IASTA-2010

B–P–17

Aerosol Radiative Forcing over Indian Region – A Study Using CERES, MISR and MODIS Data

Shailesh Kumar Kharol, M. Naresh Kumar, Anu Rani Sharma, Biswadip Gharai K.V.S. Badarinath, M. Y. Aslam

and M. Sivaprasad Reddy

Atmospheric Science Section, National Remote Sensing Centre,

Dept. of Space-Govt. of India, Balanagar, Hyderabad-500 625,India

*badrinath_kvs@nrsa.gov.in

Keywords : Radiative forcing, aerosols, aerosol optical depth, LW, SW

ABSTRACT : Observations of the earth from satellites are becoming fundamental for climate and environmental studies. Increasing attention has been paid to the effects of tropospheric aerosols on Earth’s overall radiation balance from last several years. Most of this attention has been focused on understanding how aerosols modify the solar radiation budget of the earth- atmosphere system. It is well known that aerosols exert important effects on climate, both directly through scattering and absorption of solar radiation, and indirectly by changing the cloud microphysical properties and influencing their formation. In fact, aerosol scattering and absorption can change the incoming flux of shortwave radiation besides modifying the net outgoing flux at the top of the atmosphere (TOA). In this context, the Clouds and the Earth’s Radiant Energy System (CERES), Multi-angle Imaging Spectroradiometer (MISR), and Moderate- resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra satellite make critical measurements of cloud and aerosol properties and their effects on the Earth’s radiation budget. In the present study, simultaneous and continuous observations are presented on the effect of aerosols on the radiative balance at the top of the atmosphere (TOA). The present analysis concerns with aerosol products (MISR and MODIS) and the shortwave (SW) reflected flux; the Longwave (LW) emitted flux and net flux at the Top of the Atmosphere (TOA) from CERES to estimate the aerosol direct effect over Indian region. We have also combined the strengths of three sensors from the same satellite to quantify the LW and SW forcing over the Indian region during different climatic conditions.

TOA forcing is especially responsive to the retrieved type and magnitude of the surface albedo, evidenced in both the model results and satellite retrievals. Smaller sensitivities relate to errors in aerosol optical depth, albedo spectral shape, vertical profiles of temperature and relative humidity, temperature inversions near the surface, and the altitude/thickness of the aerosol layer. Figure – 1 (a) shows the spatial distribution of monthly-mean MISR AOD575.5 for the month of April, 2006 over Indian region. We have selected three regions shown in rectangle boxes in Figure-1(a) covering North-western, North-eastern and Southern region of India where higher values of aerosol optical depth were observed. Figure – 1(b & c) shows the scatter plot of MISR derived Aerosol Optical Depth at 575.5 nm (AOD575.5) v/s CERES LW flux over north-western region of India for April, 2006 and 2007. It is clear from the figure – 1 (b & c) that as MISR AOD575.5 increases, the CERES LW flux decreases because dust aerosols emit at a colder temperature

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when compared to the surface (Zhang and Christopher, 2003). TOA forcing estimates from satellite observations were compared with radiative transfer model runs and results are discussed in the paper.

Figure 1. (a) Spatial distribution of MISR monthly mean AOD557.5 for April, 2006, (b & c) Scatter plot of MISR AOD557.5 v/s CERES LW flux over north-western region of India for the period of April, 2006 and 2007

References

Zhang, J. and Christopher, S. A., (2003). Longwave radiative forcing of Saharan dust aerosols estimated from MODIS, MISR and CERES observations on Terra. Geophysical Research Letters, 30 (23), 2188, doi:10.1029/ 2003GL018479.

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B–P–18

Temporal Variability of Aerosol Optical Depth over South India

T. Kiran Kumar1, Harish Gadhavi2, S. Vijaya Bhaskara Rao1,

and A. Jayaraman2

1S.V.University,Tirupati – 517502

2National Atmospheric Research Laboratory, Gadanki -517112

Introduction

Aerosols play a significant role in modulating the earth’s climate. They can scatter or absorb the incoming solar radiation and change the earth’s radiation budget at surface level and at top of the atmosphere. Aerosols can also change micro-physical properties and life-time of the clouds and hence affect the earth’s radiation balance through clouds. High aerosol concentration has adverse effect on human life and air quality. Residence time of aerosol in atmosphere varies from a few hours to couple years depending upon size of particles and altitude of occurrence. Aerosols in the stratosphere formed after major volcanic eruption can have longer residence time, whereas aerosol in the free troposphere has residence time of the order of one week. Understandably at the surface, their concentration is more near source and it decreases with distance from the source. Unlike green-house gases, aerosols are not well-mixed in the atmosphere. Hence, use of space-borne technique is important to get near simultaneous observations of aerosol properties over a large region. MODIS is one such instrument onboard satellite which provides observations of aerosol optical depth (AOD) over land. However, for other aerosol properties such as its chemical characterisation, scattering coefficient, absorption coefficient and size distribution we still have to rely on ground based observations. For such point observations, it becomes important to know their representativeness for the region. In other words, it is necessary to know up to what distance from a given place aerosols can be considered homogeneously mixed. In the present work we try to address this aspect using various statistical techniques on the daily MODIS AOD data available for the south Indian region (80 N to 180 N latitude and 740 E to 840 E longitudes).

