Dr. Steve Ghan
Editor, JGR-Atmospheres
February 20, 2012
Dear Dr. Ghan,
Many thanks for you alongwith comments/suggestions from three anonymous reviewers. We have considered
comments/suggestions of the reviewers and revised the manuscript.
Attached you will find point wise reply to the comments made by three reviewers.
We hope the revised manuscript will be acceptable to you and to the reviewers.
Your sincerely,
Ramesh P. Singh
behalf of all the authors
[email protected]
Encl:
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REPLY TO THE COMMENTS MADE BY REVIEWERS
Reviewer 1:
Paper: Influence of drought monsoon conditions on aerosols over India: The role of meteorology and
regional monsoon on aerosol emissions, distribution and properties
Authors: Kaskaoutis et al.
General Comments:
The paper examines the aerosol distribution over Indian subcontinent during two contrasting monsoon
years (2002 and 2003). Essentially, the paper presents an analysis to show that aerosol optical depth
(AOD) is high during low rainfall condition and since previous studies have documented that dust is one
of the primary components in this season; authors conclude that the increase in AOD is primarily due to
enhanced dust activity. The conclusion is simple and straightforward and what could have been an
important contribution, if the authors explained the changes in aerosol properties in view of
emissions and meteorology. They have made the right attempt, but the study period Apr-Jul spans over
two seasons, premonsoon and monsoon. Most of the north and northwest India (region with highest
influence of dust) do not experience much rainfall during Apr-Jun (Figure shown below). Hence,
frequent use of phrase “break phase” and “dry monsoon condition” in the title referring to dry
condition in May-Jun is misleading. The paper addresses an important issue, but is unnecessarily
lengthy with many contradictory statements (see the points below). Also, the first part of the paper does
not clarify the exact focus of the paper. The later analysis (AERONET and in-situ observations) clarifies
that the focus of the study is to understand that in 2002 and 2003 aerosol loading in general (dust in
particular) is more compared to other seasons in the decade due to dry condition. It would have been
easier to follow if the satellite analysis is presented in that way. To summarize, the paper needs to be
reorganized and concise.
Authors: The main concept of the present study is the association of the meteorology, in general, and the
drought conditions, in particular, occurred over northern India during specific months in late pre-monsoon
and monsoon seasons of 2002 and 2003 with the enhanced aerosol burden, mainly consisted of dust, over
the region. We thank the reviewer for his detailed and to-the-point review, which was taken into
consideration for improving the scientific quality of the paper. Following the above general comments,
we better clarified some parts of the discussions, mainly corresponding to dust presence and outflows, and
tried to shorten the manuscript wherever possible. The satellite analysis in the first part of the manuscript
is given in spatial distribution trends over the Indian subcontinent and not at specific locations in order to
highlight the influence of the meteorological and drought conditions to aerosol loading over northern
India and Indo-Gangetic Plains only.
1. Anomalies in the synoptic meteorology have been derived from 60 years of data, while that of AOD are
from 10 years of data. Any perturbations in the synoptic meteorology over the decades due to warming
climate may affect the interpretation of the anomalies of meteorological conditions in view of aerosol
distribution.
Authors: We have recalculated the anomalies of Mean Sea Level Pressure and Geopotential Height at 700
hPa, based on the period 1998-2009, which is the same period from which the precipitation anomalies
were derived and almost the same period from which the AOD anomalies were derived (2000-2009). The
anomaly patterns based on the 1998-2009 period are almost identical to those based on the longer (19492011) period with slight differences in the intensity of the positive or negative centers. Thus, the
conclusions are the same.
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In order i) to be consistent with the anomaly calculations of all the parameters (Precipitation, AOD,
MSLP, Z700), ii) to avoid the confusion of the reader with different time periods and iii) to appropriately
correlate and interpret the relation of the precipitation and AOD anomalies with the atmospheric
circulation ones, we have replaced the anomaly patterns of figure 1 with the new ones based on the period
1998-2009. We have also made a few alterations in the text, concerning the values of the positive and
negative anomaly centers.
2. As mentioned before, Apr-Jun is typical dry period in the northern India with very low rainfall. What is
the significance of the anomaly of these months? For example, rainfall shows negative anomaly in the
IGP in June 2002 and 2003 (Fig. 2), whereas AOD anomaly is very different in these two months (Fig. 3).
