COT altitudes for three
years (2016, 2017, and 2018), as shown in Fig. 8. As mentioned earlier, in
total, the lidar was operated for 11 778 h; of these 11 778 h, 5002 h (about 42.5 %) contained cirrus cloud observations over the period from
2016 to 2018. The POC values for the years 2016, 2017, and 2018 are 55.9 %, 38.7 %,
and 36.8 %, respectively. We have listed the POC, CPT altitude, COT
altitude, and TTL thickness (TTLt) during different seasons as well as for
different years (2016, 2017, and 2018), as shown in the Supplement
(Table S1). The years 2017 and 2018 show about the same percentage occurrence
(38 %); however, the POC during 2016 is about 56 %, indicating a large
interannual variation in the POC over Kattankulathur. The POC decreases from
72 % to 46 % during the SW monsoon season from 2016 to 2018. The POC values
during the pre-monsoon and post-monsoon seasons of 2016 were
Monthly variation in the POC as a function of altitude during
In general, the maximum POC is found to be during February, May–September, and November, whereas the minimum POC is during March and October.
The observed higher POC during May–September and November appears to be related
to the convective activities during the SW and NE monsoons, respectively.
It can also be noticed that the POC is relatively higher during the SW monsoons
in 2016 and 2017 compared with 2018. It is also observed that the POC during
the NE monsoon, especially in November 2017, is higher than in November 2016 and
2018. We have examined the monthly mean variation in the OLR over central
India, throughout Tamil Nadu, and over Kattankulathur (Chennai), as shown in
the Supplement (Fig. S7). It can be seen that OLR
The vertical extent of cirrus clouds is highly variable from month to
month, as mentioned earlier. The cirrus cloud top is generally confined
below the CPT altitude except during May–September, when the POC occurs
below the COT altitude. Similar to our results,
Pan
and Munchak (2011) and Pandit et al. (2014) reported a POC above the CPT
altitude. The layers of the maximum POC at
It is important to note that the enhanced occurrence of the POC from May to September was significantly reduced in the year 2017 except for the enhancement from March to April. We also observed enhancement in the POC immediately above the COT altitude to 14 km during February and November. The POC is observed to be significantly reduced above the COT altitude in July. The frequent occurrence of mid-level clouds could have prevented the lidar signals from detecting cirrus clouds. In contrast to 2016 and 2017, the POC during February, August, and September 2018 was significantly reduced.
Interestingly, the maximum POC observed at 16 km during April shifts to 9 km during July. The POC was also found to be just above the CPT altitude during 2016, which was not observed during 2017 and 2018. Such interannual variation in the POC appears to be related to the El Niño–Southern Oscillation (ENSO) and the quasi-biennial oscillation (QBO); these are the important factors influencing the interannual variation in the TTL cloud fractions (Tseng and Fu, 2017) and the TTL temperatures (Randel and Jensen, 2013). During the first half of 2016, stronger El Niño conditions were observed, whereas weak La Niña conditions prevailed for the other half of 2016 and during the second half of 2017 to the first half of 2018, as shown in the Supplement (Fig. S7). Westerly winds prevailed from January 2016 to June 2017 and from October to December 2018, whereas easterly winds prevailed from July 2017 to September 2018. These interannual components are known to modulate the TTL temperatures, thereby affecting the occurrence of cirrus clouds. In the presence of warm temperature anomalies, cirrus clouds may dissipate, whereas cirrus clouds may be generated in situ in the presence of cold temperature anomalies. It should be noted that relatively stronger convection was observed during the SW monsoons in 2016 and 2017 compared with the SW monsoon in 2018 over Chennai. In addition, relatively stronger convection was observed in association with a higher POC during November 2017 compared with November 2016 and 2018. It appears that the prevalence of convection is an important factor in such strong interannual variations in the POC over Kattankulathur (Chennai).
Figure 9 shows the relationship of the POC and convection (OLR) and the POC
anomalies with the ENSO and QBO indices. We observed that the POC is negatively
correlated (
Cirrus clouds play an important role in the Earth–atmosphere radiation budget due to their greenhouse and albedo effects, which depend on the physical and optical properties. Therefore, a precise understanding of the physical properties (e.g., diurnal cycle and vertical extent) of cirrus cloud occurrence and cloud optical depth is a highly essential input to climate modeling and prediction. However, to the authors' knowledge, no such studies (on the diurnal variation in cirrus clouds) exist over the Indian monsoon region, mainly due to limited long-term continuous observations.