Method

Aerosol optical depth (AOD) is a function of columnar aerosol amount and scattering and absorption efficiency. Whenever aerosol amount or their optical properties changes, values of AOD will change. Few of the causes for change in aerosol amount or their optical properties are change in wind direction, wind speed, relative humidity, source, source strength, plants flowering and land cover. Occasionally, volcanic eruption and sand storms will also cause change in AOD. Some sources do not have large seasonal cycle, for example use of biomass for cooking, vehicular emission, emission from factories etc., whereas sources such as wind blown dust particles, hygroscopic growth of particles

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and long-range transport of aerosols will be highly season dependent. When aerosols are from same source or subjected to similar atmospheric condition they will exhibit similar variability. Moderate Resolution Imaging Spectroradiometer (MODIS) is a key instrument aboard the TERRA and AQUA satellites. Terra’s orbit around the Earth is timed so that it passes from north to south across the equator in the morning, while Aqua passes south to north over the equator in the afternoon. Terra MODIS and Aqua MODIS are viewing the entire Earth’s surface every 1 to 2 days, acquiring data in 36 spectral bands, or groups of wavelengths . We have used level 2 aerosol data retrieved from MODIS/Terra Satellite for a period of 8 years that is from 2001 to 2008. The level 2 aerosol data products are retrieved with a resolution of 0.10 x 0.10 (approx. 10 km). Aerosol data are retrieved only

during cloud free sky conditions and hence for certain days AOD data may not be available. We have selected a region of study bounded between co-ordinates (80 N, 740 E) and (180 N, 840 E). The main location of our interest is Gadanki (13. 40 N, 72.40 E). We selected the region such that Gadanki is placed at the centre of the region of our study. We have divided the selected region into 625 grid boxes each of size 0.40 x 0.40. Spatial and temporal characteristics of aerosols over the region have been studied to find the spatial homogeneity and temporal variability.

A00

Figure 1. Temporal variation of aerosol optical depth over Gadanki, as observed by MODIS onboard Terra Satellite

Observations and Results

It is found that AOD over Gadanki is low during winter (Nov, Dec, Jan and Feb) and high during pre-monsoon months (Mar, Apr and May; Figure 1). During monsoon months available number of observations is less but they are closer to higher values. It is found that seasonal variation pattern is very robust. The annual mean AOD is nearly equal for all the years around 0.3. Auto regression has been applied to AOD over Gadanki for various intervals starting from one day to 720 days (Figure 2). The correlation coefficient decreases sharply for the first five days and then slowly for further increase in the interval.

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Increase in correlation coefficient at an interval of approx. 365 days is indicative of annual cycle in AOD values, which is accompanied negative correlation by exactly half the interval. In order to understand variability over the region, we calculated local coefficient of variation (LCV) for individual grid-boxes for length of 365 days. LCV is a standard deviation divided by mean. The high value of LCV indicate that at a given place aerosol variability is more compare to other locations and vice-versa.

Figure 2. Auto-regression coefficient of AOD over Gadanki

Figure 3. Local coefficient of variation (standard deviation divided by mean) over individual grid-boxes

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References

1.Chu, D. A., Y. J. Kaufman, C. Ichoku, L. A. Remer, and D. Tanre´ (2002),Validation of MODIS aerosol optical depth retrieval over land, Geophys.Res. Lett., 29(12), 8007, doi:10.1029/2001GL013205.

2.Remer, L. A., et al. (2005), The MODIS aerosol algorithm, products and validation, J. Atmos. Sci., 62, 947–973.

3.Kaufman, Y. J., D. Tanre´, and O. Boucher (2002), A satellite view ofaerosols in the climate system, Nature, 419, 215–223.

4.T. L. Anderson , Robert J. Charlson, David M. Winker,John A. Ogren and Kim Holme’n (2003), Mesoscale Variations of Tropospheric Aerosols, American Meteorological Society

5.Levy, R. C., Remer, L. A., & Dubovik, O. (2007). Global aerosol optical properties and application to Moderate Resolution Imaging Spectroradiometer aerosol retrieval over land. Imaging, 112, 1-15.

6.King, M. D., Kaufman, Y. J., Tanré, D., & Nakajima, T. (1995). Remote Sensing of Tropospheric Aerosols from Space: Past, Present, and Future.

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B–P–19

Effects of Atmospheric Aerosols on Broad Band Solar Flux Measurements over Delhi

Tarannum Bano, N.C.Gupta, Kirti Soni, R.S. Tanwar, S. Nath, and Sachchidanand Singh

Radio & Atmospheric Sciences Division,

National Physical Laboratory, New Delhi – 110012.

banot@nplindia.org

Introduction

Atmospheric aerosols influence the radiation budget directly by scattering and absorbing the solar radiation (Charlson et al., 1992) and indirectly by acting as cloud condensation nuclei (Rosefieldfield, 2000). As a result, the measurement of broadband (305-2800nm) solar radiation flux at the surface measured in terms of W/m2 gets affected. In the present study the simultaneous measurements of total (direct + diffuse) broadband flux measured at different solar zenith angle (SZA) and the aerosol optical depth have been used to estimate the observed forcing efficiency during clear sky conditions.

Methodology

The aerosol optical depths (AOD) were obtained by using hand-held portable pectrometer (MICROTOPS II, Solar Light Co. Inc., USA) operating at the central wavelengths 340, 500, 675, 870, and 1020nm .The global radiation flux was measured using the CM-21 pyranometer (Kipp and Zonen, Germany) for wavelength range 305- 2800 nm. The pyranometer measurements were used alongwith the AOD measured at 500nm to estimate the influence of reduction in flux due to aerosol, particularly at the SZA 40, 50 and 60 degrees. The advantage of choosing the fixed zenith angle is that the rays of the sun maintain a constant path length throughout the atmosphere on all the days of observation.This reduces the effect of variability in AOD due to the change of path in the atmosphere. The pyranometer flux and AOD measurements were done every half an hour since morning 10 AM to evening 4 PM and at the times when solar zenith angles were 40, 50 and 60 deg.

