**1. Introduction**

In recent times, atmospheric aerosols are receiving increasing attention as they directly affect the Earth's radiation balance by altering incoming shortwave solar radiation that can cause positive (heating) or negative (cooling) radiative forcing depending on their scattering and absorption properties, the reflectivity of the underlying surface [10, 24] and the position of aerosols with respect to the global cloud coverage [8, 88]. Aerosols also affect the outgoing longwave radiation by absorption, emission and scattering. Presently, effects of radiative forcing of atmospheric aerosols on climate is a subject of great concern to atmospheric researchers. An accurate quantification of the aerosol direct radiative forcing is critical for the interpretation of existing climate records and also for the projection of future climate change [11, 47]. Significant amount of atmospheric radiative forcing causes high atmospheric heating due to strong absorption of solar radiation which can change the regional atmospheric stability and may alter the large scale circulation and the hydrological cycle, enough so, apparently, to account for observed temperature and precipitation changes in China and India [1, 46, 62, 70]. Therefore, the effect of aerosols on the radiation budget in terms of radiative forcing calculations is challenging and demanding, especially on the regional scale for the exclusive understanding of climate change.

The uncertainties involved in the climate models are mainly due to optical properties of aerosols on the regional scale, specially underestimated absorption of solar radiation by aerosols, both, naturally and anthropogenically produced [34], their residence time [57, 58], etc, which arise mostly due to lack of observations. Black carbon (BC) or soot and dust aerosols are playing the leading role in aerosol interaction with the solar radiation due to their strong absorption properties. BC comes into the atmosphere during combustion of fossil fuels, principally, diesel and coal, and from biomass burning. BC demands large attention due to its strong absorption of incoming solar radiation and produces positive radiative forcing which is sometimes comparable to the forcing of the green-house gas methane [31].

©2012 Das, licensee InTech. This is an open access chapter distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ©2012 Das, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2012 Sunilkumar et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Rashki et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Mkoma et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons Jiménez-Escalona and Peralta, licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, Lopes et al., licensee InTech. This is a paper distributed under the terms of the Creative Commons

#### 2 Will-be-set-by-IN-TECH 82 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert <sup>3</sup>

Therefore, underestimation of BC can introduce large uncertainty in the climate models. On the other hand, dust, mainly coming from arid regions, is generally known for scattering of solar radiation. However, dust also has a strong absorption in the UV and infrared regimes and therefore, can influence radiative forcing not only in the shortwave region but also in the longwave region. Hence, the study of dust aerosols is equally important. In addition, long-range transported dust aerosols can enhance the atmospheric radiative forcing in the presence of soot aerosols [14, 54].

**2. Datasets**

*2.1.1. Microtops*

*2.1.2. QCM*

*2.1.3. Aethalomater*

on the filter as follows [5, 89]

**2.1. Ground-based instruments**

measured AOD is not more than 0.03 at all wavelengths [33].

observed that measurement error is always less than 15% [33].

Aerosol Optical Depth (AOD) was measured using a hand-held Microtops II (Solar Light Co., Inc., USA) [49] at every five minutes interval during daytime from 0730 to 1600 hours. This instrument can measure AOD at five different wavelengths centered at 0.380, 0.440, 0.500, 0.675, 0.870 *μ*m simultaneously. Another Mictotops II was used to measure AOD at 1.020 *μ*m associated with ozone and columnar water vapor . Both Microtops were regularly calibrated, once in a month, and all calibrated constants were obtained from Langley's plot analysis [30]. There is only 1% variation in the calibration constant since 2002. The absolute uncertainty of

Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert 83

Aerosol Mass Concentration was measured using a 10-stage Quartz Crystal Microbalance (QCM) cascade impactor (model PC-2, California Measurements Inc., USA) and the aerosol size distribution at the ground level was determined. Aerosols were collected in 10 stages of the impactor with cut-off radii at 12.5, 6.25, 3.2, 1.6, 0.8, 0.4, 0.2, 0.1, 0.05 and 0.025 *μ*m from stage 1 to 10 respectively. The air flow rate through the impactor was kept at 240 ml/min and the typical sampling period was 300 sec for each measurement. The QCM was operated from the terrace of the observatory building at a height of about 6m. The air inlet was installed vertically to minimize the loss of aerosol particles within the inlet tube. The relative temperature change of the crystals during each sampling period of 5 minute is too small and can be neglected. Uncertainties involved in the QCM measurements are mainly due to variations in RH [15, 33, 59]. In an earlier study, the QCM was operated simultaneously with an Anderson impactor to investigate the measurement accuracy of each stage and it was

Absorbing aerosol mass concentrations at seven different wavelengths (centered at 0.37, 0.47, 0.52, 0.59, 0.66, 0.88 and 0.95 *μ*m) were obtained using a multichannel Aethalometer (model AE-42) manufactured by Magee Scientific, USA [21]. The flow rate of ambient air was maintained at 3.0 l.min−<sup>1</sup> and the data was stored in the memory disk at a time interval of two minutes during the measurement period. BC mass concentration is estimated by detecting the light transmitted through the particle deposited sample spot and particle free reference spot

*BC* <sup>=</sup> <sup>−</sup> *<sup>A</sup>*100 ln(*I*<sup>2</sup>

where *I*<sup>1</sup> and *I*<sup>2</sup> are the ratios of light intensities of the sample beam to the reference beam before and after particle sampling at time interval Δ*t*, *Q* is the volume flow rate of the ambient air through the filter, *A* is the area of the sample spot and *k* is the absorption coefficient. The real-time BC mass concentration is considered at 0.88 *μ*m wavelength channel because the spectral response of elemental carbon particles has a peak near this wavelength [5]. The manufacturer quoted the overall uncertainty in aethalometer data to be about 10%,

*I*1 )

*kQ*Δ*<sup>t</sup>* (1)

