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B–P–4

Impact of Diurnal Cycle in the Short Wave Radiative Flux in the Thermocline Ridge Region of Southern Tropical Indian Ocean

A.Jayakumar, C.Gnanaseelan and S. Rahul

Indian Institute of Tropical Meteorology, Pune-411008

Abstract : The thermocline ridge region of the Indian Ocean (TRIO, 5oS-10oS, 55o-85oE) shows a marked variability at diurnal time scale. The VASCO-Cirene cruise program in this region during January-February 2007 observed layers of dry air over the troposphere and the diurnal warm layer affects the upper ocean heat budget and atmospheric deep convection. So the diurnal cycle in the radiative flux have significant impact on the biological and regional climate of this region.

To quantify the impact of diurnal cycle in the TRIO region we have designed a sensitivity experiment along with the usual daily average flux forcing in the general circulation model. In the experiments we used “fixed heat flux” to exclude the atmospheric feedback to quantify the impact of Short wave flux in the ocean surface layer. The inclusion of the diurnal cycle in the model will help us to better understand the processes associated with Madden Julian Oscillation (MJO) associated variability in this region as the short wave flux dominated in the total flux change.

Introduction

Thermocline ridge of the Indian Ocean (TRIO, 5S-10S, 55E-85E) is the breeding center of the generation of Madden Julian oscillation (MJO) over the tropical Indian Ocean (Izumo et al, 2009). There are large observational (Harrison and Vecchi, 2001, Vialard et al., 2008) and modeling studies (Loydd and Vecchi 2009, Jayakumar and Gnanaseelan, 2009) shown that large intraseasonal variation of sea surface temperature in the TRIO region associated with the passage of the atmospheric MJO. There was large discrepancy about the respective roles of air-sea heat flux (Harrison and Vecchi, 2001, Saji et al., 2006, Vialard et al., 2008) and oceanic processes (Vinayachandran and Saji 2008) for last few decades about the mechanism associated regarding MJO associated SST. Jayakumar et al., 2010 using an ocean model recently demonstrated that there was non-linear combination of the surface flux and wind stress where flux contribute twice as much as effects. Experiments also shown that the flux have twice as effect of wind stress with short wave flux having dominant role. So the flux associated with the MJO significantly estimates the SST response in the TRIO region.

Schiller and Godfrey, 2003 confirmed using their model studies that the diurnal cycle of solar short wave forcing significantly increases the amplitude of the SST over that produced by daily mean insolation over the tropical Indian Ocean. Diurnal modulated SST results diurnal warm layer (DWL) which favors the eastward propagation of cloudy

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phase of MJO in the tropical Indian ocean during boreal winter (Bellenger and Duvel, 2009). Vialard et al., 2009 observed a strong SST diurnal cycle developed during the suppressed phase of MJO in the TRIO on the basis of mooring datas. So this region is having a shallow thermocline and mixed layer which may have a strong effect of the diurnal cycle over the intraseasonal SST. Also previous manuscripts showed that taking the diurnal cycle into account could improve forecasts of the MJO (Woolnough et al. 2007).

In this study we investigate, in particular the designed modeling method to quantify the diurnal cycle effects on the amplitude of oceanic response to the MJO over the TRIO region. The paper is organized as follows. In Sect. 2, a description of the Model and sensitivity experiments and the analyzed observational data sets are provided. Section 3 describes the major results in the study.

Data and Modelling approach

Data sets

We have used Level 3 TRMM Microwave Imager (TMI) SST from ww.ssmi.com, and vector surface winds from the SeaWinds scatterometer on the QuikSCAT satellite to study the surface signature of MJO. The daily anomalies of are prepared based on the 1996-2006 climatology. To isolate the signal associated with the MJO, we have used 30-120 day band-pass filtering of daily anomalies with respect to the mean seasonal cycle. This is similar to the approach followed by Han et al. (2007) (105 day cutoff) or Saji et al. (2006) (200 days cutoff).

Modelling approach

The OGCM used in the present study is the latest version Geophysical Fluid Dynamics Laboratory (GFDL) Modular Ocean Model (MOM4) and is set up for the region between 40oS-25oN and 30oE-120oE with 30 vertical levels. The upper ocean mixed layer and thermocline zones are well resolved in the model with 15 vertical levels within a depth of 155 meters. The model has a realistic topography, which is derived from the 5-minute global topography ETOPO5 (Earth Topography-5 minute) database. The model has a zonal resolution of 1o and meridional resolution varying from 0.3353o at equator to 0.7o at 25oN and 1.5o at 40o s. Vertical mixing is based on the K Profile Parameterization (KPP) scheme (Large et. al. 1994) which have significant impact on the diurnal coupling. The model description in detail is given in Thompson et al. (2006). The model is forced by NCAR corrected (Large and Yeager, 2004) wind fields, downward short wave and long wave radiation, air temperature, specific humidity and precipitation from January 1, 1996 to December 31, 2006. This complete solution is considered as the Control Run (CTL).

To quantify the impact of diurnal cycle in the TRIO region we have designed a sensitivity experiment fixed heat flux in non-solar part of flux to exclude the atmospheric feedback and to quantify the impact of short wave in the ocean surface layer. This experiment is termed as “Diurnal_fix” where the diurnal cycle of the shortwave added where rest of the forcing keeping same as CTL. To include the atmospheric feedback, we designed experiment “Diurnal_relax” same as “Diurnal_fix” except relax heat flux in the non-solar part.

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Figure 1. Sample of Diurnal cycles in the Mean SWF over the TRIO region

Results

The intraseasonal heat flux perturbations over the TRIO region are generally due in equal parts to short wave and latent heat flux perturbation (Jayakumar et al., 2010). The short wave penetration into the upper ocean has long effect in terms of SST response. So

Figure 2. Standard deviation (SD) of intraseasonal SST for the following experiments over TRIO region are a) Diurnal_relax b) Diurnal_fix c) CTL for DJF period. The box indicate the TRIO region used in this study

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we converted daily short wave flux (SWF) in to the energy conserving diurnal cycle by applying sinusoidal wave on daily mean SWF similar approach as Schiller and Godfrey, 2003. Figure1 shows the representative sample of diurnal cycle of flux in the TRIO region with daily averaged SWF. The sinusoidal wave resemble to the observed hourly SWF in the TRIO region.

The Standard Deviation (SD) of intraseasonal SST for the DJF period for CTL, Diurnal_fix and Diurnal_relax (Figure 2) shows the rectification of Diurnal cycle associated with MJO associated SST. Significant reduction and change in the amplitude of the intraseasonal variability in the sensitivity experiment with the CTL shows the in the interaction of diurnal cycle with the mixed layer variability. The maximum amplitude of the variability in the intraseasonal SST variability for the DJF period in the CTL went up to 0.45, where as the corresponding value for Diurnal_fix and Diurnal_relax are 0.37 and 0.31 respectively. The Diurnal_fix SST response shows that the diurnal cycle have non- linear response in the TRIO region which reduce the ~18% in the total intraseasonal SST variability. Similarly atmospheric feedback which damp the intraseasonal SST about 30% which can be infered from the Diurnal_relax. This may due to the diurnal rectification mechanism is influenced by air–sea coupled feedbacks.

Reference

Bellenger H. and J. P. Duvel, 2009: An analysis of ocean diurnal warm layers over tropical oceans, J. Climate, 22, pp. 3629-3646.

Jayakumar , A and C.Gnanaseelan, 2009,Study of intraseseasonal events in the thermocline ridge region of Southern tropical Indian Ocean during 2002 and its impacts, Dynamics of Atmospheres and Oceans, submitted.

Jayakumar, A., J. Vialard, M. Lengaigne, C. Gnanaseelan, J. P. McCreary and Praveen Kumar, 2010, Processes controlling the surface temperature signature of the Madden-Julian Oscillation in the thermocline ridge of the Indian Ocean, climate dynamics submitted.

Large WG, McWilliams JC, Doney SC (1994) Oceanic vertical mixing: A review and a model with a no local boundary layer parametrization, Rev. of Geophys, 32, 363-403.

Saji NH, Xie SP, Tam CY (2006) Satellite observations of intense intra-seasonal cooling events in the tropical south Indian Ocean. Geophys. Res. Lett. 33: L14704, doi: 10.1029/2006GL026525

Schiller A., and J. S. Godfrey, 2003: Indian Ocean intraseasonal variability in an ocean general circulation model. J. Climate, 16, 21–39.