Results

Figure 1 shows the daily average aerosol optical depth at 500nm measured at Delhi during August 2007 to January 2009. The vertical lines denote the 1s standard deviations from the respective mean values. AOD is found to be minimum during the monsoon month of August (0.29±0.03 on 8th August 2007) and then increases gradually to reach maximum during November (01.48±0.15 on 7th Nov 2007). It starts decreasing afterwards till February, after which it again starts increasing to reach another maximum during the month of March 2008. The average AOD at 500nm observed during this period of

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observation for all the clear sky days (~148 days) was 0.76±0.29. The pyranometer measured flux in W/m2 at the SZA 40, 50 and 60 degrees were separated for all clear sky days along with the AOD measured simultaneously. Figure 2 shows the variation of total flux

Figure 1. Average aerosol optical depth at 500nm during August 2007 to January 2009

Figure 2. Variation of total solar flux (direct + diffuse) in the 305-2800nm with respect to the AOD at 500nm during clear sky days

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with AOD at 500nm at different SZA. It clearly shows that there is strong correlation between the measured flux and the AOD with flux decreasing with the increasing AOD values. The slope of the best fit between the flux and AOD gives an idea of the measured aerosol forcing efficiency at the surface.

The aerosol forcing efficiency thus measured shows the average change in total flux per unit change in AOD at 500nm. It may be noticed that the forcing efficiency decreases as the SZA increases. It is about 15 W/m2 at SZA 400, 12 W/m2 at SZA 500 and 9 W/ m2 at SZA 600.

References

Temporal heterogeneity in aerosol characteristics and the resulting radiative impact at a tropical coastal station- Part 1: Microphysical and optical properties.

K. Krishna Moorthy, S. Suresh babu and S.K. Satheesh. Ann. Geophys.,25,2293-2308 (2007). Influence of atmospheric aerosols on solar spectral irradiance in an urban area.

K.V.S. Badrinath, Shailesh Kumar Kharol, d.G. Kaskaoutis, H.D.Kambezidis. Journal of Atm ospheric and Solar- Terestrial Physics, 69, 589-599 (2007).

Climate forcing by anthropogenic aerosols.

Charlson, F.J., S.E. Schwartz, J.M. Hales,R.D.Cess, j.A. Coakley, J.E. Hansen,and D.J.Hoffman .Science, 255, 423- 430 (1992).

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B–P–20

Characterization of Spectral Aerosol Optical Depth Over Tropical Urban Site Hyderabad India

U. C. Dumka, P. R. Sinha, R. K. Manchanda, K Krishna Moorthy, S Suresh Babu and S. S. Sreenivasan

Tata Institute of Fundamental Research, National Balloon Facility, Hyderabad 500 062, India

Space Physics Laboratory, Vikram Sarabhai space Center Trivandrum, India

Introduction

Atmospheric aerosols affect the Earth’s atmosphere radiation budget by scattering and absorbing the incoming solar radiation (direct effect), by acting as cloud condensation nuclei (CCN), and altering the cloud microphysical properties (indirect effect). The direct and indirect effects of aerosols produce large uncertainty in the prediction of climate change [IPCC, 2007]. Aerosols originate both from natural and anthropogenic sources. Globally though the natural aerosols are dominated locally the scenario can be different. Aerosols in urban, semi urban and industrialized environments contain mostly the anthropogenic aerosols which are physically and chemically quite different from those in the remote regions. Under the favorable conditions aerosols of different population such as mineral dust could be advected from the distant source region to the observational site by the synoptic scale air mass movements and which produce the consequent signature on the columnar spectral aerosol optical depths. With this the scope of the present study is to analyze the results of multi-wavelength solar radiometer (MWR) measurements performed during January 2008 to May 2009 over the tropical urban site Hyderabad, India and allow characterizing the seasonal pattern of aerosol properties.

Experimental Details and Data Base

The experimental data consisted of spectral aerosol optical depths (AODs) estimated using a 10-channel Multi-Wavelength solar Radiometer (MWR). The MWR makes spectral extinction measurements of directly transmitted solar radiation at ten narrow wavelength bands (FWHM of 5 nm) centered at 380, 400, 450, 500, 600, 650, 750, 850, 935 and 1025 nm. The instrumental details, methods of analysis and error budget are described in earlier papers [Sagar et al., 2004; Gogoi et al., 2009]. The raw data obtained from the MWR are analyzed using the conventional Langley technique [Shaw et al., 1973] to deduce the columnar AOD (tp ). Estimates of AOD were made regularly on all clear/partly clear days as part of ISRO’s Geosphere Biosphere Programme and data during the periods from January 2008 to May 2009 are used in the present study.

Results and Discussions

Temporal Variation of AODs

Figure 1(a) shows the monthly variation of AODs at four representative wavelengths

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(400, 500, 750 and 1025 nm) for the period 24 months during December 2007 to May 2009. The vertical bars over the solid points are the standard error of the mean. The gap is due to the absence of MWR observation. Figure 1(a) reveals a significant monthly variation in AOD500, from ~0.25 to 0.6, with the lower values in the December and January period and higher in May-June. The large temporal variation in AOD is attributed due to the prevailing meteorology and air mass back trajectory.

