Comparative study of aircraft- and satellite-derived aerosol and cloud ...

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Comparative study of aircraft- and satellite-derived aerosol and cloud microphysical parameters during CAIPEEX-2009 over the Indian region a

a

a

B. Padmakumari , R.S. Maheskumar , G. Harikishan , J.R. a

Kulkarni & B.N. Goswami a

a

Indian Institute of Tropical Meteorology, Pune, 411008, India

Version of record first published: 18 Sep 2012.

To cite this article: B. Padmakumari, R.S. Maheskumar, G. Harikishan, J.R. Kulkarni & B.N. Goswami (2013): Comparative study of aircraft- and satellite-derived aerosol and cloud microphysical parameters during CAIPEEX-2009 over the Indian region, International Journal of Remote Sensing, 34:1, 358-373 To link to this article: http://dx.doi.org/10.1080/01431161.2012.705442

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International Journal of Remote Sensing Vol. 34, No. 1, 10 January 2013, 358–373

Comparative study of aircraft- and satellite-derived aerosol and cloud microphysical parameters during CAIPEEX-2009 over the Indian region Downloaded by [Indian Institute of Tropical Meterology] at 02:17 04 October 2012

B. Padmakumari*, R.S. Maheskumar, G. Harikishan, J.R. Kulkarni, and B.N. Goswami Indian Institute of Tropical Meteorology, Pune 411008, India (Received 4 April 2011; accepted 14 December 2011) This article presents the spatial and vertical distribution of aerosols and cloud microphysical parameters from the combined data sets of aircraft and satellites. The aircraft-based Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) was conducted in India during May to September 2009. During the experimental period, 3 days were identified on which space-borne lidar (CALIPSO) and radar (CloudSat) were nearby/over passed the observational regions, which covered north, south central, and southern parts of the Indian subcontinent. The results obtained from these three cases are explored. Similar features of aerosol layering and water/ice cloud signatures are observed by both aircraft and CALIPSO. In addition, events where dust aerosols acting as ice nuclei and polluted aerosols increase the depth of warm rain initiation are observed. The CloudSat profiles of liquid water content, droplet number concentration, and effective radii are underestimated when compared with the corresponding aircraft profiles. The aircraft measurements are able to bring out fine variability in vertical distribution, which would be more useful for regional parameterization schemes and model evaluation.

1. Introduction Atmospheric aerosols play a major role in climate change by directly scattering and absorbing the incoming and outgoing radiation (direct effect) as well as through modifying cloud properties, such as droplet size distribution and cloud lifetime (indirect effect) (Twomey 1974; Kaufman et al. 2005). As atmospheric aerosols are widely distributed, their role in cloud microphysics is very complex and is being understood by the scientific community through a wide variety of measurements made from ground, air, and space. The increasing aerosol loading, contributed by both regional sources and long-range transport, changes in cloud microphysics due to aerosol–cloud interactions, and the warm oceans surrounded by peninsular India, play a significant role in Indian monsoon variability. However, aerosol and cloud measurements, particularly their vertical distribution, are sparse over the Indian region. The vertical distribution of aerosols is studied from in situ probing using rocket- and balloon-borne instruments (Jayaraman, Subbaraya, and Acharya 1987; Ramachandran and Jayaraman 2003), ground-based lidar (Devara, Raj, and Pandithurai 1995; Jayaraman et al. 1995; Satheesh, Vinoj, and Moorthy 2006), and airborne lidar *Corresponding author. Email: [email protected] ISSN 0143-1161 print/ISSN 1366-5901 online © 2013 Taylor & Francis http://dx.doi.org/10.1080/01431161.2012.705442 http://www.tandfonline.com

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(Gadhavi and Jayaraman, 2006). There exist a few studies using aircraft-based measurements (Moorthy et al. 2004, Tripathi et al. 2005) but their temporal and spatial coverage is limited. In order to understand the variability of background aerosols, cloud microphysical properties and pathways through which aerosols modify clouds and precipitation processes, a field campaign called the Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) was conducted by the Indian Institute of Tropical Meteorology (IITM) over various regions of India under different environments during May to September 2009. This is the longest aircraft experiment conducted for the first time in India. Under this experiment, an instrumented aircraft was used for the measurements of aerosols and cloud microphysical parameters (Kulkarni et al. 2012). In situ measurements are essential to improve the understanding of cloud processes and cloud feedbacks and constrain model uncertainty. The vertical and spatial distribution of aerosols and cloud parameters can be obtained from space-borne lidar such as Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on-board the satellite, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) (Winker, Pelon, and Mccormick 2003), and Cloud Profiling Radar (CPR) on-board the satellite, CloudSat (Stephens et al. 2002, 2008), respectively. They were launched in 2006. CALIOP data have been used to study the properties of pollution aerosols (Kim et al. 2008), dust aerosols (Christopher et al. 2009; Gautam et al. 2009; Kuhlmann and Quaas 2010), and biomass burning aerosols (Labonne, Breon, and Cherallier 2007; Jeong and Hsu 2008). The retrieved estimates of cloud parameters such as cloud liquid water content (LWC), ice water content, effective radius, number concentration, and related quantities for each radar profile are obtained from CPR on CloudSat (Wood 2008). Although the above two satellites provide a variety of aerosol and cloud information, they have certain limitations. For instance, radar alone cannot accurately estimate particle size and is insensitive to small hydrometeors, whereas lidar is more sensitive to optically thin clouds but suffers from attenuation (Delanoe and Hogan 2010). In situ measurements are essential for validating satellite-derived products and for better understanding the vertical, spatial, and temporal variability from combined data sets. To evaluate the capability of CALIOP, a field experiment was organized over France, and a reasonable agreement was found between the aerosol optical properties inferred from CALIOP and those deduced from the ground-based and airborne lidar observations in the pollution plume (Chazette et al. 2010). The Canadian CloudSat CALIPSO Validation Project (C3VP) aimed to evaluate data products from CloudSat and CALIPSO over Canada (Hudak et al. 2007). Intercomparisons of CALIPSO data have also been carried out over different European Aerosol Research Lidar Network (EARLINET) stations (Pappalardo et al. 2010). There are several studies comparing CloudSat and ground-based cloud radar observations (Liu, Heygster, and Suping 2010; Liu, Marchand, and Ackerman 2010). A few studies exist where CALIPSO and CloudSat vertical profiles are compared with aircraft measurements. Such comparisons were made for the first time over the Indian region and are essential to constrain the uncertainties in the regional cloud parameterization schemes. During CAIPEEX, 3 days were identified on which CALIPSO and CloudSat were nearby/over passed the observational regions. These 3 days fall in different months and over different locations (23 May in the north; 22 June in the southeast; 8 July in the south). In this study, the results obtained from the above three cases, where in situ aircraft measurements were coincident with CALIPSO and CloudSat over passes, were explored.

