1
Continental Tropical Convergence Zone (CTCZ)
Programme
ANNUAL PROGRESS REPORT
2012 -2013
CTCZ Programme Office
Centre for Atmospheric and Oceanic Sciences
Indian Institute of Science, Bengaluru
Under the Support of
The Ministry of Earth Sciences
Government of India, New Delhi
2
S.No Project No. PI and
Organization
Project Title Page No.
1
PC1 - Project 1 Dr. Arindam
Chakraborty,
IISc., Bangalore
Cloud microphysics characteristics
and modeling over the Indian Region
using a cloud resolving model
4-9
2
PC1 - Project 2 Dr. Sagnik Dey,
IIT Delhi
Understanding microphysical
evolution of clouds in the Indian
CTCZ : Variability and impacts of
aerosols
10-21
3
PC1 -Project 3 Dr. M.Chate , IITM
Pune
Investigations of aerosol-cloud-
environment interactions using
combined aerosol, CCN and rain
measurements during CTCZ Field
Campaigns
22-26
4 PC1 - Project 4
Dr. A.Karipot, Uni
. Pune
Surface layer characteristics and
moisture budget of the monsoon
boundary layer - A study using
micrometeorological measurements
and Large-eddy simulation
27-40
5
PC1 - Project 5 Dr. M.Mandal, IIT
Kharagpur
Regional assimilation of land surface
parameters over Indian landmass for
providing surface boundary
condition to numerical models for
simulation of monsoon processes
41-46
6
PC1 - Project 6 Dr. Manoj Kumar,
BIT Ranchi
Surface process observational studies
coupled with atmospheric transfer
interaction along eastern end of
monsoon trough
47-66
7
PC1 - Project 10 Prof. Maithili
Sharan, IIT Delhi
Boundary layer characteristics over
surfaces representative of CTCZ
region of India
67-70
8
PC1 - Project 11 Dr. M. V. Ramana,
IIST Trivandrum
Near simultaneous measurements of
Aerosols, clouds and turbulence as
the Maximum Cloud Zone (MCZ)
moves northward - Coordinated
airborne, ship-borne/ground - based
and space-borne measurements.
71-72
9
PC1 - Project 12 Dr. A.N.V.
Satyanarayana, IIT
Kharagpur
Observational and Modelling of
atmospheric boundary layer over
different land surface conditions in
the CTCZ domain during different
epochs of Indian Summer Monsoon
73-76
10
PC1 - Project 15 Dr. V.V.Srinivas,
IISc., Bangalore
Modelling Hydrology of Mahanadi
River basin considering changes in
Land-use/Land-cover
77-82
List of contents
3
11
PC2 - Project 1 Prof.G.S.Bhat,
IISc., Bangalore
Surface energy Balance and
Atmospheric Structure over the
CTCZ Area : An observational study
83-99
12
PC2 - Project 2 Dr. D. Shankar
NIO, Goa
Oceanographic observational
component during CTCZ 2011-12
100-105
13
PC2 - Project 3 a.Dr. P. N.
Vinayachandran
IISc., Bangalore
b. Dr. R.Jyothibabu
NIO, Kochi
Underwater radiation and
chlorophyll measurements during
CTCZ 2011-12
106-109
110-112
14
PC2 - Project 4 Mr. K.Vijay
Kumar, NIO Goa
Air-Sea flux observations from
research vessel during CTCZ
113-125
15
PC3 - Project 1 Dr. Arindam
Chakraborty,
IISc. Bangalore
Development of a prognostic Cloud
scheme for Global Climate Models
126-129
16
PC3 - Project 2 Dr. Saumyendu De,
IITM,Pune
Role of high frequency oscillations
on the predictability of Monsoon
Transients over the CTCZ through
Nonlinear error energetics of
prognostic model
130-133
17
PC3 - Project 3 Prof. Ravi
Nanjundiah, IISc.,
Bangalore
Impact of Bay of Bengal Cold pool
on the seasonal and intraseasonal
pattern of rainfall
134-138
18
PC3 - Project 4 Prof. U.C.
Mohanty,
IIT Delhi
Simulation and prediction of intense
convective systems associated with
Indian summer Monsoon : Role of
land surface processes
139-153
19
PC3 - Project 6 Prof. G.S.Bhat
IISc., Bangalore
Proposal for CTCZ Programme
Office at CAOS, IISc., Bangalore
154-157
4
PROGRESS REPORT
1. Project Title :
Cloud Microphysics Characteristics and
Modeling over the Indian Region Using a
Cloud Resolving Model
Project No.:
PC1-Project1
2. Implementing Organization Indian Institute of Science
3.PI (Name, Address, e-mail, land line,
mobile)
Arindam Chakraborty
Centre for Atmospheric and Oceanic
Sciences
Indian Institute of Science
Bangalore - 560 012, INDIA.
Email: [email protected]
Tel: +91-80-22933074
Cell: 9611982854
4. Co-PI (Name, Address, e-mail, mobile)
V Venugopal
Centre for Atmospheric and Oceanic
Sciences
Indian Institute of Science
Bangalore - 560 012, INDIA.
Email: [email protected]
Tel: +91-80-22933073
5. Approved Objectives of the Project
1. To study the fine-scale spatio-temporal characteristics of cloud microphysics over the Indian region for various convective systems including those are responsible for
heavy precipitation.
2. Propose improvements to existing cloud microphysical parameterization used in WRF model in cloud resolving configuration.
5. 1 Date of Start September 2011
5.2 Expected date of completion August 2014
5.3 Total cost of the Project: Rs. 19.43 Lakhs
5.4 Expenditure as on 31/03/2013: Rs. 2,87,286.00
6. Summary of progress made:
Please see attached document (Annexure 1).
7.Work which remains to be done under the project
a. Preliminary model simulations and identification of biases in existing cloud microphysics representations
b. Improvement of cloud microphysical processes c. Investigation of the skill of the model using the improved cloud microphysical
scheme
d. Write up the results and publications (modelling part).
5
8. Publications from this project
Bhattacharya, A, A. Chakraborty and V Venugopal, 2013:Variability of Cloud Liquid Water
and Ice over South Asia from TMI Estimates, Climate Dynamics, Under Revision.
Bhattacharya, A, A. Chakraborty and V Venugopal: Observed and Modeled space-time
characteristics of cloud hydrometeors over Indian region, OCHAMP, Indian Institute of
Tropical Meteorology, February 2012.
Bhattacharya, A, A. Chakraborty and V Venugopal: Space-time characteristics of cloud
hydrometeors over Indian region, International conference on Monsoon and Its
Variability, Indian Institute of Science, July 2011.
Bhattacharya, A, A. Chakraborty and V Venugopal: A Comparative Study of Cloud Liquid
Water and Ice Over Indian Region, Annual Conference of the American Meteorological
Society, New Orleans, USA, February 2012.
9. Major equipments (Please see attached expenditure sheet)
S. No. Item Procurement and
installation status
including model and
make
Cost
(Rs. in lakhs)
Working
condition
10. Difficulty, if any, in implementing the project or any other comments/suggestions
Date : 28 Jun. 13 (Arindam Chakraborty)
Place : Bangalore ( PI's signature )
6
Annexure 1
Project Title: Cloud Microphysics Characteristics and Modeling over the Indian Region
Using a Cloud Resolving Model
PI: Arindam Chakraborty, CAOS, IISc. Bangalore
Co-PI: V Venugopal, CAOS, IISc. Bangalore
Summary of Research:
In this study, using TRMM 2A12 microwave estimates of cloud liquid water and cloud ice
for 7 years (2004-2010), we systematically document the vertical distribution of cloud liquid
water and cloud ice over the Indian land and surrounding ocean regions, and attempt to
understand some of the observed geographical and seasonal differences. In general, we find
that the mean cloud liquid water and cloud ice content of land and oceanic regions are
different, with the ocean regions showing higher amount of cloud liquid water (CLW)
(Figure 1). The western parts of the Indian region show a striking land-sea contrast (Table 1
defines these regions). While the CLW and cloud ice (CLI) over the land part of the Arabian
Sea coast (WCL) have similar distribution as those of central India; the CLW and CLI
profiles over the oceanic part (WCO) are higher than the profiles for the land regions and
lower than profiles for the Bay of Bengal (trapped ocean) and the Equatorial Indian Ocean
(open ocean) regions. Specifically, at relatively low rainfall intensities, higher amount of
CLW was noticed over the Arabian Sea as compared to that over the Bay of Bengal and the
Equatorial Indian Ocean. The converse is true for high rainfall regimes. In addition, we find
for both land and ocean, CLW and CLI have a monotonically increasing relation with
precipitation intensity, which in itself is perhaps not surprising.
