IASTA 2010 Proceedings
+ Invited Talks
+ SESSION A - AEROSOL CHARACTERIZATION
A-O-1 Aerosol Effect on Precipitation...
A-O-2 Sunshine Duration Trend...
A-O-3 A Model Study of the...
A-O-4 Small Ion Concentration...
A-O-5 Vertical Distribution of...
A-O-6 Aerosol transport and...
A-O-7 Aerosol and Cloud...
A-O-8 Effects of Rain Drop-...
A-O-9 On the Association...
A-O-10 Evaluation of the Seasonal...
A-P-1 A Study on Distribution...
A-P-2 A Study on Optical...
A-P-3 The Relationship between...
A-P-4 Influence of Tropical...
A-P-5 Vertical Aerosol Profiles...
A-P-6 Dissimilarities in Maximum...
A-P-7 Measurement of the Atmospheric...
A-P-8 Assessment of Solid and...
A-P-9 Seasonal Variations in PM10...
A-P-10 Variation of Aerosol Optical...
A-P-11 Effect of Dust and Rain...
A-P-12 Aerosol Properties of the...
A-P-13 A Study of the Aerosol...
A-P-14 Retrieval of Background...
A-P-15 Influence of Charged Dust...
A-P-16 Number Density Characteristics...
A-P-17 Temporal and Spectral...
A-P-18 Numerical Estimation of the...
A-P-19 Lidar Measurements of Vertical...
A-P-20 Aircraft Observations of Cloud...
A-P-21 Aerosol Characteristics at High...
A-P-22 Seasonal Variability in Aerosol...
A-P-23 Spatial and Temporal Variability...
A-P-24 Airborne Measurements of Micron-...
A-P-25 Wintertime Vertical Profiles of...
A-P-26 Relationship between Pre-monsoon...
A-P-27 Seasonal Variation of Aerosol...
A-P-28 Influence of Aerosols on near...
A-P-29 Association between Stratosphere...
A-P-30 Response of Surface Ozone...
A-P-31 Aerosol Source Characteristics...
------------------------
+ SESSION B - AEROSOL REMOTE SENSING-I
+ SESSION C- RADIOACTIVE AEROSOL, HEALTH EFFECTS
+ SESSION D AEROSOL CAMPAIGNS / SPECIAL EVENTS
+ SESSION E AEROSOL REMOTE SENSING
+ SESSION F CARBONACEOUS AEROSOLS
+ SESSION G NANO PARTICLES SYNTHESIS
+ SESSION H AEROSOL CHARACTERIZATION II
+ SESSIONS I INDOOR AEROSOLS
IASTA-1

SESSION A

Aerosol Characterization I

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

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IASTA-2010

A–O–1

Aerosol Effect on Precipitation: Understanding from Microphysical Analysis

Anupam Hazra1,2 and Jen –Ping Chen2

1Indian Institute of Tropical Meteorology, Pune, India

2Department of Atmospheric Science, National Taiwan University,Taipei,Taiwan

Introduction

Aerosols are one of the key components of the climate system and the hydrological system (Ramanathan et al., 2001). Water soluble aerosols that act as good condensation nuclei for cloud drop formation are usually quite abundant in the troposphere. The situation may be different when ice-phase processes are involved, as many studies have shown that increasing cloud condensation nuclei (CCN) may actually result in more precipitation by enhancing mixed-phase precipitation formation (Lin et al. 1983) or by altering cloud dynamics as a result of enhanced latent heat release (Goswami et al. 2006). It get even more complicated when the aerosols of concern are insoluble particles which may induced ice formation by acting as ice nuclei (IN) for heterogeneous nucleation, a process none of the above studies have considered. This function of aerosols in modifying clouds and precipitation has been one of the most fascinating questions in cloud physics and climate change. In urban areas the effects of anthropogenic aerosols on precipitation are of great interest.

In this present endeavor the quantification of the microphysical effect of atmospheric aerosols on precipitation amounts on a regional scale (tens to several hundreds of kilometers) have been taken as a special interest. But when ice-phase microphysics is considered, aerosol effect on clouds and rains becomes more complex; for example, ice crystal can be initialized either from vapor deposition onto ice nuclei (IN) or from freezing of liquid drops, which are initialized from cloud condensation nuclei (CCN) activation. The mixed- phase cloud processes are sensitive to not only the soluble aerosols that serve as condensation nuclei for cloud drop formation but also the insoluble aerosols that serve as IN for the initiation of ice particles. The observation of climate change due to IN concentration change is even more difficult. Nowadays, the atmospheric aerosol concentration increases for human activities and some natural changes. Aerosol can play an important role as CCN or IN in the microphysical process of warm or cold clouds. In fact, ice nuclei are very important in many weather events. Some observations have showed that IN concentrations increased in some places, so we hope to know the influence of increased IN concentration on cloud properties and climate.

Model description

A non-hydrostatic mesoscale cloud model (MM5) modified with two-moment warm- cloud parameterization of Chen and Liu (2004; hereafter as the “CL-scheme”) which

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

considers the effect of condensation nuclei (CN) and explicitly predicts the masses and numbers of cloud drops and raindrops (Cheng et al., 2007). The warm cloud scheme is further coupled with the ice-phase processes of Reisner et al. (1998), here denoted as the “CLR-scheme” to examine the importance of ice processes on precipitation formation. It is one of the major challenges of cloud physics to improve the ice nucleation equations for different species in cloud models. More sophisticated laboratory experiments have been designed toward measuring the ice nucleation efficiency of specific types of IN (e.g., mineral dust, sea salt, soot, bacteria, spores, fungi, algae and pollen), and their results are crucial to the numerical study. Chen et al. (2008) reanalyzed several of these experimental results to provide physically-based parameterization formulas of heterogeneous ice nucleation from several types of IN.

Results & discussions

Figure 1a shows the final accumulated surface precipitation obtained during the cold front simulation for different IN species (e.g. bacteria, dust and soot) at various concentrations. This figure indicates that surface precipitation is significantly more for bacteria than dust & soot ice nuclei at lower concentration whereas at higher concentrations the results simply reversed. There must be important difference on the different microphysical properties for various species at two concentrations, lower (4 #/L) and higher (400 #/L) part. Therefore, in this present endeavor we are trying to explain the possible cause. Figure 1b depicts the average of total melting productions at different IN concentrations for bacteria. Thus, putting in more numerous or more effective IN might not be favorable to ice-phase precipitation formation. But the possible cause and explanations are not simple. Hence cloud microphysical budgets are important for concrete conclusions. The effect of surface emission of ice nuclei on precipitation formation involves many microphysical processes, which are highly complicated and uncertain in many ways. So, we focus on the role of bacteria (Pseudomonas syringae), mineral dust (Asia dust) and soot which acts as potential ice nuclei.

(cm) 2.30            
           
             
hours 2.25            
             
48              
after 2.20            
             
precipitation 2.15       bac    
           
        dust    
2.10       siit    
Surface          
2.05            
           
  0.04 0.4 4 40 400 4000

IN concentrations (#/L)

Figure 1a. Final surface precipitation for various IN at different concentrations

(mg/kg/hr) 18.0          
17.5          
           
oriduction 17.0          
16.5          
           
(raub 16.0          
15.5          
cikd          
15.0          
titak          
14.5          
if          
average 0.04 0.4 4 40 400 4000
  IN concentrations (#/L)    
       

Figure 1b. Average total melting Productions (snow+graupel)

They affect the ice phase processes, such as, accretion, Bergeron-Findeison, and heterogeneous immersion freezing nucleation processes. We already mention early that in

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IASTA-2010

this present simulation homogeneous freezing was turned off. We classified all production terms for cloud ice, snow and graupel into four category namely, initiation, deposition, riming and melting. Cloud ice initiation includes true heterogeneous nucleation by IN (e.g. bacteria, dust, soot) and ice multiplication process. Cloud ice, snow and graupel initialization are presented for two IN concentrations in Fig. 2. As more IN serves more nucleation sites and forms numerous number of ice crystals certainly cloud initiation becomes larger. Ice

Figure 2. Initialization of cloud ice, snow and graupel for two concentrations

Figure 3. Snow and graupel riming and total melting for two concentrations

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

nuclei which are more effective (e.g. bacteria) starts to produce more cloud ice at lower concentration.

Accretion is sometimes reserved for the capture of super cooled droplets. If ice crystal sizes are bigger, they fall quickly and freeze immediately on contact forming a coating of rime, leading to rimed crystals or snow flakes.

Conclusions

The increase of effectiveness of the ice nuclei leads to a larger number of mixed-phase particles with smaller radii and a strong reduction of liquid water mass. Microphysical changes influence the amount of precipitation for different species. However, the results agree with the expectation that the presence of the ice phase should cause an increase of precipitation. The precipitation is reduced the more, the higher the effectiveness of IN. For mixed phase clouds, the focus was on the sensitivity to varying efficiency of ice nuclei and also on the effect of a varying number.

It is obvious that there is some possibility of internal and external mixing of dust composition and we have to look into the solute effect of those substance. In our next attempt we do further research for this interesting topic that we already starts.