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2. Data and methodology 2.1. Aircraft data A twin engine Piper Cheyenne-II research aircraft was used during CAIPEEX-2009. The instrument used on-board for aerosol measurements was a Passive Cavity Aerosol Spectrometer Probe (PCASP-100), which is capable of measuring fine and accumulation mode size particles such as sulphate, soot, organic carbon, and smaller mineral dust, with diameters ranging from 0.1 to 3 µm (Liu et al. 2009). A Hot Wire Liquid Water Sensor (LWC-100), sensitive in the range 0–3 gm−3 , was used for the measurement of LWC. A cloud droplet probe (CDP) was used to measure the drop size distribution, concentration and cloud LWC. The CDP was sensitive in the size range of 2–50 µm. A cloud imaging probe (CIP) registered images of cloud particles in the size range 25–1550 µm. Data were collected at an interval of 1 s (∼100 m). More details about the instrumentation can be found at http://www.tropmet.res.in/~caipeex/ai_P1.php and Kulkarni et al. (2012). Standard procedures were adapted periodically to calibrate the aircraft instruments during the campaign.

2.2. Satellite data In this study, CALIPSO-, CloudSat-, and Moderate Resolution Imaging Spectroradiometer (MODIS)-derived products were used. The aircraft operations were during afternoon (takeoff after 1300 UTC) and the above satellite passes over India were also around the same time during the observational period. CALIOP emits polarized light at two wavelengths 1064 and 532 nm with a pulse energy of 110 mJ and a pulse repetition rate of 20.25 Hz. In addition to the total backscatter at the two wavelengths, CALIOP also provides profiles of linear depolarization at 532 nm. The depolarization measurements enable discrimination between ice clouds and water clouds. Details on the CALIOP instrument, data acquisition, and science products are given by Anselmo et al. (2006) and Winker et al. (2009). There exist certain discrepancies in the retrievals of CALIPSO and groundbased lidars, which can be explained by the influence of multiple scattering (Wandinger et al. 2010). In this study, total attenuated backscatter coefficients from CALIOP level-2 (ver. 3.01) data at 532 nm with a spatial resolution of 30 m vertically and 333 m horizontally are considered. CloudSat, carrying a CPR (94 GHz and 3 mm wavelength), looks straight down at the Earth to measure the vertical structure of clouds and rain from space. CPR, being a nadirlooking radar, measures the backscattered power from hydrometeors along its path as a function of distance from the radar, with a minimum detectable threshold of about −30 dbZ (Tanelli et al. 2008). The CloudSat data product, Radar-Visible Optical Depth Cloud Water Content (2B-CWC-RVOD), which contains retrieved estimates of cloud LWC, number concentration, and effective radius for each radar profile (Wood 2008), is used. CloudSat has a resolution of 1.4 km across track and 1.7 km along track. Its vertical resolution is 480 m but is oversampled to 240 m in its products (Liu, Marchand, and Ackerman 2010). MODIS on-board the Aqua satellite provides integrated properties of aerosols and clouds. In this study, aerosol optical depths from Level 2 data and real-time images are used. The instrument has a wide swath of 2330 km along the orbital path. In the presence of clouds, MODIS cannot give aerosol optical depths. However, in the case of broken clouds, it can give measurements in between the clouds due to its high spatial resolution (Constantino and Breon 2010).



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3. Results and discussion In this study, the vertical and spatial distribution of aerosols and cloud parameters measured by aircraft, CALIPSO, and CloudSat during CAIPEEX for three experimental days (23 May, 22 June, and 8 July 2009) are discussed as three cases. On 23 May, CAIPEEX took place from the base at Pathankot, which is in the extreme north of India near the foothills of the Himalayas; on 22 June, from the base at Hyderabad, which is in south central India; and on 8 July from the base at Bengaluru, which is in South India. For these three days, the tracks of both aircraft and CALIPSO/CloudSat are shown in Figure 1 with the MODIS– Aqua images in the background. More detailed information about the coordinates of the bases, the measurement times, and the parameters of interest measured by aircraft and the satellites are given in Table 1. 35° N

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15° N 75° E

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80° E

Figure 1. Flight tracks of aircraft and CALIPSO/CloudSat on MODIS–Aqua images for (a) 23 May 2009, (b) 22 June 2009, and (c) 8 July 2009. The curved lines represent the aircraft tracks. Note: The straight lines indicate the satellite tracks. The circles indicate the aircraft profiled area. PTK, Pathankot; HYD, Hyderabad; BNG, Bengaluru.

