Format for NMM International project proposals
1. Title of the
proposed project :
Improving multi-scale variability and
interactions in a global coupled seasonal climate forecast system through
embedded regional modeling at weather and cloud resolving scales
2. Brief information about Principal Investigator (PI) and Co-PI(s) :
PI:
Name:-
SAJI N HAMEED
Date of birth:-
29/4/1967
Institution:-
UNIVERSITY OF AIZU, FUKUSHIMA, JAPAN
Official website:-
http://www-aizu.ac.jp
E-mail Id:-
saji@u-aizu.ac.jp
Qualification:-
PhD
Co - PI (1):
Name:Date of birth:Institution:Official website:E-mail Id:Qualification:-
Co - PI (2):
Name:Date of birth:Institution:Official website:E-mail Id:Qualification:-
3. Project Summary (1 page) :
(a) Intellectual merits of the proposed work
Dynamical global coupled models have recently been identified as the way forward in
long-lead prediction of the spatio-temporal evolution of the Indian Summer Monsoon
Rainfall (ISMR). Unlike most of the tropics, where slowly varying interannual modes
dominantly control the evolution of the seasonal climate, the Indian monsoon is
characterized and its predictability limited by a large contribution from subseasonal scale
phenomenon, much of which arises from internal dynamics (Goswami et al 2006). Here
we hypothesize that the predictability of ISMR in the NCEP-CFS system, the candidate
model identified by the Indian Monsoon Mission, may have gone unrealized in spite of
its potential, as a result of the system unduly emphasizing impacts from slowly varying
climate modes such as ENSO while under representing the subseasonal statistics of the
ISMR. In this research we propose to critically examine the multiscale variability of
ISMR in the NCEP-CFS retrospective hindcasts and the extent to which embedded oneway regional weather and cloud resolving modeling based on the Weather Research and
Forecast (WRF) model could improve such representations. Results from this research
will advance our understanding of the multiscale variability and predictability of ISMR in
the NCEP-CFS system, and evaluate the role of resolution, topography, regional air-sea
interactions and other controlling factors in improving its representation. If our approach
is successful it may not only improve the overall predictability of ISMR, but may also
offer a cost-effective solution in resolving extreme events such as severe droughts and
floods in addition to resolving the finer spatio-temporal statistics of ISMR evolution.
(b) Broader impacts of the proposed work
The need for high resolution regional climate predictions for societal application of
climate forecasts is widely recognized. The high resolution data generated in this study
will of direct use in application studies and decision making tools. Thus we expect that
this research will have considerable broader impacts with its societal and scientific
benefits. In particular, we hope that it will enable societal and industrial use of the
developing predictive capability that will be realized through the Indian Monsoon
Mission.
Project Description:
1. Research Objectives
The objectives of this project are to evaluate a) the skill and space-time evolution of
ISMR in NCEP-CFS retrospective predictions, b) the ability of NCEP-CFS to predict
sub seasonal statistics associated with ISMR evolution, with a focus on intraseasonal
oscillations and mesoscale phenomena such as monsoon lows and depressions, and the
relevant interactions across various scales, c) the extent to which embedded regional
weather and cloud resolving models can remove biases of NCEP-CFS over ISMR region
and improve upon the predicted multi-scale variations and interactions and d) sensitivity
of the simulated multiscale interactions and ISMR predictability to resolution,
topography, regional air-sea interactions and other controlling factors.