Ice nuclei concentrations impact on cloud microphysical processes and then surface precipitation. There is an optimum value of IN concentration where surface precipitation is maximum, below and after that value precipitation decreases. We analyzed the full spectrum, below that optimum concentration production of ice, snow & graupel is less. Whereas above that value ice, snow and graupel are more but less size that effects on riming and melting processes due to competition. Another important finding is this optimum value is not fixed/same for all kind of IN. It obviously depends on the nucleation ability of IN particles. Ice nuclei those have higher nucleating ability achieve optimum value early. Hence, IN is important rain spectrum shift & climate change studies now a day.

Acknowledgement

The authors acknowledge National Science Council (NSC), Taiwan for the sanction of the research project and the work forms a part of it. We are also thankful to referres for their valuable comments.

References

Chen, J.-P., Liu, and S.-T., Quart. J. Roy. Meteor. Soc., 123, 51-78, 2004.

Chen, J.-P, Hazra, A. and Levin, Z., Atmos. Chem. Phys. Discuss., 8, 14419–14465, 2008. Cheng, C.-T., Wang, W.-C., and Chen, J.-P., Quart. J. Roy. Meteor. Soc., 133, 283-297, 2007.

Goswami, B. N., V. Venugopal, D. Sengupta, M. S. Madhusoodanan and Prince K. Xavier, Science, 314, 1442, 2006.

Lin, Y.-L, Farley, R. D. and Orville, H. D., J. Clim. Appl. Meteorol., 22, 1065-1092, 1983. Ramanathan, V., Curtzen, P.J., Kiehl, J. T., and Rosenfeld, D., Science, 294, 2119-2124, 2001. Reisner, J., Rasmussen, R.M., and Bruintjes, R.T., Quart. J. Roy. Meteor. Soc., 124, 1071-1107, 1998.

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IASTA-2010

A–O–2

Sunshine Duration Trend During 1983-2007 over Indo- Gangetic Plain

Manoj K Srivastava1*, R K S Maurya1, B P Singh1, S Tiwari2, L Narain3, A K Srivastava2 and S. N. Pandey1

1Department of Geophysics, Banaras Hindu University,Varanasi – 221005, India

2Indian Institute of Tropical Meteorology – Delhi Branch, New Delhi – 110060, India

3Department of Geography, Mahatma Gandhi Kashi Vidyapith, Varanasi – 221002, India * Corresponding Author,Email: mksriv@gmail.com

Introduction

Aerosols influence incoming solar radiation through scattering and absorption and act in the process of cloud formation by acting as cloud condensation nuclei (CCN) (Warner and Twomey, 1967). Once inside the cloud, aerosols can change the quality of available water and thus give impact on the quality and quantity of radiation that passes the cloud. In other words, the aerosol is actively involved in influencing the natural radiation balance of the earth-atmospheric system.

Results obtained so far in this direction indicate that the increasingly large number of anthropogenic CCN could create smaller cloud droplets and decelerate the collision and coalescence growth of droplets.

The clouds thus formed generally do not precipitate; and the ‘immature’ cloud droplets float freely in the atmosphere to change the lifetime of clouds, and hence the cloud albedo, and the regional radiative budget (Twomey, 1974).

Researches towards sunshine intensity and duration show a long-term relationship between high cloud (Changnon, 1981, Liepert, 1997, Zheng et al., 2008) and low cloud (Rebetez and Beniston, 1998). The clouds which are formed either by the aircraft emissions (Liou et al. 1990; Frankel et al. 1997; Buocher 1998, 1999, Minnis et al. 1998) or ship contrails (Coakley et al. 1987; Radke et al. 1989) at high

Figure 1. Considered locations in the Indo-Gangetic Plain

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

or low level (Rebetez and Beniston, 1998) are found to be affected by anthropogenic aerosols.

Taking these results and their interpretations as a gap area over Indo-Gangetic Plains (IGP) and, so, to understand the behavior of cloud as a proxy for aerosol presence and dominance, the collected and quality checked data of sunshine duration for 4 Indian stations that belong to IGP have been analysed for the period 1883-2007 in this trend study. The considered stations are thoroughly spread over the IGP, extending from northwest (Amritsar) to northeast (Kolkata) and centrally located Allahabad and New Delhi. These data are selected on the basis of availability of long-term data of at least 10 years.

Data and General Weather in IGP

Monthly averaged sunshine duration data for meteorological stations from IGP region, where continuous data sets are available for at least 10 years, have been obtained from National Climatic Data Center, USA for the period 1983-2007. Consequently, a set of 4 stations have been identified for the analysis, which are shown in Figure 1. These stations are Amritsar, New Delhi, Allahabad, and Kolkata.

Climate of IGP can be understood as follows in brief: during Jan-Feb (winter), the IGP is under the influence of relatively strong western disturbance, whereas, during March- April-May (spring), effect of western disturbances, cases of afternoon thundershowers and cases of desert dust transport from Thar Desert is seen. During monsoon season, almost all the subcontinent, including IGP, experiences southwest monsoon cloud/rainfall. During post-monsoon season, however, mostly clear sky is found over northern India.

Result and Discussions

Figure 2 shows the anomaly of sunshine duration of the annual average for Indian Subcontinent from 1988 to 2007 along with the five-year running mean, as computed from stations from various locations around the continent, including island locations and mountains. The mean monthly sunshine duration for India is found to be ~195.0 ± 8.5 Hrs and suggest that the mean sunshine duration is decreasing at the rate 1.10 hrs/ year. If considered other way, this dimming can be interpreted as an increment in the aerosols content in the atmosphere due to the action of aerosols on the cloud development processes.

Figure 2. Average annual sunshine duration for Indian Subcontinent comprising 21 stations for the period 1988-2007 (vertical bars). The solid line represents 5-years running mean

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IASTA-2010

The 4 stations for IGP considered in this study pose different distances from the nearby sea. The closest being the Kolkata, followed by Allahabad, New Delhi and Amritsar. The IGP experiences the pre-monsoon and early monsoon showers apart from major precipitation during Indian Summer Monsoon. The routine daily-rhythm for these locations also experiences few days with evening thunderstorms during pre-monsoon. For IGP (Figure 3), the average monthly sunshine is found to be 197.00 ± 18.02 hours, which shows the maximum of ~222 hrs and minimum of ~171 hrs. The running mean informs an overall decreasing trend for the period 1983-2007, although, from 1993 till 2002, it was decreasing and since 2002 it is found increasing. Few years, from 1993-1998, although show a hump in the trend, but in decreasing trend. Annual linear trend inform a decrease at the rate of 2.10 hrs/ year during 1983-2007. Station-wise statistics are shown in the Table 1.

Table 1: Statistics for sunshine duration for various stations in Indo-Gangetic Plains

  Allahabad Amritsar New Delhi Kolkata
         
Average 171.81 222.60 191.91 177.33
Max 208.91 246.22 249.00 222.67
Min 136.78 172.89 149.42 149.42
Stdev 25.92 18.49 25.00 19.20
Number of data 10.00 24.00 24.00 23.00
         

Conclusions

With the study of sunshine duration of 21 stations over India, we have found that the sunshine duration for India has decreased between years 1988 and 2007, in general. To understand the behavior of regional aspect of sunshine duration, the considered stations have been selected from IGP, where at least 12 years of monthly average sunshine duration data is available. In all, this comprises 4 stations.

On the basis of 5 years running mean and annual trend computed for the period 1983- 2007, IGP show the decreasing rate of 2.10 hrs/ year. The results, as found, are alarming for the country like India, where the source of many activities run on the availability of sunlight. The trend may have been caused due to climate change related change in cloud

Sunshine Anomaly (Hrs)

40      
30      
20      
10      
0      
-10      
-20      
-30   Indo-Gangetic Plain
Average Monthly Sunshine : 197 Hrs
-40
Sunshine Anomaly Trend =-2.10 (Year)+28.02
 
-50      
      Years

Figure 3. Monthly variation of sunshine duration for Indo-Gangetic Plain, averaged for 4 locations

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

cover or due to increasing aerosols which are induced by changing land use pattern, but in any case, the changes are sensitive for future planning of the country and should be considered in such studies. Further, many other locations needs such computations for the regional planning.

Acknowledgements

Authors are thankful to National Climatic Data Center, USA for proving the data. Authors MKS and BPS are thankful to ISRO-ARFI for financial support.

References

Boucher, O., 1998, Note Interne du LOA No. 1, Laboratoire d’Optique Atmosphérique, UFR de Physique, Université de Lillie-I, Villeneuve d’Ascq, France, 17pp.

Boucher, O., 1999, Nature, 397, 30-31.

Changnon, S. A., Jr., 1981, J. Appl. Meteor., 20, 496-508.

Coakley, J. A., R. L. Bernstein, and P.A. Durkee, 1987, Science, 237, 1020-1022.

Frankel, D., K.-N. Liou, S. C. Ou, D. P. Wylie, and P. Menzel, 1997, Proceedings, Ninth Conference on Atmospheric Radiation, February 2-7, 1997, Long Beach, CA, Amer. Meteor. Soc., 414-417.

Liepert, B., 1997, Int. J. Climatology, 17, 1581-1593.

Liou, K.-N., S. C. Ou, and G. Koenig, 1990, In U. Schumann(ed.): Air Traffic And the Environment: Background, Tendencies,and Potential Global Atmospheric Effects. Springer-Verlag, Berlin, Germany, pp. 154-169.