Date

23 May 2009

22 June 2009

8 July 2009

Coordinates

32.2◦ N, 75.63◦ E

17.44◦ N, 78.38◦ E

13.13◦ N, 77.62◦ E

Note: IST, Indian Standard Time.

Bengaluru

Hyderabad

Pathankot

Base

Towards NW 11:58 to 14:52 IST

Towards SW 13:30 to 16:17 IST

Towards NW 13:29 to 14:38 IST

Direction/time

Aerosol concentration, cloud drop concentration, effective radii, and liquid water content

Aerosol concentration, cloud droplet concentration, effective radii, and liquid water content Aerosol concentration, cloud drop concentration, effective radii, and liquid water content

Parameters

Aircraft

Away from the base, while near to the location where the aircraft profiled the cloud (14:02:14 to 14:03:44 IST). While night track passes through the base (2:13:15 to 2:14:45 IST) Towards NW, passing through the base 13:52:28 to 14:05:56 IST

Along the flight track 13:54:01 to 14:07:30 IST

Direction/time

Parameters

Total attenuated back scatter, aerosol sub-types, and ice/water phase



Calipso

Table 1. Details of aircraft locations, Calipso/CloudSat overpasses, directions, times, and the parameters compared.

Same as CALIPSO (but not compared)

Same as CALIPSO 14:02:29 to 14:03:59 IST

Same as CALIPSO (but not compared)

Parameters

Cloud droplet concentration, effective radii, and liquid water content

CloudSat Direction/time


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3.1. Case 1: 23 May 2009 On 23 May 2009, the aircraft flew from the base at Pathankot towards the northwest (Srinagar). During this period, heat wave conditions prevailed over northwest Rajasthan and central India. Western disturbance was active over North India. Initially, weak convection prevailed, and late afternoon convective clouds were observed. The sky was mainly hazy during the observational period. On this day, the tracks of both aircraft and satellite are almost parallel and very close to each other (Figure 1(a)). The flight track falls within the swath area of CALIPSO. Figure 2(a) shows the CALIPSO vertical feature mask (VFM), which identifies clean air, clouds, aerosols, surface, and sub-surface features (for more details about VFM, see Anselmo et al. (2006)). High aerosol concentrations near the foothills and clouds above the hills are observed. These aerosols are mostly dust, as seen in the CALIPSO aerosol sub-type profile (Figure 2(b)). The area where the aircraft flew is marked on these figures. For this area, the integrated total attenuated backscatter profiles above the ground for aerosol and cloud layers are derived from CALIPSO (Figure 2(c)). The figure shows an enhanced aerosol layer from 1 to 4 km, peaking at 3 km, and a cloud layer above it at 4.5 km. This case seems like clouds on a frontal line. It clearly indicates bubbling of clouds above the aerosol layer. It is also noticed from Figure 2(a) that to the south of the base at Pathankot, aerosols persist up to a height of 5 km and clouds are observed above 5 km. In northern India, pre-monsoon aerosol characterization shows the dominance of dust aerosols extending up to 5 km (Gautam et al. 2009, Gautam, Hsu, and Lau 2010, Komppula et al. 2010). The haze was visibly dark over this region as noted

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Figure 2. Aerosol and cloud parameters derived from aircraft and CALIPSO on 23 May 2009. (a) CALIPSO vertical feature mask profile: the marked area is the region where the aircraft flew, (b) CALIPSO discrimination of aerosol types, (c) total attenuated backscatter profiles of aerosol and cloud layers for the marked area, (d) aircraft measured aerosol ascent and descent profiles from the base at Pathankot, (e) aircraft measured cloud droplet concentration and cloud droplet effective radii. Notes: Circles represent the clouds compared. (Timings of aircraft and satellite overpasses are given in Table 1.)

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Latitude (°N): Longitude (°E):

0 Not determined 32.00 75.90

33.00 75.60

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T = 0.4°C H = 4.2 km V = –1.2 m s–1 LWC = 0.004 g m–3

T = –17.6 °C H = 6.5 km V = 3.52 m s–1 LWC = 0.1 g m–3

Figure 3. 23 May CALIPSO ice/water discrimination plot showing liquid water as well as ice water in clouds and the corresponding CIP images of the aircraft-profiled clouds showing frozen hydrometeors at different altitudes. (CALIPSO and aircraft timings are shown in Table 1.) Note: T, temperature; H, height from the surface; V , vertical velocity.