Further analysis shows that when interseasonal (monsoon versus pre-monsoon) or
intraseasonal (June versus August) CLW profiles were compared, the lower rainfall periods
(May and June) appeared to show higher CLW than the higher rainfall periods (JJAS or
August) (Figure 2). We speculate that the higher CLW during the lean rainfall periods could
partially be attributed to the indirect aerosol effect, considering the fact that May and June
mean aerosol optical depths are significantly higher (suggesting higher aerosol concentration)
than during the monsoon season. Specifically, during the break phase, aerosols (e.g., black
carbon) are accumulated in the region. As a consequence, the indirect effect of aerosols is to
provide favorable conditions (i.e., acting as cloud condensation nuclei)for larger
accumulation of cloud liquid water. We tested this speculation by comparing CLW over
central India (Figure 3) with a region close to the Indian subcontinent, namely, southeast
Asia, which does not have much aerosol concentration. Preliminary analysis suggests that our
speculation has value. In particular, unlike the central Indian region, where the CLW in the
break-to-active transition phase is significantly higher than in the active-to-break transition
phase, the southeast Asian region shows no significant difference in the CLW profiles across
different phases of the monsoon. Clearly, a more thorough investigation is needed with the
aid of numerical models to corroborate the hypothesis, for which the work is in progress.
7
Table 1: Spatial extent of five regions used in this study.
8
Figure1: Vertical mean distribution of observed (TRMM 2A12; JJAS 2004-2010) CLW
(left column) and CLI (right column), as a function of precipitation, over (a, b) Central
India; (c, d) Bay of Bengal; (e, f) Equatorial Indian Ocean; (g, h) West Coast Ocean; and
(i, j) West Coast Land. The precipitation values have been grouped into 2 mm/h bins.
Table 1 lists these regions.
9
Figure 2: Vertical profiles of climatological (2004-2010) mean cloud liquid
water (gm/m3) for May (blue), JJAS (red) over central India for (a) for all
grids/days, (b) for only those grids/days with measurable rain.
Figure 3: Vertical profiles of climatological (2004-2010) mean cloud liquid water (gm/m3)
for active (blue), break (red), active-to-break (green) and break-to-active (black) phases
during JJAS over central India.
10
PROGRESS REPORT
1. Project Title :
Understanding microphysical evolution of
clouds in the Indian CTCZ: variability and
impacts of aerosols
Project No.: MOES/CTCZ/16/28/10
PC1-Project 2
2. Implementing Organization Indian Institute of Technology, Delhi, Hauz
Khas, New Delhi-110016
3.PI(Name, Address, e-mail, land line,
mobile)
Dr. Sagnik Dey
Centre for Atmospheric Sciences
Indian Institute of Technology Delhi
Email: [email protected]
Phone: 011-26591315
: 9873544872
4. Co-PI (Name, Address, e-mail, mobile)
Prof. U. C. Mohanty
Centre for Atmospheric Sciences
Indian Institute of Technology Delhi
Email: [email protected]
Phone: 011-26591314
5. Approved Objectives of the Project:
Understand the microphysical and structural evolution of cloud fields in the Indian CTCZ region
Study the space-time variability of cloud properties Examination of the sensitivity of cloud microphysical properties in response to
changing aerosol properties
6. 1 Date of Start 16th
May 2011
6.2 Expected date of completion 15th
May 2014
6.3 Total cost of the Project: Rs. 19,12,040 (original), Rs. 16,92,656 (revised)
6.4 Expenditure as on 31/03/2013 : Rs. 3165
7. Summary of progress made:
See Annexure I
8.Work which remains to be done under the project: See Annexure I
9. Publications from this project:
1. Dey, S., K. Sengupta, G. Basil, S. Das, Nidhi, S. K. Dash, A. Sarkar, P. Srivastava, A. Singh and P. Agarwal (2012), Satellite-based 3D structure of cloud and aerosols over
the Indian monsoon region: Implications for aerosol-cloud interaction, SPIE
Proceeding, Vol. 8529, Remote Sensing and Modelling of the Atmosphere, Oceans,
and Interactions IV, 852907 (November 8, 2012); doi: 10.1117/12.979246.
2. Nidhi, K. Sengupta and S. Dey, Climatology of vertical distributions of clouds over the oceanic regions surrounding the Indian Subcontinent from passive remote sensing
(Under Review for J. Geophys. Res.)
11
3. K. Sengupta and S. Dey, Structural evolution of monsoon clouds in the Indian CTCZ (Under review for Geophys. Res. Lett.)
4. Nidhi and S. Dey, Cloud variability over India from a new remote sensing technique, ISRS Annual Conference, Bhopal, Nov 2011 (The work has been awarded as Best
Student Presentation).
5. Nidhi, K. Sengupta and S. Dey, Climatology of 3-D distribution of clouds in the Indian monsoon region, OCHAMP Conference at IITM, Pune, Feb 2012.
10. Major equipments
S. No. Item Procurement and
installation status
including model and
make
Cost
(Rs. in lakhs)
Working
condition
1 Desktop Dell, Installed Working
2 Laptop Dell, Installed Working
3 Accessories Installed Working
TOTAL 1,98,949
11. Difficulty, if any, in implementing the project or any other comments/suggestions: The
manpower budget for the 1st year was made nil by mistake.
Date : 10.06.2013 ( Sagnik Dey )
Place : Delhi ( PI's signature )
12
Annexure I
Works completed:
A. Cloud Climatology over the oceans adjoining the Indian subcontinent:
Summary:
Robust observation-based statistics of cloud vertical distribution (relative to aerosols) is
required to reduce the uncertainty in climate forcing due to aerosol-cloud interaction. In this
work, the climatology of cloud vertical distribution was examined over the oceanic regions
(Arabian Sea, AS; Bay of Bengal, BoB and South Indian Ocean, SIO) surrounding the Indian
subcontinent using data from Multiangle Imaging SpectroRadiometer (MISR), GCM-
Oriented CALIPSO Cloud Product (GOCCP) and the International Satellite Cloud
Climatology Project (ISCCP). Inter-comparison of these datasets reveals a multi-layer cloud
structure throughout the year that must be accounted for in the climate models to improve the
estimates of cloud radiative feedback. A combination of MISR (stereo technique) and ISCCP
(radiometric technique) cloud datasets captures the multilayer cloud view over the regions as
observed by the active GOCCP dataset. The implications of such statistics are also discussed.
The key results include: (1) total cloud cover (fc) and net cloud radiative forcing (CRF) show
strong seasonality over the AS (mean annual fc lies in the range 0.5-0.61 as estimated from
three passive and one active sensor) and BoB (mean annual fc lies in the range 0.69-0.75)
relative to the SIO (mean annual fc lies in the range 0.64-0.71); (2) a dominance of low and
high clouds throughout the year; (3) near cancellation of shortwave (SW) cooling at top-of-
atmosphere (TOA) by longwave (LW) warming leading to a small net TOA cooling at the
regions dominated by low clouds and (4) stronger SW cooling than LW warming leading to a
large net TOA cooling in the presence of optically thick high clouds.
Approach:
Since our objective is to understand variability of cloud vertical distribution over the
oceans surrounding the subcontinent, the domain was chosen as follows: the AS bounded by
20 N to equator and 58-73 E longitude, the BoB bounded by 20 N to equator and 86-94
E and SIO bounded by equator to 20 S and 58-94 E longitude. We analyzed MISR cloud
fraction by altitude (CFbA) and MODIS cloud products for ten years (Mar 2000-Feb 2010),
GOCCP-fc for five years (Jun 2006-Dec 2010) and ISCCP data for eight years (Jan 2000-Dec
2007). Mean monthly statistics have been generated for fc, its vertical distribution and relative
abundance of various cloud types. Results are interpreted in terms of the differences in the
retrieval techniques. fc is defined as the fraction of cloudy pixels in the total number of pixels
by the passive sensors and may vary simply because of different cloud detection techniques
[Stubenrauch et al., 2013] and/or different pixel resolutions of various sensors [Zhao and Di
Girolamo, 2006]. While comparing climatology of fc and cloud vertical distributions, daytime
retrievals are considered because MISR can detect clouds only in daytime.
Results:
The temporal variability of fc from various sensors is shown in Figure 1. The climatology
was derived from the multi-sensor observations within 3-hour window (10:30 am to 1:30 pm)
to minimize the influence of diurnal variability on fc. The seasonal variability of fc is strong
over the AS and BoB with highest values of fc (0.7-0.9) in the monsoon (Jun-Sep) season as
expected, and lowest values (0.4-0.5) in the winter season (Dec-Feb) as revealed by the
passive (MODIS, MISR and ISCCP) and active (GOCCP) sensors (Figure 2). GOCCP shows
a slight low bias in fc in the monsoon season, which may stem from the way fc is defined as a
direct consequence of the lidar limitation. The monsoon season is characterized by the
13
Ju
n-0
0
Dec-0
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n-0
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n-0
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n-0
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9
0.0
0.2
0.4
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0.8
1.0
South Indian Ocean
f c
Jun-0
0
Dec-0
0
Jun-0
1
Dec-0
1
Jun-0
2
Dec-0
2
Jun-0
3
Dec-0
3
Jun-0
4
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4
Jun-0
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5
Jun-0
6
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6
Jun-0
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7
Jun-0
8
Dec-0
8
Jun-0
9
Dec-0
9
0.0
0.2
0.4
0.6
0.8
1.0
Bay of Bengal
f c
Jun-0
0
Dec-0
0
Jun-0
1
Dec-0
1
Jun-0
2
Dec-0
2
Jun-0
3
Dec-0
3
Jun-0
4
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4
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8
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Dec-0
9
0.0
0.2
0.4
0.6
0.8
1.0
Arabian Sea
f c
development of optically thick convective clouds. If the lidar signal becomes attenuated due
to penetration through optically thick clouds, the number of times low-level clouds are
detected within a grid will be reduced and thus fc will also be reduced. The passive sensors
detect the cloud tops and calculate fc by counting the number of cloudy pixels within the grid.