Why? It would have been more rationale to study the AOD distribution separately for the dry period (premonsoon) and “break phase” within the monsoon months of Jul-Sep. Manoj et al. studied aerosol
condition during the break phase of the monsoon season, while this study focuses on pre-monsoon and
early part of the monsoon season. Once the monsoon starts, the dynamics controlling the aerosol
distribution during active and break phase may be different than the dynamics during the pre-monsoon
months (Page 18, Lines 420-424).
Authors: We agree with the reviewer’s comment. Actually, the studied period is from April to July and
we used this in order to be the same for the two years (2002 and 2003). As clearly stated in the whole
manuscript, the meteorological, rainfall and aerosol anomalies are observed in May-June 2003 and July
2002. Actually, over northern India the rainfall is low in May and June and the monsoon starts by the end
of June. So, as reviewer stated the rainfall anomaly for low rainfall amounts is not as important as in the
month of July. However, we plotted these months since, in general, the decrease in rainfall is associated
with increased in AOD. On the other hand, the rainfall amount was negligible and the number of rainy
days very low during the prolonged dry May-June of 2003. This is discussed in the revised version.
Actually, this increase in AOD is more intense in June 2003 (slight different for that in June 2002), as
reviewer stated. However, note that the AOD variability over a region is influenced by several parameters
except of rainfall amount and anomalies, i.e. number of rainy days, wind speed and direction, dust
intensity, aerosol lifetime, local anthropogenic emissions, etc. All these aspects are discussed in the
revised version. The reviewer’s suggestion of studying the AOD distribution in two periods will make the
manuscript very lengthy and the main findings (at least for the break phase of the monsoon) have already
been published by Manoj et al. (2011).
3. Another important issue is the sampling density. There is already a sampling bias in satellite-retrievals
of AOD, because aerosol can only be retrieved when the sky is clear. This sampling bias needs to be
quantified before interpreting the anomaly and its relation to the dry condition.
Authors: This is true, since the insufficient number of days with AOD observations may bias the monthly
mean during the studied months. However, for analyzing the anomalies in AOD for each month in 2002
and 2003, at least 10 days of MODIS observations for each pixel are required; otherwise the anomaly
remains undetermined (white gaps in the figures). Note, that the most cloudy and rainy conditions in July
2003 are associated with the lower number of AOD pixels. All these aspects are discussed in the revised
version; however, the sampling bias is rather difficult to be quantified, since we do not have the whole
MODIS observations during each month over a specific pixel.
4. Elaborating on the previous point, MODIS AOD using deep blue approach (Fig. 4) shows similar AOD
during July 2002 and 2003 over the northwestern India, whereas the precipitation anomaly is opposite in
these two years. Is this discrepancy attributed partly to the sampling bias or are there any other
explanations?
Authors: Let us to disagree with this point. The AOD data series in Fig. 4 and the inset plot show higher
AOD in July 2002 than in July 2003. The peak in AOD is for July and August in 2002 and for June in
2003. The precipitation anomaly (Fig. 2) for the July months is in general agreement with the AOD
variation over Thar desert. On the other hand, the sampling bias in satellite retrievals still exists, mainly
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due to uncertainties in the Deep Blue retrievals (Hsu et al., 2004). Other explanations for possible
inconsistency between the rainfall and AOD anomalies have been discussed above (see our response in
specific comment 2).
5. Page 16, Lines 365-367: Is the trend in AOD statistically significant? If yes, how do the authors
attribute this to decrease in dust activity? Agricultural burning also shows seasonal peak during the
premonsoon season. How does that change with years? Is there any trend in Angstrom exponent?
Authors: The AOD trend obtained from MODIS Deep Blue algorithm over Thar desert is not statistically
significant. However, this sentence has been deleted in the revised version. On the other hand, at the end
of pre-monsoon season the agricultural fires are also intense over IGP; however, the dominant aerosol
type is desert dust, as the present results and several studies cited in the manuscript shown. Regarding the
trends in Angstrom exponent, a study under preparation at Kanpur AERONET station revealed a
statistically significant increase during the period 2001-2010 suggesting abundance of coarse-mode
aerosols (low alpha) during the first years of the study period. It was found that the increase in alpha was
statistically significant in May and July strongly influenced by the very low values in May 2003 and July
2002. However, these results are not cited in the manuscript since the data are still unpublished. Also, this
is beyond the scope of the present work and this part of the manuscript has been deleted in the revised
version.