1.1 Intellectual merit of the proposed work
Dynamical global coupled models have recently been identified as the way forward in
long-lead prediction of the spatio-temporal evolution of the Indian Summer Monsoon
Rainfall (ISMR). Unlike most of the tropics, where slowly varying interannual modes
dominantly control the evolution of the seasonal climate, the Indian monsoon is
characterized and its predictability limited by a large contribution from subseasonal scale
phenomenon, much of which arises from internal dynamics (Goswami et al 2006). Here
we hypothesize that the predictability of ISMR in the NCEP-CFS system, the candidate
model identified by the Indian Monsoon Mission, may have gone unrealized in spite of
its potential, as a result of the system unduly emphasizing impacts from slowly varying
climate modes such as ENSO while under representing the subseasonal statistics of the
ISMR. In this research we propose to critically examine the multiscale variability of
ISMR in the NCEP-CFS retrospective hindcasts and the extent to which embedded oneway regional weather and cloud resolving models based on the Weather Research and
Forecast (WRF) model could improve such representations. Results from this research
will advance our understanding of the multiscale variability and predictability of ISMR in
the NCEP-CFS system, and evaluate the role of resolution, topography, regional air-sea
interactions and other controlling factors in improving its representation. If our approach
is successful it may not only improve the overall predictability of ISMR, but may also
offer a cost-effective solution in resolving extreme events such as severe droughts and
floods in addition to reolving the finer spatio-temporal statistics of ISMR evolution.
1.2 Broader Impact of proposed work
The need for high resolution regional climate predictions for societal application of
climate forecasts is widely recognized. The high resolution data generated in this study
will of direct use in application studies and decision making tools. Thus we expect that
this research will have considerable broader impacts with its societal and scientific
benefits. In particular, we hope that it will enable societal and industrial use of the
developing predictive capability that will be realized through the Indian Monsoon
Mission.
2. Technical Section
2.1 Technical subsection (Background)
Extremes in the Indian monsoon summer rainfall (ISMR) lead to devastating floods and
droughts, causing enormous economic loss and human misery. Within a rainy season,
there are considerable variations of rainfall in space and time over India (Goswami,
2005), associated with factors such as topography, preferred paths of propagating low
pressure systems and intraseasonal oscillations manifesting in extended breaks and active
spells (Gadgil, 2003).
In fact the statistical characteristics of the monsoon intraseasonal oscillations (ISO), such
as frequency and magnitude of active and break spells, has a relatively large influence
and is a major determinant of the seasonal mean rainfall and hence agricultural
production (Goswami et al 2006). In turn the monsoon ISO is comprised of a highfrequency westward propagating mode with a period of between 10 and 20 days
(Krishnamurthi and Bhalme, 1976) and northeastward propagating lower-frequency band
between 25 and 80 days (Sikka and Gadgil, 1980). Monsoon synoptic systems namely
lows and depressions account for most of the rain during ISM. Goswami et al (2003)
showed that monsoon ISO activity significantly modulates the statistics of monsoon
synoptic systems, for instance the frequency of occurrence of lows and depressions, and
the clustering along the monsoon trough.
As the above discussion suggests, a considerable range of sub seasonal scales are
involved in the seasonal evolution of the ISMR, with the monsoon ISO playing a central
role. The monsoon ISO in turn has significant interactions with larger space and time
scale phenomena, such as the mean state of the Indo Pacific domain (Ajayamohan and
Goswami 2007) and to some extent on interannual climate modes such as ENSO and IOD
(Joseph et al 2011, Ajayamohan et al 2008). Hence we argue that the success of a
dynamical forecast system for the ISMR is strongly affected by its ability to reproduce
the statistical behavior and relationships across the multiple scales involved with the
ISMR.
Further in the case of ISMR, there is another important reason why scale
interaction is strongly tied to predictability. This is related to the fact that sub seasonal
scales may to a certain extent be strongly influenced by internal chaotic dynamics
(Goswami et al 2006). Hence a failure to accurately simulate the statistics of the chaotic
component may lead to an overestimation of impacts from predictable low-frequency
components and hence to unrealized predictability.