Seasonal variability of fc is much lower over the SIO compared to the AS and BoB as shown
by the passive and active sensors (Table 1). The mean (1) annual fc over the AS are 0.610.18, 0.610.17, 0.50.17 and 0.550.19 as estimated by MODIS, MISR, ISCCP and
GOCCP respectively. The corresponding values are 0.750.14, 0.710.16, 0.700.12 and
0.690.16 for the BoB, and 0.690.06, 0.710.06, 0.640.05 and 0.640.06 for the SIO. We
note here that some difference in the statistics (Table 1) between the active and passive
sensors may arise from different time period of observations [Wu et al., 2009]. More regional
scale analysis may resolve this issue, but this further emphasizes the importance of height-
stratified cloudiness in interpreting the cloud variability [Stubenrauch et al., 2013].
MISR-derived mean monthly vertical distribution of clouds from surface to 20 km altitude
at 0.5 km vertical resolution is shown in the top panel of Figure 2. Dominance of low level
clouds in the first 3 km over all the three ocean basins is noticeable throughout the year. Mid-
to-high level clouds are observed to evolve over the AS and BoB during the monsoon season.
On the contrary, the SIO shows no seasonality in mid-to-high level clouds; instead, there is
an increment in the low clouds during the monsoon season (Jun-Sep). Mean (1) annual low cloud amount over the AS, BoB and SIO are 0.340.06, 0.240.05 and 0.390.11
respectively. Corresponding values for the mid-level and high clouds are 0.080.02,
0.080.01, and 0.160.15 and 0.190.07, 0.320.07 and 0.210.10 respectively. Annually,
Figure 1 Temporal variability of fc from MISR and MODIS (during Mar 2000-Feb
2010), ISCCP (during Jan 2000-Dec 2007) and GOCCP (during Jun 2006-Feb 2010)
over the AS, BoB and SIO.
MODIS
MISR
ISCCP
GOCCP
14
low clouds contribute 57%, 34% and 55% to fc over the AS, BoB and SIO respectively, while
the corresponding relative contributions of high clouds are 31%, 46% and 30% respectively.
Since ground truth data do not exist in this case to evaluate the MISR statistics, the
vertical structure of clouds is also examined using GOCCP data (bottom panel of Figure 2).
Active sensor can detect multilayer clouds within the same pixel and hence can be considered
as more accurate than passive sensor. Our analysis reveals large amount (fc>0.3) of high-level
clouds at ~14-16 km over the AS and BoB, especially during the monsoon season. More
uniform monthly fc at this altitude range is observed over the SIO relative to the other two
regions. In the tropics, large fc at such high altitudes may be attributed to the anvil cirrus
[Folkins et al., 2000], which was confirmed by GOCCP scattering ratio profiles. MISR fails
to detect cirrus clouds whose optical depth is below 0.3 [Prasad and Davies, 2012], while the
GOCCP detect clouds with COD>0.07 [Chepfer et al., 2010]. Instead, MISR can see through
the thin cirrus clouds and detect the low clouds by stereo technique. During the monsoon
season, there is an overall increase in fc over all three ocean basins. The increase in fc with
height, especially over the AS and BoB where cloud heights reach 10-15 km, is an indication
of the formation of deep convective clouds over these basins. The high intensity winds
transport moisture northwards from the SIO leading to large convective activity over the AS
and BoB resulting in the formation of convective clouds [Mohanty et al., 2002]. However,
such seasonal change in cloud vertical structure is not observed over the SIO. Monthly
variation of fc of low-level clouds are similar for MISR and GOCCP. Slightly high bias in
MISR statistics relative to GOCCP may be attributed to clear conservative cloud mask
approach of MISR [Zhao and Di Girolamo, 2006], which detects any pixel as completely
cloudy even if it is partially filled by clouds. Hence this approach overestimates fc in the
tropical regions dominated by small cumulus clouds [e.g. Jones et al., 2012]. Low bias in
low-level cloudiness in GOCCP data may also result from the masking effect of high clouds
as noted by Konsta et al. [2012]. Climatology of cloud vertical structure from MISR for the
same period as of GOCCP does not change the overall conclusion.
To gain further understanding of the multilayer cloud field over the oceans as seen from
GOCCP and MISR statistics, the ISCCP D2 dataset is also analyzed to derive mean monthly
contributions of each individual cloud type to fc (Figure 3). Climatologically, differences in
mean annual fc of low, mid-level and high clouds from ISCCP and MISR are -9%, 3% and
8% respectively over the AS. Over the BoB, ISCCP and MISR-retrieved fc of low clouds are
similar, while ISSCP overestimates mid-level cloud by 9% and underestimates high clouds
by 5% relative to MISR. ISCCP underestimates the fc of low, mid-level and high clouds by
7%, 3% and 5% respectively relative to MISR over the SIO.
On the other hand, high clouds are found to occur more frequently (similar to GOCCP)
than other cloud types with the mean annual values of 65% over the BoB, 61% over the AS
and 51% over the SIO (Figure 3). Cirrus dominates among the high clouds throughout the
year (as also shown by Meenu et al., 2010); however, the relative abundance of deep
convective clouds shows a strong seasonal cycle consistent with the monsoon circulation in
this region. Cumulus and altocumulus dominate among the low and mid-level clouds
respectively and their relative abundances are higher during the post-monsoon to winter
seasons over the AS and BoB relative to other seasons [Bony et al., 2000].
15
Months Figure 3 Monthly statistics of relative abundance of the individual cloud types from ISCCP
over the (a) AS (b) BoB and (c) SIO for the period Jan 2000-Dec 2007. Months (in X-axis) are
represented by numbers starting from 1 (Jan) to 12 (Dec). 'Cu', 'Sc', 'St', 'Ac', 'As', 'Ns', 'Ci', 'Cs'
and 'Dc' represent 'cumulus', 'stratocumulus, 'stratus', altocumulus, 'altostratus, 'nimbostratus',
'cirrus', 'cirrostratus' and 'deep convective' clouds respectively.
Arabian Sea Bay of Bengal South Indian Ocean
Months Figure 2 Mean monthly climatology of cloud vertical structure using MISR data for the
period Mar 2000-Feb 2010 (top panel) and GOCCP data for the period Jun 2006-Feb 2010
(bottom panel) over the AS, BoB and SIO. Months (in X-axis) are represented by numbers
starting from 1 (Jan) to 12 (Dec).
16
B. Structural evolution of clouds in the CTCZ region:
Summary:
Structural evolution of monsoon clouds in the core monsoon region of India has been
examined using multi-sensor data. Positive rainfall anomaly is associated with invigoration of
warm clouds above 4.5 km that occurred in only 15.4% days in the last 11 monsoon seasons.
Cloud top pressure reduces with an increase in aerosol optical depth with a higher rate of
invigoration in drier condition (represented by negative rainfall anomaly) characterized by
larger fraction of absorbing aerosols than wet condition (i.e. positive rainfall anomaly). Cloud
effective radius for warm clouds does not show any significant change in presence of high
aerosol concentration in presence of high liquid water path. The structural evolution of
monsoon clouds is influenced by both dynamic feedback and microphysical processes that
prolongs the cloud lifetime, leading to infrequent rainfall.
Approach:
MISR derived cloud fraction by altitude (CFbA) daily product was used for the cloud
vertical structure for the period of eleven monsoon seasons (Jun-Sep) during the period 2000-
2010. Active remote sensing data are available (e.g. CALIPSO and CloudSat) for the present
analysis, but their shorter temporal coverage (Jul 2006 onwards) and narrower swath relative
to MISR lead to low sampling frequency for robust analysis using daily data. Cloud
microphysical parameters (liquid water path, LWP and Reff), cloud top pressure (CTP) and
columnar aerosol optical depth (at 550 nm), AOD are taken from MODIS onboard the same
Terra satellite (on which MISR is also flying). Level 3 (spatial resolution of 11) daily
C005 data for the same period were analyzed. Global validation of MODIS AOD was
discussed in Levy et al. [2010], while LWP and Reff were found to be highly correlated with
in-situ data, but with a high bias [Min et al., 2012]. Aerosol Index (AI) data were taken from
Ozone Monitoring Instrument to characterize absorbing aerosols. Typically, AI>0.2 denotes
absorbing aerosols [Torres et al., 2007].
