Convective Boundary Layer Clouds As Observed with Ground-Based Lidar at a Mid-Latitude Plain Site

remote sensing

Article Convective Boundary Layer Clouds as Observed with Ground-Based Lidar at a Mid-Latitude Plain Site

Yifan Zhan 1,2,3 , Fan Yi 1,2,3,*, Fuchao Liu 1,2,3, Yunpeng Zhang 1,2,3, Changming Yu 1,2,3 and Jun Zhou 1,2,3

1 School of Electronic and Information, Wuhan University, Wuhan 430072, China; [email protected] (Y.Z.); [email protected] (F.L.); [email protected] (Y.Z.); [email protected] (C.Y.); [email protected] (J.Z.) 2 Key Laboratory of Geospace Environment and Geodesy, Ministry of Education, Wuhan 430072, China 3 State Observatory for Atmospheric Remote Sensing, Wuhan 430072, China * Correspondence: [email protected]

Abstract: A total of 3047 individual shallow cumuli were identiﬁed from 9 years of polarization lidar measurements (2011–2019) at Wuhan, China (30.5◦N, 114.4◦E). These fair-weather shallow cumuli occurred at the top edge of the convective boundary layer between April and October with the maximum occurrence in July over the 30◦N plain site. They persisted mostly (>92%) for a short period of ~1–10 min and had a geometrical thickness of ~50–600 m (a mean of 209 ± 138 m). The majority (>94%) of the cloud bases of these cumuli were found to appear ~50–560 m (a mean of 308 ± 254 m) above the lifting condensation level (LCL). In this height range from the LCL to the

cloud base, the lidar volume depolarization ratio (δV) slightly decreased with increasing height, showing gradually increasing condensation in this sub-cloud region due to penetrative thermals. Most of the observed shallow cumuli (79%) formed under the conditions of high near-surface air ◦ −1 temperature (>30 C) and water vapor mixing ratio (>15 g kg ).

Citation: Zhan, Y.; Yi, F.; Liu, F.; Keywords: polarization lidar; cumulus; lifting condensation level; convective boundary layer Zhang, Y.; Yu, C.; Zhou, J. Convective Boundary Layer Clouds as Observed with Ground-Based Lidar at a Mid-Latitude Plain Site. Remote Sens. 1. Introduction 2021, 13, 1281. https://doi.org/ The atmospheric boundary layer (ABL) is the lowest part of the troposphere that is 10.3390/rs13071281 directly influenced by the earth’s surface. It can respond to surface forcing within hours or less [1–3]. In the daytime, the earth’s surface is heated by solar radiation to produce rising Academic Editor: Simone Lolli warm air plumes so that the ABL is controlled by thermal convection and is designated a “convective boundary layer (CBL)” or “mixing layer (ML)” [1]. Clouds play a pivotal Received: 25 February 2021 role in the weather, climate, and regional/global hydrological cycle on Earth [4–6]. The Accepted: 24 March 2021 Earth’s radiation budget largely depends on the cloud coverage, height, thickness, and Published: 27 March 2021 composition [7–9]. The hydrological cycle can be driven by the radiation balance and, in turn, determines where clouds form [10–12]. This coupling of clouds, water circulation, and Publisher’s Note: MDPI stays neutral radiation budget composes the feedback process, and clouds, especially low clouds, are the with regard to jurisdictional claims in main uncertainty in the system [13]. Under fair-weather conditions, convective clouds or published maps and institutional affil- iations. shallow cumuli would form on the top of the plumes when moisture is sufficient [14]. The shallow cumuli are likely to have cloud bases at the lifting condensation levels (LCL) or above [15]. Although shallow cumuli have coverage of only ~5% over land and ~12% over ocean [16,17], they can significantly influence the solar radiation to the earth’s surface [18], modify the structure of the CBL by affecting turbulent mixing [19], and play a significant Copyright: © 2021 by the authors. role in the initiation of ice or precipitation [20,21]. Licensee MDPI, Basel, Switzerland. Various measurements with ground-based lidar/radar and airborne and spaceborne This article is an open access article sensors have revealed the cloud morphology and statistical properties of shallow cumuli. distributed under the terms and conditions of the Creative Commons They can exist for several minutes with a typical horizontal scale of ~1 km or less [14,22,23]. Attribution (CC BY) license (https:// Their geometrical thickness is mostly less than 1 km [24]. The cloud top/base heights creativecommons.org/licenses/by/ and their spatial/temporal distributions for shallow cumuli over the tropical belt and 4.0/). the Tibet Plateau have been characterized based on the spaceborne lidar measurements

Remote Sens. 2021, 13, 1281. https://doi.org/10.3390/rs13071281 https://www.mdpi.com/journal/remotesensing Remote Sens. 2021, 13, 1281 2 of 18

(the cloud-aerosol lidar and infrared pathfinder satellite observation, CALIPSO). Most shallow cumuli over the tropical ocean have cloud tops below 3 km, whereas those over tropical land tend to have higher cloud tops which are more strongly affected by diurnal variation in convection [25]. Cumulus clouds represent one of the dominant cloud types over the Tibet Plateau in the northern summer. The corresponding occurrence rate is much higher than that in the Tibet Plateau’s surrounding regions [26]. Rodts et al. [27], using aircraft in situ measurements, found that the mass flux and buoyancy flux were dominated by intermediate-sized clouds (horizontal dimension of about 1 km) while the cloud fraction was by the smallest clouds (horizontal dimension less than 1 km), stating that the large-sized clouds contribute more to the dynamical properties, and the small-sized clouds largely outnumber the large-sized clouds. Based on the three-day observations of updraft and downdraft in the convective boundary layer with a ground-based Doppler lidar on a 51.4◦N flat terrain, the relationship between the draft occurrence frequency and the shallow cumulus formation has been examined [28]. In the case of cumulus formation, the draft is enhanced by ~50% in frequency near the cloud base. The atmospheric radiation measurement (ARM) climate research facility southern Great Plains (SGP) sites are located in north-central Oklahoma and south Kansas (36.5◦N), a flat area that is sparsely populated. Combined observations with remote and in situ sensors at the ARM SGP sites have yielded a comprehensive look into the characteristics of continental shallow cumulus clouds and corresponding CBL atmospheric conditions [14,23,29–31]. The cloud properties show a clear-cut diurnal cycle [29]. The cloud fraction has a maximum value at around 14:00 local time (LT), which is sensitive to both the low-level moisture and the surface sensible heat flux. The average cloud-base height rises throughout the day, while the average cloud thickness falls with time. It is shown that the vertical velocity has increased variance during periods of medium cloud cover and larger skewness on shallow cumulus days than on clear-sky days [14]. The clouds with a positive cloud-based mass flux account for 63% of clouds and are linked to coherent updrafts extending over the entire CBL. In contrast, negative mass flux clouds lack coherent subcloud (the region below cloud base) drafts. Although many works have been reported, there is still a lack of research based on process-level observation that can present the detailed characterization of variation and structure of the cumulus. The shallow cumuli remain, however, incompletely represented in general circulation models (GCMs) because of their small time (~10 min or less) and space (~1 km) scales, as well as behavior differences under different weather systems [14,32]. As a result, the GCMs suffer from errors in the location, timing, and extent of shallow clouds [33], which then affects the other components of the simulated system such as the structure of the ABL [34]. Moreover, the lifting mechanism varies on the distinct underlying surfaces (continent or ocean, mountain or plain, urban or rural area, forested or deforested surface) [30,35–38]. To deepen our understanding relevant to the formation of the CBL cumuli, and enhance the performance of the GCMs, long-term, routine, and process-level lidar observations at more sites with different latitudes and underlying surfaces are required. This work presents the long-term CBL cumulus observations using a ground-based polarization lidar. The polarization lidar has been operated routinely under fair weather conditions since October 2010 at Wuhan University atmospheric observatory, Wuhan, China (30.5◦N, 114.4◦E) [39]. The shallow cumuli were observed on 117 out of 848 observational days during 2011–2019. Each cumulus cloud day contains at least 6-hour lidar profiles in the period from 09:00 to 18:00 LT. Such abundant lidar data, together with simultaneously collected surface weather parameters, allow us to systematically investigate the continental cumulus cloud formation and relevant CBL atmospheric conditions over a megacity located on a mid-latitude plain. Here, this paper starts with instruments and methodology in Section2. Then, Section3 presents two examples and statistics on the observed shallow cumuli. The discussion and conclusions are finally given in Sections4 and5. Remote Sens. 2021, 13, 1281 3 of 18