Minnis, P., D. F. Young, D. P. Garber, L. Nguyen, W. L., Smith, Jr., and R. Palikonda, 1998a, Geophys. Res. Lett., 25, 1157-1160.

Radke, L. F., J. A. Coakely, Jr., and M. D. King, 1989, Science, 246, 1146-1148. Rebetez, M., and M. Benison, 1998, Geophys Res. Lett., 25, 3611-3613. Twomey, W., 1974, Atmos. Environ., 8, 1251-1256.

Warner, J., and S. Twomey, 1967, J. Atmos. Sci., 24, 704-706.

Zheng X, Kang W, Zhao T, Luo Y Duan C and Chan J, 2008, Geoph, Res, Lett, 35, L15707, doi:101029/ 2008GL034482, 2008.

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IASTA-2010

A–O–3

A Model Study of the Electrical Parameters of a Dusty

Mesosphere

N. Srinivas1 and K. Narasimhamurthy2

1 Department of Post Graduate Studies in Physics (Mysore University), Government Autonomous College, Mandya-570401, Karnataka State, India.

(On Deputation from Maharani’s Science College for Women (Mysore University), Mysore-570 005, India

2 Professor(Retd), Department of Physics, Maharani’s Science College for Women, Mysore, India

ABSTRACT : Considerable quantities of small dust/aerosols of meteoric origin are present at all heights and latitudes in the mesosphere. These particles are known to have an important role to play in the Physics and ion-chemistry of the region. In the dusty mesosphere, the contribution of charged dust to the electrical conductivity, and hence to the electric fields, is known to be important.

In the present paper, a model study has been attempted to compute the background conductivity and electric field profiles for an equatorial dusty mesosphere under quiet daytime condition. The results presented are for small particles of size (radius) 5 nm or less. The results of this study indicate the possible role of small dust particles in modifying the electrical conductivity resulting in an increase of the electric field strengths in the region.

Preamble

Studies of the mesospheric electric fields and conductivity are very important from the point of understanding the electrical state of the atmosphere, sun-weather relationship and so on. Vertical electric fields with strength exceeding 1 V/m have been detected in the lower mesosphere in several experiments. There is a need to study the role of large vertical electric fields in the physics and the chemistry of the middle atmosphere (Zadarozhny and Tutin, 1998). The extremely low effective conductivity of the mesospheric dusty plasma, often observed in experiments, is shown to explain the existence of V/m vertical electric fields observed in the lower mesosphere Zadarozhny (2001).

The role of dust on the electrical structure of the mesosphere has been discussed by several research groups in the past (for example, Aikin and Maynard, 1990). Direct link between the mesospheric electric fields and dust content have been observed in experiments (Zadarozhny, et. al., 1994).

This points out the need to study the role of heterogeneous ion-chemistry in the mesosphere and also the importance of charged dust in the production of the V/m vertical electric fields in the region. In this background, a model study has been attempted to compute the background height profiles of the electrical conductivities and electric fields of a dusty mesosphere. Some of the results obtained for equatorial quiet daytime mesospheric conditions are discussed in this paper.

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

Fig. 1a

Fig. 1b

Fig. 1c

Fig. 1d

Model, methodology and results

The equations employed/derived in this study are shown in Appendix-1 and a brief methodology of computation is given in Appendix-2. It is well known that the equatorial mesospheric conditions do not support formation of large particles. Hence only small particle sizes are assumed in the computations. The present results are for the assumed dust sizes of 0.5, 1, 2 and 5 nm only. The results of this study are shown for the equatorial mesospheric region (60—90 km).

The average charge per particle, positive and negative dust ion densities and the molecular ion densities are computed using the detailed heterogeneous model (Srinivas, 2008) where the experimental electron density [e] (used as input to the model) is assumed after Chakrabarty et al (1989). The method of computations of various ion densities is discussed in detail by Srinivas et al. (2007).

The model-derived electrical conductivity profiles, with and without dust, are shown for different dust sizes in Figs. 1a, 1b, 1c and 1d. These dust profiles show a similar height variation for all the dust sizes. Careful observation of these figures shows that the conductivity of the mesosphere decreases by about two orders of magnitude with respect to increase in the dust size by one order of magnitude. Comparison of sDe with se, si+ with sD+, sj- with sD- in Figs. 1a—1d clearly indicates the effect of dust on the electrical conductivity of the mesosphere. It is also clear from these results that the role of dust in reducing the atmospheric conductivity is non- negligible at all heights of the mesosphere, and is significant at lower mesospheric heights. The conductivity profiles from this model show a general agreement with experimental conductivity profiles of the mesosphere both with respect to height variation and magnitude at any given height.

Reduction in the conductivity naturally leads to an increase in the electric field for any given height.

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This is demonstrated in Figs. 1a through 1d. An increase in the dust size from 0.5 nm to 5nm (one order of magnitude) is seen to increase the electric field by two orders of magnitude (Figs. 1a—d). In Fig. 1a, E+ 1 V/m is observable around 60 km altitude for 0.5 nm dust particles in the region. In Fig. 1d, E - 1 V/m occurs at the same height for r=5 nm. Thus it is evident that presence of small particles of size 5 nm or less can account for the often observable high electric field of the order of 1 V/m in the lower mesosphere.

In Figs. 1a—1d a sudden increase in the E- around 75 km is observable irrespective of dust size. In the model computations, the steady state dust density profiles show a steep layer of negatively charged dust in this region. In the MST radar echo studies over low latitude (Gadanki, Tirupati) enhanced echoes are constantly observed from this height during daytime throughout the year. Thus the structure in E- profile around 75 km altitude (Figs. 1a—1d) may be indicative of the role of dust in enhancing the MST radar echoes observed from the lower mesospheric region.

Acknowledgements

One of the authors (NS) is grateful to the University Grants Commission, New Delhi, India for financial support to this research work under Letter No. MRP(S)-047/07-08/ KAMY004/UGC-SWRO Dated 28 March 2008.

References

1.Zadorozhny, A. M. and Tyutin, A. A., Effects of geomagnetic activity on the mesospheric electric fields, Ann. Geophys., 16, 1544-1551, (1998).

2.Zadorozhny, A. M., Effects of charged dust on the mesospheric electrical structure, Adv. Space Res., 28: 1059—1064, (2001).

3.Aikin, A. C., and Maynard, N. C., A van de Graaf source mechanism for middle atmospheric vertical electric fields, J. Atmos. Terr. Phys.,52: 695—705 (1990).

4.Zadorozhny. A. M., Kikhtenko, V. N., Kokin, G. A., Tuchkov, G. A., Tyutin, A. A., Chizhov, A. F. and Shtirkov, O. V., J. Geophys. Res, 99: 21059—21069 (1994).

5.Srinivas, N., Prasad, B.S.N., Jayati Datta and Chakravarty, S.C., Application of heterogeneous mesospheric ion-chemistry model to MST radar echoes over low latitude, Adv. Space Res., 39: 1256-– 1266, 2007.

6.Chakrabarty, D. K., Beig, G., Sidhu, J. S. and Das, S. R., Fine scale structure and turbulence parameter of the equatorial middle atmosphere, J. Atmos. Terr. Phys., 51: 19-17, 1989

7.Srinivas, N., A detailed ion-aerosol/dust model study of an equatorial mesosphere, Research Project Report No. Phy/1-2008, Submitted to the University Grants Commission, New Delhi, India, Maharani’s Science College for Women, Mysore, India-570 005, April 2008.

8.Subbaraya, B.H., Prakash, S. and Gupta, S.P., Electron densities in the equatorial lower ionosphere from the langmuir probe experiments conducted at Thumba during the years 1966—1978. Sci. report ISRO-PRL-SR-15-83, Indian Space Research Organization, Bangalore, India, 1983.

Appendix-1: The Model Equations

The ionic/electronic conductivity of the mesosphere is given by

(1)

where Zi.e. is the number of charge on ion/electron (=1), ni.e. is the number density of ions/electrons, KB is the Boltzmann constant, e is the elementary charge, T is the absolute temperature and

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AEROSOLS & CLOUDS : CLIMATE CHANGE PERSPECTIVES

Di.e is the ion/electron diffusion coefficient (available from standard data). The diffusion coefficient for the dust particles is given by (Zadorozhny, 2000)

(2)

where the subscript p, refers to the particle, [N], r and μ are respectively the neutral density, radius of dust particle and reduced mass, respectively. Obviously μ is given by

(3)

where m represents the mean mass and the subscript a refers to air particle. Now the electric field generated by the downward falling charged dust is given by (Aikin and Maynard, 1990)

(4)

where the subscript z denotes the vertical direction, Z is the number of elementary charges on the dust particle, Np is the number density of the charged particle of interest and Vp is its fall speed, given by (Jensen and Thomas, 1988):

(5)

where pp is the density of the particle material, g, the acceleration due to gravity and P is the atmospheric pressure at any given height. The conductivity due to charged dust particles is given by [similar to Eq. (1)]

(6)

The effective conductivity is given by

(7)

and the effective electric field is now given by [similar to Eq.~(4)]

(8)

Appendix-2: Methodology of Computation

1.Take standard data on e, KB T, Di, Zi,e = 1, compute ni from the Heterogeneous ion-chemistry model [Srinivas(2008)] from experimental data on [e] as input to the model. Compute si,e from Eq.~(1), Appendix-1.