Tropical Rainfall Measuring Mission (TRMM) TMI data was used for the daily
precipitation in each 11 grid within the core monsoon region (defined by 20-25N and
70-88 E), where the variation of rainfall shows a significant correlation (0.87) to the all-
India rainfall [Gadgil, 2003]. The rainfall anomaly normalized with respect to the standard
deviation (R) is estimated based on the daily rainfall data of eleven monsoon seasons. 58.2%
of the total 1342 days in the last eleven monsoon seasons show negative R, while large
precipitation events (R>2) occurred in only 4.5% of the days (Table 1). All aerosol and cloud
parameters are classified for five regimes of R, -2
17
Since the possibility of aerosol-cloud interaction is largest for the low-level clouds that
coexist with aerosols, the changes in fc of low clouds in response to increasing AOD over the
India monsoon region are examined (Figure 5). Analysis has been carried out separately for
each season because of the seasonality in aerosol characteristics. Mean fc doubles with an
increase in AOD from 0.05 to 0.25 during the winter season, which is significant at 95%
confidence level, CI according to t-test. Mean fc does not vary significantly until AOD
reaches 0.35, beyond which it drops down to 0.196. The magnitude of the variation is less
during the pre-monsoon season, when fc increases by ~33% (from 0.137 to 0.183) until AOD
reaches 0.25, beyond which it decreases with any further increase in AOD. In the monsoon
season, the reduction in fc of low clouds is observed at AOD>0.15. The variation in the post-
monsoon season is similar to that in winter season. Mean fc increases from 0.083 to 0.196
with an increase in AOD from 0.05 to 0.2, remains more or less constant with an increase in
AOD to 0.35 and decreases to 0.156 with further increase of AOD. The fc-AOD relationships
observed here over the entire subcontinent (covering both land and ocean) during the post-
monsoon and winter seasons, similar to the variations observed over a part of the Indian
Ocean using high resolution ASTER data during winter season, may be explained by a
transition from aerosol indirect to semi-direct effect. Aerosols over this region are highly
absorbing during this period to cause semi-direct effect. The insignificant changes of fc of
low clouds with AOD in the range 0.25
18
hand, the change is more rapid during the other two seasons. For example, fc increases with
an increase in AOD until AOD reaches 0.25 in the pre-monsoon season and starts reducing
with further increase in AOD. The corresponding threshold for the monsoon season is
AOD=0.15. This rapid transition from an increasing to decreasing cloudiness of low clouds
may be explained by conversion of shallow to deep convection in presence of large aerosol
concentration.
C. Invigoration of clouds by aerosols:
When classified as a function of AOD, CTP also shows decrease with an increase in
AOD at all ranges of R (Figure 6). For example, CTP reduces from ~800 hPa (~480 hPa) at
AOD0.7 for -2
19
2010]. At negative R (i.e. dry condition), AI is high (1.210.6), probably due to larger dust
and smoke transport [Ramachandran and Kedia, 2012] and continues to decrease with an
increase in R. However, note that mean AI is 0.830.26 even at R>2 suggesting that the
aerosols that were observed to be persistent throughout the monsoon season, have a large
fraction of absorbing component. Aircraft measurements in the CTCZ region during the
monsoon season [Jaidevi et al., 2011] also revealed presence of absorbing aerosols up to 3
km altitude resulting in a large heating in the lower troposphere. We interpret that this local
convective heating by absorbing aerosols may strengthen the updraft in favourable synoptic
condition by destabilizing the atmosphere above the aerosol layer [Koren et al., 2008]. The
results imply that the aerosol dynamic effect coupled with the microphysical effect, facilitate
invigoration of monsoon clouds, leading to more infrequent rainfall in the last decade. At
R>2 (i.e. large precipitation days), strongest downdraft is seen between 300-450 hPa altitude
ranges, where the high clouds show maximum positive anomaly.
Figure 6 Changes of mean CTP in response to an increase in AOD as a function of R.
20
Progress (Ongoing work)
(i) Cloud microphysical parameters are being analyzed in view of the structural changes in the cloud vertical structure and aerosol loading in the core monsoon region.
(ii) The previous analysis is being extended to all rainfall homogeneous zones, separately for the four monsoon months (Jun-Sep).
(iii) The microphysical relationships between aerosol-cloud-rainfall established by
CAIPEEX campaign are being examined using the satellite data for closure studies.
(iv) Simulated cloud field by regional climate model RegCM is being evaluated against observations.
Works remaining
(i) Examination of robustness of the observed aerosol-cloud-precipitation relationships in the Indian CTCZ region.
(ii) Quantifying precipitation susceptibility its variation in space and time.
References:
Bony, S., Collins WC, Fillmore D (2000), Indian ocean low clouds during the winter
monsoon, J Clim 13: 20282043.
Chepfer, H., S. Bony, D. Winker, G. Cesana, J. L. Dufresne, P. Minnis, C. J. Stubenrauch,
and S. Zeng (2010), The GCM Oriented CALIPSO Cloud Product (CALIPSO-GOCCP),
J. Geophys. Res., 115, D00H16, doi:10.1029/2009JD012251.
Folkins, I., S. Oltmans, and A. Thompson (2000), Tropical convective outflow and near
surface equivalent potential temperatures, Geophys. Res. Lett., 27, 2549 2552,
doi:10.1029/2000GL011524.
Gadgil, S. (2003), The Indian monsoon and its variability, Annu. Rev. Earth Planet Sci., 31,
429-467.
Jaidevi, J., S. N. Tripathi, T. Gupta, B. N. Singh, V. Gopalakrishnan and S. Dey (2011),
Observation-based 3-D view of aerosol radiative properties over Indian Continental
Tropical Convergence Zone: implications to regional climate, Tellus, 63B, 971-989.
Jones, A. L., L. Di Girolamo and G. Zhao (2012), Reducing the resolution bias in cloud
fraction from satellite derived clear-conservative cloud masks, J. Geophys. Res., 117,
D12201, doi:10.1029/2011JD017195.
Konsta, D., H. Chepfer, and J.-L. Duresne (2012), A process oriented characterization of
tropical oceanic clouds for climate model evaluation, based on a statistical analysis of
daytime A-train observations, Clim. Dyn., 39 (9-10), 2091-2108.
Koren, I., J. Vanderlei martins, L. A. Remer and H. Afargan (2008), Smoke invigoration
versus inhibition of clouds over the Amazon, Science, 321, 946-949.
Levy, R. C., L. A. Remer, R. G. Kleidman, S. Matoo, C. Ichoky, R. Kahn and T. F. Eck
(2010), Global evaluation of the collection 5 MODIS dark-target aerosol products over
land, Atmos. CHem. Phys., 10, 10399-10420.
Li, Z., F. Niu, J. Fan, Y. Liu, D. Rosenfeld and Y. Dang (2011), Long-term impacts of
aerosols on the vertical development of clouds and precipitation, Nat. Geosci., 4, 888-
894.
21
Meenu, S., K. Rajeev, K. Parameswaran, A. K. M. Nair (2010), Regional distribution of deep
clouds and cloud top altitudes over the Indian Subcontinent and the surrounding oceans,
J. Geophys. Res., 115, D5, doi:10.1029/2009JD11802.
Mohanty, U.C., R.Bhatla, P. V. S.Raju, O. P.Madan and A.Sarkar (2002), Meteorological
fields variability over the Indian Seas in pre and summer monsoon months during
extreme monsoon seasons, Earth Planet. Sci.,111 (3), 365-378.
Ramachandran, S., and S. Kedia, (2012), Aerosol, clouds and rainfall: inter-annual and
regional variations over India, Clim. Dyn., 40 (7-8), 1591-1610.
Rosenfeld, D., H. Wang, and P. J. Rasch (2012), The roles of cloud drop effective radius and
LWP in determining rain properties in marine stratocumulus, Geophys. Res. Lett., 39,
L13801, doi:10.1029/2012GL052028.
Stubenrauch, C. J. et al. (2013), Assessment of global cloud datasets from satellites: Project
and database initiated by the GEWEX radiation panel, Bull. Am. Meteorol. Soc. (in press).
Zhao, G. and L. Di Girolamo (2006), Cloud fraction errors for trade wind cumuli from EOS-
Terra instruments, Geophys. Res. Lett., 33, L20802, doi:10.1029/2006GL027088.
22
PROGRESS REPORT
1. Project Title:
Investigation of Aerosol-Cloud
Environmental interactions using combined
aerosol, CCN and rain measurements during
CTCZ field campaigns
Project No.:
PC1- Project 3
2. Implementing Organization Indian Institute of Tropical Meteorology,
Pune
3.PI(Name, Address, e-mail, land line,
mobile)
Dr. D. M. Chate, IITM, Pune
9637327928 (M) 020-25904257 (Off)
4. Co-PI (Name, Address, e-mail, mobile)
V. Gopalakrishnan, IITM, Pune
9423243026 (M) 020-25904283 (Off)
5. Approved Objectives of the Project:
(a) To study the nucleation scavenging process for aerosols by making simultaneous
observations of CCN, aerosol and raindrop size distributions over Bay of Bengal.
(b) To establish a quantitative relationship between cloud micro-physical properties and role
of CCN in cloud-environment interactions for precipitation formation.
(c) To determine roles of marine aerosols on CCN formation using CCN distributions and
new particle formation and their growth properties by aerosol size distributions.
(d) To understand the role of cloud nucleation on stratiform and convective rain formations.
(e)To synthesize the land-ocean contrast of aerosol-cloud-precipitation interactions.
5. 1 Date of Start May 2011
5.2 Expected date of completion May 2014
5.3 Total cost of the Project: Rs. 11,30,000
5.4 Expenditure as on 31/03/2013 : IITM funding
6. Summary of progress made:
(on a separate sheet if required)
1. Measurements of Cloud Condensation Nuclei (CCN) distribution with super saturation (ss) between 0.2 and 1 %, aerosol size distribution and raindrop spectra
were made over the Northern Bay of Bengal (BoB) during Continental Tropical
Convergence Zone (CTCZ) cruise campaign (9th
July-8th
August, 2012). 2. With the analysis of data for CCN and aerosol distribution on board during stationary
position of Sagar Kanya cruise observations (21 to July 28 2012) over the BoB, we
presented these results in the International workshop on "Changing Chemistry in
Changing Climate: Monsoon (C4) during May 1st to 3
rd, 2013.