2. Instruments and Methodology Cloud observations were made by a 532 nm polarization lidar deployed at Wuhan University atmospheric observatory. The observatory site (70 m above sea level) is located on a vegetation-covered small hill with a maximum peak height of 118 m which lies in the heart of the city of Wuhan. Wuhan is an industrialized megacity in central China. It is situated on the eastern Jianghan Plain, which has an area of ~46,000 km2 and a mean elevation of only 27 m above sea level. Wuhan has a humid subtropical climate with abundant rainfall and four distinctive seasons.

2.1. Instruments 2.1.1. Polarization Lidar During the period from October 2010 to the end of 2019, all of the polarization lidar observation sessions started under fair weather conditions and were terminated before extensive cloud cover or precipitation. The system parameters of our polarization lidar and its performance have been described in detail by Kong and Yi [39]. Here, we brief the technical improvement about its polarization measurement. A Brewster polarizer is used to increase the polarization purity of the output laser beam (up to 10,000:1). In the receiver optics, two additional polarizers are placed, respectively, on the two output sides of the polarization beam splitter prism (PBS) to reduce the crosstalk (probably occurring during cloud observation) between the two orthogonal polarization channels. The raw lidar data were stored with a vertical resolution of 3.75 m and a temporal resolution of 1 min. The lowest measurement height was 0.3 km due to an overlap factor effect caused by the off-axis lidar design. The backscatter ratio (BSR) is defined as the ratio of the total (particulate and molecular) backscatter coefficient divided by the molecular one. It generally reflects the content of aerosols or clouds. For the standard lidar equation, two unknown variables (backscatter coefficient and extinction coefficient) are included in one equation. We need to make the following assumptions [40]: the molecular lidar ratio (molecular extinction coefficient divided by molecular backscatter coefficient) can be calculated from Rayleigh scattering theory, the lidar ratio (aerosol extinction coefficient divided by aerosol backscatter coefficient) is chosen according to the type of dominated aerosol, and the backscatter ratio BSR is known at a certain height. Once the assumptions are confirmed, there are two options to solve the lidar equation. The first is choosing the reference height without aerosols at a high altitude, assuming the BSR value, and making the backward integration (from the reference height to the surface). The result of this option is stable and this is the common choice for aerosol study. The other option is choosing the reference height at a low altitude, confirming the BSR value, and making the forward integration (from the low to the high altitude). The forward integration is unstable and may encounter the failure of retrieval. Normally, for optically thin layers, the backscatter ratio BSR can be retrieved from the Mie signal (backscatter signal from aerosols or clouds) profile of lidar by assuming a constant lidar ratio and choosing an aerosol-free reference altitude. In the case of cloud, it is always difficult to find a reference altitude above the cloud base due to strong attenuation. In this study, the backward retrieval scheme with a lidar ratio of 50 sr and a reference altitude of ~7 km was utilized for the cloud-free profiles [41], while the forward retrieval scheme with a lidar ratio of 18.6 sr and a reference altitude of ~0.3 km was used for the cloud profiles [42]. The error of R comes from the noise of the signal, lidar ratio, and BSR at the reference height. In this study, the backward retrieval uncertainty of R is estimated as 15–20% (corresponding to the uncertainty of 10% and 4% for lidar ratio and BSR at the reference height, respectively) based on the error analysis by Comerón et al. [43]. As for the forward retrieval, the uncertainty of BSR at the reference height is larger due to the variation of aerosols at the low altitude. If we assume the uncertainty of the lidar ratio and BSR at the reference height is 10% and 50%, respectively, the uncertainty of BSR is estimated to be 45–55%. Remote Sens. 2021, 13, 1281 4 of 18

Besides, the CBL height was calculated by using the variance method [39,44] based on 30 min cloud-free BSR profiles (if available). The foundation of the variance method is taking the aerosols as the tracer of the convective evolution of the boundary layer. The maximum in the vertical profile of the variance of BSR is taken as the CBL height. The height values in this article are all relative to sea level. The volume depolarization ratio δV is defined as the ratio of the perpendicular- to parallel-polarized backscatter coefficients. It can be calculated from the lidar signals of the two channels with the channel relative gain calibrated in advance using a method presented by Freudenthaler et al. [45]. The δV could be used to investigate the particle shapes of clouds and aerosols [46], enabling us to obtain the sub-cloud liquid droplet layer properties due to condensation or hygroscopic growth [47].

2.1.2. Surface Weather Station A surface weather station (CR800, made by Campbell Scientiﬁc, Inc., Logan, UT, USA) was installed near our 532 nm polarization lidar from March 2010. This allowed us to obtain the surface temperature, relative humidity, horizontal wind speed, and direction in 1 min time resolution, showing the surface meteorological parameters during the presence of shallow cumuli. Due to instrument breakdown, the data for the periods of August 2014, February–August 2015, and February–May 2016 are not available.

2.1.3. Cloud Camera A fisheye lens camera was placed beside the lidar for taking all-sky images over our site from August 2018. The fisheye camera has a field-of-view (FOV) of 108◦. The all-sky images were captured every 2 min and stored automatically. The all-sky images were used to confirm that the formation or dissipation process of the cumulus occurred in the field- of-view of our lidar. In this study, we only utilized the lidar data with the simultaneous all-sky images from August 2018 to December 2019 to present the case studies.