South-East Asia, with its fast growing urbanization and industrialization, is one of the major hot-spot regions on the global aerosol map. A study of historical records from different locations on the globe reported an increasing trend of BC emissions in South and Central Asia [6]. In addition, dust aerosols are also transported from the Middle-East region to over South-East Asia. A mixture of locally produced anthropogenic aerosols with natural aerosols like mineral dust and seasalt, reported over this hot spot region [42, 60–62] aids in the warming of the atmosphere. There were several campaigns of ship-, land- and air-borne measurements over Indian subcontinent and surrounding marine regions to investigate the regional effects of anthropogenic aerosols [32, 48, 75, etc.]. In-situ measurements during the Indian Ocean Experiment (INDOEX) and several campaigns under Indian Space Research Organisation – Geosphere Biosphere Programme (ISRO–GBP) found that the sources of the anthropogenic aerosols are biomass burning and fossil-fuel combustions [33, 61]. The second phase of the ISRO-GBP land campaign during winter conducted in the Indo-Gangetic Plain (IGP), a hot-spot region over India, reported significant anthropogenic aerosol loading in the atmosphere coming from industries and vehicular emissions [15, 18, 50]. Satellite-based observations suggested that significant amount of dust is also transported over IGP from Thar Desert located in western India during premonsoon (March to May) [16, 17, 54]. This transported dust helps to sustain the hot-spot over IGP maintaining the large background aerosol loading. Majority of the earlier research works focused on aerosol contribution, either locally produced anthropogenic aerosols or transported natural dust, to regional climate change over this hot-spot region. However, uncertainties in those results are found to be relatively large, especially in studies on transported dust, as the dust becomes aged by externally and internally mixing with locally produced pollutants.

This chapter investigates and quantifies the natural and anthropogenic contribution of background aerosols over western India where both the source regions, Thar Desert, source of natural dust, and IGP, hot spot region of anthropogenic aerosols, are present. The contributions of both types of aerosols are estimated for the years 2006 and 2007 from ground-based and satellite measurements of aerosol optical and physical properties. Ground-based observations have been conducted at Mt. Abu (24.65◦N, 72.78◦E, 1.7 km asl), the highest location in Aravalli mountains in western India. The main advantage of the location is its proximity to both, Thar Desert and IGP. Also, due to the high altitude, the observation site is less affected by the boundary layer aerosols. The hill-top background aerosols are significantly influenced by wind that carries aerosols from either Thar Desert or IGP and show strong seasonal variation. Therefore, the site becomes a unique location for the investigation of both, natural and anthropogenic aerosols. The present study investigates the seasonal variation of aerosol properties at Mt. Abu and estimates the contribution of both aerosols on the radiation budget during the four seasons – winter (Dec-Feb), premonsoon (Mar-May), monsoon (Jun-Aug), and postmonsoon (Sep-Nov).

82 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert <sup>3</sup> Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert 83

## **2. Datasets**

2 Will-be-set-by-IN-TECH

Therefore, underestimation of BC can introduce large uncertainty in the climate models. On the other hand, dust, mainly coming from arid regions, is generally known for scattering of solar radiation. However, dust also has a strong absorption in the UV and infrared regimes and therefore, can influence radiative forcing not only in the shortwave region but also in the longwave region. Hence, the study of dust aerosols is equally important. In addition, long-range transported dust aerosols can enhance the atmospheric radiative forcing in the

South-East Asia, with its fast growing urbanization and industrialization, is one of the major hot-spot regions on the global aerosol map. A study of historical records from different locations on the globe reported an increasing trend of BC emissions in South and Central Asia [6]. In addition, dust aerosols are also transported from the Middle-East region to over South-East Asia. A mixture of locally produced anthropogenic aerosols with natural aerosols like mineral dust and seasalt, reported over this hot spot region [42, 60–62] aids in the warming of the atmosphere. There were several campaigns of ship-, land- and air-borne measurements over Indian subcontinent and surrounding marine regions to investigate the regional effects of anthropogenic aerosols [32, 48, 75, etc.]. In-situ measurements during the Indian Ocean Experiment (INDOEX) and several campaigns under Indian Space Research Organisation – Geosphere Biosphere Programme (ISRO–GBP) found that the sources of the anthropogenic aerosols are biomass burning and fossil-fuel combustions [33, 61]. The second phase of the ISRO-GBP land campaign during winter conducted in the Indo-Gangetic Plain (IGP), a hot-spot region over India, reported significant anthropogenic aerosol loading in the atmosphere coming from industries and vehicular emissions [15, 18, 50]. Satellite-based observations suggested that significant amount of dust is also transported over IGP from Thar Desert located in western India during premonsoon (March to May) [16, 17, 54]. This transported dust helps to sustain the hot-spot over IGP maintaining the large background aerosol loading. Majority of the earlier research works focused on aerosol contribution, either locally produced anthropogenic aerosols or transported natural dust, to regional climate change over this hot-spot region. However, uncertainties in those results are found to be relatively large, especially in studies on transported dust, as the dust becomes aged by

This chapter investigates and quantifies the natural and anthropogenic contribution of background aerosols over western India where both the source regions, Thar Desert, source of natural dust, and IGP, hot spot region of anthropogenic aerosols, are present. The contributions of both types of aerosols are estimated for the years 2006 and 2007 from ground-based and satellite measurements of aerosol optical and physical properties. Ground-based observations have been conducted at Mt. Abu (24.65◦N, 72.78◦E, 1.7 km asl), the highest location in Aravalli mountains in western India. The main advantage of the location is its proximity to both, Thar Desert and IGP. Also, due to the high altitude, the observation site is less affected by the boundary layer aerosols. The hill-top background aerosols are significantly influenced by wind that carries aerosols from either Thar Desert or IGP and show strong seasonal variation. Therefore, the site becomes a unique location for the investigation of both, natural and anthropogenic aerosols. The present study investigates the seasonal variation of aerosol properties at Mt. Abu and estimates the contribution of both aerosols on the radiation budget during the four seasons – winter (Dec-Feb), premonsoon

externally and internally mixing with locally produced pollutants.

(Mar-May), monsoon (Jun-Aug), and postmonsoon (Sep-Nov).

presence of soot aerosols [14, 54].

