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the overall uncertainty. Dey and Tripathi
23
have presented a detailed
analysis on the error budget of the estimations, where they have found that
uncertainties vary in the range 5-20% due to various individual parameters.
The overall uncertainty in the anthropogenic ADRF comes out to be
∼
21%.
3. Results and Discussion
3.1
. Spatio-temporal variations of ADRF in IGB
Looking spatially for clear-sky ADRF, the central portion of IGB from
west to east has highest surface ADRF in the winter (
30 W m
−
2
)along
the major urban areas. The values reduce in February in general with
higher ADRF still visible in isolated patches in the western and easternmost
regions. Surface ADRF starts building up again from March, reaching the
maxima (
<−
45 W m
−
2
) in May-June. As monsoon arrives in the IGB,
aerosols are being washed out and the reduced burden of aerosols decreases
the surface ADRF until September. From October, aerosol loading again
starts increasing and continues to winter. Mean (
>−
SD) annual clear-sky
TOA, surface, and atmospheric ADRF in the IGB are estimated to be
−
±
12 W m
−
2
, respectively. In the presence
of clouds, mean annual TOA ADRF switches from cooling to heating,
while the surface ADRF becomes less negative. This has compensated the
excess heating at TOA maintaining the atmospheric heating almost similar
to the clear-sky condition. The reduction in magnitude of the negative
surface ADRF in cloudy-sky condition is high (more than 10 W m
−
2
) during
the December-January and May-July. In these months, TOA forcing also
increases by more than 7 W m
−
2
. During the winter, as most of the aerosols
are confined within the boundary layer, they get lesser chance to interact
with the incoming solar radiation, a major part of which is reflected back to
the space by optically thick clouds. Hence the surface cooling due to aerosols
reduces and TOA ADRF flips toward positive side indicating warming
effect. In August, the absolute magnitude of surface forcing is low due
to least aerosol loading; hence the relative change in surface ADRF due to
inclusion of cloud is also less. In other months, as the cloud fraction is low
(
<
0.3), the effect is not so conspicuous.
The spatial heterogeneity in surface ADRF for four distinct seasons
is shown in Fig. 3, where the latitudinally averaged ADRF values are
presented with their standard deviations (plotted as vertical bars). Surface
ADRF in winter and post-monsoon seasons display similar range of
2.9
±
4.3,
−
25.5
±
13, and +22.6
±