2.2. Methodology 2.2.1. Cloud Information and Event Identification In terms of the range-squared-corrected lidar signal (X) profile, the shallow cumulus clouds are characterized by large signal enhancement in a narrow height range (~300 m or less) at the top of the convective boundary layer (see Figure1). The cloud base can be defined as a height above which the signal enhancement starts immediately. In the narrow height range, the cloud peak was determined as a height where the range-corrected lidar signal maximizes. The cloud base, peak, and top height were calculated using the method introduced by Platt et al. [48]. In detail, the cloud base was determined as the level at which the signal continued to increase for at least 5 height intervals. The cloud top (or effective top) was calculated as the level at which the signal continued to decrease for 5 height intervals. If the continuous decrease search failed, the height at which the signal drops to the background level was defined as the effective top. Then, the cloud peak height was the level at which the signal maximized. Following the criterion of the peak-to-base signal ratio for distinguishing cloud from aerosol layers [49], the signal profile was registered as a cumulus cloud profile when the ratio value was larger than 4.0. For identifying individual cumulus cloud events, we consecutively surveyed all the 117-day sequences of the 1-min lidar signal profiles according to the criterion of peak-to-base ratio value of 4.0. Figure1 presents a typical cumulus lidar profile and the cloud information determined by the abovementioned method. The lifting condensation level (LCL), cloud base height, cloud peak height, and cloud top height are shown, respectively, by the black long dash, red long dash, red dash-dotted, and red short dash lines. A cumulus cloud event was defined as follows. For sequences of the 1 min range- squared-corrected lidar signal profiles, the event started with a cloud-free profile and ended with a cloud profile. The interval between the two events must be larger than 3 min (3 cloud-free profiles). A cumulus case day must contain at least 10 events. For a Remote Sens. 2021, 13, 1281 5 of 18

short-duration cumulus cloud event for which the lidar signal enhancement was visible in only one single profile, its parameters (cloud base/peak/top) were obtained simply from the 1 min profile. For a long-duration cumulus cloud event where the signal enhancement Remote Sens. 2021, 13, x FOR PEER REVIEW 5 of 20 was discernible in several consecutive profiles (occurring in nearly the same height range), its parameters were from the average of the consecutive profiles.

Figure 1. A plotFigure of 1 1.minA polarization plot of 1 min lidar polarization range-squa lidarred-corrected range-squared-corrected signal X profile signal observed X proﬁle at observed at 1125 LT on 091125 August LT on 2019. 9 August The lifting 2019. Thecondensation lifting condensation level (LCL), level cloud (LCL), base cloud height, base cloud height, peak cloud peak height, height, and cloudand cloudtop height top height are shown, are shown, respective respectively,ly, by the by theblack black long long dash, dash, red red long long dash, dash, red red dash-dotted, dash-dotted, andand red red short short dash dash lin lines.es. The The LCL LCL is is calculated calculated based based on on Equation Equation (1) (1) in in Section Section 2.2.2. 2.2.2 .

A cumulus2.2.2. cloud Lifting event Condensation was defined Level as follows. For sequences of the 1 min range- squared-correctedThe lidar lifting signal condensation profiles, the level event (LCL) started is the with height a atcloud-free which water profile vapor and in an air parcel ended with abecomes cloud profile. saturated The interval if the parcel between is lifted the two adiabatically. events must It be simpliﬁes larger than some 3 min actual physics (3 cloud-free processesprofiles). A (heat cumulus exchange, case day condensation) must contain happening at least 10 in events. the upward For a airshort- parcel and can duration cumulusbe used cloud as aevent reasonable for which estimate the lidar of signal cloud enhancement base height when was visible parcels in experience only forced one single profile,ascent its [50 parameters]. We present (cloud the CBLbase/peak/top) height evolution were obtained and LCL simply variation from during the 1 the daytime min profile. Forto discuss a long-duration the formation cumulus mechanism cloud event of cumulus where the in casesignal studies. enhancement Besides, was we compare the discernible inobserved several consecutive cloud base heightprofiles with (occurring the calculated in nearly LCL the and same infer height what range), causes its the difference. parameters wereThe LCLfrom Z theLCL averagewas computed of the consecutive from the surface profiles. temperature (T) and relative humidity (RH) using the approximation [51]: 2.2.2. Lifting Condensation Level T The lifting condensation level (LCL) isZ theLCL height≈ 20 at+ which(100 water− RH vapor) in an air par- (1) cel becomes saturated if the parcel is lifted adiabatically. It5 simplifies some actual physics processes (heat exchange, condensation) happening in the upward air parcel and can be used as a reasonable estimate of cloud base height when parcels experience forced ascent [50]. We present the CBL height evolution and LCL variation during the daytime to discuss the formation mechanism of cumulus in case studies. Besides, we compare the observed cloud base height with the calculated LCL and infer what causes the difference. The LCL ZLCL was computed from the surface temperature (T) and relative humidity (RH) using the approximation [51]:

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3. Results The polarization lidar started routine operation under fair weather in October 2010, and a total of ~20,000 hours of lidar data were collected till the 31st of December, 2019. Using the abovementioned method, 117 days with CBL cumulus occurrence are determined out of 848 observation days between the 1st of January, 2011 and the 31st of December, 2019. Beneﬁtting from the 1 min time and 3.75 m range resolution of our lidar, the processes of cumulus formation, evolution, and dissipation could be captured. In this section, we start with two representative cases, followed by a series of statistics of the CBL cumulus from 117 case days.

3.1. Case on 9 August 2019 Figure2 shows the time–height contour plots (1 min/3.75 m resolution) of the X and δV on the 9th of August, 2019. The X contour (Figure2a) illustrates a typical daytime CBL evolution (CBL height marked by filled black circles): rapidly growing CBL height from 09:00 to 11:30 LT, slower CBL height growth (mixed with the cumulus then the CBL heights are determined by cloud base height [52]) from 12:00 to 15:00 LT, and decreasing CBL height from 15:30 to 17:30 LT. The CBL height started growing at 09:00 LT (observed by our lidar) from ~0.43 km and reached 1.1 km at 11:30 LT. Meanwhile, the LCL was always above the CBL height, maintaining a state which was unsuited to the formation of cumuli. The surface T and water vapor mixing ratio (WVMR) generally kept growing, as seen from Figure2c. However, after a rapid-rise phase, the CBL height jumped over and maintained above the LCL from 11:30 to 15:30 LT. During this period, it could be expected that the increasing surface moisture was transported upward (a decrease of surface WVMR could be found at ~11:00 LT from Figure2c) by convective lifting (surface T above 35 ◦C), filling the growing CBL. As air parcels with sufficient moisture were lifted across the LCL level, they could become oversaturated, which led to the formation of a series of clouds in a height range of 1.2–2.0 km. A total of 19 intermittent cumulus events were observed during this period, with each lasting less than 15 min. From Figure2b, the region under the cumulus base presented relatively low δV values during 13:00–16:00 LT, suggesting the existence of water droplets. The CBL height began decreasing rapidly from 15:00 LT, and was lower than the LCL after 15:30 LT; the accompanying surface T started a sharp decrease, indicating that the net radiation to the surface became negative starting from this period, and the thermal convection would weaken. The surface WVMR presented a sudden decrease starting from 15:25 LT, a short delay in contrast to the decrease in surface T. No other cumulus events were observed after 15:00 LT. To demonstrate the short time evolution of the cumulus cloud, a representative event was chosen and the corresponding sequences of the 1 min backscatter ratio BSR and δV profiles during 11:24–11:29 LT on the 9th of August, 2019 are plotted in Figure3a. The quasi-simultaneous all-sky images (captured every 2 min) are also shown in Figure3b to confirm that the cumulus forms/dissipates in the lidar field-of-view (FOV). As seen from Figure3a, no liquid water layer or cloud was observed above the LCL (~1.07 km) at 11:24 LT. One minute later, the initial stage of cumulus was observed, with a cloud base height of ~1.27 km. The cumulus cloud peak was located at ~1.3 km with a peak BSR of ~84 and a corresponding δV of ~0.019. A height interval of ~0.2 km for the sub-cloud zone (defined as the zone between the cloud base and LCL) suggests that strong updrafts from the air mass precipitate the phase transition from water vapor to liquid. The profiles at 11:26 and 11:27 LT showed a steady cloud base (~1.26 km and ~1.25 km, respectively) and denser, broader cloud body (respective peak BSR of ~135 and ~504, more condensed liquid water) contrasting to the 11:24 LT profile. Then, at 11:28 LT, the peak BSR was ~92 and the corresponding δV ~0.018; the cumulus structure became similar to the initial stage, probably due to the high environmental temperature and lack of lifted water supply, then, that part of the condensed water evaporated. Up to 11:29 LT, the cumulus dissipated completely. The cloud thickness did not exceed 150 m for all of the four cumulus profiles. Note that the profile values of BSR in the sub-cloud zone showed an increment with height, while Remote Sens. 2021, 13, x FOR PEER REVIEW 7 of 20