Vialard J, Foltz G, McPhaden M, Duvel JP and de Boyer Montégut C (2008 a) Strong Indian Ocean cooling associated with the Madden-Julian Oscillation in late 2007 and early 2008. Geophys. Res. Lett. 35:L19608.doi:10.1029/2008GL035238

Vialard J and Coauthors (2009) Cirene: Air Sea Interactions in the Seychelles-Chagos thermocline ridge region. Bull. Am. Met. Soc. 90: 45- 61

Vecchi GA and Harrison DE, 2004: Interannual Indian rainfall variability and Indian Ocean Sea surface temperature anomalies. In Earth Climate: The Ocean-Atmosphere Interaction, C. Wang, S.-P. Xie, and J.A. Carton (eds.), American Geophysical Union, Geophysical Monograph 147, Washington D.C., 247- 260.

Vinayachandran PN and Saji NH (2008) Mechanisms of South Indian Ocean intra-seasonal cooling. Geophys Res Lett 35: L23607. doi:10.1029/2008GL035733

Woolnough, S. J., F. Vitart and M. A. Balmaseda, 2007: The role of the ocean in the Madden- Julian Oscillation: Implications for MJO prediction. Q. J. R. Meteorol. Soc., 133, 618 622, 117-128.

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B–P–5

A Comparative Study of MODIS Derived Aerosol Optical Depth from two Consecutive Versions

Amit Misra1*, A Jayaraman2 and Dilip Ganguly3

1 Physical Research Laboratory, Ahmedabad, India

2 National Atmospheric Research Laboratory, Gadanki, India

3 Geophysical Fluid Dynamics Laboratory, Princeton, USA

*amisra@prl.res.in

Aerosols are important in the studies related to the Earth Atmosphere system due to their effect on climate. Their role is identified as direct effect through the scattering and absorption of solar radiation and indirect effect through their effect on cloud formation. In view of the important role played by aerosols, accurate quantification of their amount and properties is needed on a global scale. Ground based observations have limitations due to their being point measurements. Satellites provide means of routine unmonitored remote sensing of atmospheric constituents. The large satellite swath makes it possible to provide information over a large geographical area. The Moderate Resolution Imaging Spectroradiometer (MODIS), launched aboard NASA satellites Terra and Aqua in 1999 and 2002, is one of the sensors providing aerosol optical depth information over the globe. It follows different procedures to retrieve the aerosol information over land and ocean. The retrieved AOD values are validated by ground based sunphotometer over different geographical regions and under different environments. Based on such comparison, the retrieval algorithms are modified to come up with more accurate aerosol product. The initial MODIS aerosol product, C004, was retrieved by the dark target approach which depends on the constant ratios between surface reflectance at mid-infrared and visible wavelengths. It was updated to the version C005 which considers the angular and seasonal variations of surface reflectance ratios at visible and mid-infrared wavelengths, includes polarization in the radiative transfer calculation and incorporates the AERONET database for the aerosol models. Deep Blue algorithm is an alternative procedure for aerosol optical depth retrieval over surfaces with high surface reflectance where the conventional procedure has limited accuracy. Validation of C005 aerosol product over Ahmedabad shows considerable improvement over the C004 product. However, differences are noted which are attributed to the inappropriate assumption about the aerosol model used in the retrieval procedure. Preliminary study of the Deep Blue aerosol product over the Gujarat region shows that the product fills in the missing values of the C005 product especially over the Rann of Kuchchh. Validation of the Deep Blue algorithm derived aerosol optical depth and its comparison with the results from the C005 validation shows the slope of overall correlation plot to be better for the Deep Blue product than the C005 product. However, the correlation is better for C005. Present study deals with a comparative study of the MODIS aerosol optical depth data from two different versions viz., collection version C005 and Deep Blue algorithm. The purpose is to identify the circumstances

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wherein the two retrieval procedures hold good and those wherein one procedure must be preferred over the other. This provides necessary information for a combined data product consisting of the retrievals from both the products depending on the geolocation of the pixel and the preferred algorithm for the retrieval.

References

1)Hsu N. C., S. C. Tsay, M. D. King and J. R. Herman, 2004, Aerosol properties over bright-reflecting source regions, IEEE Trans. Geosci. Remote Sens. 42(3), 557-569

2)Hsu N. C., S. C. Tsay, M. D. King and J. R. Herman, 2006, Deep Blue retrievals of Asian aerosol properties during ACE-Asia, IEEE Trans. Geosci. Remote Sens., 44(11), 3180-3195

3)Levy R. C., L. A. Remer, S. Mattoo, E. F. Vermote and Y. J. Kaufman, 2007, Second-generation operational algorithm: Retrieval of aerosol properties over land from inversion of Moderate Resolution Imaging Spectroradiometer spectral reflectance, J. Geophys. Res., 112, D13211, doi:10.1029/2006JD007811

4)Misra A., A. Jayaraman and D. Ganguly (2007), Validation of MODIS derived aerosol optical depth over western India, J. Geophys. Res., doi: 10.1029/2007JD009075

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B–P–6

An Unusual Dust Event over North-eastern India and its Association with Extreme Climatic Conditions – A Study Using Satellite Data

Anu Rani Sharma, Shailesh Kumar Kharol and K. V. S. Badarinath

Atmospheric Science Section, National Remote Sensing Centre,

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

*badrinath_kvs@nrsc.gov.in

Introduction

Dust storms are atmospheric phenomena most frequently occurs over deserts and regions of dry soil, where particles are loosely bound to the surface (Slingo et al., 2006), which has implications for local weather, air temperature and influence ocean cooling (Goudie and Middleton, 2006). Remote sensing is an established method for the detection and mapping of dust events due to the high spatial variability of the dust plume characteristics along its transport (Legrand et al., 1989) and has been used to identify the dust-source locations with a varying degree of success. In the present study, we have analysed the unusual dust event occurred in the northeast region of India on 17th March, 2009 using multi-satellite data sets. The study region of Guwahati is characterized by a tropical climate and generally heavy rainfall, which do not favor the erosion of mineral dust. The Brahmaputra valley covers the main part of the region, which due to dry season and low rainfall in March, 2009 was arid in large part that caused the unusual dust event.

Datasets and Methodology

MODIS has been acquiring daily global data in 36 spectral bands from visible to thermal infrared (29 spectral bands with 1-km, 5 spectral bands with 500-m, and 2 spectral bands with 250-m, nadir pixel dimensions). The C005 Level 3 (spatial resolution 1ox1o) MODIS products are obtained from Giovanni website (http://giovanni.gsfc.nasa.gov) during the dust event over Guwahati, North-East India. The Atmospheric Infrared Sounder (AIRS) instrument suite was used to measure the atmospheric water vapor and temperature profiles. The TRMM 3B43 (V6) accumulated rainfall (0.25°×0.25°) product acquired from TRMM Online Visualization and Analysis System (TOVAS) were used for analysis of rainfall patterns over the region.

Results and Discussions

Figure – 1 (a) shows the False Color Composite (FCC) of Terra/Aqua MODIS for 17th March, 2009 and (b) True Color Composite of Terra/Aqua MODIS for 9th March, 2008 covering the north east region of India. An intense thick layer of dust/haze can be clearly seen from the figure -1(a) over the region on 17th March, 2009. This unusual dust storm

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event affected the daily life of local people and delayed number of flights at Guwahati Airport on 17th March, 2009. According to local newspaper reports, high intensity dust storms are very rare over the region but the current storm’s intensity was greater than

Figure 1. (a) False color composite of Terra MODIS on 17th March 2009 and (b) True color composite of Aqua MODIS on 09th March, 2008

usual because of drier-than-normal weather conditions prevailed during last three months (January-March) prior to the event. It can also be observed from figure -1(a) and 1(b) that the Brahmaputra River totally dried during March, 2009 compared to March, 2008 resulting in unusual dust storm event over the region as dried inland river basins are important source regions for the aeolian dust under favorable wind conditions. The mesoscale model (MM5) derived wind speed and directions at 850hPa overlaid on sea level pressure on 17th March, 2009 suggested a persistent north-easterly flow with high wind speed (~6 m/s) over the region resulting in mobilization and lifting of dust particles in to the atmosphere. The analysis of NCEP temperature/relative humidity (RH) anomalies variations showed ~0.60C increase in surface air temperature and ~ -4% reduction in RH during March, 2009, which resulted in dry conditions over the region. AIRS derived RH / Temperature values at different altitudes also showed reduction in March, 2009 compared to March, 2008. Figure 2 shows monthly accumulated rainfall (mm) for March, 2008 and 2009 from TRMM 3B42 (V6) over North – East India using the TRMM on-line visualization and analysis system. It can be seen from the figure 2 that deficit rainfall during March, 2009 compared to 2008 caused dry weather conditions over the region resulting in dust

Figure 2. TRMM derived accumulated rainfall (mm) during March-2008 and March-2009

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storm under favorable wind conditions. The TRMM observations of deficit rainfall matched with ground records of Indian Meteorological Department (IMD). The day-to-day variation of Terra MODIS derived aerosol optical depth at 550 nm (AOD550) and the wavelength dependence of optical depth as expressed in the Ångström exponent (a) over the region are shown in figure 3 (a – b). The mean values are spatial average of 6 pixels over the study site. A very high value of Terra MODIS AOD550 (~ 1.3) along with lower value of a (~0.78) can be clearly seen from the figure 3 (a-b) which was mainly attributed to coarse mode dust aerosol particles over the region due to dust event occurred on 17th March, 2009. However higher values of AOD550 (~1.38) on 15th March, 2009 can be associated with biomass burning aerosols particles due to high Ångström exponent (~0.87).