## **2.1. Ground-based instruments**

### *2.1.1. Microtops*

Aerosol Optical Depth (AOD) was measured using a hand-held Microtops II (Solar Light Co., Inc., USA) [49] at every five minutes interval during daytime from 0730 to 1600 hours. This instrument can measure AOD at five different wavelengths centered at 0.380, 0.440, 0.500, 0.675, 0.870 *μ*m simultaneously. Another Mictotops II was used to measure AOD at 1.020 *μ*m associated with ozone and columnar water vapor . Both Microtops were regularly calibrated, once in a month, and all calibrated constants were obtained from Langley's plot analysis [30]. There is only 1% variation in the calibration constant since 2002. The absolute uncertainty of measured AOD is not more than 0.03 at all wavelengths [33].

## *2.1.2. QCM*

Aerosol Mass Concentration was measured using a 10-stage Quartz Crystal Microbalance (QCM) cascade impactor (model PC-2, California Measurements Inc., USA) and the aerosol size distribution at the ground level was determined. Aerosols were collected in 10 stages of the impactor with cut-off radii at 12.5, 6.25, 3.2, 1.6, 0.8, 0.4, 0.2, 0.1, 0.05 and 0.025 *μ*m from stage 1 to 10 respectively. The air flow rate through the impactor was kept at 240 ml/min and the typical sampling period was 300 sec for each measurement. The QCM was operated from the terrace of the observatory building at a height of about 6m. The air inlet was installed vertically to minimize the loss of aerosol particles within the inlet tube. The relative temperature change of the crystals during each sampling period of 5 minute is too small and can be neglected. Uncertainties involved in the QCM measurements are mainly due to variations in RH [15, 33, 59]. In an earlier study, the QCM was operated simultaneously with an Anderson impactor to investigate the measurement accuracy of each stage and it was observed that measurement error is always less than 15% [33].

#### *2.1.3. Aethalomater*

Absorbing aerosol mass concentrations at seven different wavelengths (centered at 0.37, 0.47, 0.52, 0.59, 0.66, 0.88 and 0.95 *μ*m) were obtained using a multichannel Aethalometer (model AE-42) manufactured by Magee Scientific, USA [21]. The flow rate of ambient air was maintained at 3.0 l.min−<sup>1</sup> and the data was stored in the memory disk at a time interval of two minutes during the measurement period. BC mass concentration is estimated by detecting the light transmitted through the particle deposited sample spot and particle free reference spot on the filter as follows [5, 89]

$$BC = -\frac{A100\ln(\frac{I\_2}{I\_1})}{kQ\Delta t} \tag{1}$$

where *I*<sup>1</sup> and *I*<sup>2</sup> are the ratios of light intensities of the sample beam to the reference beam before and after particle sampling at time interval Δ*t*, *Q* is the volume flow rate of the ambient air through the filter, *A* is the area of the sample spot and *k* is the absorption coefficient. The real-time BC mass concentration is considered at 0.88 *μ*m wavelength channel because the spectral response of elemental carbon particles has a peak near this wavelength [5]. The manufacturer quoted the overall uncertainty in aethalometer data to be about 10%,

#### 4 Will-be-set-by-IN-TECH 84 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert <sup>5</sup>

which is calculated by comparing the data of the aethalometer to other instruments that measure BC using different techniques [2]. However, Weingartner et al. [89] reported that BC measurements using filter techniques have significant uncertainty due to "shadowing effect" after investigating several types of carbon aerosols. This effect causes underestimation of BC measurement due to its high loading on the filter. This effect is very pronounced for pure BC while almost negligible for aged atmospheric aerosols. This uncertainty is found to be less than 10% [14].

represent dust dominated regions and such high AI values are mainly observed over arid regions [78]. OMI-AI Level 3 global-gridded product with spatial resolution of 0.25◦×0.25◦ is obtained over western India for identifying the dust dominating periods in the present study.

Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert 85

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) provides a new insight into the role of atmospheric aerosols and clouds in regulating the study of Earth's climate change and air quality. It is a part of the A-train satellite constellation that includes Aqua, CloudSat, and Aura satellites. CALIPSO is in a sun-synchronous orbit at 705 km at an inclination of 98◦ and provides the vertical distribution of aerosols and clouds. It consists of three sensors: a Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP), an Imaging Infrared Radiometer (IIR), and a moderate spatial resolution Wide Field-of-view Camera (WFC). CALIPSO passes over the equator at 13:31 local hours, one minute behind Aqua. The primary instrument, CALIOP, transmits linearly polarized laser light of 0.532 *μ*m and 1.064 *μ*m at a pulse rate of 20.16 Hz. Its receiver measures the backscattered intensity at 0.532 *μ*m and 1.064 *μ*m with the former divided into two orthogonally polarized components which help to calibrate the optically thick clouds and aerosols. CALIOP observes both clouds and aerosols at high spatial resolution, but must be spatially averaged to increase signal to noise ratio. From the surface to 8 km, the vertical resolution is 30 m and the nominal horizontal resolution is 1/3 km. CALIPSO data products provide the aerosol vertical distribution along with aerosol layer height and AOD [7, 85]. CALIPSO LEVEL 2 Vertical Feature Mask (VFM) products provide vertical mapping of the locations of aerosols and clouds together with information about the types of each layer and the discrimination between aerosols and clouds

OPAC (Optical Properties of Aerosols and Clouds) model [26] is used to derive aerosol optical depth from the measured atmospheric aerosol chemical compositions obtained from literature [39, 40] at Mt. Abu. OPAC model contains two major parts: (1) a dataset of microphysical properties and the resulting optical properties of cloud and aerosol components at different wavelengths and for different humidity conditions, (2) a FORTRAN program that allows the user to extract data from this dataset, to calculate additional optical properties, and to calculate optical properties of mixtures of the stored clouds and aerosol components. In the present study, OPAC model has been used for obtaining the aerosol optical properties in shortwave region (0.25-4 *μ*m) from the known chemical compositions. OPAC, based on Mie theory, can compute aerosol optical properties at 61 wavelengths starting from 0.25 *μ*m to 40 *μ*m. It mainly has 10 aerosol components which are as follows - insolubles (mostly soil particles), water soluble aerosols (mainly sulfate and nitrate aerosols of anthropogenic origin), soot (of anthropogenic origin), sea salts (naturally produced on the oceanic surface by wind and also available in the atmosphere of coastal regions) in accumulation and coarse mode, mineral dust (generally coming into atmosphere from the arid surface by wind) in three modes, transported mineral dust and sulfate droplets (mainly found at stratospheric altitudes). This model is used to derive the AOD spectrum using a combination of aerosol components and in the present study the sulfate droplets are not considered. Some of the aerosol components which

is expected to be good in these products [4, 52, 87, etc.].