Remote Sens. 2021, 13, 1281 due to the high environmental temperature and lack of lifted water supply, then, that part7 of 18 of the condensed water evaporated. Up to 11:29 LT, the cumulus dissipated completely. The cloud thickness did not exceed 150 m for all of the four cumulus profiles. Note that the profile values of BSR in the sub-cloud zone showed an increment with height, while thethe corresponding δδV exhibitedexhibiteda a slow slow decrement decrement throughout throughout the the event. event. This This suggests suggests that thatthe sub-cloudthe sub-cloud region region is rich is inrich aerosols in aerosols lifted lifted by convection by convection and theand water the water droplets, droplets, which whichform via form the via lifting the lifting condensation condensation or convective or convective condensation, condensation supplying, supplying moisture moisture for the forcloud the above.cloud above.

Figure 2. 2. Time–heightTime–height contour contour plots plots (1 (1 min/3.75 min/3.75 m m resolution) resolution) of of (a ()a range-squared-corrected) range-squared-corrected signal signal X; (b) volume depolarization ratio 𝛿 measured by Wuhan University 532 nm polarization lidar on X; (b) volume depolarization ratio δ measured by Wuhan University 532 nm polarization lidar on the 9th of August, 2019; and (c) diurnalV variation of the surface temperature (T) and WVMR, rec- c ordedthe 9th by of a August, co-located 2019; surface and ( weather) diurnal station, variation wh ofich the exhibit surface an temperature example of a (T) shallow and WVMR, cumulus recorded day. Theby a CBL co-located height surfacein Figure weather 2a (filled station, black cycles) which exhibitis determined an example by the of variance a shallow method cumulus (calculated day. The onCBL a 30 height min inbasis) Figure and2a lifting (ﬁlled condensation black cycles) level is determined (LCL) is indicated by the variance by white method diamonds. (calculated Note that on a the30 minshallow basis) cumuli and lifting occurred condensation when both levelthe near-s (LCL)urface is indicated air temperature by white and diamonds. water vapor Note mixing that the ratioshallow were cumuli high in occurred the afternoon. when both the near-surface air temperature and water vapor mixing ratio were high in the afternoon.

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𝛿 FigureFigure 3. (a 3.) Profiles(a) Profiles of lidar of lidar backscatter backscatter ratio ratio (R, red) (R, red) and andvolume volume depolarization depolarization ratio ratio ( , (blue)δV, blue) duringduring 11:24–11:29 11:24–11:29 LT on LT the on 9th the of 9th August, of August, 2019, 2019, which which display display an example an example of individual of individual shallow shallow cumuli evolving from formation to disappearance. The lifting condensation level (LCL), cloud base cumuli evolving from formation to disappearance. The lifting condensation level (LCL), cloud height, cloud peak height, and cloud top height are shown, respectively, by black long dash, red base height, cloud peak height, and cloud top height are shown, respectively, by black long dash, long dash, red dash-dotted, and red short dash lines. (b) Photographs of the sky recorded by a ground-basedred long dash, camera red at dash-dotted, our lidar site, and which red short display dash the lines. evolving (b) Photographs appearance ofof thethis skyshallow recorded cu- by mulus.a ground-based The center of camerathe plus atsymbol our lidar shows site, the which region display which theis in evolving the field-of-view appearance of the of lidar. this shallow cumulus. The center of the plus symbol shows the region which is in the field-of-view of the lidar. 3.2. Case on 31 July 2019 3.2. Case on 31 July 2019 Figure 4 provides another case of a CBL cumulus observed on the 31st of July, 2019. Figure4 provides another case of a CBL cumulus observed on the 31st of July, 2019. As seenAs seen from from Figure Figure 4a, 4thea, the CBL CBL height height started started growing growing at 08:00 at 08:00 LT LTfrom from ~0.38 ~0.38 km km along along withwith growing growing surface surface WVMR, WVMR, and andreached reached 1.09 1.09km at km 11:30 at 11:30 LT. Starting LT. Starting from from 12:00 12:00 LT, LT, the theCBL CBL height height jumped jumped over over the theLCL; LCL; meanwhile, meanwhile, the thesurface surface WVMR WVMR exhibited exhibited a sharp a sharp decrease,decrease, indicating indicating abundant abundant moisture moisture had hadbeen been transported transported upward upward around around 12:00 12:00 LT. LT. TheThe CBL CBL maintained maintained higher higher than than the theLCL LCL and and the thecumuli cumuli occurred occurred in the in theheight height range range of of 1.1–2.01.1–2.0 km. km. A total A total of 10 of cumulus 10 cumulus events events were were observed observed from from 12:00 12:00 to 16:30 to 16:30 LT. Similarly, LT. Similarly, the region under the cumulus presented relatively low δ values during 12:00–17:00 LT the region under the cumulus presented relatively low δV values during 12:00–17:00 LT (Figure(Figure 4b).4 b).The The CBL CBL height height turned turned to be to lower be lower than than the theLCL LCL from from 16:30 16:30 LT, LT, while while the the surfacesurface WVMR WVMR experienced experienced a decrease a decrease at ~1 at7:00 ~17:00 LT. LT.Henceforth, Henceforth, no more no more CBL CBL cumulus cumulus eventsevents were were observed observed after after 16:30 16:30 LT. LT.The The clouds clouds around around ~1.8 ~1.8 km kmat 17:40 at 17:40 LT were LT were inferred inferred as cumulonimbusas cumulonimbus via viathe the all-sky all-sky image image (not (not shown shown here), here), and and the the weather weather turned fromfrom fair fair toto rainyrainy inin aboutabout 3030 min.min. ItIt isis interesting interesting that that the the surface surface WVMR WVMR suddenly suddenly dropped dropped to a to arelatively relatively lowlowvalue value at at ~18:30 ~18:30 LT,LT, probably probably contributing contributing to to the the coming coming precipitation. precipitation. FigureFigure 5a presents5a presents four four sequen sequentialtial 1 min 1 min profiles profiles of BSR of BSR and and δ, δdisplayingV, displaying a quasi- a quasi- completecomplete CBL CBL cumulus cumulus cloud cloud event event from from 12:49 12:49 to to 12:52 12:52 LT LT on on the 31st ofof July,July, 2019. 2019. As As seen seenfrom from Figure Figure5b, 5b, the the cumulus cumulus started started forming forming at 12:47at 12:47 LT, LT, which which could could be recognized be recognized via the via all-skythe all-sky image image (but (but not innot the in FOV the ofFOV the of lidar) the lidar) at 12:49 at LT,12:49 came LT, into came the into FOV the of FOV the lidar of at the 12:51lidar LTat 12:51 and broke LT and into broke dissipation into dissipati at 12:53on LT. at According12:53 LT. According to Figure5 a,to the Figure initial 5a, stage the of initialthe stage cumulus of the formation cumulus wasformation not captured was not by captured our lidar by at our 12:49 lidar LT. at However, 12:49 LT. However, the evolution the andevolution dissipation and dissipation processes fromprocesses 12:50 from to 12:52 12:50 LT to were 12:52 recorded. LT were Therecorded. cumulus The cloudcumu- base lus wascloud around base was 0.47 around km (sub-cloud 0.47 km (sub-cloud zone thickness) zone thickness) above the above LCL the (~1.05 LCL km). (~1.05 Similar km). to Similarthe profileto the profile structure structure of the of first the event, first ev anent, increment an increment with with height height for the for BSRthe BSR and and a slow a slowdecrement decrement for theforδ theV could δ could be found be found from the from profiles the profiles at 12:50 at and 12:50 12:51 and LT. 12:51 In addition, LT. In the addition,cumulus the cloudcumulus base cloud at 12:51 base LT at was 12:51 ~1.62 LT km, was about ~1.62 ~0.11km, about km higher ~0.11 than km higher that at 12:50than LT. thatThis at 12:50 height LT. bias This might height be bias due might to the be sub-cloud due to the air sub-cloud mass updraft air mass during updraft the two during minutes. the Notetwo minutes. that a microlayer Note that stratification a microlayer structure stratification could structure be found could below be the found cloud below baseat the 12:51 cloud base at 12:51 LT. The cloud peak BSR was ~326 (at ~1.68 km for 12:50 LT) and ~478