6. Page 16, Lines 370-382: Authors did not discuss any variability of local emission sources. What is the
relevance of discussion of influence of El-Nino condition? Are the years of study El-Nino years?
Authors: We did not discuss the variability in local anthropogenic emissions, since there is no such
pronounced variability during the study months. Note also, that in this paper we do not focus on the
aerosol variability and trends during a long-term period in order to analyze and discuss any variability in
anthropogenic emissions. On the other hand, the natural aerosols dominate over anthropogenic ones
during April-July period over northern India. By citing the paper of Abish and Mohankumar we want to
make clear that except of the anthropogenic emissions, variability in meteorology and dust occurrence,
the large-scale synoptic dynamics also affect the AOD variation over northern India. Actually, the AprilJuly periods for 2002 and 2003 are intense positive El Nino years favoring the accumulation of aerosol
and pollutants over the region (B. Abish, personal communication). All the above are discussed in this
paragraph, which has extensively been modified and shortened.
7. Page 3, Lines 85-86: Trend in anthropogenic aerosols in north India is not well-defined. The papers
cited at best document an increasing trend in total AOD. Recently, Dey and Di Girolamo (GRL, 2011)
have used combination of size and shape of aerosols to qualitatively infer anthropogenic contribution and
its increasing trend in the post-monsoon to winter seasons.
Authors: The reviewer has right at this point. In the revision the sentence has been slightly modified
including “…total and anthropogenic aerosols…” in order to cover all the cited articles. The reference
Dey and di Girolamo is also cited at this part.
8. Page 20, Line 476: Good correlation between AOD at the two sites does not necessarily indicate same
pathways for dust transport. What is the correlation of Angstrom exponent at these two sites? If the
pathways are same, can the extreme values observed at Delhi and Kanpur also match?
Authors: We agree that the good correlation between the AODs at the two sites does not necessarily
indicate similarity of the source regions and transport pathways. However, we also cite a paper (Prasad
and Singh, 2007b) that shows that the air masses ended at Kanpur during major dust storms are traversed
over Delhi. There is also a consistency between the peaks in AODs at the two sites since the highest Delhi
values are close associated with highest Kanpur AODs. The correlation in the respective Angstrom
exponents is rather moderate, but not statistically significant (R2=0.48) and these values are determined in
different spectral bands for the two locations. Due to this reason this correlation is not shown
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9. How well do the SPRINTARS simulations match with the observations? Fig. 15 shows that dust AOD
in Jun 2004, 2005, 2006 and 2007 are higher than in 2003. This contradicts the earlier conclusions of
higher dust in 2002 and 2003 due to drier condition. Is this discrepancy attributed to large scale spatial
averaging? The authors could have shown the results from the dust dominated northern and northwestern
India to clarify.
Authors: In general, SPRINTARS simulations match satisfactory with aerosol observations over Asian
region as several studies cited in the manuscript shown. In figure 15, we originally focused on the
variability in AOD and dust-AOD over south Asia in order to compare the SPRINTARS results with
GOCART simulations (Kaskaoutis et al., 2011). However, per Reviewer’s comment and in order to avoid
conflict and maintain consistency, we have removed Figure 15 from the paper. We are presenting the
Dust AOD anomaly distribution from SPRINTARS simulations that show enhanced dust loading over
northern India during July 2002 and pre-monsoon period (May and June 2003), as clearly shown in Fig.
14. These simulations are, in general, consistent with the main subject of the paper, and support the
observations of enhanced aerosol loading, particularly dust, associated with anomalous prolonged dry
conditions over northern India.
Reviewer 2:
The idea of the manuscript is good. Drought conditions can obviously have a strong effect of
aerosols over India and the manuscript is studying these effects using multiple data: reanalysis,
satellite and ground-based measurements and chemical transport model results. The reasoning
and conclusions are clear and the different data are used for a strong general and consistent
argument.
Authors: We are grateful for the Referee for his valuable comments that have been taken into
account in the revised version.