Figure 3 (a-b). Day- to- day variation of AOD550 and Angstrom exponent (a) during March, 2009 over the study region

Conclusions

In the present study we have analysed an unusual dust storm event occurred over North East region of India on 17th March, 2009 using multi-satellite datasets. Results of the study suggested that –

zAIRS derived RH / Temperature values at different altitudes and TRMM accumulated rainfall data showed reduction in March, 2009 compared to March, 2008. The dry soil conditions became susceptible for dust loading during high winds resulting in dust storm observed on 17th March, 2009.

zA very high value of Terra MODIS AOD550 (~ 1.3) along with lower value of Angstrom exponent ‘a’ (0.78) were observed on 17th March, 2009 suggesting dominance of coarse mode dust aerosol particles over the region due to dust event.

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Acknowledgements

The authors thank Director, NRSC and Dy. Director (RS&GIS-AA) for necessary help at various stages.

References

Goudie, A. S. and Middleton, N. J., 2001. Saharan dust storms: nature and consequences. Earth-Science Reviews 56, 179-204.

Legrand, M., Nertrand, J. J., Desbois, M., Menenger, L. and Fouquart, Y., (1989). The potential of infrared satellite data for the retrieval of Saharan dust optical depth over Africa, Journal of Climate and Applied Meteorology, 28, 309–318.

Slingo, A., Ackerman T. P., Allan, R. P., Kassianov, E. I., McFarlane and S. A., et al., 2006. Observations of the impact of a major Saharan dust storm on the atmospheric radiation balance. Geophysical Research Letters, 33, L24817, doi:10.1029/2006GL027869.

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B–P–7

Lidar and Sunphotometer Observations of Kasatochi and Sarychev-Peak Volcanic Plume over North America

A. Saha1, N.T. O’Neill1, M.L. Karumudi1, E. Eloranta2, G. Lesins3, D. Daou1, K. Strawbridge4, T. Duck3 and L.J.B. McArthur5

1CARTEL, Universite de Sherbrooke, Sherbrooke, Québec, Canada

2University of Wisconsin, Madison, USA

3Dalhousie University, Halifax, Nova Scotia, Canada

4Environment Canada, Egbert, Ontario, Canada

5Environment Canada,Toronto, Ontario, Canada

Volcanic activity is the main cause of stratospheric aerosol variability which can affect the radiative balance of the atmosphere by scattering and absorption and Earth’s climate. Stratospheric sulphate causes surface cooling and stratospheric warming. Ash clouds from volcanic eruptions also poses serious hazards to aviation. The last major eruptions occurred at El Chichon during March/April 1982 (releasing ~4 Tg S), and Pinatubo during 12-15 June 1991 (releasing ~10 Tg S). Elevated volcanic activity began in 2008 with major eruptions of Okmok and Kasatochi (Aleutian Islands, Alaska) in July- August 2008, Redoubt (Alaska) in March 2009, and Sarychev Peak (Matua & Kurile Islands, Russia) in June 2009. Of these, the eruptions from Kasatochi (52.17oN, 175.51oW; erupted on August 7, 2008) and Sarychev-Peak (48.1oN, 153.2oE; erupted on June 12, 2009) volcanoes are notable for their SO2 emissions (releasing ~1.4 Tg S and ~1 Tg S respectively) into the upper troposphere and lower stratosphere (UTLS).

We use ground-based sunphotometer measurements of the AEROCAN / AERONET network, backscatter Lidars, remote sensing imageries (CALIPSO, MODIS, OMI) and Lagrangian particle dispersion model (HYSPLIT) to analyze the small particle (sub-micron), optically thin, high altitude (UTLS) volcanic plume from the emissions of Kasatochi and Sarychev-Peak Volcano.

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B–P–8

Validation of Satellite Derived AOD by Ground Based Observation over Dibrugarh

Binita Pathak1, P K Bhuyan1, M M Gogoi2, Gayatry Kalita1

and K Bhuyan1

1Department of Physics,Dibrugarh University,Dibrugarh 786004 Assam

2Space Physics Laboratory,Vikram Sarabhai Space Centre,Trivandrum 695 022

Corresponding author’s Email: pathak.binita8@gmail.com

Introduction

With the advent of satellite remote sensing, the spatial and temporal variability of aerosols have been inferred on regional and global scales. Ground based measurements are essential in characterizing aerosol properties regionally. But due to short residence time in the atmosphere and resulting heterogeneous spatial variations in aerosol concentrations, ground based observations cannot assess trends in global aerosol distribution. Validated satellite measurements are essential in respect of filling the existing data gap and providing more homogeneous picture of the aerosol environment over the globe. The MODerate resolution Imaging Spectroradiometer (MODIS) aboard NASA’s EOS Terra and Aqua satellites has provided an opportunity to study the regional features of aerosol properties throughout the year since 2000.

In this study, we present the temporal variation of AODs measured by a ground based Multi-Wavelength Solar Radiometer (MWR) at three wavelengths viz. 380, 500, 1025nm . The MODIS derived AOD values at 550 nm are compared with the AODs measured with the MWR over Dibrugarh (27.27°N, 94.54° E, 82 m amsl), a remote continental location in the northeastern part of India, for each month during the period from October, 2001 to November, 2008.

Data and methodology

Ground based data

Spectral aerosol optical depth (AOD) measurements are made using a Multi Wavelength Solar Radiometer (MWR) at ten narrow wavelength bands centered at 380, 400, 450, 500, 600, 650, 750, 850, 935 and 1025 nm with full width at half maximum bandwidth of 5 to 6 nm. The MWR is designed on the principle of filter wheel radiometers (Shaw et al., 1973) and it measures the solar radiation intensities which are then used to determine aerosol optical depths by Langley plot technique (Moorthy et al., 2003). The instrument is operated from the rooftop of the building of the Physics Department of Dibrugarh University (~8m above ground level) on all days when unobscured solar visibility is available for at least 2 to 3 hrs.

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Satellite data

MODIS is a remote sensor on board two Earth Orbiting System (EOS), Terra and Aqua satellites which provide an opportunity to study aerosol from space with high accuracy and on a nearly global scale (Yu et al., 2004; Remer et al., 2005). These satellites are observing earth starting February, 2000 and July, 2002 respectively. In the present study, Level 3 MODIS collection 5 atmosphere daily global product aerosol optical depths at 550nm at 1o×1o grid (Ramer et al., 2005) derived daily from both Terra (MOD08_M3.005) and Aqua (MYD08_3.005) satellites are utilised. MODIS Terra and Aqua satellites operate at an altitude of 705 km with Terra spacecraft crossing the equator at about 10:30 IST (ascending towards north) and Aqua spacecraft crossing the equator at around 13:30 IST (desending southward) (Yu et al., 2004; Ramer et al., 2005). There is an uncertainty of 45 minutes in the case of crossing the equator by both satellites. Data from Terra and Aqua satellites are used respectively as FN and AN AODs. Daily AODs are average of Terra and Aqua AODs for corresponding day.

Results and Discussions

Temporal characteristics of aerosol optical depth

The seasonal variations of the aerosol optical depth at the three representative wavelengths viz. 380, 750 and 1025nm for the period October 2001 to November 2008 are shown in Fig.1. AOD at all wavelengths increases from February onwards and attains a peak value during the pre monsoon-months (March, April and May). The absolute value of AOD may vary from one year to another. The standard deviations are generally high during monsoon months indicating higher day-to-day variability during these months. The AODs are lower in retreating monsoon season except during the year 2003, where the lowest value of AOD occurred in a monsoon month. Spectrally, AOD is higher at lower wavelength 380 nm and gradually decreases towards higher wavelengths.