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LT. The cloud peak BSR was ~326 (at ~1.68 km for 12:50 LT) and ~478 (at ~1.7 km for 12:51 (atLT), ~1.7 km respectively. for 12:51 LT), Therespectively. cloud The thickness cloud thickness did not did exceed not exceed 200 200 m m throughoutthrough- the whole event. outFrom the whole the event. last proﬁle From the at last 12:52 profile LT, atthe 12:52 height LT, the rangeheight range between between ~1.51 ~1.51 and and 1.68 km was still rich 1.68of km upward was stilltransported rich of upwardaerosols transporte andd aerosols locally and condensedlocally condensed water water droplets. droplets.

Figure 4. Time–height contour plots (1 min/3.75 m resolution) of (a) range-squared-corrected signal Figure 4. Time–height contour plots (1 min/3.75 m resolution) of (a) range-squared-corrected signal X; (b) volume depolarization ratio 𝛿 measured by Wuhan University 532 nm polarization lidar on theX; 31st (b of) volumeJuly, 2019; depolarization and (c) diurnal variation ratio ofδV themeasured surface temperature by Wuhan (T) and University WVMR, recorded 532 nm polarization lidar on . bythe a co-located 31st of surface July, 2019;weather and station (c) diurnalNote that variation shallow cumuli of the rapi surfacedly formed temperature and vanished (T)at and WVMR, recorded the top edge of the convective boundary layer between 12:00 and 16:30 LT when both the near- surfaceby a air co-located temperature surface and water weather vapor mixing station. ratio Note were thathigh. shallow cumuli rapidly formed and vanished at the Remote Sens. 2021, 13, x FOR PEER REVIEW 10 of 20 top edge of the convective boundary layer between 12:00 and 16:30 LT when both the near-surface air temperature and water vapor mixing ratio were high.

FigureFigure 5. Same 5. Same as Figure as Figure 3, but 3for, but a short-duration for a short-duration cumulus cumuluscloud event cloud during event 12:49–12:52 during LT 12:49–12:52 on LT on the the31st 31stof July, of July,2019. 2019.(a) Profiles (a) Proﬁles of lidar of backscatter lidar backscatter ratio (R, red) ratio and (R, volume red) and depolarization volume depolarization ratio ratio (𝛿 , blue). (b) Photographs of the sky recorded by a ground-based camera. Note that this cumulus (δ , blue). (b) Photographs of the sky recorded by a ground-based camera. Note that this cumulus cloudV formed and vanished in a time scale of 1–2 min. cloud formed and vanished in a time scale of 1–2 min. 3.3. Statistical Characteristics of the CBL Cumulus The two cases along with two events in Sections 3.1 and 3.2 presented some similar features. Hereafter, statistics were made to explore whether these features are ubiquitous for CBL cumuli.

3.3.1. Seasonal Distribution Based on 848 day lidar observations from 2011 to 2019 at Wuhan, the monthly occurrence of the CBL cumulus is displayed in Figure 6. A total of 117 cumulus cloud days were identified. The observation days for each month are over 45, except for February when the lidar might stop operation due to the traditional Chinese Spring Festival vacation. The majority (~74%) of the cumulus days occur in summer, with corresponding occurrence frequency of ~44% (July), ~32% (August), and ~24% (June), respectively. About 26% of the cumulus days occur in late spring (April, May) and early autumn (September, October). No cumulus events are observed in the period from November to March. Wuhan’s climate is humid subtropical with abundant rainfall in summer and four distinctive seasons. The summer is humid along with strong solar radiation, providing moisture and lifting energy for the cumulus formation. Hence, the cumulus is more likely to form via convective lifting during summertime.

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3.3. Statistical Characteristics of the CBL Cumulus The two cases along with two events in Sections 3.1 and 3.2 presented some similar features. Hereafter, statistics were made to explore whether these features are ubiquitous for CBL cumuli.

3.3.1. Seasonal Distribution Based on 848 day lidar observations from 2011 to 2019 at Wuhan, the monthly occurrence of the CBL cumulus is displayed in Figure6. A total of 117 cumulus cloud days were identiﬁed. The observation days for each month are over 45, except for February when the lidar might stop operation due to the traditional Chinese Spring Festival vacation. The majority (~74%) of the cumulus days occur in summer, with corresponding occurrence frequency of ~44% (July), ~32% (August), and ~24% (June), respectively. About 26% of the cumulus days occur in late spring (April, May) and early autumn (September, October). No cumulus events are observed in the period from November to March. Wuhan’s climate is humid subtropical with abundant rainfall in summer and four distinctive seasons. The summer is humid along with strong solar radiation, providing moisture and lifting energy Remote Sens. 2021, 13, x FOR PEER REVIEWfor the cumulus formation. Hence, the cumulus is more likely to form via convective11 of lifting 20

during summertime.