FIGURE 1. (a) Monthly variation of AOD at Hyderabad at four representative wavelength (0.40, 0.50, 0.75 and 1.025 μm). (b) Spectral variations of monthly mean AOD at Hyderabad showing distinctive changes from months to months

Spectral Variation of AODs

The spectral variation of AODs is very important, as it is indicative of the changes in the aerosol size characteristics in the vertical column. Figure 1(b) shows the average picture of AOD over Hyderabad is shows as contour plot of monthly mean AOD values in a temporal spectral representation. In general the AOD values are higher at the shorter wavelengths decreasing to lower values at longer wavelengths. Beside the temporal changes Figure 1(b) clearly shows the wavelength dependency of AODs with months to months. The simplest and most common way to quantify the wavelength dependency of the AOD is by using Ångström equation [Ångström, 1961]

where a is the wavelengh exponent and is the Ångström coefficient. a and were computed for the individual AOD spectra, by evolving a least squares fit to above Equation in log-log scale. a, which is the slope of regression line, is commonly used to infer on the aerosol size distribution, being a measure of the relative dominance of fine sub micron size particle over the coarse mode aerosols, while (equal to AOD at =1 μm) is a measure of the aerosol loading and is more associated with the large particles. Higher values of a indicate an aerosol size spectrum with a relative dominance smaller aerosols. The average value of a, decreases systematically from January to June, indicating an increase in the relative dominance of coarse mode aerosols. On the other hand values were found to be maximum during May and June.

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Columnar Size Distribution

The columnar size distributions (CSDs) were retrieved from the AOD spectra following the constrained linear inversion technique [King et al., 1978; Saha and Moorthy, 2004]. For the present study, the AOD measurements at ten different wavelengths, ranging between 380 and 1025 nm are used for the retrieval of the CSDs. More details of the retrieval technique (such as selection of radius range, refractive index, Lagrange multiplier) are given in Saha and Moorthy [2004]. The representative plots of the CSDs are shown in Fig.2 (left) for winter month and Fig.2 (right) shows the log normal respectively. Figure 2(left) has 2 panels, the lower one representing the retrieved CSD and the upper one the measured AODs (points with error bars) and the AODs re-estimated from the CSDs (continuous line). It can be seen that, the basic nature of the CSDs remains the same during the study period. The retrieved CSD obtained from AODs, in general shows bimodal size distribution with a prominent secondary peak (coarse mode) occurring at large value of radius (~1 μm), while the primary (fine mode) occurring at radius ~ 0.2 μm. From the CSDs, the other characteristic physical parameters of aerosols such as power law index ( ) mode radii (rmi), width of the size distribution (smi) are evaluated. The details of the size distribution and details of the derived parameters are presented by Dumka et al., [2009].

Figure 2. Columnar size distribution

Conclusions

The seasonal variations in the aerosol optical depth and its spectral variation analysed used MWR during December 2007to May 2008 over Hyderabad were investigated. The aerosol properties exhibit large temporal variation which is attributed due to the prevailing meteorology and air mass back trajectory. The AOD shows a significant monthly variation with large values in May-June and lower values in during December- January.

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Acknowledgements

This work was carried out as a part of Indian Space Research Organization, Geosphere Biosphere Program (ISRO-GBP).

References

1.King, M.D., et al., J. Atmos. Sci., 35, 2153-2167, 1978.

2.Saha, A., and K.K. Moorthy, J. Appl. Meteorol., 43, 902-914, 2004.

3.Ångström, A., Tellus, 13, 214-223, 1961.

4.Gogoi, M. M. et al., J. Geophys. Res. 114D08202.

5.Shaw, G.E., et al., J. Appl. Meteorol., 12, 374-380, 1973.

6.Sagar, R., et al., J. Geophys. Res., 109, 10.1029/2003JD003954, 2004.

7.Intergovernmental Panel on Climate Change, Climate change-2007, (New York: Cambridge Univ. Press), 2007.

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B–P–21

A Study on Aerosol Scattering Coefficient using Nephelometer over Gadanki

V. Ravi kiran1, Harish Gadhavi1 and A. Jayaraman1

1National Atmospheric Research Laboratory, Gadanki- 517 112.

Introduction

Natural and anthropogenic aerosols have significant impact on regional and global climate. In order to study quantitatively the radiative effects of aerosol, one needs to know optical properties of aerosol such as scattering coefficients, single scattering albedo, aerosol optical depth etc. Aerosol scattering coefficient is defined as angular scattering cross-section of poly-disperse aerosol per unit volume expressed in inverse meter. Scattering coefficient depends on aerosol size distribution, number concentration and chemical composition. Here, we are presenting the seasonal behaviour of scattering coefficients observed over a rural site Gadanki (13.50N, 79.20E) in southern peninsular India.

Instrument and Methodology

Integrating nephelometer (TSI Model 3563) is used to measure scattering coefficients at three wavelengths 450,550,700 nm. Basic principle of Nephelometer is explained in Anderson et al., (1996) and Heintzenberg and Charlson (1996). Briefly, nephelometer consists of a sampling chamber, a flash lamp and detector assembly with filters. Air is drawn into sampling chamber with help of a pump and illuminated with the flash-lamp. The flash-lamp has a diffuser attached in front of it to distribute radiation evenly in the sampling chamber. However, detector geometry restricts collection of scattered photons only between 7 and 170 degree. Measurements of photons scattered from walls of chamber and air molecules are carried out separately using particle free air. Further, using appropriate calibration constants photon counts are converted into scattering coefficients. Scattering due to aerosols is obtained by subtracting the air molecule and background scattering from total scattering. Observations of scattering coefficients are carried out at interval of one minute. Data are quality checked manually along with status flags recorded by instruments, log-book and other ancillary information. In the current article we present analysis of ten months of data obtained between November 2008 and August 2009. We have calculated angstrom exponent by linear fitting the logarithm of scattering coefficients between 400 nm and 700 nm with logarithm of these wavelengths. In the present study we are reporting the seasonal variation of scattering coefficients at 550 nm, and the angstrom exponent.

We present statistics of scattering coefficient in the form of box-whisker plots. The box edges represent 25th and 75th percentile and whisker ends represent 5th and 95th percentile. Median is shown as a horizontal bar in the middle of box, whereas mean is shown with dot in red colour.