I agree with most of the conclusions, but especially two points I think would be better clarified to
allow for a better understanding. Firstly, based on the results I am convinced that higher dust
loading has indeed contributed to higher aerosol load and AOD in the IGP in 2002 and
2003, but other processes that might have contributed could be evaluated more explicitly. I
am thinking especially of reduced wet removal due to less rain. To me it seems that reduced
rain, higher dust load and higher anthropogenic aerosol load could easily all be correlated with
each other. Although this is discussed to some extent in the article, I would recommend either
presenting an argument based on the data clearly excluding higher anthropogenic aerosol
load in the years 2002 and 2003 due to reduced wet removal as a strong contributor to
higher-than-climatology AOD and aerosol load in northern India then, or softening the
conclusions regarding the importance of dust. Regarding the SPRINTARS model, perhaps the
dust emissions could be described in more detail? The section describing the model could
describe how emissions are determined based on wind speed and soil moisture (instead of just
citing the reference) and maybe a figure could be added showing how the reanalysis weather
affects the dust emissions. Secondly, perhaps a bit less importantly, I think it would be nice to
see the aerosol load in northern India mentioned in the last sentence of the abstract more
clearly (see also last sentence of this review regarding Figure 15).
Authors: In the revised manuscript a discussion is given for the other processes that might
contribute to accumulation of natural coarse-mode aerosols over northern India during the study
periods. However, the several peaks in AOD and the results from Prasad and Singh (2007b)
agree to increased dust outflows. The results (high AODs, low alpha and columnar size
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distributions with enhanced coarse mode) show that during the periods with enhanced AOD the
natural particles clearly dominate over the anthropogenic fine-mode aerosols.
In the description of SPRINTARS model the dust emissions and simulation are described in
more detail. The SPRINTARS is coupled to MIROC AGCM, so basically the meteorological
fields can be calculated by itself. But to properly simulate the meteorological fields, we used
NCEP/NCAR reanalysis data by nudging wind, water vapor and temperature every 6 hours. This
point was written in the manuscript. The soil moisture and snow are online calculated by the
model.
The figure of the weather reanalysis shows the anomaly from the mean meteorological situation
on monthly basis suggesting high pressure conditions that favor the subsidence and dry
conditions. In order to associate the synoptic weather conditions with dust outflows we need
extra figures during specific dust events, which are several during the study period. The inclusion
of some extra figures and discussions will enlarge significantly the length of the paper, which
according to reviewers must be shortened in some parts. On the other hand, the main scope is to
associate the weather conditions with the deficit of rainfall and abundance of aerosols due to
increased dust activity and longer aerosol lifetime and not to emphasize on specific dust events.
The last sentence of the abstract has been removed for shortening the revised version.
As minor comments regarding the structure, I think the abstract would be better shortened and
summarized and Supplementary figure 1 containing the TOMS AI could be included as a regular
Figure.
Authors: The abstract has been shortened in the revised version. Regarding the supplementary
figure we maintained this as supplementary material due to sensor degradation issues as stated in
the manuscript.
Figures 1-3 showing weather conditions and MODIS AOD during pre-monsoon and monsoon
months in 2002 and 2003 serve as a good starting point for the paper. Figures 4-6 could show
more clearly the comparison between the years 2002 and 2003 and the other years to be even
more convincing in that dust emissions and transport to Kanpur and Delhi have really been larger
in 2002 and 2003. Figure 4 could in addition to the years 2002 and 2003 show some kind of
comparison with other years and in Figures 5-6 a more clear comparison than the horizontal lines
showing averages over all months could be used to show how the years 2002 and 2003 deviate
from climatology. Figures 12 and 13 are excellent in supporting the conclusion regarding higher
dust emission and transport to the IGP in 2002 and 2003, assuming the data are representative for
the whole months. Maybe a bit more discussion regarding possible biases could be added. Are
these data cloud screened and could it have and effect? Figure 15 I would like more if modified
somehow to or supplemented by a figure showing clearly the AOD and dust trends for the premonsoon and monsoon season (and perhaps the annual means) instead of a regression line fitted
to a curve dominated by the seasonal cycle.
Authors: The comparison between the aerosol optical properties in the two sites (Kanpur and
Delhi) is mainly given in Figs. 8-11, where the deviation of the years 2002 and 2003 from the
decadal mean is clearly revealed.
The columnar size distributions and SSA values are obtained from almucantar AERONET
measurements by applying the Spectral Deconvolution Algorithm and are cloud-screened data.
The errors and uncertainties in such computations are discussed in several papers regarding the
AERONET, which are cited in section 2.5. However, in the revised version some possible biases
in the results of Figs. 12 and 13 are added.
Regarsing figure 15, we originally focused on the variability in AOD and dust-AOD over south Asia in
order to compare the SPRINTARS results with GOCART simulations (Kaskaoutis et al., 2011). However,
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in order maintain consistency, we have removed Figure 15 related to the SPRINTARS time series
and only show the dust AOD anomaly patterns as shown in Figure 14. This change is
incorporated in order to maintain consistency with the main theme of the paper in support of the
enhanced dust loading over northern India, as shown in observations.