FigureFigure 6. Monthly 6. Monthly occurrence occurrence statistics statistics of the of theshallow shallow cumulus cumulus days days based based on onthe the848 848day day lidar lidar observations from 2011 to 2019 at Wuhan, China (30.5°N, 114.4°E). The red bar represents the num- observations from 2011 to 2019 at Wuhan, China (30.5◦N, 114.4◦E). The red bar represents the number ber of lidar observational days in each month, while the blue bar denotes the number of cumulus of lidar observational days in each month, while the blue bar denotes the number of cumulus cloud cloud days. A total of 117 cumulus cloud days were identified from the 848 day lidar observations. Eachdays. cumulus A total cloud of 117 day cumulus contained cloud at least days 10 were cumulus identiﬁed cloud from events. the 848 day lidar observations. Each cumulus cloud day contained at least 10 cumulus cloud events.

3.3.2.3.3.2. Occurrence Occurrence Time Time and and Duration Duration FigureFigure 7 shows7 shows (a) (a) the the occurrence occurrence time time of ofCBL CBL cumulus cumulus and and (b) (b) the the duration duration of ofCBL CBL cumuluscumulus for forthe the 3047 3047 shallow shallow cu cumulusmulus cloud cloud events events observed observed from from 2011 2011 to to 2019. 2019. Accord- According ingto to Figure Figure7 a,7a, the the overwhelming overwhelming majority majority (95%) (95%) of theof the CBL CBL cumulus cumulus occurs occurs between between 09:00 09:00and and 18:00 18:00 LT, LT, which which is consistentis consistent with with the the convective convective boundary boundary layer layer evolution evolution as as well wellas as the the convection convection strength. strength. From Figure 77bb,, most of of the the events events (92%) (92%) have have a duration a duration shortershorter than than 10 min. 10 min. The The mean mean cumulus cumulus residence residence time time in the in theFOV FOV of the of thelidar lidar is 4 is min. 4 min. The cloud duration distribution presents a positive skew, indicating that the observed CBL cumuli over Wuhan are dominated by short-duration clouds. The seasonal difference is not apparent for occurrence time and duration.

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The cloud duration distribution presents a positive skew, indicating that the observed CBL cumuli over Wuhan are dominated by short-duration clouds. The seasonal difference is not apparent for occurrence time and duration.

FigureFigure 7. Distributions 7. Distributions of (a of) occurrence (a) occurrence time time (local (local time) time) and and(b) duration (b) duration time time for a for total a total of 3047 of 3047 shallowshallow cumulus cumulus cloud cloud events events obse observedrved from from 2011 2011 to 2019 to 2019 at Wuhan, at Wuhan, China. China. The Theblue blue bar, bar,yellow yellow bar, and red bar represent, respectively, the number of events in summer (June, July, and August), bar, and red bar represent, respectively, the number of events in summer (June, July, and August), autumn (September, October, and November), and spring (March, April, and May). Note that the autumn (September, October, and November), and spring (March, April, and May). Note that the cumulus clouds formed mostly (>95%) during the period of 09:00–18:00 LT, while their duration cumulus clouds formed mostly (>95%) during the period of 09:00–18:00 LT, while their duration mostly (>92%) ranged from 1 to 10 min. mostly (>92%) ranged from 1 to 10 min.

3.3.3.3.3.3. Cumulus Cumulus Height Height Statistics Statistics FigureFigure 8 gives8 gives the the statistical statistical distributions distributions of the of the CBL CBL cumulus cumulus base base height, height, top top height, height, peakpeak height, height, and and geometrical geometrical thickness thickness between between 2011 2011 and and 2019. 2019. Figure Figure 88aa indicatesindicates thatthat the the CBLCBL cumuluscumulus mostlymostly (~72%(~72% outout ofof allall thethe events)events) occursoccurs inin aa heightheight rangerange ofof 0.9–1.7 0.9–1.7 km. km.The The average average cloudcloud basebase heightheight is ~1.3 ±± 0.380.38 km. km. According According to toKong Kong and and Yi [39], Yi [39 the], the meanmean value value of the of maximum the maximum CBL CBL height height under under fair weather fair weather conditions conditions over overour station our station is 1.24is km 1.24 in km spring in spring and 1.27 and 1.27km in km summer, in summer, respectively. respectively. The Theaverage average CBL CBL cloud cloud base base heightheight is slightly is slightly above above the thefair fairweather weather maximum maximum CBL CBL height, height, suggesting suggesting the thecumuli cumuli are are moremore likely likely to form to form at the at thetop topof the of theCBL. CBL. From From Figure Figure 8b,8 c,b, the c, the cumulus cumulus top top and and peak peak are are mostlymostly located located at atthe the height height range range of of 1.1–1.9 1.1–1.9 km km (~70%) and 1.1–1.71.1–1.7 kmkm (~70%), (~70%), respectively. respectively.The The average average cumulus cumulus top top height height is ~1.51 is ~1.51± 0.4± 0.4 km km and and the the peak peak height height ~1.41 ~1.41± ±0.14 0.14 km. km.Figure Figure8 d8dshows shows thatthat the CBL CBL cumuli cumuli ov overer Wuhan Wuhan are are dominated dominated by byshallow shallow cumulus cumulus (70%(70% of the of theevents events have have a thickness a thickness of <250 of <250 m and m and the the average average is ~210 is ~210 m). m). The The seasonal seasonal differencedifference is not is notapparent apparent for forcloud cloud base/top/peak base/top/peak height, height, and andthickness. thickness. TheThe LCL LCL versus versus the thecumulus cumulus base base height height pert pertinentinent to 2744 to 2744 cumulus cumulus events events from from 2011 2011 to 2019to 2019 is plotted is plotted in Figure in Figure 9. Unlike9. Unlike the the results results from from [29] [ 29(a ]good (a good agreement agreement between between the the LCLLCL and and the thecloud cloud base base height), height), the thecloud cloud base base height height over over Wuha Wuhann is overwhelmingly is overwhelmingly higherhigher than than the thepertinent pertinent LCL. LCL. 96% 96% (2626 (2626 out outof 2744) of 2744) of the of theevents events present present this this situation situation andand the theaverage average bias bias between between the thecloud cloud base base height height and and LCL LCL is 308 is 308 ± 254± 254 m. The m. The possible possible explanationexplanation is as is follows: as follows: the theLCL LCL is calculated is calculated based based on surface on surface temperature, temperature, and and RHRH is is the thelevel level where where the theupdraft updraft air mass air mass becomes becomes satu saturated;rated; however, however, the theair airmass mass is likely is likely to to overshootovershoot this this level level due due to inertia. to inertia. Therefore, Therefore, it can it canbe speculated be speculated that that rapid rapid condensation condensation of updraftof updraft air mass air mass will will occu occurr in the in thesub-cloud sub-cloud zone zone during during the theabovementioned abovementioned process; process; accordingly,accordingly, the the𝛿 δ willV will present present a decreasing a decreasing trend trend along along the the height. height. A similar A similar structure structure couldcould be found be found from from the theWVMR WVMR structure structure of the of thetropical tropical atmosphere atmosphere in Garstang in Garstang and and BettsBetts [53]. [53 The]. The WVMR WVMR in the in thesub-cloud sub-cloud zone zone presented presented a decrease a decrease along along height, height, meaning meaning thatthat water water droplets droplets formed formed increasingly increasingly along along the theheight. height.