*2.2.3. CALIOP*

**2.3. Models**

*2.3.1. OPAC*

## **2.2. Space-borne measurements**

## *2.2.1. MODIS*

AOD over Mt. Abu is also obtained from observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on-board Terra and Aqua satellites. Terra and Aqua spacecrafts pass over the equator at 10:30 and 13:30 Local Solar Time, respectively [43]. Global images of the full disc are produced due to larger swath widths and instrument-scanning angle of 110◦ [44]. MODIS has 36 channels spanning the spectral range from 0.41 to 14.4 *μ*m at three spatial resolutions: 250 m (2 channels), 500 m (5 channels) and 1 km (29 channels). MODIS aerosol algorithm consists of three independent algorithms to retrieve the aerosol characteristics, two over land and one over oceans, and makes use of eight of these channels (0.47-2.13 *μ*m) [29, 35, 67]. The measurements at other wavelengths provide information to identify clouds and river sediments [20, 45]. MODIS provides an accurate retrieval of spectral AOD and the parameters characterizing aerosol size [79, 80]. The retrieved data used in this study include both Terra and Aqua MODIS aerosol products; such estimations are made over cloud-free regions only [67]. Long-term analysis of MODIS aerosol retrievals collocated with AERONET measurements confirm that MODIS retrieved AOD agrees with AERONET observations to within 0.10 over land and to within 0.035 over oceanic island sites. There are several studies demonstrating that MODIS AOD has a strong correlation with AERONET AOD [41, 83, etc.] and thereby provide enough confidence to use the MODIS AOD over western India, the region of interest in the current study.

## *2.2.2. OMI*

Aerosol index (AI) is obtained from observations in the UV region (UV-1, 0.270 to 0.314 *μ*m; UV-2, 0.306 to 0.380 *μ*m) of the Ozone Monitoring Instrument (OMI) on-board Aura satellite [82]. AI is defined as the difference between satellite measured (including aerosol effects) spectral contrast at 0.360 and 0.331 *μ*m radiances and the contrast theoretically calculated from radiative transfer model for pure molecular (Rayleigh) atmosphere [9, 25, 28]. The Aura satellite launched in July 2004, flies eight minutes after the Aqua satellite as a part of NASA A-train constellation. OMI has been designed for the replacement of Total Ozone Mapping Spectrometer (TOMS) to continue recording the total ozone and other atmospheric parameters related to ozone and climate study. OMI is sensitive to aerosol absorption even when aerosols are present above the cloud. Therefore, AI can be successfully derived for clear as well as cloudy conditions. OMI has a spatial resolution of 13×24 km at nadir and uses the same algorithm that is used for TOMS observations. AI provides a quantitative measurement of UV-absorbing aerosols over all the terrestrial surfaces including deserts and ice sheets. AI is positive for absorbing aerosols and negative for non-absorbing aerosols. Zero AI indicates cloud presence. High OMI-AI values with high MODIS-AOD and low Ångstr*o*¨m exponent represent dust dominated regions and such high AI values are mainly observed over arid regions [78]. OMI-AI Level 3 global-gridded product with spatial resolution of 0.25◦×0.25◦ is obtained over western India for identifying the dust dominating periods in the present study.

## *2.2.3. CALIOP*

4 Will-be-set-by-IN-TECH

which is calculated by comparing the data of the aethalometer to other instruments that measure BC using different techniques [2]. However, Weingartner et al. [89] reported that BC measurements using filter techniques have significant uncertainty due to "shadowing effect" after investigating several types of carbon aerosols. This effect causes underestimation of BC measurement due to its high loading on the filter. This effect is very pronounced for pure BC while almost negligible for aged atmospheric aerosols. This uncertainty is found to be less

AOD over Mt. Abu is also obtained from observations of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensors on-board Terra and Aqua satellites. Terra and Aqua spacecrafts pass over the equator at 10:30 and 13:30 Local Solar Time, respectively [43]. Global images of the full disc are produced due to larger swath widths and instrument-scanning angle of 110◦ [44]. MODIS has 36 channels spanning the spectral range from 0.41 to 14.4 *μ*m at three spatial resolutions: 250 m (2 channels), 500 m (5 channels) and 1 km (29 channels). MODIS aerosol algorithm consists of three independent algorithms to retrieve the aerosol characteristics, two over land and one over oceans, and makes use of eight of these channels (0.47-2.13 *μ*m) [29, 35, 67]. The measurements at other wavelengths provide information to identify clouds and river sediments [20, 45]. MODIS provides an accurate retrieval of spectral AOD and the parameters characterizing aerosol size [79, 80]. The retrieved data used in this study include both Terra and Aqua MODIS aerosol products; such estimations are made over cloud-free regions only [67]. Long-term analysis of MODIS aerosol retrievals collocated with AERONET measurements confirm that MODIS retrieved AOD agrees with AERONET observations to within 0.10 over land and to within 0.035 over oceanic island sites. There are several studies demonstrating that MODIS AOD has a strong correlation with AERONET AOD [41, 83, etc.] and thereby provide enough confidence to use the MODIS AOD over

Aerosol index (AI) is obtained from observations in the UV region (UV-1, 0.270 to 0.314 *μ*m; UV-2, 0.306 to 0.380 *μ*m) of the Ozone Monitoring Instrument (OMI) on-board Aura satellite [82]. AI is defined as the difference between satellite measured (including aerosol effects) spectral contrast at 0.360 and 0.331 *μ*m radiances and the contrast theoretically calculated from radiative transfer model for pure molecular (Rayleigh) atmosphere [9, 25, 28]. The Aura satellite launched in July 2004, flies eight minutes after the Aqua satellite as a part of NASA A-train constellation. OMI has been designed for the replacement of Total Ozone Mapping Spectrometer (TOMS) to continue recording the total ozone and other atmospheric parameters related to ozone and climate study. OMI is sensitive to aerosol absorption even when aerosols are present above the cloud. Therefore, AI can be successfully derived for clear as well as cloudy conditions. OMI has a spatial resolution of 13×24 km at nadir and uses the same algorithm that is used for TOMS observations. AI provides a quantitative measurement of UV-absorbing aerosols over all the terrestrial surfaces including deserts and ice sheets. AI is positive for absorbing aerosols and negative for non-absorbing aerosols. Zero AI indicates cloud presence. High OMI-AI values with high MODIS-AOD and low Ångstr*o*¨m exponent

than 10% [14].