7.Work which remains to be done under the project:
1. Detailed Analysis of observations
2. Detailed study of the measurements made onboard the ship.
23
8. Publications from this project:
Waghmare, R. T. Chate, D. M., Gopalkrishanan, V., Beig, G. , and P. C. S. Devara, Cloud
condensation nuclei and aerosol measurements over the Bay of Bengal, International
workshop on "Changing Chemistry in Changing Climate: Monsoon (C4) during May 1st to
3rd
, 2013, at the IITM, Pune (Please refer Annexure 1)
9. Major equipments:
S. No. Item Procurement and
installation status
including model and
make
Cost
(Rs. in lakhs)
Working
condition
N/A N/A N/A N/A N/A
10. Difficulty, if any, in implementing the project or any other comments/suggestions
NIL
Date: 27/06/2013 D. M.Chate
Place: Pune (PIs signature)
24
Annexure 1
Cloud condensation nuclei and aerosol measurements over the Bay of Bengal
R T Waghmare, *Chate, D M, Gopalkrishanan, V, Beig, G, Sachin Ghude, Cinmaykumar
Jena, P C S Devara
Abstract
Measurements of Cloud Condensation Nuclei (CCN) spectra with super saturation (ss)
between 0.2 and 1 % were made over the Bay of Bengal (BoB) during Continental Tropical
Convergence Zone (CTCZ) cruise campaign. We present CCN on board during stationary
cruise position (22 to 27
th July, 2012) over the BoB. A power law which relates CCN
concentrations with ss in terms of empirical constants C and k is presented from the CCN
spectra. The fitted spectral parameter k about 0.32 over the BoB is comparable to the CCN
observed at equatorial Pacific.
Introduction
Large-scale latitudinal transition of the Inter-Tropical Convergence Zone (ITCZ) over Indian
subcontinent including the Bay of Bengal (BoB) from winter to monsoon and vice-versa that
influences the aerosol compositions alters CCN spectra. CCN over the BoB, where this vital
subset of aerosol may exert its greatest impact is important. We report measurements taken
from shipboard over the BoB during stationary cruise position (22 to 27
th July, 2012).
Data Collection
Cloud nucleating properties of the aerosol was measured with a commercial CCN counter
(DMT model CCN-100) which is to expose the aerosol to fixed atmospheric ss at a time, and
to measure the number of activated particles with Optical Particle Counter. The ss values are
altered in a cycle, and an activated CCN concentration as a function of ss is measured. We
operated the CCN counter at ss of 0.2, 0.4, 0.6, 0.8 and 1% which covers atmospheric cloud
formation ss values. The activated CCN concentration is given with a time resolution of 1
second, but since it takes few minutes to equilibrate the system with ss, we considered a
measurement cycle of 30 minutes.
Results
CCN concentrations relates to atmospheric ss with a power law ( ), where CCN is expressed
in cm-3
and ss is expressed in percentage. The constant c corresponds to the CCN at 1% ss.
(1%), the particles activate at 1% super-saturation. We have fit our observations obtained
during stationary cruise position with this power law and compared them with other results.
The power law curves for the measured CCN spectra over these sites are shown in Figure 2.
The k value is found to be 0.32, for BoB, 0.3 for maritime (Australia) and 0.4 for equatorial
pacific (Hegg and Hobbs, 1992).
Conclusions
The observations show the CCN counts increase when ss varied from 0.2% to 1%. The fact
that CCN counts ~1000 cm-3 and k ~0.32 comparable to equatorial marine environment
indicates that activation takes place on newly formed particles due to nucleation bursts.
25
Acknowledgement
Indian Institute of Tropical Meteorology, Pune is supported by the Ministry of Earth Sciences
(MoES), Government of India, New Delhi. Authors sincerely acknowledge the wholehearted
support of Prof. B. N. Goswami, Director, IITM, Pune for CTCZ cruise campaign.
References
Hegg, D. A., and Hobbs, P. V., Cloud condensation nuclei in the marine atmosphere: A
review in Nucleation and Atmospheric Aerosols, N. Fukuta and P. E. Wagner, eds., Deepak
Publishing Hampton, VA, pp. 181-192, 1992.
26
27
PROGRESS REPORT
1. Project Title: Surface-layer characteristics
and moisture budget of the monsoon boundary
layer A study using micrometeorological
measurements and Large-Eddy Simulation
Project No.: MoES/CTCZ/16/28/10
PC1 - Project4
2. Implementing Organization University of Pune
3.PI(Name, Address, e-mail, land line, mobile)
Dr.Anandakumar Karipot
Associate Professor
Department of Atmospheric & Space Sciences
University of Pune
Pune 411007, Maharashtra.
Tel.: +91-20- 25697752, 25601161
Mob# 9765456397
E-mail: [email protected],
4. Co-PI (Name, Address, e-mail, mobile)
1. Dr. Thara Prabhakaran
Scientist E
Indian Institute of Tropical Meteorology Pashan, Pune 411 008, Maharashtra
Tel. 020-25904371
E-mail: [email protected]
2. Dr. P. Pradeep Kumar
Professor & Head
Department of Atmospheric &Space Sciences
University of Pune
Pune 411 007, Maharashtra.
Tel. 020-25691712
E-mail: [email protected]
5.Approved Objectives of the Project
To investigate variability of surface-layer fluxes, turbulence characteristics and causes of energy imbalance corresponding to diverse terrain, atmospheric and surface
conditions, including non-ideal conditions, during different phases of monsoon using
micrometeorological tower flux data collected at different locations along Indo-
Gangetic plane.
Investigate the validity of Monin-Obukhov (MO) relations during non-ideal/ extreme atmospheric and surface conditions with the help of micrometeorological data, footprint
analysis and Large-Eddy Simulation (LES), and develop alternate relations to
parameterize surface exchange processes suitable for those conditions.
To study the response of surface fluxes to soil moisture variations and understand how soil moisture variations effectively translate into latent heat flux variations beyond a
few days or weeks and modulate boundary layer processes, especially during weak/
break monsoon periods.
To elucidate the moisture budget in the monsoon boundary layer using LES, mesoscale modeling, in-situ eddy covariance flux data, soil moisture data and satellite remote
sensing data for different monsoon scenarios with varying land-surface characteristics,
soil moisture and large-scale atmospheric flow conditions.
To study the boundary-layer evolution and structure during the transition from break to active monsoon phases, where land surface processes play a crucial role in the initiation
and development of convection.
mailto:[email protected]:[email protected]:[email protected]:[email protected]
28
6. 1 Date of Start 16-05-2011 (date of sanction)
6.2 Expected date of completion 15-05-2014
6.3 Total cost of the Project: Rs. 25,32,000./-
6.4 Expenditure as on 31/03/2013 : Rs. 13,56,307/-
7. Summary of progress made:
(on a separate sheet if required)
Large Eddy Simulation (LES) and WRF model simulations have been carried out focusing on
understanding turbulence in cloudy boundary layer and to study impact of mid-level drying on
the boundary layer evolution, cloud formation and thermodynamics.
Characteristics of different Planetary Boundary Layer Regimes over Indian Sub-Continent and
Surrounding Oceans in relation to Southwest Monsoon are investigated using Modern Era
Retrospective analysis for Research and Applications (MERRA) reanalysis data products,
Global Positioning System (GPS) Radio Occultation (RO), radiosonde data and TRMM
rainfall data. This work is being extended to study the moisture budget of different PBL
regimes during monsoon.
Soil moisture variability during different phases of monsoon are being investigated using In
Situ IMD soil moisture, multi-satellite soil moisture data products and MERRA soil moisture
data products.
Manuscripts are being prepared for publication on the above three aspects.
Details given in Annexure 1.
8.Work which remains to be done under the project:
Footprint analysis using micrometeorological tower data; data analysis with special emphasis
on non-ideal atmospheric conditions and break to active monsoon transition periods;
computation of fluxes and turbulence parameters, testing and developing similarity relations
are to be performed in detail.
LES runs focusing on moisture budget estimations of different PBL regimes already identified.
Validated soil moisture data will be used to study the response of surface fluxes to soil
moisture variations and how soil moisture modulate boundary layer processes, especially
during weak/ break monsoon periods.
9. Publications from this project: JRFs working in the project presented two papers at the
IMSP Annual Monsoon Workshop held at IITM, Pune during 19-20, February, 2013.
1. Planetary Boundary Layer Regimes over Indian Sub-Continent and Surrounding Ocean in
relation to Southwest Monsoon. Anusha Sathyanadh, Anandakumar Karipot, Thara
Prabhakaran
2. Moisture Transport during Indian Summer Monsoon: An investigation using the Concept of
Atmospheric River. Chetana Patil, Thara Prabhakaran, Anandakumar Karipot.
29
10. Major equipments
S. No. Item Procurement and
installation status
including model and
make
Cost
(Rs. in lakhs)
Working
condition
1 Workstation
Computer
Procured and installed
in May, 2012.
Model: DELL
Precision T7500
Make: DELL, Inc.