Figure 1. Seasonal variation of aerosol optical depth over Dibrugarh at three representative wavelengths

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Comparison of aerosol optical depths from ground based and satellite observations:

AODs obtained from the ground based MWR are interpolated to 550 nm (t500 )using the Angstrom formula

(1)

The Angstrom exponent alpha (a) used here is derived from ground based data. The seasonal variation of MODIS and MWR derived AODs at 550 nm are shown in Figure 2.

t550 =t500 (550/500)-a

Figure 2. Aerosol optical depth at 550 nm as measured by the MODIS and MWR over Dibrugarh during the period RM, 2001 to RM, 2008

The comparison of the two sets of AOD shows a good agreement with the values agreeing well within the instrumental uncertainties. A least square fit between AODs from the two estimates shows a linear relationship of the form

Slope lower than unity (~0.95) during the period of observation (Figure 3) indicates an overestimation of AOD by MODIS with respect to MWR retrieval. The correlation between the two data sets has been found to be good with correlation coefficient R equal to 0 .74 (P < 0.0001), root-mean square difference 0.028, mean difference 0.038. It is, therefore, inferred that in the absence of measurements from ground based instruments, aerosol optical depth retrieved from the MODIS satellites could be used for obtaining the temporal distribution of aerosols over this region and for estimation of its effect on remote sensing and climate change. The uncertainties in MODIS (Terra and Aqua) derived AOD over land is ± 0.05 ± 0.15AOD (Ramer et al., 2005).The difference between the ground based and satellite data may arise due the following reasons

(a)In selection of spatial co-ordinates for retrieval of satellite data.

(b)The satellite data are for two specific times in morning and afternoon hours, but ground based AOD are derived from data collected for the whole day.

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Summary and Conclusion

Aerosol optical depth that characterizes the integrated extinction of solar radiation suffered in its transit through the atmosphere were measured from Dibrugarh using a ground based Multi Wavelength Solar Radiometer since 2001. The monthly mean AOD retrieved from MODIS satellite is compared with the MWR derived AODs for the period October 2001 to November 2008. The comparison shows a good agreement with the data from the two independent measurements agreeing well within the instrumental uncertainties. This indicates that in the absence of measurements from ground based instruments, aerosol optical depth retrieved from the MODIS satellites could be used for obtaining the temporal distribution of aerosols over this region and for estimation of its effect on remote sensing and climate change.

Figure3. Scatter plot of monthly mean aerosol optical depth measured by the MODIS and MWR over Dibrugarh from October 2001 to November 2008

Acknowledgements

BP and GK are grateful to ISRO for providing them fellowships under GBP ARFI project.

Referrences

Moorthy, K.K., Suresh Babu, S., and Satheesh, S.K.(2003): Aerosol spectral optical depths over the Bay of Bengal: Role of transport, Geophys. Res. Lett., 30(5), 1249, doi: 10.1029/2002GL016520.

Ramer, L. A., et al., (2005), The MODIS Aerosol Algorithm, Products and Validation; Journal of Atmospheric Science, Vol 62, 947-973.

Shaw, G.E., Reagen, J.A., and Herman, B.M. (1973): Investigations of atmospheric extinctions using direct solar radiation measurements made with a multiple wavelength radiometer, J. Appl. Met., 12, 374-380.

Yu, H., Dickinson, R. E., Chin M, Kaufman, Y. J., Zhou, M., Zhou, L., Tian, Y., Dubovik, O. and Holben, B. N., (2004), Direct radiative effect of aerosols as determined from a combination of MODIS retrivals and GOCART simulations, J. Geophys. Res., Vol. 109, D03206, doi:10.1029/2003JD003914.

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B–P–9

Study of Columnar Aerosol size Spectra During Different Observing Seasons at Pune

G. R. Aher1 and S. D. More2

1Physics Dept., Nowrosjee Wadia College, Pune 411 001

2Dept. of Atmospheric and Space Sciences, University of Pune 411 007

email: aher.g.r@gmail.com, dsanjaymore@gmail.com

Introduction

Aerosols play an important role on Earth’s radiation budget due to their scattering and absorbing capability and indirectly serving as cloud condensation nuclei. Aerosols differ in terms of their physical and chemical properties as well as their sources of origin. Their concentrations and optical properties are one of the largest uncertainties in current assessment of climate change (IPCC, 2007).

Aerosol size information is critical for studying radiative transfer and model studies have shown that its size distribution effect might overweigh some other aerosol properties like the mixing type and vertical profile (Schuster et al., 2006; Tang, 1996). Knowledge of aerosol size distribution is useful to distinguish anthropogenic aerosols from urban and biomass burning and natural aerosols like sea salt and dust. Such discrimination is important since their effect on the Earth’s radiation budget depend on the aerosol type (Andreae, 2001).

Ground based measurements allow estimation of fine and coarse mode aerosol (Eck et al., 2005) as well as their respective contributions to other optical properties like aerosol optical depth (Dubovik and King, 2000; O’Neill et al., 2003). The aerosol size distributions are useful indicators to investigate the aerosol’s evolution process such as its hygroscopic growth, coagulation and aging. Aerosol size distributions are also useful indicators of the sources and sinks. Aerosol size distributions vary under different atmospheric conditions like light or heavy aerosol loading. The aerosol size distributions under the predominantly fine or coarse particles conditions have been studied using the Angstrom exponent as a discriminator, where a large Angstrom exponent indicates more fine mode aerosol events (Eck et al., 2008; Smirnov et al., 2003). The variation of aerosol size distribution under different aerosol loadings discriminated by aerosol optical depth have been studied at urban (Dubovik et al., 2002), desert (Eck et al., 2005), forest (Schafer et al., 2008),and costal (Smirnov et al., 2003) sites.

In this paper, we present the observation results of aerosol optical properties with emphasis on its size properties from December to May during observing seasons 1998-99, 1999-2000, 2000-2001 and 2008-2009.

Data and Analysis

An indigenously developed, automatic Sun-tracking multiple wavelength radiometer

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was operated from Pune University campus to measure the columnar aerosol optical depths (AOD) at eight discrete wavelengths in spectral range 400-1020 nm over Pune city during the years 1998-99, 1999-00 and 2000-01. Similarly, a hand-held MICROTOPS- II Sun photometer (Version 5.5) has been operated from Pune University campus during 2008-09 at spectral channels centered at 440, 500, 675, 870 and 1020 nm wavelengths to measure AOD. Daily AOD data at each wavelength is to determine the mean AOD spectral variation for each month during different observing seasons. For this, often data of 10 to 15 days in each month is used. This monthly mean spectral AOD data forms the subject matter of the present paper and is analyzed to retrieve columnar aerosol size distribution by following numerical inversion method of King et al. (1978) and to study its variation.

The columnar size distribution of aerosols [nc(r)] is related to AOD by Mie integral formula as:

(1)

Here, r is the particle radius, is their refractive index (real) and is the wavelength of incident solar radiation. Qext, is the extinction efficiency. The unknown columnar aerosol size distribution nc(r) stands for the number of particles per unit area per unit radius interval in a vertical column through the atmosphere.

Results and Discussions

Monthly Mean Aerosol Size Distribution

Results of the analysis are given in Fig.1 for four years 1998-99, 1999-2000, 2000-01 and 2008-09.

The shape of the monthly mean columnar aerosol size distribution during 1998-99 (Fig.1) is mostly bimodal indicating the likelihood of the presence of two groups of aerosol particles with different mode radii values. In December, January and April aerosols in the small size mode have radius of 0.19 m and those in the large size mode have a radius of 1.14 m indicating the presence of accumulation mode particles as the large size group. In other months (February and May), the small size group has mode radius ranging from 0.13 to 0.27 m in different months. In these months, the large size group has mode radius ranging from 0.92 to 1.82 m indicating the presence of coarse mode particles. In March the size spectrum is mono-modal with a broad hump at radii ranging from 0.18 – 1.14 m implying single haze distribution.

In 1999-2000 (Fig. 1), the monthly mean columnar aerosol size distribution is found to be either Junge power law or mono-modal type implying the presence of single haze distribution with dominance of small size aerosols. The mode radius lies between 0.15 to 0.22 m with a number concentration ranging from 2.31x108 cm-2 to 1.75x108 cm-2 respectively.

During 2000-01(Fig.1) the shape of the monthly mean columnar aerosol size spectrum is mostly monomodal showing the presence of small size aerosols. The mode radius has the value ranging between 0.20 – 0.26 m with 4.57x107 cm-2 to 1.08x108 cm-2 respectively. However, in the month of April it is bimodal showing the presence of two components.

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Figure 1. Monthly mean spectral variation & corresponding columnar aerosol size spectra

The small size mode has radius around 0.15 m and the radius of the large size mode is 0.36 m.

The monthly mean columnar aerosol size distribution during 2008-09 (Fig. 1) is Junge power law type through out the period of observation which once again indicates the dominance of small size aerosols. The columnar concentration varies between 1.03 x 108 cm-2 to 5.24 x107 cm-2 and the corresponding average particle radii are 0.22 m and 0.23 m.

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Conclusion

The study indicates the mixed type of columnar aerosol size distributions during 1998- 99, 1999-2000, 2000-01 which indicates the presence of fine (sub-micron) as well as coarse (super –micron) mode aerosols during this period. While during 2008-09 the occurrence of Junge power law type size distribution implies the presence of single haze distribution with dominance of small size aerosols.