*2.2.1. MODIS*

*2.2.2. OMI*

**2.2. Space-borne measurements**

western India, the region of interest in the current study.

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) provides a new insight into the role of atmospheric aerosols and clouds in regulating the study of Earth's climate change and air quality. It is a part of the A-train satellite constellation that includes Aqua, CloudSat, and Aura satellites. CALIPSO is in a sun-synchronous orbit at 705 km at an inclination of 98◦ and provides the vertical distribution of aerosols and clouds. It consists of three sensors: a Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP), an Imaging Infrared Radiometer (IIR), and a moderate spatial resolution Wide Field-of-view Camera (WFC). CALIPSO passes over the equator at 13:31 local hours, one minute behind Aqua. The primary instrument, CALIOP, transmits linearly polarized laser light of 0.532 *μ*m and 1.064 *μ*m at a pulse rate of 20.16 Hz. Its receiver measures the backscattered intensity at 0.532 *μ*m and 1.064 *μ*m with the former divided into two orthogonally polarized components which help to calibrate the optically thick clouds and aerosols. CALIOP observes both clouds and aerosols at high spatial resolution, but must be spatially averaged to increase signal to noise ratio. From the surface to 8 km, the vertical resolution is 30 m and the nominal horizontal resolution is 1/3 km. CALIPSO data products provide the aerosol vertical distribution along with aerosol layer height and AOD [7, 85]. CALIPSO LEVEL 2 Vertical Feature Mask (VFM) products provide vertical mapping of the locations of aerosols and clouds together with information about the types of each layer and the discrimination between aerosols and clouds is expected to be good in these products [4, 52, 87, etc.].

## **2.3. Models**

### *2.3.1. OPAC*

OPAC (Optical Properties of Aerosols and Clouds) model [26] is used to derive aerosol optical depth from the measured atmospheric aerosol chemical compositions obtained from literature [39, 40] at Mt. Abu. OPAC model contains two major parts: (1) a dataset of microphysical properties and the resulting optical properties of cloud and aerosol components at different wavelengths and for different humidity conditions, (2) a FORTRAN program that allows the user to extract data from this dataset, to calculate additional optical properties, and to calculate optical properties of mixtures of the stored clouds and aerosol components. In the present study, OPAC model has been used for obtaining the aerosol optical properties in shortwave region (0.25-4 *μ*m) from the known chemical compositions. OPAC, based on Mie theory, can compute aerosol optical properties at 61 wavelengths starting from 0.25 *μ*m to 40 *μ*m. It mainly has 10 aerosol components which are as follows - insolubles (mostly soil particles), water soluble aerosols (mainly sulfate and nitrate aerosols of anthropogenic origin), soot (of anthropogenic origin), sea salts (naturally produced on the oceanic surface by wind and also available in the atmosphere of coastal regions) in accumulation and coarse mode, mineral dust (generally coming into atmosphere from the arid surface by wind) in three modes, transported mineral dust and sulfate droplets (mainly found at stratospheric altitudes). This model is used to derive the AOD spectrum using a combination of aerosol components and in the present study the sulfate droplets are not considered. Some of the aerosol components which

#### 6 Will-be-set-by-IN-TECH 86 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert <sup>7</sup>

are hygroscopic in nature, may change their optical properties, and hence OPAC outputs are available for eight different relative humidity (0%, 50%, 70%, 80%, 90%, 95%, 98% and 99%) conditions. Optical properties for different aerosols are different. Single scattering albedo (SSA) is one of the important optical parameters for aerosol radiative effect calculations. OPAC derived SSA is the weighted average of SSA of all aerosol components. Water soluble (SSA ≈ 0.9 at 0.5 *μ*m) aerosols which contain mainly sulfate, nitrate, etc. and seasalt (SSA ≈ 0.99 at 0.5 *μ*m) do not absorb significantly in the visible range but they do absorb significantly in the infrared region (SSA ≤ 0.4 at 10.0 *μ*m). Major aerosol components are scattering type in the shortwave range (0.25-4.0 *μ*m), whereas, in the longwave range (4.0-40.0 *μ*m) they can be totally absorbing. The SSA of soot in the shortwave is 0.22 (at 0.5 *μ*m), whereas, in the longwave range it is totally absorbing. Dust (SSA ≈ 0.98 at 0.5 *μ*m) is mainly scattering in nature in the shortwave range but exhibits strong absorption in UV region and also in the longwave range. On one hand, in the longwave region absorption decreases the outgoing radiation, while on the other hand, the energy re-emitted consequent to this absorption increases the surface reaching infrared radiation. The net SSA over a particular location is the weighted average of SSA of all aerosol components.

or maritime conditions can be simulated using the standard aerosol models of Shettle & Fenn [72]. SBDART gives the opportunity to specify up to five aerosol layers (i.e., at five different altitudes), with radiative characteristics that model fresh or aged volcanic, meteoric,

Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert 87

The major inputs required to estimate the aerosol radiative effects for DISORT module in SBDART include spectral values of solar radiation incident on the atmosphere, spectral values of columnar AOD, SSA and angular phase function of the scattered radiation or asymmetry factor. The asymmetry factor is used to generate a scattering phase function through the Henyey-Greenstein approximation. The Henyey-Greenstein parameterization provides good accuracy when applied to radiative flux calculations [22, 84]. It can also compute radiation fluxes with less uncertainty from the aerosol optical properties at 0.55 micron wavelength obtained from satellite observations. Spectral values of AOD, SSA and asymmetry parameter are also obtained from OPAC using the chemical properties of the atmospheric aerosols. OPAC model derived aerosol optical parameters are obtained by varying the number concentration of individual components in small steps until the model derived parameters satisfactorily match the observed values. Another important input parameter that is required for accurate computation of the aerosol radiative effects over land is the surface reflectance [71, 90]. Radiative forcing is determined from the difference of the solar radiation with and without aerosols during clear-sky conditions in the short wave (0.25-4.0 *μ*m) by running SBDART for every one hour interval in a day using the profiles for tropical atmosphere. The present work gives more realistic results considering the aerosol vertical profiles from CALIPSO and MODIS surface reflectance over Mt. Abu. The seasonal forcing is estimated from the diurnally averaged forcing which represents the mean of the hourly

Major aerosol parameters have been monitored during 2006 and 2007 inside the campus of Physical Research Laboratory situated at Gurushikhar, Mt. Abu – the highest peak (1.7 Km asl) of Aravalli range in India. Topography of the Indian Peninsula, Himalayas and the Tibetan plateau are shown in Figure 1a. Arid (dashed line) and semi-arid (solid line) regions of Thar Desert in western India are shown in Figure 1b. More details on physical features of Thar Desert are described in literature [92]. Mt. Abu is situated within the semi-arid region of Thar Desert. A picture of the campus is shown in Figure 1c, which is better known for the astronomy observatory. Aravalli mountains are located in between Thar Desert and IGP. Major part of these mountains on the western side is in the semi-arid region of Thar Desert while the north-east region of the mountains is in IGP. The highest location, Mt. Abu is situated in the south-west of the mountain range. The observatory being a prohibited hilltop area makes the measurement site anthropogenic free and hence, is a suitable place for background aerosol measurements in western India. The observatory is built on rocky mountainous terrain surrounded by forest and therefore, there is significantly less soil dust coming from the surface of the nearby mountain region. Being very close (∼300 Km) to Thar Desert, measurement site gives an opportunity to study desert dust. Freshly generated desert dust aerosols are transported within few hours to Mt. Abu and thereby are exposed to local pollutants minimally. Also, due to the high altitude, these aerosols are less influenced by the boundary layer aerosols that consist mostly of locally produced anthropogenic aerosols.

and upper-tropospheric background aerosols.

forcing as derived from SBDART for 24 h/day.

**3. Site location and meteorology**

### *2.3.2. SBDART*

Atmospheric radiative transfer code, named Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) [68] developed at the University of California, Santa Barbara, is used to estimate aerosol radiative forcing over the study area. SBDART is a well established code for estimation of radiation flux in the shortwave (0.25-4.0 *μ*m) as well as longwave (4.0-40.0 *μ*m) range. It is a radiative transfer code that computes plane-parallel radiative transfer in clear and cloudy conditions within the Earth's atmosphere and at the surface. In the present study only clear sky conditions are considered. All the important processes that affect the ultraviolet, visible, and infrared radiation, are included in this code. For molecular absorption SBDART uses the low-resolution band models of LOWTRAN-7 atmospheric transmission code [56]. LOWTRAN-7 codes can take into account the effects of all radiatively active molecular species found in the Earth's atmosphere with wavelength resolution of about 5 nm in the visible and about 200 nm in the thermal infrared. In SBDART, the radiative transfer equations are numerically integrated with DISORT (Discreet Ordinate Radiative Transfer) code [74]. This discrete ordinate method provides a numerically stable algorithm to solve the equations of plane-parallel radiative transfer in a vertically inhomogeneous atmosphere. The intensity of both scattered and thermally emitted radiation can be computed at different heights and directions. Presently, SBDART is configured to allow up to 65 atmospheric layers and 20 radiation streams (20 zenith angles and 20 azimuthal modes).

The ground surface cover is an important determinant of the overall radiation environment because spectral albedo of the surface which defines the ratio of upwelling to downwelling spectral irradiance at the surface determines upwelling irradiance from the surface. In SBDART there are five basic surface types, namely (1) ocean water [76], (2) lake water [36], (3) vegetation [65], (4) snow [91], and (5) sand [73]. The spectral albedo describing a given surface is often well approximated by combinations of these basic surface types. Input parameters in SBDART allow the user to specify a mixed surface consisting of weighted combinations of water, snow, vegetation and sand. SBDART can compute the radiative effects of several lower and upper atmosphere aerosol types. In the lower atmosphere, typical rural, urban, or maritime conditions can be simulated using the standard aerosol models of Shettle & Fenn [72]. SBDART gives the opportunity to specify up to five aerosol layers (i.e., at five different altitudes), with radiative characteristics that model fresh or aged volcanic, meteoric, and upper-tropospheric background aerosols.

The major inputs required to estimate the aerosol radiative effects for DISORT module in SBDART include spectral values of solar radiation incident on the atmosphere, spectral values of columnar AOD, SSA and angular phase function of the scattered radiation or asymmetry factor. The asymmetry factor is used to generate a scattering phase function through the Henyey-Greenstein approximation. The Henyey-Greenstein parameterization provides good accuracy when applied to radiative flux calculations [22, 84]. It can also compute radiation fluxes with less uncertainty from the aerosol optical properties at 0.55 micron wavelength obtained from satellite observations. Spectral values of AOD, SSA and asymmetry parameter are also obtained from OPAC using the chemical properties of the atmospheric aerosols. OPAC model derived aerosol optical parameters are obtained by varying the number concentration of individual components in small steps until the model derived parameters satisfactorily match the observed values. Another important input parameter that is required for accurate computation of the aerosol radiative effects over land is the surface reflectance [71, 90]. Radiative forcing is determined from the difference of the solar radiation with and without aerosols during clear-sky conditions in the short wave (0.25-4.0 *μ*m) by running SBDART for every one hour interval in a day using the profiles for tropical atmosphere. The present work gives more realistic results considering the aerosol vertical profiles from CALIPSO and MODIS surface reflectance over Mt. Abu. The seasonal forcing is estimated from the diurnally averaged forcing which represents the mean of the hourly forcing as derived from SBDART for 24 h/day.