6,48,900./- Working
satisfactorily
11. Difficulty, if any, in implementing the project or any other comments/suggestions:
Funding for the second year of the project has not been received till date, and we are facing
difficulties in paying salary for two JRFs working in the project and to meet other project
related expenses due to this.
(Anandakumar Karipot)
Date : 4th July, 2013 ( PI's signature)
Place : Pune
30
Annexure 1
Continental Tropical Convergence Zone (CTCZ) programme: Report of the
work done during 2012 - 2013
Project Title : Surface-layer characteristics and moisture budget of the monsoon boundary layer A study using micrometeorological measurements and Large-Eddy Simulation.
Investigators: Anandakumar Karipot1, Thara Prabhakaran2, P. Pradeep Kumar1 1Department of Atmospheric and Space Sciences, University of Pune
2Indian Institute of Tropical Meteorology, Pune
Progress on three aspects related to the proposed objectives of the proposal are presented in
the report: i) Large Eddy Simulation ii) Characterization of different PBL regimes associated
with monsoon and iii) Satellite and MERRA reanalysis soil moisture validation and their
variability.
I) Large Eddy Simulation
Detailed understanding on the spatial and temporal behavior of the boundary layer turbulence
in presence of clouds are required to derive the moisture budget of different PBL regimes
associated with monsoon. Case studies are performed with LES to understand Turbulence in
the cloud topped boundary layer and impact of mid-level drying on the boundary layer
evolution, cloud formation and lifetime.
Weather Research and Forecasting model with Large eddy Simulation (WRF-LES) is used in
the present study with a WRF double moment (WDM) microphysics parameterization. A 10
km x 10 km domain in the horizontal and 4 km in the vertical with 50 m horizontal and 30 m
vertical resolution are used for the study.
Data used in this study are from the Integrated Ground Observational Campaign (IGOC)
experiment during CAIPEEX 2011 where diurnal cycle of convection was monitored with
the help of several sensors, such as a microwave radiometer, wind Lidar and aircraft
observations for cloud microphysics. The surface layer fluxes of sensible heat and latent heat
fluxes needed as input for LES are observed with the help of an eddy covariance system
sonic anemometer and a LiCOR CO2 and water vapor sensor.
31
Output of the LES simulation are presented in the following figures.
Figure 1. Variance of wind components, temperature and water vapor from LES: sheared
convection with BLCs. Blue line corresponds to inside cloud and red line correspond to
outside cloud profiles.
Figure 2. Momentum and Heat flux from LES: sheared convection with BLCs
Inside cloud outside cloud
32
Figure 3. PDF of entraining warm moist and detraining cool dry plumes at the cloud base
Simulations are also performed to understand the role played by mid level water vapor in the
formation and development of the shallow clouds to deeper cumulus and how they impact the
cloud albedo and boundary layer processes. Emphasis in the present study is on the non-
precipitating clouds.
The model is initialized with the temperature, wind profiles and mixing ratio from a
radiosonde profile conducted at 1100 LST. The simulations were carried out for 4 hours.
Shallow clouds were formed after 30 min of LES. The model initialized vertical profiles and
the water vapor mixing ratio sensitivity profiles used in the experiments for 10 %, 20 %, and
30 % reduction in the water vapor mixing ratio in the mid layer. These reduced initialized
profiles are used to mimic more dry air intrusion into this area, similar to the transition to
break/ post monsoon in the peninsular India. The mid level winds are from NE and N and
they carry more continental dry and polluted air into the study area.
33
Figure 4. Moist boundary layer, mixing ratio profile from CAIPEEX observations, but
reducing water vapor above 1 km by different amounts.
Figure 5. Impact of mid level drying on variance profiles of wind components, air
temperature and mixing ration in BL
34
Figure 6. Impact of mid-level drying by different amounts on Cloud Liquid water
content
Wet Dry
Figure 7. Impact of mid level drying on water vapor variance with height and time (given in
minutes)
Large Eddy Simulation of mid level drying in the postmonsoon conditions, conditions typical
of boundary layer topped by shallow cumulus clouds, are considered in the simulations. The
results indicate that a 30% drying above the boundary layer could drastically reduce the
liquid water path and may lead to 10% reduction in the cloud albedo. Drying above the
boundary layer increased the turbulence inside the boundary layer and make it more moister.
The midlevel drying is found to reduce the deep convective events in the simulations
drastically. The results indicate that errors in the midlevel water vapor can influence the
shallow to deep convective cloud transitions and thus moisture budget and precipitation
estimates.
35
II) Characterization of different PBL regimes associated with monsoon
Investigation on occurrence of different PBL regimes in accordance with variations in surface
fluxes, soil moisture and cloud amount in association with different phases of monsoon has
been carried out. Analyses are carried out using Modern Era Retrospective analysis for
Research and Applications (MERRA) reanalysis data products, Global Positioning System
(GPS) Radio Occultation (RO), radiosonde data and TRMM rainfall data. MERRA 3D data
products of hourly PBL height, latent and sensible heat fluxes, fractional cloud cover and soil
moisture content at a horizontal grid resolution of 0.5o x 0.66
o during April November,
2011 are used for the study. MERRA PBL heights were earlier validated against PBL heights
derived from routine as well as campaign based radiosonde observations and GPS RO air
temperature and specific humidity profiles over the study domain.
PBL height in relation to progress of Monsoon
Figure 8 a and b shows variation of longitudinal cross section (75oE 77oE) of rainfall
and PBL height with latitude and time (May to October, 2011). Figure 9 a and b shows
variation of latitudinal cross section (24oN 26
oN) of rainfall and PBL height with longitude
and time. Latitudinal and longitudinal progression of monsoon and associated PBL height
variations are well-evident from the figures. Pre monsoon PBLH is higher in comparison
with monsoon as expected. Negative correlation between PBLH and rainfall is clear. Onset,
active and withdrawal conditions are in good agreement with PBLH. Lower PBLH values
during monsoon are distinguishable from pre and post monsoon values on both sides.
a b
Figure 8. Latitudinal variation of TRMM rainfall and PBL height along the longitudinal cross
section75oE to 77
oE.
MAY JUN JUL AUG SEPT OCT
MAY JUN JUL AUG SEPT OCT
36
a b
Figure 9. Longitudinal variation of PBL height along the latitudinal cross section 24
oN to
26oN.
Our analyses focused on understanding different Boundary layer regimes associated
with monsoon and different parameters responsible for the occurrence and control of the
regimes and their spatio-temporal variability.
The variation of PBL height with evaporative fraction, which is a representation of
available energy at the surface given by the formula EF = LE/ (H+LE), where LE is latent
heat flux and H the sensible heat flux, is looked at initially. Correlations are found between
daytime average evaporative fraction and PBLH for JJAS, 2011 at all grid points. Figure 10
shows large negative correlations over most of inland locations and positive correlations over
some of oceanic locations. Correlations over coastal regions are generally poor.
Figure 10. Correlation of daytime average PBLH and Ev.fraction. Data used are for JJAS,
2011.
MAY JUN JUL AUG SEPT OCT
MAY JUN JUL AUG SEPT OCT
37
Further detailed analyses showed the existence of a large range of PBLHs corresponding to
same evaporative fraction, indicating the existence of complex PBL regimes that depends on
the available energy at the surface, occurrence and types of clouds, stability of the lower
boundary layer, wind shear etc. and the combination of all this parameters and their
interactions.
Figure 11. Variation of PBLH with sensible and latent heat fluxes (a) and Richardson number
and friction velocity (b).
One category of PBL regime identified is dry PBL associated with pre-monsoon and
prolonged break conditions, with low soil moisture. Sensible heat flux is much larger than
latent heat flux, with maxima close to noon, and decreases thereafter. However, PBLH
continues to grow till 6 pm with contribution from dry air entrainment from above. Surface
forcing and stability (Ri) close to the surface has influence on PBL height only in morning
hours. Wind shear (u*) helps BL to remain turbulent.
The second category identified is the moist PBL during active monsoon periods.
Figure 12. Same as in figure 11, but for active monsoon period.
Such periods are associated with large latent heat flux. PBLH maximum are found to
coincide with H & LE max, and decreases in the afternoon hours unlike in dry PBL case.
Surface forcing, stability (Ri), wind shear (u*) close to the surface are found to influence PBL
height throughout.
1000 1200 1400 1600 1800
0
100
200
300
400
LE
H
PBLH
Time (IST)
Flu
x (
W m
-2)
0
500
1000
1500
PB
L H
eigh
t (m
)
0.05
0.10
0.15
0.20
0.25
0.30
1000 1200 1400 1600 1800-0.5
0.0
0.5
Ri
PBLH
Time (IST)
Ri
0
500
1000
1500
PB
LH
(m
)
u* (
m s
-1)
u*
a b
1000 1200 1400 1600 1800
0
100
200
300
400
LE
H
PBLH
Time (IST)
Flu
x (
W m
-2)
1000
2000
3000
4000
PB
L H
eig
ht
(m)
0.25
0.30
0.35
0.40
0.45
1000 1200 1400 1600 1800-2
-1
0
1
Ri
PBLH
Time (IST)
Ri
1000
2000
3000
4000
PB
LH
(m
)
u* (
m s
-1)
u*
a b
38
Figure 13. Same as in Figure 11 and 12, but for coastal location.