by the aircraft crew. PCASP-measured aerosol profiles (screened for clouds) are shown in Figure 2(d) (ascent profile, Pathankot – Srinagar, towards the north and descent profile, Srinagar–Pathankot). In the ascent profile, a lower aerosol concentration, with an aerosol layer at 2 km, is observed when compared with the descent profile, which showed high aerosol concentrations from the surface to 4 km. This indicates that aerosols are lofted up to higher altitudes and feeding the clouds above, largely due to the up-slope flows near the foothills. MODIS–Aqua observed AOD over this region is ∼0.5. The aircraft sampled the cloud between 4 and 5 km and at 6.5 km. For these clouds, the CDP measured cloud droplet concentration and the respective effective radii (Re ) are shown in Figure 2(e). The clouds at these altitudes are seen in the CALIPSO profile as well. The droplet number concentration in these clouds is about 200 cm−3 . The maximum Re is only 6 µm. The lower cloud (4–5 km) sampled by the aircraft is not observed by CloudSat. The higher cloud (∼6.5 km) is observed by CloudSat, but not compared as the aircraft had only two passes through this cloud. The CALIPSO ice water/liquid water phase profile and the CIP images at the altitudes where the aircraft sampled the cloud are shown in Figure 3. The CIP image at 6.5 km, where the temperature is −17.6◦ C and updraft velocity is 3.5 m s−1 , shows only frozen hydrometeors, which might be due to the possible effect of dust aerosols as they are dominant over this region. Dust aerosols might inhibit the growth of cloud droplets and act directly as ice nuclei (Klein et al. 2010). According to earlier studies, freezing due to dust aerosol occurs at higher altitudes and thus at much lower temperatures between −15 and −25◦ C (Ansmann et al. 2009; Seifert et al. 2010). At these altitudes, the CALIPSO ice water/liquid water phase profile shows ice water as well as liquid water cloud. The CIP image at 4.2 km (0.4◦ C) also shows frozen hydrometeors, but they seem to be falling from above. The CALIPSO depolarization measurements enable discrimination between ice water and liquid water clouds, whereas the in situ CIP data show exactly the cloud phase at that particular altitude. 3.2. Case 2: 22 June 2009 On 22 June 2009, the experiment took place from the base at Hyderabad towards the southwest (see Figure 1(b)). June 21 is the usual onset date of monsoon at Hyderabad. The westerly flow was stronger in the morning, and small cumuli were moving rapidly to the

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east. On this day, the satellite day track is slightly far from the base at Hyderabad, while being near to the location where the aircraft profiled the cloud. The CALIPSO day VFM profile (Figure 4(a)) shows a thick cloud band above 5 km, extending almost 2◦ in latitude with an aerosol layer up to 3 km. The aerosol layer is composed of smoke, polluted dust, and dust, as observed in the CALIPSO aerosol sub-type in Figure 4(g). The integrated total attenuated backscattered profiles, for aerosol and cloud layers, are shown in Figure 4(b). The profile for cloud shows two cloud layers, a low broken cumulus at 2–3 km with less attenuation and a higher alto cumulus at 5.5–6.5 km with more attenuation. As CALIPSO is a space-borne lidar, it observes aerosol characteristics but cannot penetrate thick cloud; the identification method used in CALIPSO is only limited in thin cloud (Delanoe and Hogan 2010). The aerosol backscatter profile shows high aerosol concentrations from the

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Figure 4. Aerosol and cloud parameters derived from aircraft and CALIPSO on 22 June 2009. (a) CALIPSO – day vertical feature mask profile, (b) total attenuated backscatter profiles (day), (c) aircraft measured aerosol profile, (d) CALIPSO – night vertical feature mask profile, (e) total attenuated aerosol backscatter profile (night), (f ) radio-sonde temperature profiles at 1300 hrs and 1730 hrs on 22 June and 0530 hrs on 23 June at Hyderabad, (g) CALIPSO – day discrimination of aerosol types, and (h) CALIPSO – night discrimination of aerosol types. (Timings of aircraft and satellite overpasses are given in Table 1.)


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surface to 3 km. The vertical profile obtained with aircraft (Figure 4(c)) not only shows high aerosol concentrations from the surface to about 3 km but also shows two typical aerosol layers with a decreasing trend with height. The CALIPSO night track passed exactly through Hyderabad; the VFM profile and the corresponding aerosol profile are shown in Figures 4(d) and (e), respectively. The aerosol layers at 2.5–3.5 km and at 4–5 km as observed with CALIPSO are also observed in the aircraft profile. It is interesting to note that the aerosol layers that are observed during afternoon flight are persistent till midnight as observed by CALIPSO. To understand the reason for this, the temperature profiles have been observed. Figure 4(f ) shows the radiosonde profiles during the flight time, i.e. 1330 hrs, 1730 hrs (of 22 June), and 0530 hrs (of 23 June) at Hyderabad, measured by the India Meteorological Department and obtained from the University of Wyoming site. During the afternoon, two inversion layers are seen, one layer at 2.0–2.4 km and another layer at 3.6–4.0 km. Below these inversions, aerosols are trapped, and in the inversion layer, aerosol concentrations remain constant due to a lack of vertical mixing (as seen in Figure 4(c)). Horizontal advection could also be the most likely cause for constant or changing aerosol concentrations in the free troposphere. During the evening (12 GMT) and early morning (0 GMT) of the next day, the lower inversion layer still persists with a small shift in height, and similar features in the aerosol profile are observed in the CALIPSO profile also (see Figure 4(e)). Hence, aerosol layers seem to persist due to the stability of the atmosphere. These layers are composed of smoke, polluted dust, and dust, as observed in CALIPSO aerosol sub-type in Figure 4(h). When compared with daytime aerosol distribution, dust and polluted dust seem to be lifted up to higher altitudes, whereas smoke is accumulated in the lower 2 km. Strong pollution and temperature inversions are frequently correlated and temperature inversions act as aerosol traps (Grassel 1973). Downward cloud profiling was done by aircraft in the southwestern region of Hyderabad. The first cloud penetration took place at a height of 7 km. A total of 17 cloud passes were made during descent, and during each cloud pass, the aircraft was kept straight and level. The cloud base was at 2 km. The CDP-measured cloud drop concentration (Figure 5(a)) showed a maximum concentration of ∼400 cm−3 at the cloud base and decreased with height while the corresponding Re increased with height. Cloud droplets of size ≥14 µm were observed at higher depths from the base. This delayed growth of droplets may be attributed to the highly polluted aerosols. The CIP images at the altitudes where the aircraft penetrated the cloud are shown in Figure 5(b). The CIP images in the altitude range from 2.2 to 6.8 km, temperature ranging from 13.5◦ C to −11.5◦ C, showed the existence of only cloud droplets with the occasional presence of larger liquid hydrometeors. The cloud base is at around 2 km on this day and the CIP images near the cloud base show rain drops. Low LWC values at the cloud base confirm that the drops are falling from above. The collision–coalescence process at higher altitudes (discussed above) might have initiated the formation of warm rain by the time the aircraft sampled near the cloud base. The CALIPSO profile also shows only a water phase in the lower as well as in higher clouds. It indicates that cloud droplets (i.e. liquid water) are observed much above the freezing level. Re increased with height at a slower rate and attained the maximum value (16 µm) only above 6 km, thus the depth of warm rain initiation is increased, which might be due to high aerosol concentrations mostly composed of polluted dust (Rosenfeld et al. 2008). The MODIS real-time image (seen in Figure 1(b)) shows the horizontal extent of the cloud that is observed by CALIPSO and CloudSat near the observational region. The aircraft cloud-profiled area falls within the swath area of CloudSat. The CloudSat-derived cloud parameters as well as the aircraft-derived cloud parameters (averaged for each penetration), such as LWC, droplet number concentration, and effective radius (Re ), are shown