Reviewer 3:
Specific comments to author:
Abstract, line 74-78: Please see comments made in the conclusion section.
Authors: See our response below.
Introduction, line 83: In addition to this two, changes in the source types and their distribution are also
responsible for the space-time aerosol heterogeneities over the Indian region.
Authors: We included these processes in the revised version.
Section 1 Introduction, line 134: Early or peak monsoon months (June and July)
Authors: For north/northwestern India June is early monsoon month. The monsoonal rain starts by the end of
June, July is a rainy month and the peak of the monsoon is usually in August. In the present work the period
April-July for the years 2002 and 2003 is examined.
Section 2.3 MODIS data, line 166-169: Please re-write this statement. There are no dark-target retrievals over
ocean! The MODIS algorithm for land and ocean are different. I understand that author uses MODIS Collection
005 aerosol optical depths derived following dark target approach.
Authors: This sentence has been corrected.
Section 2.3 MODIS data, line 170: "Since the aim of this study to analyze the aerosol properties over greater
Indian region, the Indo-Gangetic plain in particular, we believe that the aerosol data at 1 deg by 1 deg should
suffice for the analysis."
Authors: Actually, this is our mean. We cannot see any objection here.
Section 2.3 MODIS data, line 174-175: the nearest source region for dust aerosols in the northern India.
Authors: This sentence has been modified and shortened in the revised version.
Section 2.4 TOMS Data, line 181-183: In addition to south Asia, TOMS data was also analyzed over the
surrounding regions like Pakistan, southern Afghanistan, Iran, and part of Arabian Peninsula, since these are the
potential sources of dust emission and can influence the aerosol properties over the northern Indian region.
Authors: this sentence has partly been modified according to the reviewer’s suggestion.
Section 2.6 Microtops measurements, line 210 : did you have sun tracker for this task?
Authors: No, the Microtops-II is manually operated instrument. However, as mentioned in the manuscript in
order to avoid any discrepancy in the actual sun-disk targeting the instrument is placed on a tripod stand.
Section 2.6 Microtops measurements, line 210 : how do you exclude could effect from measurements? Visual
inspection of sky?
Authors: The possible cloud contamination was excluded from the spectral AODs by applying the method by
Kaskaoutis et al (2011) as referred in the manuscript. In the revised version this has been better clarified.
However, the Microtops-II measurement have been performing under cloudless conditions, when the sun disk is
free of clouds and when the clouds are far from sun’s field of view.
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Section 2.6 Microtops measurements, line 219 : what is the expected uncertainty in MICROTOPS
measurements (as provided by the manufacturer)?
Authors: The expected uncertainty in spectral AOD from Microtops-II is ±0.03. It is included in the revised
version.
Section 3.1 Atmospheric circulation and precipitation regime line 316: As far as I remember correctly, the lack
of rainfall July 2002 contributed most towards the drought condition in that year. The rainfall picks up during
following months and obey expected pattern.
Authors: This is taken into account and the sentence has been accordingly modified.
Section 3.1 Atmospheric circulation and precipitation regime line 319 : Later two may be associated with, or I
should say, influenced by the weak monsoon rainfall. The anti-cyclonic circulation, dry airmass deprived of
moisture is major reasons for weak/deficit monsoon in 2002.
Authors: This sentence was modified according to the reviewer comments. In the previous discussions in the
text we noted the association between anti-cyclonic circulation and deficit of rainfall in monsoon 2002 and
especially in July 2002.
Section 3.2 Aerosol field over south Asia, line 422: I do not consider May and half of June to be the monsoon
months. This period is well characterized with increase in the dust loading over the northern Indian either due to
locally wind-driven dust emissions or long-range transport.
Authors: We agree with the reviewer and this sentence has been strongly modified. Actually, the active and
break spells refer to the rainy monsoon period and throughout the manuscript we removed such statements for
the pre-monsoon months.
Section 3.2 Aerosol field over south Asia, line 426: long break spell in most part of July 2002 followed by an
active spell in Aug 2002.
Authors: This sentence has been modified following the reviewer’s suggestions.
Section 3.2 Aerosol field over south Asia, line 428: break spells during May and June does not make any sense
as these two months, particularly May and half of June, for the northern Indian region is still considered to be
pre-monsoon. And likely for the same reason no or weak correlation found between OLR and precipitation
anomaly during 2003.