Acknowledgements

The research project is supported by the UGC, New Delhi under the major research project scheme. The authors thank the Head of the Department of Environmental Sciences, and the Pune University authorities for encouragement.

References

1)Intergovernmental Panel on Climate Change: Climate Change 2007: The Physical Science Basis, Cambridge Univ. Press, Cambridge UK, 2007.

2)Schuster, G. L., Dubovik, O., and Holben, B. N.: Angstrom exponent and bimodal aerosol size distributions, J. Geophys. Res., 111, D07207, doi:10.1029/2005JD006328, 2006.

3)Tang, I. N.: Chemical and side effects of hygroscopic aerosols on light scattering coefficients, J. Geophys. Res., 101, 19245-19250, 1996.

4)Andreae, M. o.: The dark side of aerosols, Nature, 409, 671-672, 2001.

5)Eck, T. F., Holben, B. N., Dubovik, O., Smirnov, A., Goloub, P., Chen, H. B., Chatenet, B., Gomes, L., Zhang, X.-Y., Tsay, S.-C., Ji, Q., Giles, D., and Slustsker, I.: Columnar aerosol optical properties at AERONET sites in central eastern Asia and aerosol transport to the tropical mid-Pacific, J. Geophys. Res., 110, D06202, doi:10.1029/2004JD005274, 2005.

6)Dubovik O. and King, M. D.: A flexible inversion algorithm for retrival of aerosol optical properties from Sun and Sky radiance measurements, J. Geophys. Res., 105, 20673 -20696, 2000.

7)O’Neill, N. T., Eck T. F., Smirnov, A., Holben, B. N., and Thulasiraman, S.: Spectral discrimination of coarse and fine mode optical depth, J Geophys. Res., 108,4559, doi:10.1029/2002JD002975,2003.

8)Smirnov, A., Holben, B. N., Dubovik, O., Frouin, R., Eck T. F., and Slutsker, I.: Maritime Component in Aerosol Optical models derived from Aerosol Robotic Network data, J. Geophys. Res., 108, 4033, doi:10.1029/2002JD002701, 2003.

9)Dubovik O. Holben, B. N., Eck, T. F., Smirnov, A., Kaufman, Y. J., King, M. D., Tanre, D., and Slutsker, I.: Variability of absorption and optical properties of key aerosol types observed in world wide locations, J. Atmos.Sci., 59, 590 – 608, 2002.

10)Schafer, J. S., Eck, T. F., Holben, B. N., Artaxo, P., and Duarte, A. F.: Characterisation of optical properties of atmospheric aerosols in Amazonia from long term AERONET monitoring (1993 -1995 and 1999 – 2006), J. Geophys. Res., 113, D04204, doi:10.1029/2007JD009319, 2008.

11)King, M. D., Byrne, D. L., Herman, B. M., and Reagan, J. A.: Aerosol size distributions obtained by inversion of spectral optical depth measurements, J. Atmos. Sci., 35, 2153-2167, 1978.

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B–P–10

Aerosols Optical Properties Prone to Climate Change over Mohal-Kullu in the Northwestern Himalaya, India

Jagdish C. Kuniyal* and Raj Paul Guleria

G.B. Pant Institute of Himalayan Environment and Development, Himachal Unit,

Mohal-Kullu, 175 126, Himachal Pradesh, India

*Corresponding author : E-mails: jckuniyal@rediffmail.com / kuniyaljc@yahoo.com

Introduction

Aerosol optical depth (AOD) is one of the important optical properties of columnar aerosols considered to be crucial in affecting radiation budget and altering the climate of the Earth. It modifies atmosphere and ground heat budget either by scattering or absorbing solar radiation (Charlson et al., 1991; Ranjan et al., 2007). Studying aerosols especially in the Himalayan context is important because of its long mountain range which is topographically very fragile and ecologically very delicate and acts as an ecological guard of the Asian continent in many aspects. So much so it is also termed as third pole after north and south poles of the Earth because of its huge water reserve in the form of snow. Unfortunately, the Himalayan glaciers in this ecosystem have been the first hit ecological biome suffering due to ever increasing aerosols and its consequent warming effect in the region (Ramanathan et al., 2007; Ming et al., 2008). The other parameters of columnar aerosols responsible to influence the energy budget of the Earth’s atmosphere are wavelength exponent ‘a’ that contain information on the aerosol size distribution and atmospheric turbidity ‘ ’, which is a measure of total particulate load in a columnar environment. Aerosols generated at one place are also transported over long distances by an action of wind and produce consequent effects at locations far away from its sources (Prospero et al., 1983; Hoppel et al., 1990; Kuniyal et al., 2009). In this context, study of aerosols and its effect on the Himalayan perspective will help in maximizing our knowledge on climate change.

Experimental Site and Data

The present experimental site is located at Mohal (31.9° N, 77.12° E, and 1154 m amsl) in the Kullu valley of the northwestern Indian Himalayan Region. Studying aerosol optical properties under full clear sunny days were made using Multi-wavelength Radiometer (MWR) from April 2006 to December 2007. AODs as monitored from ground base observation; Langley technique was deployed to deduce the total columnar optical depth ‘t’ by making a linear regression fit to the Lambert-Beer Law (Shaw et al., 1973; Moorthy et al., 1991) as under:

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on the top of the atmosphere (TOA); and m is the relative air mass computed at solar zenith angle = 70°.

Aerosol spectral optical depth contains information pertaining to their size distribution retrieved from Angstrom Power Law (Angstrom, 1961) as follows:

Where is aerosol optical depth in relation to wavelengths from 380 to 1025 nm. The optical depth at wavelength 935 nm was not included for retrieval of size distribution due to its strong water absorption band (Moorthy et al., 1991).

Validation of Moderate resolution Imaging Spectro-radiometer (MODIS) sensors derived AODs onboard the Earth Observing System Terra platform at wavelength 550 nm was attempted by comparing with mean AODs of MWR at the same wavelength. MWR derived AOD at 500 nm was applied to evaluate AOD at 550 nm using linear interpolation technique in Power Law (Prasad et al., 2007) as under:

Where ‘a’ was estimated from MWR derived AODs in the visible spectrum 400-750 nm.

Results and Discussions

The mean value of AOD at 500 nm during 2006 was observed highest as 0.43 ± 0.04 in April (summer) and lowest as 0.16 ± 0.02 in December (winter). While during 2007, the AOD value was highest as 0.34 ± 0.02 in July (local summer) and minimum as 0.15 ± 0.01 in March (local winter). The lowest value of wavelength exponent ‘a’ in April during 2006 and 2007 was observed 0.57 ± 0.00 and 0.73 ± 0.05, while particulate load ‘ ’ showed 0.29 ± 0.01 and 0.17 ± 0.02 respectively. The high particulate load from April to August having low value of a during 2006 and 2007 suggest dominating coarse mode particles over fine mode during mostly in pre-monsoon season.

In general, variations in a and remain in paradoxical situation. To examine this aerosols characteristic, an inverse relationship was established statistically between a and. The Karl Pearson’s co-efficient of correlation was computed where r = -0.88 was found more than 39 times the value of probable error (PE) in 2006. However, its value in 2007 slightly decreased indicating r = -0.65 which remained more than 14 times the value of PE. This further indicates a significant negative correlation between a and .

Statistical analysis revealed a close agreement between AOD from satellite and daily averaged AOD from MWR, interpolated at 550 nm. As root mean square error (RMSE), t-test and correlation coefficient was ~0.079, 0.016 and 0.53 respectively. Fig.1a is showing variations in daily averaged MWR AOD, interpolated at 550 nm and MODIS Terra satellite. AOD observations after applying both the techniques showed high concentration of aerosols during summer and low during winter and autumn (Fig. 1b). Least square fit between mean AODs from MWR (interpolated at 550 nm) and MODIS Terra satellite showed a linear relationship in this way as follows:

(MODIS)AOD = (MWR) AOD × 0.50 + 0.13

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Slope lower than unity (~0.50) during the period of observation indicates an under estimation of AOD by MODIS with respect to MWR retrieval.

The heavy particulate load observed on 29 April 2006 showed AOD as 0.69 at 500 nm; a 0.63 and 0.44. While on 17 August 2007, AOD was 0.36 at 500 nm; a 0.50 and 0.27. During these observations period, the back trajectory analysis was also made indicating the impact of dust laden air masses from the countries situated in the north-western part of India. As a result, external sources have also been the major contributor in increasing the existing load of aerosols from local sources within the present study region. This was further proved from the satellite imaginary used as one of the important tools of the present study.

Figure 1. Aerosol optical depth (AOD) variations from MODIS Terra and MWR interpolated at 550 nm over Mohal: (a) monthly, and (b) seasonal

There seems to be a large variability in the ground reaching solar flux during equinox and solstice months in 2007 (Fig. 2). Any alteration in ground energy budget can bring significant changes within climatic system (Charlson et al., 1991). During winter solstice, there remains small amount of surface reaching solar flux compared to summer solstice months. It is estimated that during this

time, there is a loss of 42 Wm-2 AOD-1 in winter solstice and 28 Wm-2 AOD-1 in summer solstice at 500 nm in respect to the Himalayan ecosystem.