## **3. Site location and meteorology**

6 Will-be-set-by-IN-TECH

are hygroscopic in nature, may change their optical properties, and hence OPAC outputs are available for eight different relative humidity (0%, 50%, 70%, 80%, 90%, 95%, 98% and 99%) conditions. Optical properties for different aerosols are different. Single scattering albedo (SSA) is one of the important optical parameters for aerosol radiative effect calculations. OPAC derived SSA is the weighted average of SSA of all aerosol components. Water soluble (SSA ≈ 0.9 at 0.5 *μ*m) aerosols which contain mainly sulfate, nitrate, etc. and seasalt (SSA ≈ 0.99 at 0.5 *μ*m) do not absorb significantly in the visible range but they do absorb significantly in the infrared region (SSA ≤ 0.4 at 10.0 *μ*m). Major aerosol components are scattering type in the shortwave range (0.25-4.0 *μ*m), whereas, in the longwave range (4.0-40.0 *μ*m) they can be totally absorbing. The SSA of soot in the shortwave is 0.22 (at 0.5 *μ*m), whereas, in the longwave range it is totally absorbing. Dust (SSA ≈ 0.98 at 0.5 *μ*m) is mainly scattering in nature in the shortwave range but exhibits strong absorption in UV region and also in the longwave range. On one hand, in the longwave region absorption decreases the outgoing radiation, while on the other hand, the energy re-emitted consequent to this absorption increases the surface reaching infrared radiation. The net SSA over a particular location is

Atmospheric radiative transfer code, named Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) [68] developed at the University of California, Santa Barbara, is used to estimate aerosol radiative forcing over the study area. SBDART is a well established code for estimation of radiation flux in the shortwave (0.25-4.0 *μ*m) as well as longwave (4.0-40.0 *μ*m) range. It is a radiative transfer code that computes plane-parallel radiative transfer in clear and cloudy conditions within the Earth's atmosphere and at the surface. In the present study only clear sky conditions are considered. All the important processes that affect the ultraviolet, visible, and infrared radiation, are included in this code. For molecular absorption SBDART uses the low-resolution band models of LOWTRAN-7 atmospheric transmission code [56]. LOWTRAN-7 codes can take into account the effects of all radiatively active molecular species found in the Earth's atmosphere with wavelength resolution of about 5 nm in the visible and about 200 nm in the thermal infrared. In SBDART, the radiative transfer equations are numerically integrated with DISORT (Discreet Ordinate Radiative Transfer) code [74]. This discrete ordinate method provides a numerically stable algorithm to solve the equations of plane-parallel radiative transfer in a vertically inhomogeneous atmosphere. The intensity of both scattered and thermally emitted radiation can be computed at different heights and directions. Presently, SBDART is configured to allow up to 65 atmospheric layers and 20

The ground surface cover is an important determinant of the overall radiation environment because spectral albedo of the surface which defines the ratio of upwelling to downwelling spectral irradiance at the surface determines upwelling irradiance from the surface. In SBDART there are five basic surface types, namely (1) ocean water [76], (2) lake water [36], (3) vegetation [65], (4) snow [91], and (5) sand [73]. The spectral albedo describing a given surface is often well approximated by combinations of these basic surface types. Input parameters in SBDART allow the user to specify a mixed surface consisting of weighted combinations of water, snow, vegetation and sand. SBDART can compute the radiative effects of several lower and upper atmosphere aerosol types. In the lower atmosphere, typical rural, urban,

the weighted average of SSA of all aerosol components.

radiation streams (20 zenith angles and 20 azimuthal modes).

*2.3.2. SBDART*

Major aerosol parameters have been monitored during 2006 and 2007 inside the campus of Physical Research Laboratory situated at Gurushikhar, Mt. Abu – the highest peak (1.7 Km asl) of Aravalli range in India. Topography of the Indian Peninsula, Himalayas and the Tibetan plateau are shown in Figure 1a. Arid (dashed line) and semi-arid (solid line) regions of Thar Desert in western India are shown in Figure 1b. More details on physical features of Thar Desert are described in literature [92]. Mt. Abu is situated within the semi-arid region of Thar Desert. A picture of the campus is shown in Figure 1c, which is better known for the astronomy observatory. Aravalli mountains are located in between Thar Desert and IGP. Major part of these mountains on the western side is in the semi-arid region of Thar Desert while the north-east region of the mountains is in IGP. The highest location, Mt. Abu is situated in the south-west of the mountain range. The observatory being a prohibited hilltop area makes the measurement site anthropogenic free and hence, is a suitable place for background aerosol measurements in western India. The observatory is built on rocky mountainous terrain surrounded by forest and therefore, there is significantly less soil dust coming from the surface of the nearby mountain region. Being very close (∼300 Km) to Thar Desert, measurement site gives an opportunity to study desert dust. Freshly generated desert dust aerosols are transported within few hours to Mt. Abu and thereby are exposed to local pollutants minimally. Also, due to the high altitude, these aerosols are less influenced by the boundary layer aerosols that consist mostly of locally produced anthropogenic aerosols.

8 Will-be-set-by-IN-TECH 88 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert <sup>9</sup>

there is no significant variation present in RH. During monsoon and postmonsoon RH shows large variations about the means. During monsoon all the measurements of aerosol parameters were carried out only in June (mean RH = 63.9±12.6%). Observations were very few in July and August due to heavy rain and high RH. The seasonal variation of wind pattern over India subcontinent, obtained from National Center for Environmental Prediction (NCEP) reanalysis data is shown in the bottom row of Figure 2. Wind speed over study region was minimum and mainly coming from IGP during winter,. During premonsoon, wind over western India was westerly and coming from desert areas. During monsoon and

Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert 89

postmonsoon, wind became stronger coming from coastal region of Arabian Sea.