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H = 6.8 km T = –11.5 °C V = 1.57m s–1 LWC = 0.37g m–3

H = 5.8 km H = 5.1 km H = 4.4 km T = –6.9 °C T = –3.7 °C T = 1.25 °C V = 4.35m s–1 V = 5.29m s–1 V = 2.17m s–1 LWC = 1.06g m–3 LWC = 0.91g m–3 LWC = 0.15g m–3

H = 3.7 km T = 5.8 °C V = 4.1m s–1 LWC = 0.1g m–3

H = 2.8 km T = 10.34 °C V = 1.71m s–1 LWC = 0.21g m–3

H = 2.2 km T = 13.47 °C V = 2.14m s–1 LWC = 0.007g m–3

Figure 5. 22 June 2009: (a) aircraft measured cloud droplet concentration and droplet effective radii, (b) CALIPSO ice/water discrimination plot showing only liquid water clouds, and the corresponding CIP images of the aircraft-profiled cloud showing only cloud droplets at different altitudes. (CALIPSO and aircraft timings are shown in Table 1.) Note: T, temperature; H, height from the surface; V , vertical velocity.

in Figures 6(a)–(c). The aircraft-derived LWC and Re showed a steady increase from cloud base to cloud top with a variable droplet number concentration. The variations in droplet number concentration and LWC look somewhat similar to that of the aircraft when compared with Re . The aircraft measurements (0–1.8 gm−3 ; 70–300 cm−3 ; 3–16 µm) are higher than the corresponding CloudSat measurements (0–0.8 gm−3 ; 55–80 cm−3 ; 7–17 µm). These biases are expected in cloud thickness and cloud layering as a result of the 480 m vertical resolution of CloudSat measurements apart from the spatial resolution (Hudak et al. 2006). The CloudSat algorithm uses a priori information based on the cloud classification and an optimal estimation method (Li, Durden, and Tanelli 2007). The product would be highly influenced by radar reflectivity’s increased sensitivity to droplet size (D) because reflectivity is proportional to D raised to power 6. Further ice water and liquid water discrimination is solely based on ECMWF (European Centre for Medium Range Weather Forecasts) analyses temperature (Li et al. 2008). Due to the mixed phase nature of many clouds, including the presence of precipitating hydrometeors such as drizzle, these estimates may have uncertainties (Stephens et al. 2008). In addition, a small difference in spatial and temporal sampling of aircraft and satellite retrievals may also add to the bias.

3.3. Case 3: 8 July 2009 On 8 July 2009, the aircraft moved northwestward from the base at Bengaluru (see Figure 1(c)). On this day, westerly monsoon flow continued to prevail. The CALIPSO/ CloudSat track passed exactly through the cloud-sampled locations of the aircraft. The

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Figure 6. 22 June 2009: CloudSat-and aircraft-derived cloud parameters such as (a) droplet number concentration, (b) liquid water content, and (c) droplet effective radii. Note: The bars represent standard errors. Different symbols are given for CloudSat, each symbol representing the retrievals at different coordinates along the satellite track close to the aircraft profiled area. Aircraft retrieved the same cloud after 30 min of the CloudSat pass, which persisted for a long time.

CALIPSO VFM profile (Figure 7(a)) and the corresponding integrated vertical profile (Figure 7(c)) show the presence of strato cumulus cloud at 1.5–3 km and a series of clouds above 6 km. The aerosols are composed of dust and polluted dust elevated up to 2 km (Figure 7(b)). The CALIPSO could see only one sampled cloud (towards the south) and it could not see the other sampled cloud due to the presence of high clouds, as seen in Figure 7(a). The aircraft sampled the same lower cloud as sampled by CALIPSO and showed cloud drop concentration of maximum 1000 cm−3, and the corresponding Re increased rapidly with height and reached 16 µm at the cloud top (i.e. 3 km) (Figure 7(e)). The drop concentrations below 20 cm−3 at higher altitudes indicate that the aircraft flew below the cloud base and had not penetrated those clouds. The aerosol vertical profiles during ascent and descent of aircraft (Figure 7(d)) showed concentrations about 3000 cm−3 from the surface to the cloud base (2 km) and also above the cloud (i.e. above 3 km). The aerosols above the lower cloud are not retrieved from CALIPSO due to the presence of high clouds. The aerosols at the lower height are composed of dust and polluted dust (Figure 7(b)). The lidar observations over the east coast also showed a large fraction (60–75%) of aerosol above the clouds leading to enhanced aerosol absorption above the clouds (Satheesh et al. 2009).