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IASTA-2010

2.Take [N], ri,e, ma as standard data. Assuming r and = 2 gm/cc compute mp assuming that the particle is spherical. Find μ and then Dp± from Eqs. (3) and (2), Appendix-1, respectively.

3.Take P and g from standard data. Find Vp from Eq.~(5), Appendix-1.

4.Compute Zpi,e and Npi,e using the HIC model [Srinivas(2008)] from experimental

[e]as input to the model. Compute seffi,e from Eqs. (6) & (7), Appendix-1.

5.Compute from Eq. (8).

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A–O–4

Small Ion Concentration and its Dependence on Aerosol Size Distribution

Nagaraja K1, BSN Prasad2, SD Pawar3, P Murugavel3 and V

Gopalakrishna3

1Department of Physics,Bangalore University, Bangalore – 560 056

2Former Professor, University of Mysore,Mysore – 570 006

3Indian Institute of Tropical Meteorology, Pune – 411 008

* Corresponding author, E-mail: kamsalinagaraj@bub.ernet.in

ABSTRACT : The electrical conductivity of air is entirely due to small ions and depends upon the number of small ions present in the atmosphere. The conductivity decreases if the small ion concentration reduces. The small ion concentration is altered by the presence of aerosols due to attachment with aerosols, apart from the usual loss due to mutual recombination between the ions of opposite polarity. To see the variation of the small ions, the aerosol concentration alone is not sufficient, and it envisages the measurements of number concentration of aerosol along with their sizes. The size distribution of aerosols will provide actual concentration of small ions. The percent decrease in small ion concentration reaches about 32% in the afternoon when aerosols concentration had shown its maximum over a typical day.

1. Introduction

The electrical conductivity, ion mobility and small ion number density are important for understanding the electrical nature of the atmosphere. The small ions consisting of aggregates of a few molecules practically determine the electrical conductivity over the region. The number densities of these ions are controlled by ionizing mechanisms for the production of ions and electrons and the loss processes for these charged species. Ion - production is chiefly due to radioactive substances present in the earth’s crust and the cosmic rays coming from the extra - terrestrial origin, and the resulting electrons and positive ions rapidly undergo hydration reactions which lead to the formation of negative and positive molecular ion clusters referred to as small ions. Only singly charged ions are important since the cross section for the production of multiply charged ions by particle impact are smaller than those for the production of singly charged ions by an order of magnitude. Further, the multiply charged ions that are formed will rapidly undergo charge transfer reaction within neutral molecules to result in singly charged ions. The small ions have mobilities large enough to move appreciably under the influence of electric field and thus determine the electrical conductivity of the atmosphere.

The higher mobility small ions, which are formed due to ionization, attach themselves to the larger aerosol particles and form smaller mobility larger ions. Aerosol concentrations and the rate of ionization due to ground radioactivity close to the earth’s surface largely depend upon the prevailing meteorological conditions. The conductivity is one of the important parameters for understanding the electrical nature of the earth’s atmosphere

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and is sensitive to the presence of aerosols. Thus, variation of small ion concentration depends not only on the aerosols but on the size distribution of aerosols. Considering this an effort is made to understand the variation of small ions and its dependence on the size distribution of aerosol.

2. Experimental Methodology

Radon and its progeny concentration:

Estimation of radon concentration in air above the surface is made using the Low Level Radon Detection System. The procedure consists of sampling the air in a collection chamber and exposing a circular metallic disc to the radon inside the collection chamber. The collection is carried out for an optimized period and thereafter the charged plate is removed from the chamber and alpha-counted and then the concentration of radon is calculated.

An air flow meter is used to measure the radon progeny concentration. Air is drawn through a glass fiber filter paper by means of a suction pump at a known flow rate. The radon progeny in air sample are retained on the filter paper. The filter paper is then alpha-counted at any specific delay time. Total activity on the filter paper is measured at different counting intervals and the activity is calculated.

Aerosols and electrical conductivity:

The aerosol measurements were made with Electrical Aerosol Analyzer. It is capable of performing rapid in situ size distributions on aerosols from 0.003 to 1 m diameter. The instrument is based on the diffusion charging mobility analysis principle. The atmospheric electrical conductivity of both positive and negative polarities is simultaneously measured with two Gerdien condensers housed separately in a single unit.

3. Results and Discussion

It is observed that the concentration of radon and its progeny follow the trend of the relative humidity, in general. This is due to the fact that as temperature increases, the saturation vapour pressure increases so that the given air can take more water vapour. Consequently the relative humidity will decrease. The raise of temperature causes increased vertical mixing and rising of aerosols to the higher altitudes resulting in lower concentration of radon at the ground level. When the temperature decreases and relative humidity increases, the vertical mixing and raising of aerosols to the higher altitude reduces. As a consequence, the aerosol to which radon is attached, will be present at higher concentrations during night and in the early morning hours at ground level. This results in the increase of radon concentrations near the surface of the earth.

Figure (1) represents two hourly values of the aerosol concentration obtained for each of the eight size categories in the range of 13 to 750 nm. It shows a diurnal variation with the concentration showing a minimum during the early morning around 0600 hours IST and an increasing trend towards noon-hours. Early in the morning, due to anthropogenic activity and also due to the onset of convection resulting from the increase in atmospheric temperature, aerosols are pushed into the atmosphere resulting in an increased aerosol concentration.

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The size distribution of aerosols is plotted in Fig. (2). Size distributions are generally bimodal with their maxima at 75 and 23 nm during night (1800 to 0400 hrs). After 0400 h with slight shift in maxima in the accumulation mode towards the higher size. During daytime, particularly in the afternoon, the shift in maxima in the accumulation mode to a higher diameter of 133 nm is distinct and the maximum in the nucleation mode seems to shift to smaller diameter.

As a result of increase in the concentration of small particles, the size distribution curves during daytime are mostly open ended at the small particle side. The magnitude of the peaks varies with time.

Figure 1. Diurnal variation of aerosol concentration

Figure 2. Size distribution of aerosols

The number of ion densities gives rise to the conductivity of the atmosphere. The positive and negative conductivities observed are approximately equal and their diurnal variations are generally mirror images to each other. It is observed that the conductivity of both polarities show maxima in the early morning hours, it decreases after sunrise, and attains minimum in the afternoon. This is due to the fact that the raise in temperature causes increased vertical mixing and rising of aerosols to the higher altitudes, which results in the lower value of ionization rate, and hence conductivity at the ground level. Also it depends on the size distribution of aerosols and their attachment and recombination processes on small ions. During nighttime the atmosphere is relatively calm with low

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winds and little convective motion. The radon exhaled from the soil therefore accumulates near the ground and leads to increased ionization and higher conductivity. After sunrise, due to human activity and also due to the onset of convection resulting from the increase in atmospheric temperature, aerosols are pushed into the atmosphere. This causes a conversion of small ions that are responsible for conductivity, into large ions through attachment, and an increase in the destruction of small ions through recombination with large ions of opposite polarity. The onset of circulation also removes radon from near the ground to higher altitude regions. These factors contribute to the observed reduction in conductivity in the afternoon. In the evening, with decreasing ground temperatures and also the anthropogenic activity, the aerosols that had been pushed to higher altitudes begin to settle down, and a greater fraction of small ions is lost through attachment. Finally, at nightfall, the aerosols settle down, and the conductivity recovers its normal night time high values.

Influence of aerosols on ions is well known. The percent decrease in small ion concentration also shows a diurnal variation with a minimum in the early morning hours when the aerosol concentration is minimum and reaches a maximum of 32% in the afternoon when aerosols also show maximum. Due to pollution the concentration of aerosols increases and leads to decrease in concentration of ions in the atmosphere. During early morning the concentration of aerosols is less and the conductivity is more. Convective currents in the morning carry aerosol particles up from ground surface by combination; change the high mobility small ions into low mobility large ions. Thus the conductivity decreases after sunrise. As the day advances the aerosol concentration increases due to anthropogenic activities and conductivity decreases. The percent decrease in conductivity shows a diurnal variation with a minimum in the early morning hours when the aerosol concentration is minimum and reaches a maximum in the afternoon when aerosols also show maximum for background aerosols. Due to pollution the concentration of aerosols increases and leads to decrease in conductivity of the atmosphere near the surface. This gives an idea that the measurement of conductivity can be used as an index of pollution measurement provided the existence of data on size distribution of aerosols.

Summary

The small ion concentration and hence the electrical conductivity of the atmosphere is mainly due to the radioactive substances in the earth’s crust and their emanation near the surface. The radiations emitted by the radioactive substances ionize the atmospheric air and leads to conductivity. The conductivity gets altered because of the existence of aerosols in the atmosphere. While considering the aerosols, the number distribution alone is not sufficient but demands for the size distribution of aerosols. With this it is possible to give satisfactory explanation for the production and loss of small ions.