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B–P–22

DPMPL Evaluation of Boundary-Layer Aerosol and Cloud

Structures

Y. Jaya Rao, P. C. S. Devara and M. G. Manoj

Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pune 411 008, India

Introduction

Lidar, an active remote sensing device, plays important role in understanding the characteristics of aerosols and clouds and their interaction with climate because of its capability to make continuous measurements of different aerosols and cloud parameters on near-continuous basis with better height and time resolutions. Polarization lidar provides additional information but most important parameter, namely, depolarization ratio that determines the phase of the cloud as well as isotropic/anisotropic nature of aerosol particles. In the present study, we have carried out experiments using a state-of-the-art Dual Polarization Micro Pulse Lidar (DPMPL) at IITM, Pune, India to study the characteristics of clouds associated with monsoon. Detailed description of the DPMPL system; and preliminary results have been published by Devara et al. (2008).

Experiment, Data and Analysis

The DPMPL is an eye-safe versatile system that utilizes diode pumped solid state Nd:YAG laser second harmonic (532 nm) with switching between parallel and perpendicular polarization as transmitter and a Schmidt–Cassegrain telescope, with a high-speed detection and data acquisition and processing system, as receiver. This online system in real-time mode provides backscatter intensity profiles up to upper atmospheric altitudes at height resolution up to 30 cm and time resolution less than a minute in both parallel and perpendicular polarization channels, corresponding to each state of polarization of the transmitted laser radiation.

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interval of one minute. Each profile is then subjected to range and noise corrections. Simultaneous measurements of surface meteorological parameters have also been carried out to understand the association between meteorological parameters and clouds.

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Devara, P.C.S., P.E. Raj, K.K. Dani, G. Pandithurai, M.C.R. Kalapureddy, S.M. Sonbawne, Y. Jaya Rao and S.K. Saha, 2008: Mobile lidar profiling of tropical aerosols and clouds. Journal of Atmospheric and Oceanic Technology, AMS, USA, 25, 1288-1295.

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B–P–23

Lidar Observations of The Descending Nature of Tropical

Cirrus Clouds

Anish Kumar M. Nair*, Bijoy V. Thampi, Manoj Kumar Mishra, S. Meenu, K. Rajeev and K.Parameswaran

Space Physics Laboratory,Vikram Sarabhai Space Centre, Thiruvananthapuram 695022

*E-Mail: akmnair@gmail.com

Introduction

Cirrus clouds play a pivotal role in the moisture and energy budget of the upper troposphere and lower stratosphere (UTLS) region and can influence the thermal structure of the tropical tropopause layer (TTL) (Jensen et al., 1996). Occurrence of clouds in the upper troposphere is one of the main processes responsible for the dehydration in this altitude band. Thus, the cirrus clouds can modulate the stratosphere-troposphere exchange of water vapour and the chemical reactions in the UTLS region. Cirrus clouds originating from the insitu generation processes or deep convective outflows constitute the largest fraction of the upper tropospheric clouds. Globally, the Indian subcontinent, Bay of Bengal, and Tropical Indian Ocean are among those regions having largest frequency of occurrence of cirrus clouds. A significant fraction of them is optically and physically thin. However, the horizontal extent and life time of cirrus are appreciably larger than that of the other cloud types.

Regular long-duration observations carried out using a ground-based dual polarization Micropulse Lidar (MPL) have revealed the frequent occurrence of descending cirrus clouds over Thiruvananthapuram (8.5°N, 77°E) throughout the year. This important aspect of cirrus clouds is not extensively investigated so far. Descending cirrus clouds can lead to removal of moisture from the upper troposphere, which can have considerable influence on the water vapour budget of the Tropical Tropopause Layer.

Experimental Setup and Data Analysis

High resolution dual-polarization Micropulse Lidar (MPL) observations have the potential to discriminate even the ultra thin cirrus clouds occurring in the upper troposphere. Systematic observations carried out using MPL at Thiruvananthapuram during the period of March 2008 – July 2009 are used in this study to characterize the cirrus clouds and their descending nature. MPL has a diode-pumped solid state Nd:YAG laser emitting laser pulses at the wavelength of 532 nm with a pulse width of 7 ns and PRF of 2500 Hz. Maximum pulse energy is 8 J. A Maksutov-Cassegrain type telescope having diameter of 178 mm and field of view of 96 rad is used for transmitting the laser beam and receiving the backscattered radiation. Two identical interference filters are used to limit the background to a minimum, making the MPL suitable for daytime operation. The detector is a Silicon Avalanche Photodiode (Si-APD) operated in photon counting mode. The observations are made with a range resolution of 30m and time integration of 60 seconds.

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The lidar system alternates between the co-polarization and depolarization mode at an interval of 60 seconds. Cirrus clouds contain highly non-spherical ice crystals and are best discriminated in the depolarized component of the lidar signal.

Results

Figure 1 shows the time-altitude variations of the range-compensated attenuated lidar backscattered signal (cross-polarized component) during 29 March and 17 April 2008 as typical examples. Significant descending of cirrus clouds are manifested in Fig.1, which appear as downward slanting structures in the time-altitude cross sections of the attenuated backscattered signal, lasting for few hours and descending for ~2-4 kilometres. Several such descending clouds are observed on a single day. Most of these clouds are semitransparent and hence their top altitudes are clearly identifiable. Stable layers of cirrus clouds are sometimes observed within few kilometres above and below the descending cirrus clouds, which rules out the possibility of a pronounced downdraft in the upper troposphere as the mechanism responsible for the descending of cirrus in such cases.