The time series of
Hence, for the first time, our study presents the diurnal variation in
cirrus clouds during different seasons over the NE monsoon region,
Kattankulathur, located near the west coast of the Bay of Bengal. The cirrus
cloud occurrence for the single and multiple layers identified by the
zero-crossing method is evaluated using MPL observations between 14:00 IST on the first day and 11:00 IST on the second day over the period from 2016 to 2018. The main
conclusions from this study are briefly summarized as follows:
Cirrus cloud occurrence shows a unique diurnal structure with a higher
occurrence of single-layer cirrus in the late evening hours (18:00–21:00 IST) controlled by convective processes during the SW and NE monsoon
seasons. For multilayer cirrus, in contrast, the occurrence is higher in
the early morning hours (04:00–05:00 IST), subjugated by both
freeze-drying and deep convection processes. Deep convection and low tropopause temperatures are crucial for the
enhancement of cirrus cloud occurrences. We calculated the frequency of
occurrence of a brightness temperature The overall (single and multiple layers together) cirrus cloud occurrence
shows a substantial seasonal variation. The occurrence is During the pre-monsoon season (March–May), cirrus cloud occurrence varies
from 10 % to 30 %. The minimum occurrence is observed during March.
During April–May, the occurrence shows a significant enhancement in the
altitude range of 10–17 km, with peak occurrence (20 %–30 %) in the altitude range of
During the SW monsoon season, cirrus cloud occurrence reaches a maximum
( During the NE monsoon seasons, cirrus occurrence has a limited vertical extent.
It is generally confined within the TTL, with fewer or no occurrence of
cirrus clouds above the CPT. Due to the weakening of local convection,
the inadequate moisture supply reduces the sustenance of cirrus clouds
during October. However, a relatively higher occurrence during November
appears due to the prevalence of the NE monsoon over Kattankulathur. The
convection during the NE monsoon is not as strong as that during the SW monsoon, leading
to the formation of cirrus clouds at relatively lower heights during the
former season. The occurrence shows a distinct interannual variability, with higher
occurrence during the year 2016 compared with 2017 and 2018. The occurrence
during 2016, 2017, and 2018 was found to be
The present study shows the diurnal cycle of cirrus clouds, which will be helpful in the assessment of climate models. Although MPL detection is limited to mostly nocturnal cirrus clouds between 15:00 IST on the first day and 11:00 IST on the second day, it has captured the diurnal pattern in the occurrence of the single- and multilayer cirrus clouds that show augmentation during the evening and morning hours. In a future study, we are planning to explore temporally co-located satellite data simultaneous to MPL observations to unravel the day–night difference in cirrus cloud occurrence over Kattankulathur and adjoining regions.
The MPL data used in this study are not yet publicly available; however, the data can be provided upon request to the corresponding author.
The supplement related to this article is available online at:
SKM was responsible for conceptualizing and supervising the study; carrying out the investigation; and writing, reviewing, and editing the paper. SA contributed to data curation, carried out the investigation, and prepared the original draft of the paper. AA was responsible for curating the data, developing software, and carrying out the investigation. TVRR contributed to data curation and carried out the investigation.
The contact author has declared that neither they nor their co-authors have any competing interests.
Publisher' note: Copernicus Publications remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This work has been fully supported by the Department of Science and Technology, Government of India – Science and Engineering Research Board (DST-SERB) project (grant no. EMR/2015/000525). Sanjay Kumar Mehta wishes to thank the Earth Science and Technology Cell (ESTC), Ministry of Earth Sciences (MoES), for MPL observations. Saleem Ali is grateful to SERB for providing a fellowship for this study. Sanjay Kumar Mehta acknowledges MHRD, Government of India, for support within the framework of the Scheme for Promotion of Academic and Research Collaboration (SPARC) project (grant no.SPARC/2018–2019/P835/SL). The SRM HPCC facility was used to process the MPL data. The authors thank the reviewers and the handling editor, Peter Haynes, for their valuable comments and suggestions.
This research has been supported by the Science and Engineering Research Board (grant no. EMR/2015/000525).
This paper was edited by Peter Haynes and reviewed by Artem Feofilov and one anonymous referee.