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A–O–5

Vertical Distribution of Aerosls over tropical urban site Hyderabad

P. R. Sinha1, U. C. Dumka1, R. K. Manchanda1, Y Bhavani Kumar2 and S. Sreenivasan1

1Tata Institute of Fundamental Research, National Balloon Facility, Hyderabad 500 062, India 2National Atmospheric Research Laboratory, Gadanki,India

E-mail: ucdumka@gmail.com

1. Introduction

The knowledge of the altitude profile of aerosols is very important in estimating its radiative forcing. In order to study the vertical profile of aerosols a micro pulse Lidar (MPL) system was installed at tropical urban site Hyderabad by National Atmospheric Research Laboratory (NARL), Gadanki, under a joint scientific collaborative programme between National Balloon Facility (NBF), Tata Institute of Fundamental Research (TIFR), Hyderabad and NARL. The Lidar system was operated during April 2009 to November 2009. During the observation Lidar system has collected backscatter return signal from the lower atmospheric aerosol and also high altitude cloud such as cirrus. In this paper we present the preliminary results of observed Lidar profiles during April 2009 to December 2009 as well as to investigate diurnal cycle of planetary boundary layer structure.

2. Experimental Details and Data Base

The portable micro pulse LIDAR [popularly known as Boundary Layer Lidar (BLL)] was developed by National Atmospheric Research Laboratory (NARL) Gadanki [Bhavani Kumar, 2006], to monitor the vertical profiles of atmospheric aerosol properties in the lower troposphere has been installed in a temperature and humidity controlled room. The operation principal of BLL is based on micro pulsed LIDAR (MPL) technology [Spinhirne, 1993]. The LIDAR observations are carried out at Hyderabad on regular basis to study the aerosol vertical profile, boundary layer structures etc. Further more details of the instruments and data analysis are given elsewhere [Hegde et al., 2009]. For the present study the LIDAR measurements are analysed for the periods of April 2009 to December 2009. Generally the measurements were made from 1900 Indian Standard Time (IST) to 2400 IST, but for few occasions the data were recorded for entire night (1900 IST to 0500 IST).

3. Results and Discussion

The Portable LIDAR system has been successfully used to study the evolution of boundary layer dynamics, spatial and temporal variations of atmospheric boundary layer (ABL), monitoring of low and high level clouds and the height profile of lower tropospheric aerosols at 532 nm wavelength have been derived using the standard Klett [Klett, 1985] technique.

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The aerosol backscatter measurements are obtained in the lower troposphere using the Fernald-Klett inversion algorithm [Fernald, 1984; Klett, 1985] and employing standard atmospheric molecular data, the height profiles of aerosol backscatter were derived up to an altitude range of 5 km with an altitude height resolution of typically 30 m. A typical profile obtained from the Boundary Layer Lidar (BLL) system during the period between 19:35 to 19:47 Hrs on 16th April 2009 is shown in Figure 1. On some night time measurements there are a thin layer of aerosols exists in the free troposphere in the altitude region of 2 to 4 Km (See Figure 2). Figure 2 shows the time series profiles of range corrected for photon count and range corrected signal measured over Hyderabad for 16th April 2009. All the profiles correspond to a time integration of 50 minutes. A layer of thick cirrus clouds clearly seen in the

Figure 1. Vertical profiles of back scatter coefficient ( ; m-1 sr-1), extinction coefficient (a; km-1), back scatter ratio (R), range corrected photon count and range corrected signal for 16th April 2009

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upper troposphere at heights between 10 to 14 km above the ground level (Figure 2). The BLL system was operated for a period of 20 days during April to November 2009 between 19:00 and 24:00 Hrs. The LIDAR profiles obtained on each day is further averaged and the daily mean aerosol profile for each day is computed. Most of the time a thick aerosol layer was always present in the lower most troposphere, which is around ~1.5 to 3 Km above the ground level and which corresponds to the local mixing.

Figure 2. Time series of range corrected photon count (Left) and range corrected signal (Right) for 16th April 2009

4. Conclusions

The boundary layer lidar was developed to study the vertical profiles of aerosol properties in the lower atmosphere and has been in regular observation since April 2009. The Lidar observation over the tropical urban site Hyderabad has indicated the presence of a aerosol layer in the lower most troposphere, which was considered as the local mixing layer. Also the lidar profiles reveal the presence of cirrus clouds at an altitude of 10 to 14 Km above the ground level.

Acknowledgements

This work was carried out as a part of Indian Space Research Organization, Geosphere Biosphere Program (ISRO-GBP). The authors are thankful to the Director NARL Gadanki for their encouragement to undertake this work.

References

1.Spinhirne, JD, IEEE Transaction on Geosciences & Remote Sensing, 31(1):48-54, 1993.

2.Fernald F. G, Applied Optics, Vol 23, 652-653, 1984.

3.Klett JD., Applied Optics, Vol 24, 16382-1643, 1985.

4.Bhavani Kumar Y, Journal of optical Engineering, 45(7): 076201, 2006.

5.Hegde et al., Atmos Sci Let, 10: 48-57, 2009.

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A–O–6

Aerosol transport and atmospheric extinction over India using the STEM model

Pankaj Sadavarte1, Chandra Venkataraman 1, Sarika Kulkarni2, Greg Carmichael 2, Kuldeep Sharma 3 and Akshara Kaginalkar 3

1 Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai 400 076, India

2 Centre for Global and Regional Environmental Research, University of Iowa, USA

3 Centre for Development of Advanced Computing, Pune

Background and Motivation

Aerosols are significant contributors to atmospheric extinction and play an important role in atmospheric heating patterns by scattering and absorbing solar radiation. Recent studies indicate that the variations in heating patterns affect the monsoon rainfall patterns by modulating cloud processes (Lau et al., 2006). These studies hypothesize that patchy atmospheric heating is responsible for uneven distribution of rainfall which could affect the monsoon in the Indian region. Therefore, a better understanding is needed of aerosol origin and transport over India.

A field program TIGERZ, was conducted from April 2008 and April – November 2009 to investigate the elevated heat pump hypothesis (Lau et al., 2006) which states that uplift of anthropogenic aerosols during April – May in the Indo-Gangetic Plain (IGP) and the neighboring Himalayan region and Tibet could result in early advance of monsoon into the IGP. Spatially and temporally resolved anthropogenic aerosols affect aerosol heating patterns. This study investigates aerosol transport, using a state of the science chemical transport model, to assess spatial distribution of aerosol surface concentration and burden over the Indian region, during June-September, 2008.

Methodology and data sets

Atmospheric simulations were made at the University of Iowa with tracer version of the STEM chemical transport model (Carmichael 2003). We use offline WRF-Meteorology to run the model with horizontal resolution of 27 km x 27 km and vertical resolution of 41 layers. The meteorology pre-processor of STEM used to calculate sea-salt emissions based on rate of sea water droplet generation per unit area of sea surface and dust emissions were calculated online. Dry deposition scheme is based on a parameterization which uses the resistance is series for deposition flux. Wet deposition is parameterized as first-order loss rate with precipitation. The model uses the SCAPE module to calculate soluble ion species and water content of the aerosols.

The model uses fixed/variable initial and boundary condition from MOZART/RAQMS. The simulation domain over Asia included China, South Korea, Japan and the Indo-

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Gangetic plain stretching from Pakistan over India and the neighboring Himalayas and the East part of India along with Bangladesh and Myanmar. Emissions for Asia (Zhang et al., 2006) included estimates for China based on improved methodologies and integration of national emissions for various countries like India and Japan, projected to 2006.

Figure 1. Schematic figure of STEM2K1 regional-scale modeling system

The AOD module calculation is based on aerosol concentration amount and aerosol species – specific extinction co-efficient for dry sea salt, 3.45, 0.69, 0.20 m2g-1 for diameter in size range from 0.2 to 2 m; 2 to 8 m and 8 to 20 m, respectively and 9.94 m2g-1 for sulfate. The aerosol species under consideration for the simulation are BC, OC, SO2, Dust, Sea-salt, Sulfate and the balance of particulate mass designated “other PM” or OPM2.5 and OPM10.

Figure 2. Results from preliminary runs for TIGERZ sites

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Preliminary results

Preliminary runs have been made using the STEM model for June - July 2008. Figure 2 shows the model predicted daily mean surface concentrations of BC, OC and SO2 at Delhi and Kolkata, which were among TIGERZ sites.

Simulations will be made for June-July, 2008, to obtain complete spatial distributions of the chemical species over the Indian subcontinent. The results obtained will be evaluated against available measurements of AOD and aerosol species concentrations. The paper will evaluate aerosol distributions and assess the contribution of carbonaceous species to aerosol loading and AOD over the Indo-Gangetic plain.

References

1.Carmichael, G. R., et al., Regional-scale chemical transport modeling in support of the analysis of observations obtained during the TRACE-P experiment, J. Geophys. Res., 108(D21), 8823, doi: 10.1029/ 2002JD003117, 2003.

2.Lau, K. M., M. K. Kim, and K. M. Kim (2006) Aerosol induced anomalies in the Asian summer monsoon- the role of the Tibetan Plateau, Climate Dynamics, 26 (7-8), 855-864.

3.Q. Zhang et al., Asian emissions in 2006 for the NASA INTEX-B mission, Atmos. Chem. Phys., 9, 5131

– 5153, 2009.