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Figure 7. Aerosol and cloud parameters derived from aircraft and CALIPSO on 8 July 2009. (a) CALIPSO – day vertical feature mask profile, (b) CALIPSO profile showing the discrimination of aerosol types, (c) CALIPSO – total attenuated backscatter profile, (d) aircraft measured ascent and descent aerosol profiles from the base at Bengaluru, and (e) cloud droplet concentration and droplet effective radii. (CALIPSO and aircraft timings are shown in Table 1.)

The MODIS real-time image in Figure 1(c) shows monsoon clouds over the observational region. The cloud parameters of lower cloud were, seen by CALIPSO, were not retrieved by CloudSat because CPR tends to miss thin clouds composed of small cloud particles as the minimum detection limit is −30 dBZ. However, the cloud parameters were retrieved for the higher clouds, but those clouds were not sampled by the aircraft. The lower cloud seen by CALIPSO is composed of only cloud droplets, as shown in Figure 8. The CIP images in this cloud at altitudes 2.8 km and 3 km also show only cloud droplets. However, the clouds above 5 km show water as well as ice, as shown by CALIPSO.

4. Summary The present paper focused on a few case studies of almost simultaneous observations from aircraft, CALIPSO, and CloudSat. This study brought out the possible comparisons of the measured aerosols and cloud microphysical parameters by different techniques. During CAIPEEX-2009 over India, there were three cases during which space-borne lidar (CALIPSO) and radar (CloudSat) were nearby/over passed the experimental areas. Aircraft and CALIPSO data showed almost similar features of aerosol layering. Polluted aerosols are observed from the surface to the base of the clouds, indicating that the aerosols are lofted up and are feeding the clouds. Whereas in the absence of clouds, they are lofted further to higher altitudes, forming elevated polluted layers in the presence of temperature inversions. High aerosol concentrations are also observed above the low monsoon clouds

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H = 2.8 km T = 10.60 °C V = 2.2m s–1 LWC = 1.34g m–3

H = 3.0 k m T = 9.5 °C V = 2.2m s–1 LWC = 0.81g m–3

Figure 8. CALIPSO ice/water discrimination plot showing only liquid water clouds and the corresponding CIP images of the aircraft profiled cloud showing only cloud droplets at two different altitudes. (CALIPSO and aircraft timings are shown in Table 1.) Note: T, temperature; H, height from the surface; V , vertical velocity.

by the aircraft. On 23 May (northern part of India), the profiled clouds had smaller Re , where dust aerosols are dominant. These dust aerosols might have acted as ice nuclei at higher altitudes and the falling frozen hydrometeors are observed below the freezing level. On 22 June (south central India), larger cloud droplets are observed much above the freezing level, increasing the depth of the warm rain initiation. In this case, the polluted aerosols might have delayed the fast growth of the cloud droplet. Whereas in a shallow monsoon cloud on 8 July (southern India), the maximum droplet concentration is 1000 cm−3 , with Re increasing rapidly and reaching 16 µm at the cloud top (3 km), indicating a maritime precipitating cloud. From the above case studies, the effect of different aerosol types on cloud microphysics in different environments can be inferred. However, aerosol indirect effects would be explored more in detail from larger data sets acquired from aircraft. Similar features of water/ice cloud signatures are observed by both aircraft and CALIPSO. The aircraft-derived LWC and Re showed a steady increase from cloud base to cloud top with a variable droplet number concentration. The variations in CloudSat droplet number concentration and LWC profiles look similar to those of aircraft. The CloudSat measurements are underestimated. However, the CloudSat measurements are useful for understanding large-scale cloud processes. While in situ measurements, which give better detailed fine variations of cloud parameters, will be useful for the parameterization of cloud processes in the numerical models and also for model evaluation. Although there exist certain limitations of different remote-sensing techniques, the combination of the data sets gave more insight and understanding of the spatial and vertical distribution of aerosols, clouds, and their interactions.

Acknowledgements The authors thank the Ministry of Earth Sciences (MoES), Govt. of India, for project funding, CAIPEEX team members and Prof. Daniel Rosenfeld, Hebrew University, Jerusalem. They acknowledge NASA Langley Research Center Atmospheric Science Data Center for CALIPSO data and the NASA CloudSat project for cloud parameters.