Coastal locations show a different PBL regime, with H & LE of comparable magnitude and
maxima close to noon hours. PBLH remains large for prolonged hours. Wind shear (u*) close
to the surface has dominant influence on PBL height. This PBL regime is an example for sea
breeze influenced BL.
Analyses also indicated the complex nature of PBLH dependence on parameters such as
cloud radiative forcing, Richardson number and friction velocity.
Figure. 14. Variation of PBL height with evaporative fraction over a 2 x 2 region over
southern peninsula: a) color coded with cloud radiative forcing (CRF) b) Richardson number
(Ri) and c) friction velocity (u*)
0 500 1000 1500 2000 2500
0.0
0.2
0.4
0.6
0.8
1.0
EF
PBLH (m)
0
100.0
200.0
300.0
400.0
500.0
CRF (Wm-2)
0 500 1000 1500 2000 2500
0.0
0.2
0.4
0.6
0.8
1.0
EF
PBLH (m)
-2.000-1.750-1.500-1.250-1.000-0.7500-0.5000-0.25000
Ri
0 500 1000 1500 2000 2500
0.0
0.2
0.4
0.6
0.8
1.0
EF
PBLH (m)
0
0.1000
0.2000
0.3000
0.4000
0.5000
u* (ms
-1)
a
b c
1000 1200 1400 1600 1800
0
100
200
300
400
500
600
LE
H
PBLH
Time (IST)
Flu
x (
W m
-2)
0
1000
2000
PB
L H
eigh
t (m
)
0.2
0.4
0.6
1000 1200 1400 1600 1800-0.8
-0.4
0.0
0.4
0.8
Ri
PBLH
Time (IST)
Ri
0
500
1000
1500
2000
PB
LH
(m
)
u* (
m s
-1)
u*
a b
39
Large variations in PBLH corresponding to a particular EF are noted during monsoon period.
In general, large PBLH corresponds to low CRF, low friction velocity and strongly unstable
conditions. Several such complex PBL regimes with large spatio-temporal variability are
noted in the analyses.
III. Satellite and MERRA reanalysis soil moisture validation and their variability.
The soil moisture has considerable influence on the boundary layer process and it is an
important boundary condition used in numerical models. One important objective of the
project is to study the response of surface fluxes to soil moisture variations and understand
how soil moisture variations effectively translate into latent heat flux variations beyond a few
days or weeks and modulate boundary layer processes, especially during weak/ break
monsoon periods. Some of the available soil moisture products are validated and compared
for this purpose.
Data Used: IMD AWS-Agri in situ hourly soil moisture measurements (at 20 cm depth) from
70 locations spread over the Indian subcontinent during the period June September, 2010.
Multi-Satellite daily average soil moisture data at a spatial resolution of 0.25o x 0.25
o during
the period June September, 2010.
MERRA reanalysis hourly soil moisture data at a spatial resolution of 0.5o x 0.66
o during the
period June September, 2010.
IMD soil moisture data is used for the validation of satellite derived soil moisture. Satellite
derived soil moisture extracted at the grid points nearest to the IMD measurement locations
are used for the validation. Correlations are found for each location using daily averaged soil
moisture values during June- September, 2010. Fairly good correlation is noted at most of the
locations with a correlation coefficient of 0.6 and above.
Composite plots are made for active and break monsoon periods from all active and break
monsoon days during 2001 2010. Distinct variations are seen between the two in the figure
with central and western part of the subcontinent showing soil moisture in the range 0.3 0.5
m3 m
-3, whereas soil moisture during break monsoon periods in those regions are in the range
0.2 to 0.3 m3 m
-3.
Figure 15. Composite of multi-satellite soil moisture during all active and break monsoon
days of 2001 2010.
40
Since the satellite derived soil moisture has data gaps, MERRA reanalysis data also
will be used for detailed analyses to study the variability in surface fluxes and response in
boundary layer characteristics. In order to get an understanding on how good the two data
products match, correlation between the two are found at all MERRA grid points using all
available satellite derived soil moisture at the corresponding grid points during the period
June-September, 2010. As seen in the figure, most of the grid points show a correlation of 0.8
and above.
Figure 16. Correlation between multi-satellite soil moisture data and MERRA soil moisture
data. Data used for the analysis are for the period June September, 2010.
The above data products are being used to study the influence of soil moisture variability and the feedback between soil moisture and energy budget components on boundary-layer processes, with
emphasis on the break to active monsoon transition periods.
The studies will now focus on:
LES runs focusing on moisture budget estimations of different PBL regimes already
identified.
Validated soil moisture data will be used to study the response of surface fluxes to soil
moisture variations and how soil moisture modulate boundary layer processes, especially
during weak/ break monsoon periods.
Footprint analysis using micrometeorological tower data; data analysis with special emphasis
on non-ideal atmospheric conditions and break to active monsoon transition periods;
computation of fluxes and turbulence parameters, testing and developing similarity relations
are to be performed in detail.
______________________________
41
PROGRESS REPORT
1. Project Title
Regional assimilation of land surface
parameters over Indian landmass for
providing surface boundary condition to
numerical models for simulation of monsoon
processes
Project No.:
PC-1- Project-5
2. Implementing Organization Indian Institute of Technology Kharagpur
3.PI(Name, Address, e-mail, land line,
mobile)
Dr. M. Mandal
Assistant Professor
Centre for Oceans, Rivers, Atmosphere and
Land Sciences (CORAL)
Indian Institute of Technology Kharagpur
Kharagpur-721302, West Midnapore, WB.
Email: [email protected]
Tel: (+91-3222) 281822 (O), 281823 (R),
+919933043560 (M)
Fax: (+91-3222) 255303
4. Co-PI (Name, Address, e-mail, mobile)
Prof. U.C. Mohanty
Professor
Centre for Atmospheric Sciences
Indian Institute of Technology, Delhi
Hauz Khas, New Delhi -110 016, INDIA
Email: [email protected]
Tel: (+91-11) 26591314 (O), 26591829 (R),
+919868957957 (M)
Dr. C. M. Kishtawal
Space Application Centre (SAC)
Indian Space Research Organization (ISRO)
Ahmedabad 380015, INDIA
Email: [email protected]
Tel: (+91-79)-26916108 (O), 26860922 (R),
+919276859920 (M)
5.Approved Objectives of the Project
Preparation of regional analysis of land surface parameters viz., surface and sub-surface soil temperature and moisture over Indian landmass using 2-D Noah LSM
[Analysis domain: 5N - 35N & 65E 95E; Analysis resolution:25 km]
Validation of the prepared analysis with observations
Study the variation of soil temperature & moisture and sensible, latent & ground heat fluxes including the surface layer parameters at Kharagpur in different epochs of
monsoon
6. 1 Date of Start 30/09/2011
6.2 Expected date of completion 29/09/2014
6.3 Total cost of the Project: Rs. 64,92,440/-(original), Rs. 63,40,376/-(revised)
6.4 Expenditure during 01/04/2012 - 31/03/2013 : Rs. 38,04,302/-
mailto:[email protected]:[email protected]:[email protected]
42
7. Summary of progress made:
Kindly refer Annexure-I
8.Work which remains to be done under the project:
The analysis with assimilation of observed surface parameters (in progress).
Analysis of land surface parameters in different epochs of monsoon (in progress)
9. Publications from this project: The manuscript entitled Simulation of soil temperature and
moisture at two tropical sites using Noah LSM is to be communicated soon.
10. Major equipments
S. No. Item Procurement and
installation status
including model and
make
Cost
(Rs. in Lacs)
(without insurance
and vat)
Working
condition
1. Infrared open path
gas analyzer
EC150 15,30,000 Yes
2. Net Radiometer CNR4 5,50,000 Yes
3. Soil temperature
sensor
Soil Temperature
Probe (109) 4
numbers
31,515 Yes
4. Water content
reflectometer
CS616-L20 3
numbers
52,500 Yes
5. Data logger and
other accessories
CR3000 5,20,000 Yes
6. Battery, solar panel
and other power
supply accessories
50,000
7. Computing server 6,39,170 Yes
10. Difficulty, if any, in implementing the project or any other comments/suggestions
Not getting suitable manpower for the project.
Date: 30 June 2013 (M.Mandal)
Place: Kharagpur (PI's signature)
43
Annexure-I
Summary of the progress made (PI : Dr. M.Mandal)
Objective-1 & 2: (Preparation of regional analysis and validation)
A. Sensitivity study: The sensitivity of atmospheric forcing parameters i.e., the parameters to be
assimilated for generation of the land surface analysis on simulation of land surface parameters
over Kharagpur (a site where land surface is covered by grass-land and agricultural land
mosaic) is conducted using 1-D Noah land surface model. The study indicates that the
simulated land surface parameters are significantly sensitive to surface temperature,
downward shortwave and downward longwave radiation at the surface.
B. Simulation and validation of land surface parameters: The 1D version of NOAH LSM (2D
version of which will be used in preparing the analysis) is used to simulate land surface
parameters over two meteorological tower sites Kharagpur and Ranchi with different soil
types and vegetation cover and the simulations are validated against observation.
(Kharagpur: Soil Sandy loam, Vegetation cover Cropland / Grassland mosaic; Ranchi:
Soil Sandy clay loam, Vegetation cover Grassland). The forcing parameters are provided
from meteorological tower observations at temporal frequencies half an hourly and hourly
respectively at Kharagpur and Ranchi. At Kharagpur site, the downward shortwave and
downward longwave radiation parameters at surface derived as a fraction of net radiation
using a functional relation established using NCEP. At Ranchi the soil temperature and
moisture sensors are not at same depths therefore, for Ranchi, the simulations are conducted
twice, once for the depths of the soil temperature sensors and once for the soil moisture
sensors.