Authors: This sentence has been removed in the revised version.
Section 3.2 Aerosol field over south Asia, line 431: be cautious to use break monsoon period here. The July is
climatologically active period which in 2002 turn out to be quite anomalous with large deficits in precipitation.
And in the wake of deficit rainfall, the suspended particulate matter continued to remain in the atmosphere
which otherwise during normal monsoon would have been washed out.
Authors: Actually, July is active period for monsoon, but the most part of July 2002 was a break period as also
stated above. Thus, we refer to this season. The break conditions and the deficit of rainfall enhance the
atmospheric lifetime of aerosols as written in the manuscript. On the other hand, this sentence has been
modified in the revised version.
Section 3.3.1 Aerosol Optical Depth and Angstrom Exponent, line 457-459: Not agreed with this one. Actually,
the AODs during July 2002 are higher than its respective decadal mean which is also associated with low alpha
values.
Authors: The AOD during July 2002 is higher than the respective decadal mean, but the peaks in AOD are not
so often as in May-June 2003. This is clear from Fig. 5. Some more discussions are given at this part of the
manuscript following the suggestions from all the reviewers.
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Section 3.3.1 Aerosol Optical Depth and Angstrom Exponent, line 471-474: The elevated AODs during MayJune 2003 could be just due to inter-annual variation in dust loading strength and not necessarily linked to the
draught condition because climatologically Apr-May-June are considered to be dry pre-monsoon months where
very less rain is expected which again do not contribute much towards all India monsoon rainfall.
Authors: At this part of the manuscript, i.e. in the lines noted by the reviewer, we discuss the association of the
AOD peaks over Delhi and Kanpur with the positive anomalies in satellite-derived AOD and AI over northern
India. We do not associate them, especially in May-June 2003, with the deficit of rainfall, which as reviewer
says and we agree is low over north/northwestern India. Regarding the latter, we took special care throughout
the manuscript of avoiding such statements following the reviewer’s comments.
Section 3.3.1 Aerosol Optical Depth and Angstrom Exponent, line 485: Using MODIS data, Jethva et al. (2005)
showed a phase diagram of ALPHA Vs AOD over the IGP stations in which a gradient of AOD and ALPHA
were associated with the relative distance of stations from the dust source region.
Authors: Jethva et al. (2005) analyzed the MODIS AOD and fine-mode fraction (not alpha) over specific
locations in IGP. In their phase diagram (Fig. 8) they show larger AODs and lower fine-mode fraction in
western locations (Amritsar) during May-June, which are consisted with our statement. The reference of Jethva
et al. (2005) has been included at this specific line in the revised version.
Section 3.3.2 Aerosol size distribution, line 601: author may add Russell et al. (2010) ACP paper here.
Authors: Thank you for suggesting this paper. It has been cited in the revised.
Section 4.0 Conclusion, line 658-661: As I have pointed out this issue 2-3 times in this report, the rise in aerosol
load during pre-monsoon of 2003 may not be linked to deficit rainfall over the IGP. The rainfall during May
and first half of June is anyway very less over the northern Indian region, and therefore associating increase in
load of natural aerosols with the rainfall anomaly doesn't hold any point here. I strongly recommend author to
rethink about considering monsoon-aerosol link for the pre-monsoon of 2003. And if author still wish to include
pre-monsoon 2003 analysis then he should adopt an adjusted or appropriate tone with keeping the above fact in
the mind.
Authors: At this specific point, and in the whole manuscript, we avoided a direct association of the AOD peaks
in May-June 2003 with deficit of rainfall, since rainfall is less at this time of the year over IGP region. However,
the rainfall in May-June 2003 is even lesser from the climatological value as shown via TRMM figures. Indeed,
such an association might be occurred, but since it is not as intense as in July 2002 such a “strong” statement
was avoided in the revised version.
Section 4.0 Conclusion, line 668: this is also true in short-term climatological sense. The IGP region during premonsoon period characterized by dust loading and associated changes in aerosol properties with respect to its
background. However, what was unique about 2002 was the anomaly in dust loading/properties with reference
to the long-term mean during that period.
Authors: We agree with the reviewer and there is no objection here. In the revised version, we removed the
sentence “In particular, uniqueness… monsoon season.” For shortening the manuscript, since the main
findings are highlighted in the previous and following sentences.
