continental tropical convergence zone (ctcz) programme2012-13).pdf · 1 continental tropical...

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.


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


Phone: 011-26591315

: 9873544872


Prof. U. C. Mohanty


Indian Institute of Technology Delhi


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


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.)

mailto:[email protected]:[email protected]

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


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

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Ju

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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


mobile)

Dr. D. M. Chate, IITM, Pune

[email protected]

9637327928 (M) 020-25904257 (Off)


V. Gopalakrishnan, IITM, Pune

[email protected]

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


(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.

mailto:[email protected]:[email protected]

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:


installation status

including model and

make

Cost

(Rs. in lakhs)

Working

condition

N/A N/A N/A N/A N/A


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

(*[email protected])

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.

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],

[email protected]


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/-


(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.


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



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


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.



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


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.


Tel: (+91-3222) 281822 (O), 281823 (R),

+919933043560 (M)

Fax: (+91-3222) 255303


Prof. U.C. Mohanty

Professor


Indian Institute of Technology, Delhi

Hauz Khas, New Delhi -110 016, INDIA


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


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


Kindly refer Annexure-I


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.



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


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],

[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;


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


(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.


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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