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A–O–7

Aerosol and Cloud Characteristics over the Normal and Rain Shadow Regions in India

R.S. Maheskumar1, J.R. Kulkarni1, Mahen Konwar1

and Daniel Rosenfeld2

1Indian Institute of Tropical Meteorology, Pune, India

2The Hebrew University of Jerusalem, Jerusalem, Israel

Introduction

Rainfall processes in the clouds occur in variety of pathways and atmospheric aerosols have been found to play an important role in cloud microphysics. It is important to understand the pathways through which aerosols modify clouds and lead to precipitation. Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX) is an Indian National Program conceived and conducted by the Indian Institute of Tropical Meteorology (IITM), Pune, funded by the Ministry of Earth Sciences, Govt. of India. CAIPEEX has two components viz. (1) Cloud–Aerosol interaction and (2) Precipitation Enhancement. Understanding of cloud-aerosol interaction is pre requisite for the second component. Aircraft observational programme has been conducted as a part of the first component, that is Phase-I. CAIPEEX Phase-I had the following objectives : (i) To measure background concentrations of aerosols and CCN during the pre-monsoon and monsoon periods over the country, (ii) Observations of hydrometeors in the clouds, (iii) Cloud simulation studies by NWP models, and (iv) Selection of sites for the second phase experiments. The Phase-I aircraft observations have been conducted during the period from May-September 2009 over different parts of the country.

Data and Observations

The Arabian Sea branch of the SW monsoon first hits the West coast of the Indian sub- continent and rain heavily over the western slopes of the Ghats. Over the eastern slopes and further east over the plains, the rain shadow effect supresses the rainfall and causes scarcity of water. The interior part of the peninsular India is rain shadow region. The seasonal monsoon rainfall there is lower compared to all India mean monsoon rainfall. The rainfall variability is larger and the region is drought prone. The CAIPEEX Phase-I observations provided a suitable opportunity to study the variability in the aerosol and cloud microphysical properties over the rainy regions (Western Ghats) and rain shadow regions to the east.

CAIPEEX research flights, equipped with probes for sampling aerosols, cloud microphysical parameters and meteorological parameters, using the methodology discussed in the references (Andrea et al., 2004 and Rosenfeld et al., 2008), were conducted from Bengaluru towards Arabian Sea through the rain shadow regions and over the Western Ghats during 3-13 July 2009. The data collected during this period has been utilized for

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this study with following objectives :

To find the role of cloud–aerosol interactions in the primarily dynamically controlled distribution of rainfall.

To understand the sensitivity to aerosols which would explain a possible further reduction of precipitation due to air pollution, and,

In the case that sensitivity to aerosols is found, explore the potential for rain enhancement by cloud seeding.

Figure 1. Regions of study

The study area is shown in Figure 1. The clouds were raining out over the Arabian Sea (1a) and over the western slopes of the Western Ghats (1b). Heavy dust haze was found over the west coast extending up to depth of about 4 km. Large drops up to about 40 micron appeared at the cloud base, probably induced by dust and sea-salt giant CCN . The clouds grew to 3 km for onset of warm rain. The clouds consolidated over the western slopes with tops that coincided with the top of the haze layer at 4 km.

Top of the Western Ghats the air became cleaner as the heavy precipitation washed- out the dust. The Clouds acquired gradually more continental nature over the eastern plains (3 & 4) and became polluted towards Bengaluru (5). Convection was subdued just to the east of the top of the Western Ghats, and gradually recovered further east.

Results and Discussions

The clouds (Figure 2) over the Arabian Sea and over the Western Ghats (1a & 1b) were thermodynamically maritime with heavy desert dust. The warm rain initiation is at ~ 3000 m. The heavier rain over the western slopes (1b) washed out the aerosols and consumed the instability. Therefore, clouds down the slopes (2) were weak and initiated warm rain at about 2500 m despite the higher bases (Figure 2). When the air moves further east (3), the solar heating during daytime renews the convection, which becomes gradually deeper. The added air pollution increases the altitude for initiation of warm rain (Figure 2). Further east up to about 250 km (4 & 5), the clouds have to grow deeper (4000-6500 m) to initiate the warm rain process due to their “continentalization” (Figure 2).

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Figure 2. Variation in the altitude of warm rain initiation in different regions

In summary, the warm rain initiation starts at early stages (lower cloud depths) over the coastal areas and becomes even lower at the crest of the western slopes, probably due to intense washout of the aerosols by the rain. However, the clouds lose their microphysically maritime character farther east over the rain shadow regions, where the clouds have to grow to higher depths to initiate the process.The aerosol and CCN concentrations support the hypothesis that the shallow convective clouds (i.e., with tops < 6 km) lose their ability to rain over the rain shadow due to increased aerosols concentrations, which are probably contributed to by air pollution.

References

1.Rosenfeld D., W.L. Woodley, D. Axisa, E. Freud, J.G. Hudson and A. Givati, Aircraft measurements of the impacts of pollution aerosols on clouds and precipitation over the Sierra Nevada. J. Geophys. Res., 113, D15203, doi:10.1029/2007JD009544, 2008.

2.M. O. Andreae, D. Rosenfeld, P. Artaxo, A. A. Costa, G. P. Frank, K. M. Longo and M. A. F. Silva- Dias, Smoking rain clouds over the Amazon, Science, 303, 1337-1342, 2004.

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A–O–8

Effects of Rain Drop-size-distribution on Earth-space Radio Path at Darjeeling

S. Singh, S. K. Ghosh, A. Mitra and S. Raha

Centre for Astroparticle Physics and Space Science(CAPSS),

Bose Institute, Kolkata

E-mail : soumendras@gmail.com

ABSTRACT : The present day trend of growing telecommunication services, especially in the earth-space path through satellites, is significantly noticeable in higher microwave bands above 10GHz, particularly in Ku(14-11GHz) and Ka(30-20GHz) bands. The presence of hydrometeors in such propagation, particularly rain, could produce real impairments to the received radio signal on the earth. For all weather reliability it has become necessary to study the effects of rain on this propagation path. The raindrops find its passage to the earth by scattering, absorbing and finally getting transmitted through the radio path causing attenuation to the transmitted signal from the satellite. Thus such signal attenuation becomes a function of rain drop-size- distribution (DSD), which in turn depends on the type of cloud, its height, extent and rate of precipitation. There are several DSD models available, e.g., Laws and Parsons [1] and Marshall and Parmer [2] and many more. These DSD models are different for its application at the temperate or tropical region. It has been found that there is so far no unique DSD available over vertical profile of rain for which the radio attenuation at Ku band signal could be correlated at this location.

Introduction

In this paper a quantitative study of radio signal attenuation in the earth-space microwave satellite link through Ku band DTH receiver has been done in conjunction with simultaneously available data of rain over vertical atmosphere as well as that of surface. The dependence of DSD for same ground rain rate with simultaneously varying rain rate/DSD over altitude, where the Ku-band link signal attenuations are different, was observed. There has been a dearth of data for Ku band microwave signal propagation study during rain for a high altitude location. It is evident from the bright band observed in the micro-rain radar that the height of the zero degree isotherm at this high altitude location is one of the key parameters in the formation of rain drops.

Instrumentation

In the experimental set up a Laser precipitation monitor (Thies Clima, Germany) has been used to obtain surface rain parameters, whereas the Micro-rain Radar(Mode:MRR-2, METEK, Germany) at 24.1GHz measures in FMCW mode rain rate(mm/hr), DSD and rain drop velocity profiles with altitude in vertical looking mode with range gates of 150m up to 4.5 km altitude at Darjeeling. Here we have used indigenous commercial Ku- band microwave link receiver meant for DTH( Direct-to-Home) signal reception through TV( before viterbi correction stage) as earth space satellite link signal. Ku-band DTH signal from INSAT-4B (93.5 Deg. E) is being received with offset parabolic dish antenna of 60 cm

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diameter and elevation angle 62.5°. The received QPSK modulated signal frequency is at 11.57 GHz and was vertically polarized. The output of the low noise block (LNB) converter at the dish is connected to satellite receiver. The AGC voltage from satellite receiver is collected through a Data logger with suitable computer interface. Received power fluctuation at the LNB input is proportional to the AGC voltage change which follows a linear relationship with received power. The Satellite Signal-level meter(Promax,Prolink- 4C) connected with Ku-Band receiver also records Channel power level, Carrier to Noise Ratio, the “Bit Error Rate” (before and after vitervi) with integration time of 40 Sec. The signal attenuation due to rain is calibrated using the average clear day signal strength on days prior to and after the rainy day(s). The average clear day signal level maintains an approximate level of 15 dB. Thus the effective dynamic range of our system is 15-16 dB. Laser Precipitation monitor measures surface rain rate(mm/hr) and DSD in 1 min interval. All the sensor outputs are finally connected to data-logger/computers for automatic recording of data.

Result

A quantitative study of rainfall parameters has been done in conjunction with the signal attenuation in the earth-space microwave satellite link in Ku band. Special emphasis on drop size distribution and its variation from the theoretical value has been presented. The need of having a better model or data matrix has been stressed.