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As a result, the climatic abnormalities are much associated with the values of AODs in the study region with loss of 42 Wm-2 AOD-1 in winter solstice and 28 Wm-2 AOD-1 in summer solstice at 500 nm which cannot be said low in values especially in local summer season (0.34 ± 0.02 in July at 500 nm) contributed by both—the local sources (vehicular emissions, forest fires and use of biofuels) and the external sources (industrial emissions, desert aerosols, and oceanic sulphate aerosols) from outside the region.

Acknowledgement

The authors are heartily thankful to the Director, G.B. Pant Institute of Himalayan Environment and Development, Kosi-Katarmal, Almora, Uttarakhand for providing facilities in Himachal Unit of the Institute which could make the present study possible.

References

Angstrom, A. (1961) Techniques of determining the turbidity of the atmosphere, Tellus 13, 214-223.

Charlson, R.J., Langner, J., Rodhe, H., Leovy, C.B. and Warren, S.G. (1991) Perturbation of the northern hemispheric radiative balance by backscattering from anthropogenic sulfate aerosols. Tellus 43AB, 152-163.

Hoppel, W.A., Fitzgerald, J.W., Frick, G.M., Larson, R.E. and Mack, E.J. (1990) Aerosol size distributions and optical properties found in the marine boundary layer over the Atlantic Ocean, J. Geophys. Res. 95, 3659-3686.

Kuniyal, J.C., Thakur, A., Thakur, H.K., Sharma, S., Pant, P., Rawat, P.S. and Moorthy, K.K. (2009) Aerosol optical depths at Mohal-Kullu in the northwestern Indian Himalayan high altitude station during ICARB, J.Earth System Sci. 118(1): 41-48.

Ming, J., Cachier, H., Xiao, C., Qin, D., Kang, S., Hou, S. and Xu, J. (2008) Black carbon record based on a shallow Himalayan ice core and its climate implications, Atmos. Chem. Phys. 8, 1343-1352.

Moorthy, K.K., Nair, P.R., Murthy and B.V.K. (1991) Size distribution of coastal aerosols: effects of local sources and sinks, J. Appl. Meteorol. 30, 844-852.

Prasad, A.K., Singh, S., Chauhan, S.S., Srivastava, M.K., Singh, R.P. and Singh, R. (2007) Aerosol radiative forcing over the Indo-Gangetic plains during major dust storms, Atmos. Environ. 41, 6289-6301.

Prospero, J.M., Charlson, R.J., Mohnen, V., Jaenicke, R., Delany, A.C., Moyers, J., Zoller, W. and Rahn, K. (1983) Atmospheric aerosol system: An overview, Rev. Geophys. Space Phys. 21, 1607-1630.

Ramanathan, V., Ramana, M.V., Roberts, G., Kim, D., Corrigan, C., Chung, C. and Winker, D. (2007) Warming trends in Asia amplified by brown cloud solar absorption, Nature 448, 575-578. doi:10.1038/nature06019.

Ranjan, R.R., Joshi, H.P. and Iyer, K.N. (2007) Spectral variation of total column aerosol optical depth over Rajkot: A tropical semi-arid Indian station, Aerosol and Air Qual. Res. 7(1), 33-45.

Shaw, G.E., Reagan, J.A. and Herman, B.M. (1973) Investigations of atmospheric extinction using direct solar radiation measurements made with a multiple wavelength radiometer, J. Appl. Meteorol. 12, 374-380.

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B–P–11

Remote Sensing of Strongly Absorbing Aerosols

Nivedita Sanwlani *† and Prakash Chauhan†

† Space Applications Centre, (ISRO), Ahmedabad-380015, Gujarat, India.

The two opposite and direct effects of aerosols are the scattering of solar radiation back to space, i.e., a cooling effect, and the absorption of solar and earth radiation in the lower atmosphere, i.e., a heating effect. The most important aerosol types are soil dust, carbonaceous, sulfate, and sea salt aerosols. Soil dust aerosol particles are large in size and significantly absorb shortwave radiation, while sulfate aerosol particles are small in size and are non-absorbing. Carbonaceous aerosols are more complicated in their chemical and optical properties, but they are commonly recognized as a strongly absorbing aerosol with the inclusion of soot particles. The coastal regions of India are highly industrialized and urbanized and presence of strongly absorbing aerosols resulting from these activities dominate nearby coastal regions. To detect absorbing dust aerosols over the ocean, one must know the optical properties of both the ocean and the aerosols, as well as the effect of these aerosols on the TOA signal recorded by a satellite borne sensor. Dust optical properties have been extensively studied by many researchers regarding their effect on the TOA reflectance. The absorbing aerosols issue can be solved by the satellite measurements at the ultraviolet (UV) wavelengths but the ocean colour sensors currently in use do not have the UV sensors. This study extensively presents the identification of absorbing aerosols using remote sensing techniques. Monotonic dependence of (raerosol+rayleigh/rrayleigh) ratios on aerosol optical thickness, ta based approach has been demonstrated to be successful for open oceans. Identification of strongly absorbing aerosols is also done using the combinations of the MODIS-measured radiances at the short wave infrared (SWIR) channels. These observations are also compared detection of absorbing aerosols based on simple band ratio and band subtraction algorithm. An index for such aerosols namely Normalised absorbing aerosol index (NAAI) based on near infra red and visible channel has also been evaluated and demonstrated.

**To be presented at Conference of Indian Aerosol Science and Technology Association on AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES during March 24-26, 2010

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B–P–12

Ultra High Resolution Measurements of 3-Dimensional Winds using Doppler Lidar at Pune: First Results

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

Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road,

Pune 411 008, India

Introduction

Wind measurements using the Lidar technique has many advantages as compared to the conventional and other remote sensing techniques such as Sodar, mainly because of its higher altitude coverage with more spatial and temporal resolution (Devara, 1992).

So far, the lidar probing of atmospheric winds is very much limited all over the globe and more so in India (Devara, 1989). Ever since the lidar technique has been developed, because of complex nature of its design to respond ultimately to limited availability of suitable tracers, which these systems basically make use of, in deriving the vertical profiles of winds over different environments, not many wind lidars have been put into operation.

High resolution measurements of three-dimensional wind (zonal, meridional and vertical components) have been carried out, for the first time, using a portable low-power Doppler wind lidar (DWL), a proto-type but high power wind lidar that can continuously measure all the three components during day and night under all-weather conditions that the Indian Institute of Tropical Meteorology (IITM) is planning to install soon for its research activities at Pune and other locations in coordination with M/s Leosphere, France. This is an active remote sensor based on laser detection and ranging finding technique. The heterodyne lidar principle relies on the measurement of the Doppler shift of laser radiation backscattered by the particles in the air (dust, water droplets from clouds and fog, pollution aerosols, salt crystals, biomass burning aerosols etc.). The instrument is equipped with an IP65 waterproof and dustproof housing, which protects the system from harsh weather conditions. It is also equipped with window de-icing and an automatic wiper system. The accuracy of the system has been proven in rain, snow, and cold climates.

Doppler shift observed for different beam positions have been used to derive the three components of winds. Capability of the system operated at IITM includes (a) measurement of winds with ultra high time interval (1 sec) and with range resolution of ~20 m and (b) automatic data filter to maintain data quality by adopting a criterion of threshold signal- to-noise ratio (SNR). The system is also equipped with real-time data processing software that provides final products i.e. height profiles three wind components, wind direction apart from the SNR for each beam position. In this paper we present first and preliminary results of winds derived from Doppler lidar observations that have been carried out in the IITM campus, Pune during 15-23 July 2009.

Continuous measurements have been made covering an altitude range of 100-1000 m. Simultaneous measurements of winds have also been carried out at surface using an

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Automatic Weather Station (AWS). Figure 1 shows time series of zonal (U), meridional

(V) and vertical (W) components of wind measured on 23 July 2009 during the period 17:00 – 22:00 LT. Top and bottom panels of the figure show wind direction derived from wind components and SNR. It can be observed from this figure that measurement of wind components is sensitive to the detectability of the lidar signal. Vertical velocity measurements are observed to be more sensitive to the detectability of signal as these measurements are observed to be more random when the SNR falls below the threshold value i.e. ~ -12 db.