2.2 Technical subsection (The NCEP CFS model – challenges and prospects in
forecasting ISMR)
The latest version of the NCEP-CFS model (Saha et al 2010, Weaver et al 2011) has been
recently adopted as a base model for the Indian Monsoon Mission Project. Recent
evaluations suggest that the model forecasts display a relatively realistic mean state and
ENSO variability compared to those in free simulations (Weaver et al 2011). The latest
version (Version 2) has also improved SST forecasts over the Indian Ocean compared to
its predecessor (Schemm 2011). However, verification metrics for retrospective forecasts
suggest poorer than expected skill in forecasting seasonal variations of rainfall in the
ISMR region and the larger Indian Ocean basin in general, even at short lead forecasts
(Schemm 2011). Further, MJO simulation in this model continues to have challenges,
especially over the Indian Ocean and the maritime continent (Weaver et al 2011), perhaps
as a result of the model’s inability to realistically simulate the MJO scale air-sea
interaction over the Indian Ocean (Zhang et al 2006). Finally we note that the model
ENSO has been documented to have a too strong impact on the monsoon (Liang et al
2009), apparently related to signals of model SST and precipitation over the western
Pacific simulated too far westward compared to observations.
However despite these challenges, this model has considerable potential in improving ISMR
forecasts for various reasons. Based on inter-model comparisons at APEC Climate Center
(personal communication), we note that the NCEP CFS is perhaps the best model in the
world in terms of 6-month lead prediction of summer rainfall over the larger South Asian
region. The APEC Climate Center evaluations also show that the model has strong skill
in predicting large scale circulation parameters, for instance the 500hPa geopotential
height, a result further verified by the good simulation (Yang 2010) of various ISMR
indices such as Webster Yang index (Webster and Yang 1992) and the South Asian
monsoon index (Goswami et al 1999).
2.3 Embedded cloud resolving modeling as an approach to improving NCEP CFS
prediction
Regional models are becoming increasingly popular for simulating regional climates. Highresolution regional models are capable of resolving more accurately regional variations in
the orography and land surface characteristics that are important for regional climate
simulations. Although the NCEP CFS already has good skill in simulating global
circulation patterns associated with low-frequency oscillatory modes such as ENSO, and
has consistently good skill in predicting ENSO itself at long lead times, the model is still
coarse in resolution to resolve in detail any regional ISMR impacts associated with local
variations in the topography or land surface.
Increasing resolutions globally, is a very cost prohibitive option, and computational capacity
and costs limit the extent to which such resolution increases can be realized.
Alternatively, resolving a limited area at weather (close to 20 kms) and cloud resolving
resolutions (close to 4 km) is an approachable task even with modest high performance
computing infrastructure and is the strategy advocated in this proposal.
Nested regional modeling has recently been applied to seasonal prediction with success, over
the United States and other regions of the world. One of the first approaches by Cocke
and LaRow (2000) embedded a regional spectral model inside the FSU seasonal
prediction system demonstrated value-addition to the prediction in terms of detailed
information as well as improved skills over South East United States. Recently a project
“Multi-RCM Ensemble Downscaling (MRED) of Multi-GCM Seasonal Forecasts” has
organized a wider assessment of the benefits of
regional climate model seasonal
predictions for the United States. Yuan and Liang (2011) found that nesting the Weather
Research and Forecasting (WRF) model inside the CFS led to improved prediction of
cold season precipitation over the US. The WRF based downscaling reduced CFS
forecast errors of seasonal mean precipitation by 22% on the average and produced
greater skill for heavy rainfall events.
The inability of GCMs to resolve scale interactions may be a factor responsible for poor
simulations and predictability over the Indian Ocean and the ISMR region in particular
(Goswami et al 2010, Joseph et al 2010). As the ability of WRF in simulating multiscale
features of the ISMR, including intraseasonal oscillations appears to be promising
(Routray et al 2009, Rajeevan et al 2010, Taraphdar et al 2010), this may be another way
by which the high resolution simulations advocated in this proposal may improve the
IMSR simulation and predictability.
3. Statement of Work ( methodology to be adopted)
This research approaches the question of improving NCEP-CFS predictions by focusing on
the regional factors and phenomena that govern the space-time evolution of ISMR, and
their possible improvement by using embedded weather and cloud resolving models.
Central to our efforts is the attempt to improve the representation of intraseasonal
statistics in the predictions, which in turn may be influenced by a variety of scales from
mean state of the Indo-Pacific domain, interannual modes down to interaction of
topography with mesoscale phenomenon (Xie et al 2006, Boos and Kuang 2010,
Goswami et al 2010).