Figure 1. Time-height variations of the range-compensated attenuated lidar backscattered signal (cross- polarized component) during 29 March (top) and 17 April 2008 (bottom). Time is represented as the fraction of the day. The white space represents the time when the MPL was not operational

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The monthly mean frequency of occurrence of descending cirrus clouds (Fdes) during March 2008 to May 2009 is depicted in Fig.2(a), which shows that Fdes varies over a wide of ~5 to ~55% with a mean value of ~20%, which is a significant portion of the total amount of cirrus occurring in this region. The values of Fdes do not show any discernible seasonal variation. Histogram of the duration of descending shows a skewed symmetric distribution with peak at 1.5 hours and median at 2.5 hours. About 40% of such clouds have duration of descending >3 hours. Stable layers of cirrus clouds are often observed at ~3-5 km above or below the descending cirrus. Figure 2(b) shows the frequency distribution of cloud top altitude before and after descending, which indicates that the top altitude of cirrus typically descends from ~14.5 km to ~11 km. Importantly, this altitude region corresponds to the lower boundary of the tropical tropopause layer observed over Thiruvananthapuram. The geometric centres of the majority of such clouds descend by ~1-3.5 km within around 1-4 hours, and have a typical descend rate of 0.3 to 1.8 km/hr.

Figure 2. (a) Monthly mean frequency of occurrence of descending cirrus clouds, and (b) Frequency distribution of cloud top altitude before and after descending

The long-duration of descending and the occurrence of stable cirrus layers within few kilometres above and below the descending cirrus indicate that the source mechanism responsible for the generation of these clouds cannot be completely attributed to the processes such as physical nature of the clouds (e.g., cirrus uncinus), atmospheric waves, downdraft, and gravitational sinking. Note that the cirrus uncinus have relatively short duration and small horizontal scale, and may not last for several hours or descend for few kilometres. The presence of stable cirrus layers within a few kilometres below and above the descending cirrus rules out the possibility of persistent downdraft, gravitational sinking or atmospheric waves as the mechanisms responsible for the descending of such cirrus clouds. Remarkably, the descending of cirrus is highly frequent in the 10-14 km altitude band, which nearly coincides with the lower boundary of the TTL over Thiruvananthapuram. This indicates that the dynamics associated with the Tropical Tropopause Layer might be significant in the occurrence of descending cirrus clouds.

Conclusions

Long-period Micropulse lidar observations of cirrus clouds reveal the descending nature of the tropical cirrus clouds. This aspect is not extensively reported in the literature. On

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average, the descending cirrus clouds are observed around 5-55% of the total number of days of observation and do not show any pronounced seasonal variation. Histogram of the duration of descending shows a skewed symmetric distribution with peak at 1.5 hours and median at 2.5 hours. About 40% of such clouds have duration of descending >3 hours. On average, the top altitude of cirrus typically descends from ~14.5 km to ~11 km and the descending is almost insignificant outside this band. This altitude region is the lower boundary of the tropical tropopause layer. The observed characteristics of the descending cirrus clouds cannot be completely explained on the basis of the processes such as physical nature of the clouds, atmospheric waves, downdraft, and gravitational sinking. The altitude band over which most of these clouds occur and the long duration of descending indicate that the dynamics associated with the Tropical Tropopause Layer might be a prominent mechanism for the descending of cirrus clouds. Such descending clouds can remove water vapour from the TTL layer and will have considerable influence on the water vapour budget and dehydration of the UTLS region.

References

Jensen, E.J., Toon, O.B., Selkirk, H.B., Spinhirne, J.D., Schoeberl, M.R., 1996. On the formation and persistance of subvisual cirrus clouds near the tropical tropopause. J.Geophys. Res. 101, 21361-21375.

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B–P–24

Satellite Observed Aerosols over Indian Region and Monsoon Rainfall Variability and Trend in High Cloud

S.S. Dugam

Indian Institute of Tropical Meteorology, Pune-4110008

Email<dugam@tropmet.res.in>

ABSTRACT : In this paper to see the effect of aerosols concentration on rainfall activity over Indian region the monthly aerosols data over Indian region (5°N to 40°N and 50°E -100°E) have been analyzed from 1981 to 2008. The trend analysis has been carried out and it is found that in recent period there is decreasing trend in aerosols concentrations. Similar analysis have been carried out for West central India North East India, Peninsular India monsoon, rainfall (June- September) departure , even though the aerosols concentrations decreasing over Indian region it is observed that there is decreasing trend in rainfall activity during summer monsoon period which is contradiction to above observation. Probable reason may that the less aerosols concentrations may provide the lesser cloud condensation nuclei for the formation of rain producing clouds. Trend analysis of high cloud cluster in contrasting monsoon is also study. It is also seen that increasing temperature at mid-troposphere and 500 h Pa temperature anomalies and cloud cluster shows a positive association for same period.

Introduction

Human activities are releasing small particles called as aerosols into the atmosphere. These man-made aerosols enhance scattering and absorption of solar radiation. They also produce brighter clouds that are less efficient at releasing precipitation. These in turn lead to large reductions in the amount of solar irradiance reaching Earth’s surface, a corresponding increase in solar heating of the atmosphere, changes in the atmospheric temperature structure, suppression of rainfall. These aerosol effects can lead to a weaker hydrological cycle, which connects directly to availability and quality of fresh water, a major environmental issue of the 21st century

Data and Methodology

From, the daily grid point aerosols data and high cloud cluster data over Indian region (5°N to 40°N and 50°E -100°E); for period 1980-2005 taken from TOMS (NASA) , monthly series are prepared. The rainfall data for same period is taken from I.I.T.M. web side. The trend analysis has been carried out for these parameters.