Figure 1. Time series of zonal (U), meridional (V) and vertical (W) components of wind measured by Doppler Lidar. Bottom panel shows signal-to-noise ratio (SNR) and bottom panel shows wind direction

Wind speeds measured at 100 m level by the DWL, and at surface level by the AWS are compared in Figure 2. These two measurements show a reasonably good

Figure 2. Comparison of wind speeds measured by DWL and AWS on 23 July 2009

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agreement within the measurement accuracies except small deviation which is obvious because of the height difference between the measurements. These ultra high time resolution measurements of winds have been subjected to spectral analysis to study the high frequency waves in the boundary layer. Figure 3 shows sample spectrum of zonal wind variations constructed for 100 m level. The spectral analysis of these measurements clearly shows the dominance of ultra high frequency waves with periodicities less than 10 minutes. These ultra high resolution measurements of winds have been used to study the propagation of ultra high frequency waves in the troposphere.

Figure 3. Spectrum of zonal (E-W) wind velocity at 100 m height level derived from DWL measurements

Acknowledgements

The authors acknowledge with thanks the support from Sebastien Dubois and Matthieu Boquet during the installation and operation of the DWL at the Institute. Thanks are also due to Director, IITM for infrastructure support. One of the authors (MGM) is thankful to CSIR, New Delhi for awarding the Research fellowship to him.

Reference

Devara, P.C.S., 1992: Wind Measurements from radars at micrometer-meter wavelengths. Journal of Institution of Electronics and Telecommunications Engineers (IETE), Technical Review, 9, 283-291.

Devara, P.C.S., 1989: Active remote sensing of the atmosphere using lasers. Journal of Scientific and Industrial Research, 48, 71-83.

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B–P–13

An Overview of Twenty Years of Optical Remote Sensing Studies of Tropical Atmospheric Aerosols, Gases and Clouds at Pune, India

P.C.S. Devara and P. Ernest Raj

Indian Institute of Tropical Meteorology, Pashan, Pune 411 008, India

E-Mail: devara@tropmet.res.in

The impact of aerosols, gases and clouds, through scattering and absorption of solar and terrestrial radiation, on global/regional/local weather and climate, satellite remote sensing, air and water quality has been the subject of numerous investigations in recent years. Efficient methods for real time monitoring of these parameters over longer period are of great interest in the programs connected with impact, assessment, control and forecast of anthropogenic activities on climate system. Compared to direct measuring techniques, which provide reasonably reliable information with good time resolution at a specific location, more representative information can be obtained with remote sensing techniques. Of the latest optical remote sensing techniques, laser radar or LIDAR (active remote sensing) and solar radiometry (passive remote sensing) have been recognized to be powerful and versatile tools for atmospheric diagnostics. A variety of lidar and radiometric techniques, operating for the past several years, at the Indian Institute of Tropical Meteorology (IITM), Pune, India and the multi-year, multi-institutional, poly-platform, vertical profile / columnar distributions of aerosols, gases and clouds archived with these facilities and the data archival and analysis procedures, and salient results are reviewed in this paper. With the advent of recent technological developments, the advanced sun- sky radiometers and autonomous Dual Polarization Micro Pulse Lidar (DPMPL), installed at the Institute in the recent past for understanding the direct and indirect aerosol effects, particularly of anthropogenic origin, will be discussed. Some stimulating results, bringing insight into the complex interactions and feedback processes underlying aerosols, boundary- layer, clouds and precipitation using these advanced light scattering techniques from land and oceanic regions, documenting the impact of aerosols on weather and climate are presented. Future directions of atmospheric remote sensing, and scientific joint collaborations to fill the research gaps and address the key crosscutting issues among the above parameters in different time scales will be highlighted.

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B–P–14

Spectral Variation of Aerosol Optical Thickness over Kannur- Some Preliminary Results

Praseed K M*, Nishanth T*, Sheela M Joseph*, M K Satheesh Kumar*, Madhubala Talaulikar † and T Suresh†

*Department of Atmospheric Science,Kannur University, Kannur,Kerala 670 567

† National Institute of Oceanography, Dona Paula, Goa

ABSTRACT : Aerosols are considered to be enigmatic yet indispensable atmospheric component in global climate studies and modeling. It has been revealed that the physical characteristics, composition, abundance, spatial distribution and dynamics of aerosols are influencing global climate change. Aerosol spectral optical thickness (AOT) and precipitable water vapour amount are two vital physical parameters for characterising aerosols. Routine observations of total atmospheric column AOT on a global scale is a fundamental way of determining aerosol optical characteristics and its influence in the radiation budget and the consequent climate change. Ground-based observations are being carried out at different stations and various campaigns have been successfully conducted to retrieve the dynamics of aerosols [Ramanathan, V et al. (2001), Krishnamurthy et al., (1997), Jayaraman et al., (1993)]. Recently, remote sensing of AOT using satellite data has been carried out and validation of these two methods are quite promising to analyse prominent role of aerosols.

To retrieve the spatial and temporal aerosol distributions over a specific location, a long term ground based observation is often required. To enhance the resolution of data, the present network of observatories may be expanded to investigate the fine signature of aerosols on a global scale. This is the first and preliminary attempt from Kannur (11.93N, 75.36E) to study the spectral variation of AOT and the consequent angstrom coefficients over this region at two different locations.

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Light Inc.) was successfully used for monitoring the AOTs at five different wavelength ranges (440nm, 500 nm, 675nm, 870 nm and 936 nm).The field of view of the sun photometer is 2.50 with a resolution 0.01 watts m-2. The observations were carried out on clear sky days in the first week of December after the north - east monsoon has subsided in this region.

The observations were made on clear sky days in the mornings at Kannur University campus and Paithalmala. Since the afternoons were partially cloudy at these two locations, the data were not consistent. The best data were selected and processed and time variations of AOTs were recorded and they are shown in fig. 2 at these two locations.

Figure 2. Time variations of AOT at Kannur University Campus (A) and at Paithalmala (B)

From these two observations, it is found that the spectral AODs at Paithalmala are quite consistent in all days of observation while at the university campus it shows rapid variations. This may be due to the presence of clouds in the vicinity of this area. The Angstrom formula is used for quantitative characterization of the spectral dependence and the respective Ångström parameters a and are used to retrieve the physical properties of aerosols. The spectral dependence of AOT is typically approximated using Ångström’s formula [Ångström, 1961] derived on the premise that extinction of solar

radiation by aerosols

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Kannur university, which agrees with earlier

observations (Dani et al. 2003; Satheesh et al. 2006). The relatively smaller values of a indicate the presence of coarse-mode particles; however, larger values indicate the presence of fine-mode particles over the station.

Acknowledgement

The authors deeply acknowledge the support of Kannur University for providing all facilities to carry out this work.

References

Ångström, A.(1961). Techniques of Determining the Turbidity of the Atmosphere. Tellus. 8: 214-223.

Dani, K.K., Maheskumar, R.S. and Devara, P.C.S. (2003). Study of Total Column Atmospheric Aerosol Optical Depth, Ozone and Precipitable Water Content Over Bay of Bengal During BOBMEX-99. Proc. Indian Acad. Sci. (Earth. Planet. Sci.) 112: 205-221. 473

Devara, P.C.S.,Pandithurai, G.,Raj, P.E. and Sharma, S.(1996). Investigations of Aerosol Optical Depth Variations Using Spectroradiometer at an Urban Station,Pune,India J. Aerosol Sci.27:621.

Holben, B. N., Tanre, D., Smirnov, A., Eck, T. F., Slutsker, I., et al.(2001), An emerging ground-based aerosol climatology: Aerosol optical depth from AERONET, J. Geophys. Res., 106, 12 067–12 097.

Jayaraman,A, and B H Subbaraya,(1993), In-situ measurements of aerosol extinction profiles and their spectral dependence at tropospheric levels, Tellus, 45B,473-478.

Moorthy, K. K., Satheesh, S. K. and Murthy, B. V. K., J. Geophys. Res., 1997, 102, 18,827.

Ramanathan, V., Crutzen, P.J. and Lelievld, J. (2001). Indian Ocean Experiment: An Integrated Analysis of the Climate Forcing and Effects of the Great Indo-Asian Haze. J. Geophys. Res. 106: 28371-28398.

Sakerin and D.M. Kabanov(2006) ,Spectral Dependences of the Atmospheric Aerosol Optical Depth in the Extended Spectral Region of 0.4-4 ìm. Sixteenth ARM Science Team Meeting Proceedings, Albuquerque, NM, March 27 – 31.

Satheesh, S.K., Moorthy, K.K., Kaufman, Y.J. and Takemura, T. (2006). Aerosol Optical Depth, Physical Properties and Radiative Forcing Over the Arabian Sea. Meteorol. Atmos. Phys. 91: 45-62.