1. Space time structure of ISMR
We approach our task in three major steps. In the first step, we will comprehensively
evaluate the NCEP CFS forecasts for its skill in reproducing the space-time evolution of
ISMR. For this analysis, we request to be provided with CFS reforecasts for a period of
20 or more years, with data frequency at 6 hrs if available to facilitate the analysis of the
model’s ability to represent weather-scale statistics over the Indian region. The data will
also be use to integrate embedded high resolution models at weather and cloud resolving
scales.
CFS data for five or more ensembles are requested, to perform ensemble
simulations with the embedded model, in the absence of which model physics
perturbations would be used to create ensemble simulations.
2. Embedded regional scale cloud resolving modeling and evaluation.
We propose to use a nested approach using 3 domains at 32, 16 and 4 kms horizontal
resolution. The mother domain will be driven by the 6hourly NCEP CFS retrospective
forecasts at the boundaries, while the inner weather and cloud resolving domains will
take its input from the respective parent domains. We will use a one-way nested approach
for two reasons. Firstly it will allow us to evaluate the impact of successive
improvements in resolution. Secondly it will allow us to pace the experiments and results
and allow flexibility in further experimentation on sensitivities to various controlling
factors such as topography and mean state of Indo-Pacific domain etc.
The high resolution reanalyses such as NCEP-CFSR (Saha et al 2010) and/or the MERRA
reanalysis (Rienecker et al 2011) along with conventional high resolution observation
data sets, such as the gridded high resolution daily rainfall over India (Rajeevan et al
2006) and CMORPH (Joyce et al 2004) will be used to verify both the NCEP CFS
reforecasts and the embedded high resolution simulations.
3. Sensitivity analysis.
This last stage will examine the sensitivity of the simulations to the controlling factors viz.,
SST in the Indo Pacific domain, accurate representation of topography etc. Two further
simulations will be performed for selected years at the cloud resolving resolution to
examine how the representation of topography and mean SST conditions of the Indo
Pacific basin would influence the representation of multiscale statistics and thereby the
predictability of ISMR
3.1 Schedule (Year wise)
Year
Expected Outcome
Deliverables
Year - 1
a) Analysis of multiscale
a) Research Progress report
ISMR variations during
b) Submission of at least
extreme El Nino and Indian
two journal publications
Ocean Dipole years in CFS
describing multiscale
retrospective forecasts.
variations of ISMR in
b) Complete embedded
NCEP-CFS retrospective
regional prediction at
forecasts
weather resolving scales
Year - 2
a) Critical analysis of the
a) Research Progress report
embedded weather
b) Submission of at least
resolving resolution
two journal publications
simulations on its ability to
describing research
improve upon multiscale
outcome (a) of Year-2
monsoonal variations
c) Delivery of high
generated by CFS.
resolution weather resolving
b)Finish embedded regional data to IITM
modeling at cloud resolving
scales
Year - 3
a) analysis of cloud
a) Final Research report
resolving simulations
b) Submission of at least
b) further experiments by
two journal publications.
modifying SST and
c) Delivery of cloud
topography
resolving data to IITM
c) sensitivity analysis to
d) Delivery of source code
resolution, SST and
of models and analaysis to
topography
IITM
3.2 Team Composition and expertise *
Investigator
Qualification
Expertise
PI
PhD
Analysis of observational
and global climate model
data.
Regional Climate
Modeling
applications.
and
societal
High
Performance Computing.
Co-PI (1)
Co-PI (2)
*MoES encourages to include one Indian partner in the project proposal, preferably
from MoES institutes.
3.3 Connections to Operational forecast and Human resource development

The project strives to hire Indian Postdoctoral and doctoral students for this
project and improve/widen their expertise in high impact seasonal prediction and
applications research

The proposed system will aid operational forecasting of the detailed space-time
behavior of extreme events during ISMR if successful

The project will provide regional modeling tools and enhance the capability for
regional climate predictions and application research/products
4. Related works and project assessment :
4.1 National status
The PI is of Indian origin and earned his PhD in Atmospheric Sciences from the Indian
Institute of Science, Bangalore.