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References Anselmo, T. R., W. Clifton, K. Hunt, T. Lee, K. Murray, O. Powell, M. Chomette, A. Viollier, and J. Garnier Pelon. 2006. “Cloud Aerosol LIDAR Infrared Pathfinder Satellite Observations (CALIPSO).” Data Management System and Data Products Catalog. CALIPSO doc., rel. 23, Doc. PC-SCI–503. Ansmann, A., M. Tesche, P. Seifert, D. Althausen, R. Engelmann, J. Fruntke, U. Wandinger, I. Mattis, and D. Müller. 2009, “Evolution of the Ice Phase in Tropical Altocumulus: SAMUM Lidar Observations over Cape Verde.” Journal of Geophysical Research Letters 114: D17208. doi:10.1029/2008JD011659. Chazette, P., J.-C. Raut, F. Dulac, S. Berthier, S.-W. Kim, P. Royer, J. Sanak, S. Loaëc, and H. GrigautDesbrosses. 2010. “Simultaneous Observations of Lower Tropospheric Continental Aerosols with a Ground-Based, an Airborne, and the Spaceborne CALIOP Lidar Systems.” Journal of Geophysical Research Letters 115: D00H31. dio:10.1029/2009JD012341. Christopher, S. A., B. Johnson, T. A. Jones, and J. Haywood. 2009. “Vertical and Spatial Distribution of Dust from Aircraft and Satellite Measurements during the GERBILS Field Campaign.” Journal of Geophysical Research Letters 36: L06806. doi:10.1029/2008GL037033. Constantino, L., and F. M. Breon. 2010. “Analysis of Aerosol-Cloud Interaction from MultiSensor Satellite Observations.” Geophysical Research Letters 37: L11801. doi:10.1029/2009GL 041828. Delanoe, J., and R. J. Hogan. 2010. “Combined CloudSat-CALIPSO-MODIS Retrievals of the Properties of Ice Clouds.” Journal of Geophysical Research Letters 115: D00H29. doi:10.1029/2009JD012346. Devara, P. C. S., P. E. Raj, and G. Pandithurai. 1995. “Aerosol-Profile Measurements in the Lower Troposphere with Four-Wavelength Bistatic Argon-Ion Lidar.” Applied Optics 34: 51–65. Gadhavi, H., and A. Jayaraman. 2006. “Airborne Lidar Study of the Vertical Distribution of Aerosols over Hyderabad, an Urban Site in Central India, and Its Implication for Radiative Forcing Calculations.” Annales Geophysicae 24: 2461–70. Gautam, R., N. C. Hsu, and K.-M. Lau. 2010. “Premonsoon Aerosol Characterization and Radiative Effects over the Indo-Gangetic Plains: Implications for Regional Climate Warming.” Journal of Geophysical Research 115: D17208. doi:10.1029/2010JD013819. Gautam, R., Z. Liu, R. P. Singh, and N. C. Hsu. 2009. “Two Contrasting Dust-Dominant Periods over India Observed from MODIS and CALIPSO Data.” Geophysical Research Letters 36: L06813. doi:10.1029/2008GL036967. Grassel, H. 1973. “Aerosol Influence on Radiative Cooling.” Tellus XXV, no. 4: 386–95. Hudak, D., H. Barker, K. Strawbridge, M. Wolde, A. Kankiewicz, and W. Strapp. 2007. “The Canadian CloudSat CALIPSO Validation Project: Evaluation of Sensitivity and Sub-Pixel Variability of CloudSat Data Products.” In 33rd Conference on Radar Meteorology, American Meteorological Society, Cairns, QLD, August 6–10, CD-ROM paper 3.3. Jayaraman, A., S. Ramachandran, Y. B. Acharya, and B. H. Subbaraya. 1995. “Pinatubo Volcanic Aerosol Layer Decay Observed at Ahmedabad (23 N) India Using Nd: YAG Backscatter Lidar.” Journal of Geophysical Research Letters 100: 23209–14. Jayaraman, A., B. H. Subbaraya, and Y. B. Acharya. 1987. “The Vertical Distribution of Aerosol Concentration and their Size Distribution Function over the Tropics and their Role in Radiation Transfer.” Physica Scripta 36: 358–61. Jeong, M.-J., and N. C. Hsu. 2008. “Retrievals of Aerosol Single-Scattering Albedo and Effective Aerosol Layer Height for Biomass-Burning Smoke: Synergy Derived from A-Train Sensors.” Geophysical Research Letters 35: L24801. doi:10.1029/2008GL036279. Kaufman, Y. J., I. Koren, L. A. Remer, D. Rosenfeld, and Y. Rudich. 2005. “The Effect of Smoke, Dust and Pollution Aerosol on Shallow Cloud Development over the Atlantic Ocean.” Proceedings of National Academy of Science (USA) 102, no. (32): 11207–12. doi:10.1073/pnas.0505191102. Kim, S. W., S. Berthier, J.-C. Raut, P. Chazette, F. Dulac, and S.-C. Yoon. 2008. “Validation of Aerosol and Cloud Layer Structures from the Space-Borne Lidar CALIOP Using a Ground-Based Lidar in Seoul, Korea.” Atmospheric Physics and Chemistry 8: 3705–20. doi:10.5194/acp–8–3705. Klein, H., S. Nickovic, W. Haunold, U. Bundke, B. Nillius, M. Ebert, S. Weinbruch, et al. 2010. “Saharan Dust and Ice Nuclei over Central Europe.” Atmospheric Chemistry and Physics 10: 10211–21.