The model simulated soil temperature and moisture are validated against observation at
different depths at both the sites in measurement scale, for day time and night time, daily
scale and also for different seasons.
Soil moisture At measurement scale (half-hourly at Kharagpur and hourly at Ranchi), the
model consistently over-predicts soil moisture at all levels. The simulated values are closer to
the observations during wet conditions than during dry. The model over-predicts the daily
mean value of soil moisture consistently. A comparison of the normalized percent error of
simulated soil moisture with rainfall shows that the model has a better skill under wet
conditions (Figure 1). It is also seen that the model has better skill in day time than at night
time (Table-1). Though the model shows wet bias, the variation of soil moisture in diurnal,
daily and seasonal scale is well reasonably well simulated by the model.
44
Figure 3: Normalized percentage error in prediction of soil moisture in 2009 at (a)
Kharagpur (b) Ranchi.
Table - 1: Root mean square error of daily mean modeled soil moisture
Soil temperature The diurnal variation of soil temperature is well simulated by the
model at all depths at both sites. However, compared to observation, the model
simulated lesser variation than observed during the months of May to September and
higher variations in the other months. The daily mean soil temperature is consistently
under-predicted by the model in summer and monsoon months (May to September)
but over-predicted in drier months (Figure -2 & 3). At Ranchi, the lower depths
(20cm and 40 cm) are under-predicted in all seasons and the colder bias is greater
for deeper levels (Table 2). The model exhibited greater skill in modelling day time
soil temperature than night time soil temperature at both sites, for all levels (Table 3).
Figure 2: Comparison of modeled and observed soil temperature at 20 cm depth at
Kharagpur
45
Figure 3: Comparison of modeled and observed soil temperature at Ranchi
It is also seen that land surface parameters generated by the model is sensitive to some of the
initialized fields. Both soil temperature and moisture fields are more sensitive to the soil type
than the deep soil temperature. It may also be mentioned here that model generated land
surface parameters are almost insensitive to the seasonal variation of vegetation fraction at the
site.
The model generated land surface parameters when compared the observation and NCEP
data, it is found that the model generated land surface parameters are closer to the observed
parameters than that obtained from NCEP analysis in the wet period. In the dry period, NCEP
land surface parameters are closer to the observation than the one generated by the model.
Table 2: Seasonal error (in Kelvin) of modeled daily mean soil temperature
46
Table 3: Root mean square error of daily mean modeled soil moisture
C. A regional analysis is prepared through assimilation of land surface parameters
to 2D NOAH LSM over a smaller domain considering MERRA analysis data as observation
provided every hourly. The land surface heterogeneity seems to be better reproduced in the
analysis than that in NCEP. The analysis shows larger bias compared to the bias in the 1D
simulations over Kharagpur and Ranchi. This is attributed to cold bias in assimilated surface
temperature datasets. There are some problems in the analysis in the coastal region; we are
trying to rectify that. The assimilation of observed surface parameters in 2D NOAH LSM is
in progress.
Objective-3: (Variation of land surface parameters during monsoon)
The surface fluxes are computed and the analysis of surface parameters in different epochs
of monsoon is in progress.
47
PROGRESS REPORT
1. Project Title: Surface process observational
studies coupled with
atmospheric transfer interaction
along eastern end of monsoon
trough
Project No.:MOES/568/2011-2012
PC1-Project 6
2. Implementing Organization Birla Institute of Technology, Mesra, Ranchi
3. PI(Name, Address, e-mail, land line, mobile)
Dr. Manoj Kumar, Centre of Excellence in
Climatology (Dept. of Applied Mathematics),
Birla Institute of Technology, Mesra, Ranchi
835 215
Email: [email protected],
Tel No. +91-9431901969, 0651-2276183(O)
4. Co-PI (Name, Address, e-mail,
mobile)
Co-PI (1): Prof. N.C. Mahanti, Prof. & Head,
Dept. of Applied Mathematics, Birla Institute of
Technology, Mesra, Ranchi 835 215
Telefax-0651-2276183, 2275401, Tel.-0651-
2275444/Ext.486, Cell No.- 09431597168;
Email: [email protected]
Co-PI (2) Dr. G. K. Mohanty, Director, (Met.
Centre), India Meteorological Department, Birsa
Munda Air Port, Ranchi 834 001
Telefax: 0651-2501572, 09470370293
5. Approved Objectives of the Project
1. To study the variability (diurnal, seasonal and inter-annual) of surface energy budget
as a function of synoptic weather conditions (Lows, Western disturbances,
Thunderstorms, Monsoon trough oscillations).
2. Land-vegetation-atmosphere interactions 3. Develop appropriate parameterization scheme for land surface atmosphere
interactions
4. Land surface atmosphere coupled study using high resolution RS/RW and meteorological parameters to improve the understanding of physical processes
5. 1 Date of Start Date of receipt of DD: 10-08-2011 Actual Date of start: 1
st January, 2012 (After
joining JRF)
5.2 Expected date of completion March, 2015
5.3 Total cost of the Project: Rs. 52,13,440 (original), Rs. 50,61,376 (revised)
5.4 Expenditure as on 30/06/2013: Rs. 31,50,873
6. Summary of progress made:
(Pl see the Annexure)
mailto:[email protected]:[email protected]:[email protected]
48
7. Work which remains to be done under the project
In the proposed project it is planned to study the dynamics and thermodynamics of the
convective boundary layer coupled with surface boundary layer during pre-monsoon severe
thunderstorm and monsoon season cyclone system over the region using already existing
observational system at BIT Mesra (Includes micro met tower equipped with slow and fast
response sensors, radiation, soil moisture, soil heat flux, electric field meter for lightning
etc.). Profiles of temperature, mixing ratio and wind determine the nature of turbulence in the
atmospheric boundary layer (ABL) that transports heat and moisture near the surface to
higher levels. Surface energy budget, ABL turbulence, wind field and high-resolution radio
sonde measurements in the troposphere are essential for studying the atmospheric convection
over the trough region. It is also proposed to develop a suitable parameterization scheme for
the region.
During the current project year, surface layer processes coupled with atmospheric
boundary layer during pre-monsoon turbulence period and also during monsoon period
oscillation will be studied.
8. Publications from this project
List of Publication in Journals
S.
No
.
Title of the paper Name of the
Journal
Vol. No.,
Issue
no., pp,
year
Publisher Impact
Factor
Whether
indexed
in
SCI/Sco
pus
ISSN
No.
National/
International
1 Atmospheric surface
layer responses to the
extreme lightning
day in plateau region
in India
Journal of
Atmospheric
and Solar-
Terrestrial
Physics
M S No.
ATP358
9
Under
Review
Elsevier 1.596 SCI,
Scopus
1364-
6826
International
2 Estimation of Bowen
Ratio Surface Energy
Fluxes in the
Boundary layer over
BIT Mesra, Ranchi
Meteorology
and
Atmospheric
Sciences
M S No.
MAP-D-
13-
00064
Under
Review
Springer 0.903 SCI,
Scopus
0177-
7971
International
3 Characterization of
the atmospheric
boundary layer from
radiosonde
observations along
eastern end of
monsoon trough of
India
Boundary
Layer
Meteorology
Submitti
ng on
process
Springer 1.737 Scopus 0006-
8314
International
PROGRESS INDICATOR:
1. One M.Sc. Thesis completed 2. Two Ph.D. Students working using the data
M.Sc. Thesis Title : WINTER-TIME NOCTURNAL BOUNDARY LAYER
PAREMETERS OVER INDIA
49
9. Major equipments
Following equipments have been ordered for the purchase and installed in July, 2012 before
the main phase of CTCZ field campaign.
10. Difficulty, if any, in implementing the project or any other comments/suggestions
NIL.
Date : 30.06.2013
Place : Ranchi ( Manoj Kumar )
Principal Investigator
50
Annexure
Summary of the progress (PI : Dr. Manoj Kumar, BIT Ranchi)
Sanction order for the project was issued during the month of May, 2011, but cheque /
DD was received on 10th
August, 2011 by the institute. After receipt of the DD, the process
for procurement of the computational system and replacement of existing equipments was
started and finally order was placed for the procurement of additional sensors during
February. For the selection of JRF & RA, interview was held on November 18, 2011, but non
found suitable for the post of RA. Mr. Arun Kumar Dwivedi joined the project on 02nd
January, 2012 as a JRF with total emoluments of Rs. 18,400/- p.m. Therefore, the actual date
of start of the project may be treated as 2nd
January, 2012. As some of the sensors need to be
replaced or calibrated, additional analysis has been done based on the data obtained from
radiosonde, EFM, existing tower data and SODAR data during the first years first quarter of
the project. During the second year of the project, objective no.1 and objective no.4 have
been fulfilled. These objectives are 1. To study the variability (diurnal, seasonal and inter-
annual) of surface energy budget as a function of synoptic weather conditions (Lows,
Western disturbances, Thunderstorms, Monsoon trough oscillations) and 2. Land surface
atmosphere coupled study using hi
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