Figure 1. Sample Record of Ku band microwave signal parameters at 11GHz at earth-space path during rain event

Discussion

Primarily the dielectric absorption due to water droplets leads to signal attenuation beside that from absorption by oxygen and water vapour molecules and suspended particles associated with water droplets in the atmosphere. Depolarization effects in radio signal is observed due to asymmetry in rain drop cell shapes. The signal level suffers often experience

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9 to 10 dB loss in its dynamic range during rain. During occasions of heavy rain substantial loss of signals which effects signal outages are almost regular phenomena in the signal attenuation characteristics at Darjeeling. The receiving antenna which is pointing a specific satellite in the space covers a certain cone in the atmosphere and hence detects attenuation from the entire path which may not be completely filled with rain environment. The ground based Laser precipitation monitor only gives us the rain rate and DSD that comes to the ground and hence does not cater for cloud attenuation as well as virga (rain in upper atmosphere that do not reach the earth), while Micro-rain radar with a limitation of covering a narrow angle towards zenith does not remain always in the rain environment

Figure 2. A sample spectrogram from micro-rain radar shows the rain rate over Darjeeling during the cyclone Aila on 26th May 2009.

Figure 3. A plot of drop dia (mm) versus number of drops at ground for a sample rain event at Darjeeling

Figure 4. Altitude profile plot of drop diameter (mm) at three different altitude versus corresponding number of drops for a sample rain event as obtained from micro rain radar

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due to moving passage of rain cloud and does not often cover completely the rain overhead In tropical regions the instantaneous value can go up to 250 mm/hr. That however is possible in late afternoon and is basically convective type of rainfall.

Figure 5. Altitude profiles of three different drop diameters, 1.5, 1.0 & 0.246 mm versus corresponding number of drops.

Reference

Laws, J. 0. and Parsons, D. A., “The Relation of Raindrop-size to Intensity,” Trans. Amer. Geophys. Union, Vol. 24, Part II, 1943, pp. 452-460.

Marshall, J. S. and Palmer, W. McK., “The Distribution of Raindrops with Size,” J. Meteor., Vol. 5, 1948, pp. 165-166.

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A–O–9

On the Association Between Cloud Droplet Spectral Dispersion and Number Concentrations over Different Environments in India

S. Dipu, G. Pandithurai and A. S. Panicker

Indian Institute of Tropical Meteorology, Pune

ABSTRACT : Cloud Aerosol Interactions and Precipitation Enhancement Experiment (CAIPEEX) is an extensive observational campaign to unravel the influence of complex aerosol-cloud interactions on precipitation using aircraft based measurements over Indian region. In this study, we focus on estimating the cloud droplet spectral dispersion and its relationship with cloud droplet number concentration using aircraft measurements of cloud drop size distributions. The analysis was carried out for five regions covering northern, central, southern and eastern India with observational base stations Pathankot, Hyderabad, Bangalore, Bareilly, and Guwahati. In general, it is found that with increase in cloud droplet number concentration, the spectral dispersion decreases and converges towards a narrow range for higher droplet number concentrations, which can induce a significant uncertainty in indirect effect estimates under lower droplet number concentrations.

Introduction

Clouds have the largest uncertainty in our current understanding of the climate system (IPCC, 2007). Aerosol particles have the potential to influence cloud microphysical properties by acting as cloud condensation nuclei (CCN) and ice nuclei (IN). Subsequent changes in water droplets, ice crystal concentration and size thereby impacting radiative forcing on the climate. These effects are called indirect aerosol effects (Lohmann and Feichter, 2007). Climate models have been using variables related to cloud droplet size distribution in their physical schemes (Lohmann et al 2007). Cloud droplet effective radius is one of the key variables used for the calculation of radiative properties of liquid water clouds (Slingo, 1989). Slingo et al. (1990) has already shown the importance of re in

climate models for describing global climate change.

Anthropogenic aerosol can exert an additional effect on cloud properties (Liu and Daum, 2002). This additional effect can be represented by spectral dispersion, which plays a significant role in describing the cloud radiative forcing (Liu and Daum, 2000). Spectral dispersion is also affected by meteorological and dynamic conditions, causing uncertainty in the relationship between spectral dispersion and droplet concentration. It is already reported that, when number concentration increases, the relative dispersion of cloud droplet converges towards narrow range (Zhao et al, 2006). This convergence is similar for cleaner and polluted atmosphere. For high droplet concentrations, the uncertainty in estimation of indirect radiative forcing is significantly reduced due to the convergence of the relative dispersion.

In this paper we demonstrate the spectral dispersion of cloud droplet size distribution over different regions influenced by different environmental conditions. The purpose of

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this work is to improve our understanding of aerosol indirect effect and its treatment in climate models. The data sets used in this study were obtained from aircraft measurements taken over Indian sub-continent between May and September 2009.

Data and Methodology

CAIPEEX datasets collected over five regions during May to September 2009 were used in the analysis. A detailed description of the above project, instruments mounted on CAIPEEX aircraft N361JC can be found (http://www.tropmet.res.in/~caipeex/). The cloud droplet probe (CDP) is used for the measurements of cloud droplet size distribution from 3 to 50 micrometer in 30 interval bins. Various other parameters that can be calculated from CDP includes liquid water content (LWC), effective radius, cloud droplet number concentration etc. The CDP can make measurements at 1 second interval.

There has been increasing evidence that, most of the climate models use a ‘1/3’ power law to parameterize reff as a function of liquid water content ‘L’ and cloud droplet number concentration ‘N’. The expression can be written as;

or

Where is the water density and is a dimensionless scaling factor, named the effective radius ratio, which depends on the spectral shape of the cloud droplet size distribution and is specified in most climate models as a fixed parameter. Climate models that attempt to quantify the first indirect effect must therefore account for the influence of the cloud droplet spectrum on the scaling factor .

Cloud droplet dispersion is the ratio of the standard deviation of the droplet size distribution and mean radius. Using different distribution functions Liu and Daum (2000) derived expression to calculate the parameter . They compared the expression to observations and concluded that Weibull or gamma distributions best describe the dependence of effective radius on spectral dispersion. For gamma distribution, can be expressed as,

where is the relative dispersion of cloud droplet size distribution, its defined as the ratio of the standard deviation to the mean radius of the droplet size distribution and has been calculated using above described data.

Results and discussion

The effective radius ratio is plotted as a function of relative dispersion calculated from CDP measurements over different regions spreading from pre-monsoon to monsoon conditions during CAIPEEX experiment is shown in Figure 1. The plot also includes a theoretical curve calculated using equation (3). The calculated mean value for varied from 1.00 to 2.99 and the mean relative dispersion varied from 0.065 to 1.19. In both

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cases, the maximum variation was found over Bangalore region. The change in cloud droplet size dispersion is jointly determined by aerosol loading and cloud dynamical processes. For similar dynamical conditions, it has been suggested that higher aerosol concentrations lead to an increased dispersion (Liu and Daum, 2002). Dynamical effects such as updraft and turbulent processes may cause a negative dispersion relation, that is, a decreased dispersion relation with increasing updraft or turbulence (Liu et al 2006).

Figure 1. Effective radius ratio as a function of the relative dispersion, calculated from gamma distribution and CDP measurements over different regions during CAIPEEX experiment

Figure 2 shows the relationship between the cloud droplet number concentration (N) and the relative dispersion å derived from measurements. There is clear evidence that, the relative dispersion of the cloud droplet is characterized by wide range of values when the number concentration of the cloud droplet is low. With increase in cloud droplet number concentration, the relative dispersion decreases and converges towards a very narrow range. Zhao et al. (2006) also has reported similar trends over different regions in Asia (clean, polluted and marine regions). In general over Indian region, with increase in cloud droplet number concentration, the relative dispersion decreases and convergence towards a narrow range between 0.25 and 0.4. By considering the each region separately, over Pathankot the relative dispersion varies between 0.19 - 1.11, when the cloud droplet concentrations are around 10-400 cm-3. In Hyderabad region the relative dispersion varies between 0.15 to 0.78 and the cloud droplet concentration are around 10-1000 cm-3. In Bangalore the relative dispersion varies between 0.066 - 1.19 and the cloud droplet number concentration was around 10-600 cm-3. In Bareilly the relative dispersion varies from 0.05- 1.0 and the cloud droplet number concentration varies between 5-1250 cm-3, and in Guwahati relative dispersion has a range of 0.12-0.95 and cloud droplet number concentration from 2-1100 cm-3. The convergence of the relative dispersion at high values of N is similar at the five different regions.

The relative dispersion has an important impact on the estimated indirect radiative forcing (Zhao et al 2006). From earlier studies, it is clear that the increase in the cloud

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Figure 2. Relationship between the relative dispersion of cloud droplets and their number concentration at there different region. (a) Over India (composite of all five regions) and over (b) Pathankot (c) Hyderabad (d) Bangalore (e) Bareilly and, (f) Guwahati

droplet number concentration is because of high anthropogenic aerosol concentration (Twomey, 1974). Under low droplet concentrations, the relative dispersion is higher and the uncertainty in Twomey effect is higher. The present result implies that under high aerosol conditions the uncertainty in aerosol indirect radiative forcing estimates is significantly reduced.