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Figure 8. Distributions of (a) cloud base, (b) cloud top, (c) cloud peak heights, and (d) cloud Figure 8. Distributions of (a) cloud base, (b) cloud top, (c) cloud peak heights, and (d) cloud geo- Remote Sens. 2021, 13, x FOR PEER REVIEW geometrical thickness for the total of 3047 shallow cumulus cloud events observed14 of 20 from 2011 to 2019 metrical thickness for the total of 3047 shallow cumulus cloud events observed from 2011 to 2019 at Wuhan,at China. Wuhan, The China. blue Thebar, blueyellow bar, bar, yellow and bar,red bar and represent red bar represent the number the numberof events of in events summer in summer (June, July,(June, and July, August), and August), in autumn in autumn (September, (September, October, October, and November), and November), and in Spring and in (March, Spring (March, April, andApril, May), and respectively. May), respectively.

Figure 9. ScatterplotFigure showing 9. Scatterplot the relationship showing thebetween relationship the cloud between base height the cloud of the base lidar-observed height of the lidar-observed shallow cumulishallow and lifting cumuli condensation and lifting level condensation (LCL) calculated level (LCL) from the calculated data of surface from the temperature data of surface temperature and relative humidityand relative several humidity minutes several(depending minutes on the (depending cloud base on height the cloud and an base assumption height and of 1 an assumption of m s−1 upward velocity of the air parcel [54]) before corresponding shallow cumulus occurred. In 1 m s−1 upward velocity of the air parcel [54]) before corresponding shallow cumulus occurred. In this plot, only 2744 shallow cumulus events are included because the data of corresponding surface this plot, only 2744 shallow cumulus events are included because the data of corresponding surface temperature and relative humidity are available therein. temperature and relative humidity are available therein.

In order to verify the 𝛿 decreasing trend along with height in the sub-cloud zone, comparisons of 𝛿 at the LCL level and cloud base level are plotted in Figure 10. The LCL 𝛿 and cloud base 𝛿 were an average from eight height intervals which were above the LCL and below the cloud base, respectively. 1515 out of the 1941 (78%) counted events (803 events were excluded due to the low SNR) presented a 𝛿 decrease trend along height. The average 𝛿 decrease between these two levels is 0.0045 ± 0.0058.

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In order to verify the δV decreasing trend along with height in the sub-cloud zone, comparisons of δV at the LCL level and cloud base level are plotted in Figure 10. The LCL δV and cloud base δV were an average from eight height intervals which were above the LCL and below the cloud base, respectively. 1515 out of the 1941 (78%) counted events (803 Remote Sens. 2021, 13, x FOR PEER REVIEW 15 of 20 events were excluded due to the low SNR) presented a δV decrease trend along height. The average δV decrease between these two levels is 0.0045 ± 0.0058.

Figure 10. ScatterplotFigure 10.showingScatterplot the relationship showing the between relationship the values between of the the volume valuesof depolarization the volume depolarization ratio 𝛿 at the lifting condensation level (LCL) and at cloud base level based on a total of 1941 shal- ratio δV at the lifting condensation level (LCL) and at cloud base level based on a total of 1941 shallow low cumulus events. Note that out of the 1941 events, 78% are characterized by larger 𝛿 values at cumulus events. Note that out of the 1941 events, 78% are characterized by larger δV values at the the LCL height than that at the cloud base height, exhibiting a gradually increasing condensation LCL height than that at the cloud base height, exhibiting a gradually increasing condensation with with height in the sub-cloud region. height in the sub-cloud region.

3.3.4. Surface3.3.4. Meteorological Surface Meteorological Parameters Parameters The surface TThe versus surface WVMR T versus for cumulus WVMR da forys during cumulus 2011–2019 days during are plotted 2011–2019 in Fig- are plotted in ure 11. As seenFigure from 11 Figure. As seen 11, the from majority Figure (>79%) 11, the of majority the cumulus (>79%) events of the occurred cumulus under events occurred the surface meteorologicalunder the surface conditions meteorological of the near-surface conditions oftemperature the near-surface being temperature higher than being higher 30 °C and thethan WVMR 30 ◦C larger and thethan WVMR 15 g kg larger−1. The than cumulus 15 g kgday−1 surface. The cumulus T versus day WVMR surface T versus presents a clusteringWVMR presentspattern with a clustering a linear pattern correlation with coefficient a linear correlation of ~0.81. The coefﬁcient average of ~0.81. The near-surface averageWVMR in near-surface Lareau, Zhang, WVMR and in Klein Lareau, [14] Zhang, was lower and than Klein 15 [14 g ]kg was−1, while lower the than 15 g kg−1, result at our whilesite was the 19.9 result g kg at−1 our(a relatively site was large 19.9 g value). kg−1 (a We relatively infer that large high value). near-surface We infer that high temperature near-surface(mostly in summertime temperature under (mostly fair-w ineather) summertime is more under likely fair-weather) to cause disturb- is more likely to ances [55] andcause thus disturbancesinitiate thermal [55 ]convection, and thus initiate promoting thermal the convection,formation of promoting cumulus. the formation of cumulus.

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Figure 11. ScatterplotFigure showing 11. Scatterplot the relationship showing between the relationship surface air between temperature surface (T) air and temperature water vapor (T) and water vapor mixing ratio (r) associatedmixing ratio with (r) 2744 associated shallow with cumu 2744lus shallowcloud events cumulus observed cloud by events our polarization observed by our polarization lidar. Note that the shallow cumulus cloud events occurred mostly (>79%) when the near-surface lidar. Note that the shallow cumulus cloud events occurred mostly (>79%) when the near-surface temperature T was higher than 30° C and the WVMR larger than 15 g kg−1. temperature T was higher than 30 ◦C and the WVMR larger than 15 g kg−1.