**Figure 2.** (Top) Diurnal variation of temperature and relative humidity during different seasons. The vertical bars represents ±1*σ* variation about the mean. (Bottom) Seasonal variation of wind speed and

Underlying surface plays an important role in the aerosol radiative effects towards climate change [24, 27, etc.]. Aerosols over high surface reflectance (bright surface) can produce relatively higher positive radiative forcing than those over low surface reflectance (dark surface). Space-borne observations suggest that there is a strong seasonal variation of surface over western India. Figures 3a and 3b show images of land surface over western India during premonsoon and postmonsoon seasons, respectively, captured by MODIS-Terra satellite. The surface is very bright during premonsoon due to open bare land, while it is relatively dark

direction, obtained from NCEP reanalysis data.

**3.1. Land surface properties**

**Figure 1.** (a) Topography of the Indian subcontinent. The box is showing western India including Thar Desert and Indo-Gangetic Plain. Star shows the location of Mt. Abu, highest location in the Aravalli Mountains. (b) Arid (dashed lines) and semi-arid (solid lines) region of Thar Desert. Mt. Abu is situated in the semi-arid region. (c) A photograph of the measurement site - PRL observatory at Mt. Abu.

Diurnal variations of surface temperature and relative humidity (RH) at Mt. Abu during different seasons are shown in the top row of Figure 2. The vertical bars represent the ±1*σ* variation about the hourly mean values. Temperature is found to be minimum at 15.5±3.0◦C during winter and maximum at 23.0±3.3◦C during premonsoon, followed by monsoon (19.3±2.0◦C) and postmonsoon (18.3±1.4◦C). In case of RH, minimum is observed at 24.6±6.4% during premonsoon and maximum at 88.3±10.5% during monsoon, followed by 54.7±22.8% during postmonsoon and 30.7±8.3% during winter. There is a strong diurnal variation in the hourly averaged surface temperature at Mt. Abu during all seasons, whereas, there is no significant variation present in RH. During monsoon and postmonsoon RH shows large variations about the means. During monsoon all the measurements of aerosol parameters were carried out only in June (mean RH = 63.9±12.6%). Observations were very few in July and August due to heavy rain and high RH. The seasonal variation of wind pattern over India subcontinent, obtained from National Center for Environmental Prediction (NCEP) reanalysis data is shown in the bottom row of Figure 2. Wind speed over study region was minimum and mainly coming from IGP during winter,. During premonsoon, wind over western India was westerly and coming from desert areas. During monsoon and postmonsoon, wind became stronger coming from coastal region of Arabian Sea.

**Figure 2.** (Top) Diurnal variation of temperature and relative humidity during different seasons. The vertical bars represents ±1*σ* variation about the mean. (Bottom) Seasonal variation of wind speed and direction, obtained from NCEP reanalysis data.

#### **3.1. Land surface properties**

8 Will-be-set-by-IN-TECH

**Figure 1.** (a) Topography of the Indian subcontinent. The box is showing western India including Thar Desert and Indo-Gangetic Plain. Star shows the location of Mt. Abu, highest location in the Aravalli Mountains. (b) Arid (dashed lines) and semi-arid (solid lines) region of Thar Desert. Mt. Abu is situated in the semi-arid region. (c) A photograph of the measurement site - PRL observatory at Mt. Abu.

Diurnal variations of surface temperature and relative humidity (RH) at Mt. Abu during different seasons are shown in the top row of Figure 2. The vertical bars represent the ±1*σ* variation about the hourly mean values. Temperature is found to be minimum at 15.5±3.0◦C during winter and maximum at 23.0±3.3◦C during premonsoon, followed by monsoon (19.3±2.0◦C) and postmonsoon (18.3±1.4◦C). In case of RH, minimum is observed at 24.6±6.4% during premonsoon and maximum at 88.3±10.5% during monsoon, followed by 54.7±22.8% during postmonsoon and 30.7±8.3% during winter. There is a strong diurnal variation in the hourly averaged surface temperature at Mt. Abu during all seasons, whereas,

Underlying surface plays an important role in the aerosol radiative effects towards climate change [24, 27, etc.]. Aerosols over high surface reflectance (bright surface) can produce relatively higher positive radiative forcing than those over low surface reflectance (dark surface). Space-borne observations suggest that there is a strong seasonal variation of surface over western India. Figures 3a and 3b show images of land surface over western India during premonsoon and postmonsoon seasons, respectively, captured by MODIS-Terra satellite. The surface is very bright during premonsoon due to open bare land, while it is relatively dark

#### 10 Will-be-set-by-IN-TECH 90 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics Natural vs Anthropogenic Background Aerosol Contribution to the Radiation Budget over Indian Thar Desert <sup>11</sup>

during postmonsoon due to green vegetation born during monsoon rain. As a result, surface reflectance is maximum during premonsoon and minimum during postmonsoon.

In the present study, MODIS derived surface reflectance data over Mt. Abu is used in the estimations of radiative forcing. It is obtained from Nadir BRDF-Adjusted Reflectance 16-Day L3 Global 0.5 km SIN Grid product which is derived at the mean solar zenith angle of Terra overpasses for every successive 16-day period, calculating surface reflectance as if every pixel in the grid was viewed from nadir direction. Surface reflectance data available in seven wavelength bands of MODIS centered around 0.47, 0.56, 0.65, 0.86, 1.24, 1.64 and 2.13 *μ*m are used to reproduce the spectral dependence of surface reflectances for the entire SW range using a combination of three different surface types, namely, vegetation, sand and water. The monthly variation of surface reflectance at 1.64 *μ*m during 2007 is shown in Figure 3c. Vertical lines in this Figure represent ±1*σ* variation about the monthly mean values. Average surface reflectance is found to be high at about 0.35 during premonsoon (Apr-May) and low at about 0.20 during postmonsoon (Sep-Nov) and winter (Dec-Feb). Space-borne observations show that the land over western India increases its brightness by about 75% during premonsoon season. This could be due to bare surface and deposited dust that is transported from arid region. Model simulations to fit the surface reflectance combining the three surfaces suggest that during premonsoon sand surface contributes a maximum of about 70% and during postmonsoon and winter it contributes a minimum of about 20% while vegetation surface contributes 15% and 60%, respectively. These varying land properties are also considered in the radiative forcing calculations.