Discussion

To see, the effect of aerosol concentration over India region on monsoon rainfall over different homogeneous regions, the time series aerosol concentration for monsoon season. (June-September) have been prepared and used for the analysis. The trend analysis has been carried out of aerosol concentration anomalies series and rainfall departure over different homogenous regions. It is found that during the monsoon season in recent

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period aerosol concentration shows decreasing trend and similar trend is observed in rainfall over the West central India. The trend analysis of cloud cluster over the Indian region is also computed. Shown in figure 2.

Conclusions

It is found that in recent period there is decreasing trend in aerosols concentration over Indian region during the monsoon period. It is also observed that there is decreasing trend in west central monsoon rainfall (June- September) departure rainfall activity during summer monsoon period it is also seen that high cloud cluster over Indian region shows an increasing trend and same time temperature at mid-troposphere and 500 h Pa temperature anomalies increases.

Probable reason may that the less aerosols concentrations may provide the lesser cloud condensation nuclei for the formation of rain producing clouds.

Figure 1. (a) monsoon rainfall percentage departure for West central Indian region. (b) Average aerosol concentration for monsoon period (1980-2000)

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Figure 2. High cloud cluster over Indian Region for period 1980-2002

Acknowledgment

The authors are grateful to Prof. B.N. Goswami Director, I.I.T.M. for providing necessary facilities for completing this study and to Dr. P. N. Mahajan the Head, Forecasting Research Division for his encouragement and valuable suggestions and the Goddard Institute for Space Studies New York, (NASA) for providing the global surface temperature data.

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B–P–25

Variations of Total Column Ozone in Tropical and

Subtropical Regions

G. S. Meena and S. D. Patil

Indian Institute of Tropical Meteorology, Pune-411 008

E-mail: gsm@tropmet.res.in

Introduction

Decreasing trends in stratospheric ozone are observed at Polar regions, which are extending towards equatorial side (WMO 1992). Both, space and ground-based measurements indicate that ozone is decreasing in the tropical and subtropical latitudes also (Chandra and Varotsos 1995). The distributions and trends of atmospheric ozone are important that affect the climate system in several ways. Decreasing trends of total ozone with large magnitudes have also been found in the northern Indian region as compared to other parts of India for the period 1978–1993 (Chakraborty et al. 1998). Meena and Jadhav (2007) have observed diurnal and seasonal variations of TCO and other trace gases over tropical station Pune (18.51ºN, 73.91ºE). The TCO distributions over the tropics are influenced by Quasi-Biennial Oscillation (QBO). The QBO is a quasi-periodic oscillation of the equatorial zonal wind between easterlies and westerlies in the lower stratosphere within period of 28 to 29 months. In the tropical region, the upward transport Kelvin wave and the mixing Rossby wave produce under certain conditions are the causes of QBO (Holton and Lindzen 1972). Thus the QBO plays a dominant role in the inter-annual variability of tropical lower stratospheric temperature, which is directly linked with ozone concentration and distribution (WMO 1998).

Worden et al. (2009) have noticed that the summer time circulations associated with the Asian monsoon are significantly influences the distribution of ozone and its precursors. The formation of an elongated zone of low pressure along the Indo-Gangetic plains over north India during southwest monsoon season is commonly known as ‘monsoon trough’. The axis of the monsoon trough is roughly oriented from the northwest to the southeast. In the monsoon trough area, the monsoon circulation during the peak monsoon months (July and August) is normally well established. As an example, appearance of tropical easterly jet stream, lowest outgoing long wave radiation (deep convection), strong vertical wind shear and highest rain fall activities are playing an important role in the monsoon trough area. Hence, this paper describes the variations of TCO on different time scales (i.e. monthly and yearly) and their trends during 2000–2008 measured from ground-based Dobson and Brewer spectrophotometer as well as satellite-based SCIAMACHY for three Indian stations, i.e. New Delhi (28.65ºN, 77.217ºE) and Varanasi (25.32ºN, 83.03ºE) (subtropical station), which are lying inside the monsoon trough region in northern part of the country and a tropical station Kodaikanal (10.23ºN, 77.46ºE), which is outside the monsoon trough.

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Data and Analysis

Ground-based Dobson spectrophotometers operated during January 2000–December 2008 at subtropical stations New Delhi and Varanasi. The Brewer spectrophotometer data were made between September 2002 and November 2005 at tropical station Kodaikanal. Satellite-based SCIAMACHY data based on Weighting Function Differential Optical Absorption Spectroscopy (WFDOAS) algorithm were available on the site http:// www.iup.uni-bremen.de/gome/wfdoas/ from August 2002 to December 2008 for New Delhi, Varanasi and Kodaikanal. These data are used in the present study to see their variation on different time scales and trend analysis over the monsoon trough region over north India. Using daily TCO data, we have calculated the monthly mean values of TCO for the study. SCIAMACHY is taking observations onboard ENVISAT satellite platform, which was launched in March 2002 (Bovensmann et al. 1999). SCIAMACHY measures the back scattered and reflected electromagnetic radiation from the atmosphere. SCIAMACHY comprises eight spectral channels between 240 and 2380 nm from which total ozone is retrieved between 325 and 335 nm at a spectral resolution of about 0.2 nm. SCIAMACHY level-1 data are compared with Brewer and Dobson measurements for New Delhi, Varanasi and Kodaikanal.

WFDOAS algorithm introduces several new features that have not been used in prior total ozone retrieved from GOME such as Raman scattering responsible for the filling-in of molecular absorption and a new cloud scheme with estimation of effective scene albedo.