4. Discussion 4. Discussion Fair-weather cumulusFair-weather could be cumulus classified could as “forced” be classified and as“active” “forced” cumulus and “active” [22]. The cumulus [22]. The “forced” cumulus“forced” presents cumulus a thinner presents vertical a thinnerextent or vertical physical extent geometrical or physical thickness geometrical and thickness and a a shorter lifetimeshorter [56]. “Forced” lifetime [ 56cumulus]. “Forced” form cumuluss via the formsconvective via the lifting convective of surface lifting ther- of surface thermals mals and locatesand at the locates top edge at the of the top convec edge oftive the boundary convective layer. boundary The two layer.representative The two representative cumulus day casescumulus in Section day cases3.1 and in Sections3.2 exhibited 3.1 and the 3.2 summer exhibited daytime the summer occurrence daytime of occurrence of “forced” shallow“forced” cumulus. shallow The two cumulus. events were The twochosen events to reflect were a chosen clear-cut to reflectprocess a clear-cutfor a process for single shallow cumulusa single shallowcloud evolving cumulus from cloud formation evolving to from disappearance formation to that disappearance could be that could be simultaneously registeredsimultaneously in both registered the lidar inmeasurement both the lidar and measurement ground-based and camera. ground-based Since camera. Since many factors (e.g.,many small factors lidar (e.g., FOV smallvs. quite lidar large FOV FOV vs. quite for the large ground FOV camera, for the ground multiple camera, multiple shallow cumulusshallow clouds cumulus in camera clouds FOV, in and camera wind FOV, advection) and wind affect advection) the availability affect the availabilityof of such such cases, the twocases, chosen the two cases chosen actually cases repr actuallyesent representthe best examples the best examples in the simultaneous in the simultaneous camera camera and lidarand observations lidar observations depicting depicting the formation the formation and vanishing and vanishing of the single of the shallow single shallow cumuli. cumuli. They provideThey provide the direct the observation direct observation of the ofcloud the cloud physics physics process process in the in natural the natural atmosphere. atmosphere. However,However, the the temporal temporal resolution resolution of of our our lidar lidar is 1 minmin whilewhile the the cumulus cumulus formation and its formation and itsvariation variation could could occur occur within within 1 min.1 min. A higherA higher temporal temporal resolution resolution lidar lidar and cloud camera and cloud cameraobservation observation could could investigate investigate the short-timethe short-time scale scale and fineand verticalfine vertical structure of the CBL structure of the CBLclouds. clouds. A full-day A full-day operation operation polarization polarization lidar lidar with with a tilted a tilted emitting emitting laser and a much laser and a muchhigher higher time time resolution resolution (10 (10 s) hass) has been been built built by by Liu Liu et al.et [al.57 ],[57], and and the the finer process-level finer process-levelobservations observations can can be expectedbe expected in thein the future. future. The cloud top determinationThe cloud top is determination very sensitive isto very the cloud sensitive optical to the depth cloud [58]. optical The CBL depth [58]. The CBL cumuli observedcumuli over Wuhan observed present over Wuhanmostly sh presentort duration mostly and short small duration size (according and small to size (according to Figure 7b and cloudFigure images).7b and In cloud this images).study, the In cloud this study, top and the cloud cloud geometrical top and cloud thickness geometrical thickness should be underestimatedshould be underestimatedslightly. slightly. The GCMs sufferThe from GCMs errors suffer in the from locati errorson, timing, in the location, and extent timing, of shallow and extent clouds. of shallow clouds. The statistical studyThe statisticalof cumulus study can ofbe cumulus a dataset can from be an a dataset urban area from at an a urbanmid-latitude area at a mid-latitude plain site, containingplain site,the containinglocation, onset the location, time, and onset thickness time, and information. thickness information. Meanwhile, Meanwhile, other other researchersresearchers who are interested who are interestedin using spaceborne in using spaceborne instruments instruments to explore tothe explore cu- the cumulus over different underlying surfaces can refer to our results [25]. mulus over different underlying surfaces can refer to our results [25].

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5. Conclusions Two typical CBL cumulus occurrences in fair-weather summer over a megacity at a mid-latitude site was exhibited by polarization lidar, simultaneous surface weather station, and cloud camera measurements. The cumulus was most likely to form at the top of the CBL when the CBL height jumps over the LCL. The clear-cut process-level cumulus formation and its sub-cloud variation were displayed. This provides us a direct observation of the shallow convective cloud in the CBL and deepens our understanding of cloud physics in the low-level atmosphere. Convective boundary layer clouds were statistically investigated based on extensive polarization lidar measurements on 848 different days from 2011 to 2019 at Wuhan, China (30.5◦N, 114.4◦E). A total of 3047 individual shallow cumulus events were identified from 117 different days out of the total 848 observational days. The 117 shallow cumulus days (each cumulus cloud day contained at least 10 cumulus cloud events) were distributed between April and October with the maximum occurrence in July. They formed mostly (>95%) in the period of 09:00–18:00 LT while surface air temperature and water vapor mixing ratio were generally larger than 30 ◦C and 15 g kg−1, respectively. These fair-weather shallow cumuli occurred at the top edge of the convective boundary layer with a duration of 1–10 min (79% having a duration of 1–5 min) and a geometrical thickness of ~50–600 m (70% having a geometrical thickness less than 250 m). Their cloud base height ranged from 0.5 to 1.9 km. The lifting condensation level (LCL) was estimated to appear ~50–560 m (a mean of 308 ± 254 m) below the cloud base. In the height range from the LCL to the cloud base, the lidar volume depolarization ratio (δV) slightly decreased with increasing altitude, showing a gradually increasing condensation in this sub-cloud region due to penetrative thermals. The current study provides the statistical results of shallow cumulus cloud properties and formation conditions based on the polarization lidar and surface weather station observations at a 30◦N plain site. It supplements the existing data library of locally generated surface-forced shallow cumuli that has been established in terms of long-term continuous ground-based observational data at a couple of sites in the mid-latitude region [14,59,60]. Long-term observations at low-latitude sites are urgently required at present in order to efficiently develop and improve conventional global climate models. In addition, the cumulus cloud formation (mechanism and characteristics) also depends on underlying surface conditions [30,35–38]. Thus, long-term observations for various underlying surface conditions are also needed. Our polarization lidar can be conveniently deployed in field conditions because of its robust configuration and unattended operation. It is actually a suitable sort of instrument for observing the shallow cumulus clouds over various underlying surfaces in the low-latitude region. In addition to a role in affecting large-scale dynamics, the presence of shallow cumulus clouds reflects a locally intensified vertical turbulent transport of heat, moisture, and momentum [61,62]. The present observations quantify statistically the local surface conditions for cumulus cloud formation that most of the observed cumuli are associated with: high air temperature (>30 ◦C) and mixing ratio (>15 g kg−1).

Author Contributions: Y.Z. (Yifan Zhan) performed the lidar observation, made the data analysis and wrote the initial manuscript. F.Y. conceived the project, led the research, and ﬁnalized the manuscript. F.L., Y.Z. (Yunpeng Zhang) and C.Y. made contributions in establishing the lidar system, auto weather station, and cloud camera. J.Z. and F.L. participated in the scientiﬁc discussions. All authors have read and agreed to the published version of the manuscript. Funding: This work is funded by the National Natural Science Foundation of China through grants 41927804. Institutional Review Board Statement: Not applicable. Informed Consent Statement: Not applicable. Remote Sens. 2021, 13, 1281 16 of 18

Data Availability Statement: Data used to generate the results of this paper are available from the authors upon request (E-mail: [email protected]). Acknowledgments: The author would like to express thanks to Yunfei Zhang, Yun He, Zhenping Yin, and Wei Wang for advice on data processing as well as on performing lidar observations. Conflicts of Interest: The authors declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work and that this paper was not published before, the funding sponsors had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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