4.2 International status
The PI has extensive experience in working with seasonal predictions and its applications
over the Asia Pacific region, with some recent projects including:
1. Extending APEC Climate Center Seasonal Forecast and Climate Adaptation
products for improved Societal Applications – collaborative work with APCC
(2011-2012)
2. Toward a Fire and Haze Early Warning System for Southeast Asia –
APN
funding for 2012-2014
4.3 The mechanisms adopted in your institute for internal review (assessment) and
validation of this Project Proposal.
Collaborative Project such as these will be reviewed by a special committee, who will
examine the proposal critically for its relevance and feasibility. Depending on the type of
cooperative agreement, the committee may recommend that a formal letter of agreement
be exchanged among the collaborating institutes. The project will also undergo an annual
review by a committee appointed for that purpose.
5. Results from prior MoES support (if any)
[Describe any prior MoES funded work by the PI, Co-PI(s)]
Investigator
MoES grant no.
Title
Year
Description
PI
Co-PI
6. Facilities available at the workspace
(e.g., existing computer facilities)
High Performance Computing facilities in the form of a 192 core cluster, each core
running at 1.7GHz and interconnected by high speed network system including
HyperTransport and InfiniBand. We also have some data storage space for NCEPCFS hindcasts and for downscaled data generated from WRF. We will provide high
speed intra and internet, office space and materials and supplies needed for
postdoctoral research fellow, research student and Research Assistants who are
involved in the work .
7. Total Budget ( JPY ) requirements ** (with justifications)
S.No
A)
Item Name
1st Year
2nd Year
3rd Year
Total
Justification
Man Power
1)Key
4,320,000 4,320,000 4,320,000
personnel
Salary and
12,960,000 mandatory benefits
for 1 postdoctoral
fellow
2)Other
1,456,000 1,456,000 1,456,000
personnel(e.g.
Remuneration for
4,368,000
Research assistance
Research
Assistants)
3)Technical
1,103,648
Assistant
Total budget
Remuneration for
1,103,648 1,103,648 3,310,944
Technical assistance
6,879,648 6,879,648 6,879,648 20,638,944
for
Manpower
B)
Travel
1) Foreign
465,000
465,000
465,000
1,395,000
Travel
Two
international
travel expenses for
research
collaboration
IITM
presentation
international
conferences
Total budget
465,000
465,000
465,000
1,395,000
for Travel
Grand Total (for
each year)
7,344,648 7,344,648 7,344,648 22,033,944
to
and
at
** As per MoES guidelines, we will not be paying any additional overheads for
international proposals. Funding is available only for manpower (not exceeding $1,
00,000/- per year/per person) and travel.
8. Bio-data (CV) of the Investigators :
8.1 PI Biography (Person A)
Name:-
Saji N Hameed
Date of birth:-
29/4/1967
Institution:- Advanced Research Center for the Environment (ARC-ENV),
University of Aizu
Address (Residence):-
1-17-25 Matsunaga, Ikkimachi D107, Aizuwakamatsu,
Fukushima, Japan
Tel. No: +81242856969
Mob No: +819058469694
E-mail Id: saji.nh@gmail.com
Address (Office):-University of Aizu, Tsuruga
Aizuwakamatsu, Fukushima, Japan
Tel. No: + 81242372736
FAX: + 81242372760
Official E-mail Id: saji@u-aizu.ac.jp
Official website address: http://www.u-aizu.ac.jp
Educational Qualification:-
School/College/University Degree
Year
Main subjects
Division/Class
Indian Institute of Science
1998
Atmospheric
N/A
PhD
Sciences
Indian Institute of Science
MS
(by 1993
research)
Cochin University
MSc
Atmospheric
N/A
Sciences
1990
Physical
First Rank/First
Oceanography
Class
Awards / Honors / Fellowship etc.:
2009- Fukuoka Ruby Award for developing Climate Information Tool Kit
2006 - Marquis' `Who's Who in the World - 2006', 23rd Edition (pub. 2005)
2005 - Marquis' `Who's Who in Science and Engineering - 2005-2006', 8th Edition (pub.