Results and discussion

The TCO variations over New Delhi and Varanasi (subtropical stations) where the monsoon trough exists whereas Kodaikanal (a tropical station) is outside the trough region are to be discussed. Figure 1 shows the annual variation and trend analysis of monthly mean TCO, which are derived using ground-based Dobson spectrophotometer (January 2000–December 2008) and satellite-based SCIAMACHY daily data (August 2002–

Figure 1. Annual variation and linear trends of TCO (DU) derived using ground-based Dobson spectrophotometer and satellite-based SCIAMACHY data

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December 2008). The Brewer spectrophotometer data (September 2000–November 2005) are used for Kodaikanal because Dobson has changed to Brewer for this station.

The Dobson, Brewer and SCIAMACHY TCO show the negative trends (decreasing tendency) for New Delhi, Varanasi and Kodaikanal. Here, linear regression model is used for trends analysis. More decreasing trend is observed over Varanasi.

Figure 2 shows the monthly mean variations of TCO, for New Delhi, Varanasi and Kodaikanal. The differences between SCIAMACHY and Dobson TCO are observed to be 0.4–4.2% for New Delhi and 2.3–6.2% for Varanasi. The differences between SCIAMACHY and Brewer TCO are observed to be 2–6.4% for Kodaikanal. Lower values of TCO are observed in winter months (December, January and February) whereas higher values are observed in spring (March, April and May) and summer (June, July, August and September). Interestingly, during peak monsoon months (July and August), the TCO values are found to be lower in August over New Delhi and in July over Varanasi for both Dobson and SCIAMACHY. The TCO values are found to be high during peak monsoon months over Kodaikanal (tropical station) whereas it is low over New Delhi and Varanasi (stations lying inside the monsoon trough region). In this connection the TCO over Kodaikanal are found to be lower in the beginning of summer-monsoon (June) whereas over New Delhi and Varanasi the TCO values are found to be higher in the month of June. The decreases in the TCO values during peak monsoon months over New Delhi and Varanasi may be due to the deep convection present in the monsoon season where the several characteristic meteorological features are associated. During the monsoon season, several intense cyclonic systems appear over the monsoon trough region may cause lowering of TCO.

Figure 2. Monthly variation of TCO (DU) derived using ground-based Dobson spectrophotometer (2000–2008) and satellite-based SCIAMACHY data (2002–2008)

The mean distribution of the global total ozone, having a minimum in the equatorial belt and increasing poleward, is well established. In this context, the TCO values over New Delhi are observed to be higher compared to Varanasi and Kodaikanal. The TCO values over Varanasi are found to be higher than Kodaikanal.

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Conclusions

The Dobson, Brewer and SCIAMACHY TCO show the negative trends indicating decreasing tendency over New Delhi, Varanasi and Kodaikanal. More decreasing trend is observed over Varanasi by about 3 DU/year. The comparisons have been made between ground-based Dobson and Brewer spectrophotometer, and SCIAMACHY satellite monthly means TCO. The differences between SCIAMACHY and Dobson TCO are observed to be 0.4–4.2% for New Delhi and 2.3–6.2% for Varanasi. The differences between SCIAMACHY and Brewer TCO are observed to be 2–6.4% for Kodaikanal. Lower values of TCO are observed in winter months whereas higher values are observed in spring and summer. The decreases in the TCO values during peak monsoon months (July and August) over New Delhi and Varanasi (monsoon trough region) may be due to the deep convection present in the monsoon season where the several characteristic meteorological features are associated. During the monsoon season, several intense cyclonic systems appear over the monsoon trough region may cause lowering of TCO. Kodaikanal shows opposite features, i.e. high values are observed during peak monsoon months. Increase/decrease in the level of tropopause height may also be cause of decrease/increase the TCO.

Acknowledgements

The authors are grateful to Prof. B. N. Goswami, Director, Indian Institute of Tropical Meteorology (IITM) Pune, and Dr. P.C.S. Devara, Head of PM&A division for providing the facilities and continuous encouragement during the course of the study.

References

Bovensmann, H., Burrows, J.P., Buchwitz, M., Frerick, J., Noel, S., Rozanov, V.V., Chance, K.V. and Goede, A.H.P., 1999, SCIAMACHY – Mission Objectives and Measurement Modes. Journal of Atmospheric Science, 56, pp. 125–150.

Chakraborty, D.K., Peshin, S.K., Pandya, K.V. and Shah, N.C., 1998, Long-term trend of ozone column over the Indian region. Journal of Geophysical Research, 103, pp. 19245–19251.

Chandra, S. and Varotsos, C.A., 1995, Recent trends of the total column ozone: implications for the Mediterranean region. International Journal of Remote Sensing, 16, pp. 1765–1769.

Holton, J.R. and Lindzen, R.S., 1972, An update theory for quasi-biennial oscillation of the tropical stratosphere.

Journal of Atmospheric Science, 29, pp. 1076-1080.

Meena, G.S. and Jadhav, D.B., 2007, Study of diurnal and seasonal variation of atmospheric NO2, O3, H2O and O4 at Pune, India. Atmosfera, 20, pp. 271–287.

WMO, 1992, International Ozone Assessment: 1991. World Meteorological Organization, Global Ozone and Monitoring Network Report 22 (Washington, DC: WMO).

WMO, 1998, Scientific Assessment of Ozone Depletion: 1998. World Meteorological Organization, Geneva, 1999. Global Ozone Research and Monitoring Project - Report No. 44.

Worden, J., Jones, B.A., Liu, J., Parrington, M., Bowman, K., Stajner, I., Beer, R., Jiang, J., Thouret, V., Kulawik, S., Li, F., Verma, S. and Worden, H., 2009, Observed vertical distribution of tropospheric ozone during the Asian summertime monsoon. Journal of Geophysical Research, 114, Doi: 10.1029/2008 JD010560.

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