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B–P–15

Seasonal and Spatial Variability of IRS-P4 OCM (Oceansat-1) Derived Aerosol and its Impact on Surface Water Chlorophyll- a in the Bay of Bengal

R.K.Sarangi

Marine and Earth Sciences Group, Space Applications Center (ISRO)

Ahmedabad-380015, India

Observation has been made to study and understand the behavior of aerosol derived from the 865nm central wavelength band (bandwidth 40nm) of Indian Remote Sensing satellite, IRS-P4 OCM (Oceansat-1) sensor derived images. The aerosol concentration found to be higher during December month (Northeast monsoon) over the Bay of Bengal (BoB) water off Sundarbans with a distinct plume. The aerosol optical depth (AOD) ranged between 0.3-0.85 for the 4 sampled points, in the image of December 24, 2002. The coastal aerosol concentration is found higher than the offshore water. There has been decreasing trend seen towards offshore water with AOD value ~0.45. The month of June also indicated high aerosol (~0.60), might have been transported as dust flux from land during southwest monsoon. The December month data indicated distinct and very high aerosol flux (~0.80) over the BoB into deeper water and away from coast, it seemed phenomenal (Fig.1). To understand its link with biological parameter, the ocean surface chlorophyll has been retrieved from 4 seasonal datasets during April, June, October and December 2002. The December has shown very high chlorophyll-a (1.0-2.0mg/m3) compared to other seasonal months, which indicated that the direction of aerosol plume from west to east, has been followed the track towards the BoB offshore water from coastal region. The high wind speed (~6 m/sec) and wind direction has played the role to move the aerosol towards offshore in the BoB. The aerosol induced increase of the surface ocean chlorophyll-a concentration is observed to be significant. Similar high concentration aerosol plume has been observed during December 2003 and 2004. This study is interesting to understand the precise composition of aerosol like iron and increase in sulfate ions and its relationship with phytoplankton and productivity in the Bay of Bengal water.

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Figure.1 Strong aerosol plume seen off the Bengal coast signifying the mineral dust source and its flux from the terrestrial source towards ocean.

*Paper to be presented at the Conference on Indian Aerosol Science and Technology Association (IASTA), to be held during March 24-26, 2010 at Bose Institute Campus, Darjeeling.

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B–P–16

Spatio-temporal Distribution of Cloud Radiative Forcing During Contrasting Monsoon Years over India

S. D. Patil, B. Preethi, J. V. Revadekar and Nityanand Singh

Indian Institute of Tropical Meteorology, Pune 411008

Introduction

The concept of Cloud Radiative Forcing (CRF) has been used extensively to study the impact of clouds on climate. The CRF at the top of the atmosphere is defined as the difference between the radiative fluxes (longwave and shortwave) with and without clouds. The years 1987 and 1988 represent one of the most contrasting situations of monsoon performance over India. Interestingly, these two years are also well known to be associated with El Niño and La Niña respectively. El Niño and La Niña are well known to be associated with significant monthly/seasonal climate anomalies at many places around the globe. The relationships between El Niño and Indian summer monsoon is well known and studied rigorously by many scientists (Sikka, 1980; Rasmusson and Carpenter, 1983; Parthasarathy and Pant, 1985; Mooley, 1997). Variability of rainfall during both the seasons (JJAS and OND) are linked towards ENSO. ENSO has a negative impact on the Indian summer monsoon rainfall with a suppression of rainfall during the warm phase of ENSO (El Niño) and an enhancement in rainfall during its cold phase (La Niña) (Sikka, 1980; Rasmusson and Carpenter, 1983; Gadgil et al., 2004). However, this relationship has weakened in recent decades (Kripalani and Kulkarni, 1997; Krishna Kumar et al., 1999). Even though El Niño is unfavourable for Indian summer monsoon rainfall whereas it is associated with heavy rainfall activities over the Peninsular India during winter monsoon rainfall (Revadekar and Kulkarni, 2008).

Chen et al. (1995) have shown that the sea surface temperature anomalies cause large CRF (both longwave and shortwave) anomalies and longwave anomalies strongly enhances the precipitation anomaly in the tropical belt. The net CRF at the top of the atmosphere represents the total energy convergence in the continental tropical convergence zone (Neelin and Held, 1987). Munot et al. (2009) has also been found that the seasonal behaviour of the NCEP-NCAR longwave CRF and its relationship with all-India summer monsoon rainfall. Significant amount of rainfall is received over west coast of India, northeastern regions, central Indian region and the broad zone north of 150N stretching northwestward from the head of the Bay of Bengal (Sikka and Gadgil, 1980), but very little rainfall occurs over southeast and northwest part of the subcontinent. Indian summer monsoon (JJAS) is major rainy season which contributes about 80-90% of the total annual rainfall (Pant and Rupa Kumar, 1997). The excess as well as deficient monsoon rainfall which is a part of natural inter-annual variability of monsoon rainfall, usually have adverse impact on Indian economy and social life (Parthasarathy et al., 1992). However, during winter or northeast monsoon season (OND), the rainfall activity is confined to the southern tip of the peninsula including the meteorological subdivisions of coastal Andhra

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Pradesh, Rayalaseema south-interior Karnataka, Kerala and Tamilnadu (Srinivasan and Ramamurty, 1973; De and Mukhopadyay, 1999). Over these regions the rainfall during winter monsoon season account for about 50% of their annual rainfall.

In view of above, an attempt is made in the present study to assess the spatio-temporal distribution in the CRF for winter and summer monsoon seasons during the years 1987 and 1988 associated with El Niño and La Niña respectively, which represent one of the most contrasting situations of monsoon performance over India.

Data and analysis

The CRF data from satellite measurements of ERBE (1985-1989) on board Earth Radiation Budget Satellite (ERBS) and cloud data from International Satellite Cloud Climatology Project (ISCCP) C-2 (1985-1989) have been used in the present study over the Indian region. In ERBE data period, the years 1987 and 1988 are encompasses the El Niño and La Niña years respectively. The ISCCP provides cloud parameters such as high cloud amount (optically thick) and cloud optical depth from a global network of geostationary weather satellite and at least one polar orbiting satellite. The ERBE data are derived from the radiance measured by ERBS. The ERBE S-4 (longwave and shortwave) CRF data archive (Barkstrom et al., 1989) at the top of the atmosphere at 2.5ºx2.5º latitude-longitude grid resolution are considered during the period 1985-1989. Monthly mean all-India rainfall for the period 1985-1989 during summer and winter monsoon seasons is also used from Climate Prediction Centre Merged Analysis of Precipitation (CMAP) at a resolution of 2.50 × 2.50 lat/long grids (Xie and Arkin, 1997) available for the entire globe to see the relationship with CRF.

Results and discussions

India is a tropical country dominated by the monsoons, with the annual march of the climate punctuated by the winter (JF), pre-monsoon (MAM), monsoon (JJAS) and post- monsoon (OND) seasons. India’s climate is affected mainly by southwest, and to a limited extent, by the northeast monsoon flow. Among the 5-years period of ERBE (1985-1989), India as a whole experienced its lowest value of summer monsoon rainfall over the country during 1987 and highest value during 1988. In association with the high (low) rainfall activites, CRF also show high (low) value in 1988 (1987). In-phase relationship between rainfall during the pre-monsoon and summer monsoon season is observed whereas an out-of-phase relationship is seen between summer and winter monsoon rainfall with maximum rainfall during winter months of 1987 and minimum during 1988. The cloud properties (high cloud amount and cloud optical depth) and CRF components (longwave, shortwave and net) also exhibits the similar behaviour. In resemblance with the heavy rainfall activities in the summer monsoon (JJAS) of 1988 over the central India, northeast India and west coast of India, high cloud amount (optically thick), cloud optical depth and longwave CRF show high values over the same region, suggesting the link between CRF and strong rainfall activities over the Indian region. Whereas during winter season, over the southeast peninsular region, in resemblance with the low rainfall activities during October-December in 1988, these parameters also show low values. Opposite feature are seen for the deficient monsoon year 1987. All the parameters (rainfall, CRF components and cloud properties) has higher magnitudes during summer monsoon months (June- September) of 1988 than that of 1987 (Fig. 1). Opposite features are clearly seen in the

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winter monsoon months (October-December). Noticeable differences are observed between average CRF, cloud properties and all-India summer monsoon rainfall during excess and deficient monsoon years. Thus in general, analysis suggest that CRF plays an important role in the rainfall activities over Indian region. However, extensive analysis using long data period and with detailed statistical analysis is further needed to bring out the clear picture and also to quantify the results.

Figure 1. Annual cycle in terms of all-India monthly means of rainfall, cloud physical properties and CRF components for the years 1987 and 1988, averaged over the region 6.50N to 26.50N and 74.50E to 86.50E. (a) Rainfall (mm/day), (b) High cloud amount (%), (c) Cloud optical depth, (d) SWCRF (Wm-2), (e) LWCRF (Wm-2) and (f) NETCRF (Wm-2)

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Acknowledgements

The authors are grateful to Prof. B. N. Goswami, Director, IITM Pune, for providing the facilities and continuous encouragement during the course of the study.

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