372


Komppula, M., T. Mielonen, A. Arola, K. Korhonen, H. Lihavainen, A.-P. Hyvärinen, H. Baars, et al. 2010. “One Year of Raman-Lidar Measurements in Gual Pahari EUCAARI Site Close to New Delhi in India: Seasonal Characteristics of the Aerosol Vertical Structure.” Atmospheric Chemistry and Physics Discussion 10: 31123–51. Kuhlmann, J., and J. Quaas. 2010. “How Can Aerosols Affect the Asian Summer Monsoon? Assessment during Three Consecutive Pre-Monsoon Seasons from CALIPSO Satellite Data.” Atmospheric Physics and Chemistry 10: 4673–88. Kulkarni, J. R., R. S. Maheskumar, S. B. Morwal, B. Padma Kumari, M. Konwar, C. G. Deshpande, R. R. Joshi, et al. 2012. “The Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX): Overview and Preliminary Results.” Current Science 102, no. 3: 413–25. Labonne, M., F.-M. Breon, and F. Chevallier. 2007. “Injection Height of Biomass Burning Aerosols as seen from a Spaceborne Lidar.” Geophysical Research Letters 34: L11806. doi:10.1029/2007GL029311. Li, J.-L. F., D. Waliser, C. Woods, J. Teixeira, J. Bacmeister, J. Chern, B.-W. Shen, A. Tompkins, W.-K. Tao, and M. Köhler. 2008. “Comparisons of Satellites Liquid Water Estimates to ECMWF and GMAO Analyses, 20th Century IPCC AR4 Climate Simulations, and GCM Simulations.” Geophysical Research Letters 35: L19710. doi:10.1029/2008GL035427. Li, L., S. Durden, and S. Tanelli. 2007. “Level 1B CPR Process Description and Interface Control Document.” Pasadena, California, version 5.3, 24 p. Liu, P., C. Zaoh, Q. Zhaon, Z. Denzg, M. Huang, X. Ma, and X. Tie. 2009. “Aircraft Study of Aerosol Vertical Distributions over Beijing and their Optical Properties.” Tellus 61B: 756–67. Liu, S., G. Heygster, and Z. Suping. 2010. “Comparison of CloudSat Cloud Liquid Water Paths in Arctic Summer Using Ground Based Microwave Radiometer.” Journal of Ocean University of China. doi:10.1007/s1182-010-1740–y. Liu, Z., R. Marchand, and T. Ackerman. 2010. “A Comparison of Observations in the Tropical Western Pacific from Ground-Based and Satellite Millimeter-Wavelength Cloud Radars.” Journal of Geophysical Research 115: D24206. doi:10.1029/2009JD013575. Moorthy, K. K., S. S. Babu, S. V. Sunil Kumar, P. K. Gupta, and B. S. Gera. 2004. “Altitude Profiles of Aerosol BC, Derived from Aircraft Measurements over an Inland Urban Location in India.” Geophysical Research Letters 31: L22103. Pappalardo, G., U. Wandinger, L. Mona, A. Hiebsch, I. Mattis, A. Amodeo, A. Ansmann, et al. 2010. “EARLINET Correlative Measurements for CALIPSO: First Intercomparison Results.” Journal of Geophysical Research 115: D00H19. doi:10.1029/2009JD012147. Ramachandran, S., and A. Jayaraman. 2003. “Balloon-Borne Study of the Upper Tropospheric and Stratospheric Aerosols over a Tropical Station in India.” Tellus 55B: 820–36. Rosenfel, D., U. Lohmann, G. B. Raga, C. D. O’dowd, M. Kulmala, S. Fuzzi, A. Reissell, and M. O. Andreae. 2008. “Flood or Drought: How Do Aerosols Affect Precipitation?.” Science 321: 1309–13. Satheesh, S. K., V. Vinoj, S. S. Babu, K. K. Moorthy, and S. V. Nair. 2009. “Vertical Distribution of Aerosols over the East Coast of India Inferred from Airborne LIDAR Measurements.” Annales Geophysicae 27: 4157–69. Satheesh, S. K., V. Vinoj, and K. K. Moorthy. 2006. “Vertical Distribution of Aerosols over an Urban Continental Site in India Inferred Using a Micro Pulse Lidar.” Journal of Geophysical Research 33: L20816. doi:10.1029/2006GL027729. Seifert, P., A. Ansmann, I. Mattis, U. Wandinger, M. Tesche, R. Engelmann, D. Müller, C. Pérez, and K. Haustein. 2010. “Saharan Dust and Heterogeneous Ice Formation: Eleven Years of cloud Observations at a Central European EARLINET Site.” Journal of Geophysical Research Letters 115: D20201. doi:10.1029/2009JD013222. Stephens, G. L, D. G. Vane, R. J. Boain, G. G. Mace, K. Sassen, Z. Wang, I. J. Illingworth, et al. 2002. “The CloudSat Mission and the A-TRAIN: A New Dimension to Space-Based Observations of Clouds and Precipitation.” Bulletin of American Meteorological Society 83: 1771–90. Stephens, G. L., G. D. Vane, S. Tanelli, E. Im, S. Durden, M. Rokey, and D. Reinke. 2008. “CloudSat Mission: Performance and Early Science after the First Year of Operation. 2008.” Journal of Geophysical Research 113: D00A18. doi:10.1029/2008JD009982. Tanelli, S., S. L. Durden, E. Im, K. S. Pak, D. G. Reinke, P. Partain, J. M. Haynes, and R. T. Marchand. 2008. “CloudSat’s Cloud Profiling Radar after 2 Years in Orbit: Performance, Calibration, and Processing.” IEEE Trans. Geosciences Remote Sensing 46: 3560–73.



373

Tripathi, S. N., S. Dey, V. Tare, S. K. Satheesh, S. Lal, and S. Venkataramani. 2005. “Enhanced Layer of Black Carbon in a North Indian Industrial City.” Geophysical Research Letters 32: L12802. doi:10.1029/2005GL022564. Twomey, S. 1974. “Pollution and the Planetary Albedo.” Atmospheric Environment 8: 1251–6. Wandinger, U., M. Tesche, P. Seifert, A. Ansmann, D. Müller, and D. Althausen. 2010. “Size Matters: Influence of Multiple Scattering on CALIPSO Light-Extinction Profiling in Desert Dust.” Geophysical Research Letters 37: L10801. doi:10.1029/2010GL042815. Winker, D. M., J. Pelon, and M. P. Mccormick. 2003. “The CALIPSO Mission: Spaceborne Lidar for Observation of Aerosols and Clouds, Status and Performance.” Proceedings of SPIE 4893: 1–11. Winker, D. M., M. A. Vaughan, A. H. Omar, Y. Hu, K. A. Powell, Z. Liu, W. H. Hunt, and S. A. Young. 2009. “Overview of the CALIPSO Mission and CALIOP Data Processing Algorithms.” Journal of Atmospheric and Oceanic Technology 26: 2310–2323. doi:10.1175/2009JTECHA1281.1. Wood, N. 2008. “Level 2B Radar-Visible Optical Depth Cloud Water Content (2B-CWC-RVOD).” Process Description Document, version 5.1.