Summary

Cloud droplet spectral dispersion over three Indian regions is studied using aircraft measurements. The effective radius ratio calculated from CDP measurements shows an

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increasing trend with relative dispersion, which in turn matches with the theoretical curve, predicted according to gamma distribution. The relation between cloud droplet number concentration and relative dispersion shows that the range in relative dispersion is large (0.1 to 1) when the droplet number concentration is low. When the droplet number concentration increases, the relative dispersion of the cloud droplet converges towards a narrow range (0.25 to 0.4). It is found that, as the cloud droplet concentration increases the relative dispersion of cloud droplet converges irrespective of region. It is proposed to undertake a detailed study on how the droplet spectral dispersion affects the aerosol indirect forcing estimates.

Acknowledgments

Authors would like to thank CAIPEEX project for datasets.

References

Liu Y and Daum P H (2002); Indirect warming effect from dispersion forcing. Nature 419 580-1.

Liu Y and Daum P H (2000); Spectral dispersion of cloud droplet size distribution and parameterization of cloud droplet effective radius; Geophys. Res. Lett., 27 1903-6.

Lohmann U and Feichter J (2007); Aerosol indirect effects: a review. Atmospheric Chemistry and Physics 5, 715– 737.

Lohmann U, Quaas J, Kinne S and Feichter J (2007); Diffrent approaches for constraining global climate models of the anthropogenic indirect aerosol effect; Bull. Am. Metorol. Soc. 88 243-9.

Reid J S, Hobbs P V, Rangno A L and Hegg D A (1999); Realtionships between cloud droplet effective radius, liquid water content, and droplet concentration for warm clouds in Brazil embedded in biomass smoke; J. Geophy. Res. 104, 6145-53.

Slingo A (1989); A GCM parameterization for the short wave radiative properties of water clouds.; J. Atmos. Sci., 46 1419-1427.

Slingo A (1990); Sensitivity of earths radiation budget to changes in low clouds.; Nature 343 49-51. Twomey S A, (1974); Pollution and planetary albedo; Atmos. Environ., 8, 1251-1256.

Zhao C, Xuexi Tie, Guy Brasseur, Kevin J. Noone, Teruyuki Nakajima, Qiang Zhang, Renyi Zhang, Mengyu Huang, Ying Duan, Gelun Li and Yutaka Ishizaka (2006); Aircraft measurement of cloud droplet spectral dispersion and implications for indirect aerosol radiative forcing; Geophys. Res. Lett., 33, L16809, doi:10.1029/2006GL026653.

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A–O–10

Evaluation of the Seasonal Variation of Aerosol Distribution over the Indian Subcontinent from LMDz-INCA General Circulation Model Simulations

S. Verma1,2 and M. Schulz2

1Department of Civil Engineering, Indian Institute of Technology Kharagpur, India 2 Laboratoire des Sciences du Climat et de l’Environnement ,

91191 Gif-sur-Yvette Cedex, France

Email: shubhaverm@gmail.com

Introduction

Atmospheric aerosols perturb the radiation energy balance of the earth-atmosphere system and hence impact the earth’s climate. In contrast to the well-mixed greenhouse gases, which are uniformly mixed around the globe, aerosols exhibit variation in their spatial and temporal characteristics. This could lead to a climate response due to aerosols different on a regional scale than the global. Modelling studies suggest that increase in black carbon loading could substantially weaken the monsoon circulation and increase the drought frequency over south Asia [Menon et al., 2002].

Background and Motivation

A striking feature of spatial distribution of aerosol optical depth (AOD) retrieved from satellite based observations from MISR (Multi-angle Imaging Spectroradiometer) [Girolamo et al., 2004] over the Indian subcontinent is the presence of high AOD over the Indo- Gangetic plain (IGP) during winter, especially on the eastern part. Recent land campaign through Indian Space Research Organisation-Geosphere Biosphere Programme (ISRO- GBP) [Jayaraman et al., 2006], showed the stations over the IGP to have higher AOD compared to off-IGP stations over the Indian subcontinent. The spatial distribution of emission patterns over India show the presence of different composition of emissions, e.g. IGP to be dominated with large emissions of black carbon due to fuel consumption, including biofuels used for domestic purposes [Venkataraman et al., 2005], while western India to be dominated by sulphur dioxide emissions arising from fossil fuel use and dust emissions. Since different aerosols interact with radiation in different ways, it is necessary to understand the interaction between aerosol and climate impacts over the different regions of India. Recent aerosol measurements of optical and chemical characteristics through various ground-based and AERONET (Aerosol Robotic Network) observations being carried out over the different parts of India, in addition to satellite based observations gives us an opportunity to evaluate the aerosol distribution and their characteristics from general circulation model simulations and use the modelling tool to understand the climate impacts due to aerosols over the Indian region.

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Results and Discussions

In the present study, we carry out aerosol transport simulations in LMDZ-INCA [Schulz et al., 2006] which couples the Laboratoire de Meteorologie Dynamique general circulation model (LMDz) and the Interaction with Chemistry and Aerosols (INCA) model. The simulations are made with a horizontal resolution of 3.8 degrees in longitude and 2.5 degrees in latitude and 19 vertical levels from the surface to the level of 3 hPa. We present an analysis on the spatial distribution of simulated AOD over the Indian subcontinent during the different seasons, its evaluation with measurements, and examine the chemical and source characteristics of the aerosols measured over the Indian subcontinent. Figure 1a shows the spatial distribution of simulated AOD during the northeast (NE) winter monsoon (January to March) over the Indian subcontinent and ocean from aerosol transport simulations for the year 2004 in LMDZ-INCA GCM. The model estimates show the spatial gradient in AOD with the higher values near the coastal regions with a decrease as we go away from the coast and shows features of high AOD near the eastern part of IGP. The model estimated AOD compares relatively well with the AOD retrieved from satellite observations with MODIS (Moderate Resolution Imaging Spectroradiometer) over the Arabian Sea. However, the estimated AOD over the Indo-Gangetic plain is lower by a factor of 2 to 3 compared to the MODIS data. Though some of the model discrepancies (e.g. uncertainty in the scavenging processes of soluble species) could be the reasons for the underestimation of modelled AOD, nevertheless, the high AOD seen in observations could be largely due to contribution from hygroscopic sulfate and organic matter at ambient relative humidity which needs to be examined. It is estimated that aerosols originating from anthropogenic emissions contribute as high as 80 to 90% to the total AOD (Figure 1b) over the Indian subcontinent and the adjoining oceanic regions of Arabian Sea and Bay of Bengal.

The GCM simulated AOD showed seasonal variations during the period of measurements carried out during the different seasons. AOD is estimated to be higher by a factor of 1.5 to 2 over the Indian subcontinent during the southwest monsoon (June to September) compared to the AOD estimated during the NE winter monsoon, followed by

Figure 1. Spatial distribution of (a) simulated AOD (b) contribution of anthropogenic emissions to AOD from LMDz-INCA GCM during northeast winter monsoon

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during summer (April-May). AOD simulated over the IGP was estimated to be dominated by dust and sulfate during the southwest monsoon compared to sulphate, organic matter, and BC, during the NE winter monsoon. The 7-days backtrajectory calculated at 10 m, 100 m, 500 m, 1000 m, and 5000 m heights showed that the air mass originated from Arabian sea over to the northwest India on most of the days during the southwest monsoon over the IGP (evaluated at Kharagpur, 22.3°N, 87.2°E and Kanpur, 26.5°N, 80.3°E, stations over the IGP), while they originated from IGP itself on most of the days during other seasons with a long range transport from west Asia on some days including transport from Bay of Bengal during few days in March. The paper will present analysis on model estimates during the different seasons and its evaluation with the measurements.

References

L.Di Girolamo, T. C. Bond, D. Bramer, D. J. Diner, F. Fettinger, R. A. Kahn, J. V. Martonchik, M. V. Ramana, V. Ramanathan, and P. J. Rasch. Analysis of Multi-angle Imaging SpectroRadiometer (MISR) aerosol optical depths over greater India during winter 2001-2004. Geophys. Res. Lett., 31, doi:10.1029/ 2004GL021273, 2004.

A. Jayaraman, H. Gadhavi, D. Ganguly, A. Misra, S. Ramachandran, and T. Rajesh (2006), Spatial variations in aerosol characteristics and regional radiative forcing over India: Measurements and modeling of 2004 road campaign experiment, Atmos. Env., 40, 6504 6515.

S. Menon, Hansen, J., Nazarenko, L., & Luo, Y. Climate effects of black carbon aerosols in China and India. Science, 297: 2250-2253, 2002.

M. Schulz, C. Textor, S. Kinne, Y. Balkanski, S. Bauer, T. Berntsen, T. Berglen, O. Boucher, F. Dentener, A. Grini, S. Guibert, T. Iversen, D. Koch, A. Kirkeveg, X. Liu, V. Montanaro, G. Myhre, J. Penner, G. Pitari, S. Reddy, X. Seland, P. Stier, and T. Takemura. Radiative forcing by aerosols as derived from the AeroCom presentday and pre-industrial simulations. Atmos. Chem. Phys., 6:5225- 5246, 2006.

C. Venkataraman, G. Habib, A. Eiguren-Fernandez, A. H. Miguel, and S. K. Friedlander. Residential biofuels in South Asia: Carbonaceous aerosol emissions and climate impacts. Science, 307:1454-1456, 2005.

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