Section 4.0 Conclusion, line 683-684: Author contradicting himself here. In the statement previous to this,
author says that an increase in dust activity was attributed to the draught/dry conditions over the northern Indian
region which is one of the major results of this paper. In the following statement, author links this increase with
a declining trend during pre-monsoon and monsoon which is result of weak aerosol activities following the
anomalous year of 2002-2003. I am having hard time to understand these two statements. How the extreme
aerosol events of 2002 and 2003 are linked with weak activities during following year or season? Also, author
compares here trends over two regions, south Asia vs. northern India. What author can say, in my opinion, is
that despite the positive anomaly in aerosol loading over this region, a slight decline in trend has been noticed
due to weaker activities during following years.
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Authors: There is no any contradiction here, but just a misunderstanding that has been clarified in the revised
version by removing these sentences. Actually, the dust activity and AOD peak over IGP in July 2002 and MayJune 2003. When examining the decadal (2000-2009) trends of aerosols over this region, we found a declining
trend in AOD during late pre-monsoon and monsoon seasons, which was significantly influenced by the
extreme values in 2002 and 2003.
Section 4.0 Conclusion, line 686: SPRINTAS simulation shows almost no trend in dust AOD!
Authors: This sentence has been removed in the revised for the reasons explained just above.
Figure 4: Adding years before 2002 and after 2003 would provide the contrast in AOD pattern.
Authors: In figure 4 we do not emphasize in the contrast in AOD pattern by presenting the daily values. This
contrast is shown in the inset figure.
Figure 6: AODs over both stations went down during late June in 2002 which is followed by a dramatic increase
in July. The differences in AOD time-series between 2002 and 2003 over Delhi are interesting! The strength of
the AOD anomaly during May and June 2003 is quite larger compared to that in 2002, although, AODs were
larger than the decadal mean in both years. While the AOD anomaly during July 2002 remains larger than
mean, it's showing a decrease in July 2003.
Authors: We strongly agree with the reviewer’s discussions. However, we cannot see any objection or
suggestion in his words.
Figure 12: This is interesting! April is a normal, however, the dust loading during May and June when rainy
season has not arrived yet, is larger in 2002-2003 compared to 10-year averaged. And of course, July stands out
to be the largest anomaly. This means that the dust buildup was higher during pre-monsoon in 2002-2003 for
some reason other than the rainfall anomaly. An identical y-axis scale for all plots is desirable here to facilitate
comparison.
Authors: From the columnar size distribution (CSD) Figs. the dust buildup during premonsoon of 2003 cannot
be seen as higher that the respective July one. Note that the CSD monthly-mean curves correspond to both years
of 2002 and 2003, as stated in the manuscript. Note also the low number of observations during June and July
(red curves). However, the decadal-mean curves show higher dV/dlnR for coarse mode during May and June,
which are the peak dusty months in India, as stated in the manuscript and in Gautam et al. (2009, GRL). In the
revised version, the y-axis scale is identical for all plots.
Supplementary figure 1: This plot could be misleading. First, the months of April, May and first half of June do
not belong to the active monsoon period, instead it's the pre-monsoon/summer time over this region. So, for
these 2 1/2 months, the anomaly in TOMS AI shown here with reference to long-term mean could be just due to
the inter-annual variation in dust loading. Same explanation/conclusion can be drawn in the case of July,
although we know that the high AI values observed during June-July are attributed to prolonged dust loading in
the absence of active rain spell.
Authors: We agree that the higher AI values in May and June are attributed to inter-annual variation in dust
loading as stated in the manuscript. In the revised version, we avoided to associate this pre-monsoon/summer
period to active monsoon. Our scope is to show the enhanced AI values due to higher presence of dust during
the specific months of 2002 and 2003.
A time-series of AI for the period 2000-2010 using combined TOMS+OMI observations over Delhi and Kanpur
will clearly bring out the contrast in dust loading during 2002-2003 compared to rest years. Also, the AI
anomaly for 2002-2003 could be calculated with reference to mean of 2000-2010 period.
Authors: As we stated in the manuscript, all the above were avoided since TOMS-AI exhibits higher errors after
2001 and, therefore, any trend analysis is better to be avoided. For this reason, we just provided the monthly
means of AI for a qualitative comparison only. On the other hand, the TOMS and OMI AI values have some
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differences as discussed in Habib et al. (2006, Atmos.Environ.) and for this reason they have not been
combined.
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