2004)
2000 - Frontier Award for Outstanding Achievement.
1994 - Senior Research Fellowship, CSIRO, India.
1991 - Junior Research Fellowship, CSIRO, India.
Appointments (Professional experience/employment record):
Organization
Designation / Position
University of Aizu, Sr. Associate Professor and
Japan
Duration ( Year / date)
Apr 2012 to present
Vice Chair, Graduate Dept of
Computer and Information
Systems
University of Aizu
APEC
Climate Director of Science
Aug 2006 – Dec 2009
Center, Korea
International Pacific Assistant Researcher
Research
Center,
USA
List of important and relevant research publications:
Feb 2002 – Jul 2006
Other publications:
Participation in Conference/Seminar/Workshop/ Summer Schools
Recent collaborations:
Research Guidance:
No. of Ph.D. students enrolled/ completed
No. of Graduate/Postgraduate students enrolled/ completed
Synergistic Activities:
Activity 1
Activity 2
8.2 Co-PI (1) Biography (Person B)
Name:
Date of birth:
Institution:
Address (Residence):
Tel. No. :
Mob No:
E-mail Id:
Address (Office):
Tel. No. :FAX:Official E-mail Id:Official website address:-
Educational Qualification:
School/College/University Degree
Year
Main subjects
Division/Class
Awards / Honors / Fellowship etc.:
Appointments (Professional experience/employment record):
Organization
Designation / Position
List of important and relevant research publications:
Duration ( Year / date)
Other publications:
Participation in Conference/Seminar/Workshop/ Summer Schools
Recent collaborations:
Research Guidance:
No. of Ph.D. students enrolled/ completed
No. of Graduate/Postgraduate students enrolled/ completed
Synergistic Activities:
Activity 1
Activity 2
8.3Co-PI (2) Biography (Person C)
Name:
Date of birth:
Institution:
Address (Residence):
Tel. No. :
Mob No:
E-mail Id:
Address (Office):
Tel. No. :FAX:Official E-mail Id:Official website address:-
Educational Qualification:
School/College/University Degree
Year
Main subjects
Division/Class
Awards / Honors / Fellowship etc.:
Appointments (Professional experience/employment record):
Organization
Designation / Position
List of important and relevant research publications:
Other publications:
Duration ( Year / date)
Participation in Conference/Seminar/Workshop/ Summer Schools
Recent collaborations:
Research Guidance:
No. of Ph.D. students enrolled/ completed
No. of Graduate/Postgraduate students enrolled/ completed
Synergistic Activities:
Activity 1
Activity 2
9. List of supplementary documents :
( e.g., authorization letter from the Head of the organization, endorsements etc.)
To be provided on request
10. References Cited :
Ajayamohan, R. S., and Goswami, B. N. 2007: Dependence of Simulation of Boreal
Summer Tropical Intraseasonal Oscillations on the Simulation of Seasonal Mean, J.
Climate, DOI: 10.1175/JAS3844.1
Ajayamohan, R. S., S. A. Rao, and T. Yamagata, 2008: Influence of Indian
Ocean Dipole on poleward propagation of boreal summer intraseasonal
oscillations, J. Clim., 21, 5437–5454
Boos, W. R and Z. Kuang 2010: Dominant control of the South Asian monsoon by
orographic insulation versus plateau heating, Nature, DOI:10.1038/nature08707
Cocke, S. and T. E. LaRow, 2000: Seasonal Predictions Using a Regional Spectral Model
Embedded within a Coupled Ocean–Atmosphere Model, Mon. Wea. Rev., 128, 689–708.
Goswami B N, Annamalai H and Krishnamurthy V 1999: A broad scale circulation index
for interannual variability of the Indian summer monsoon. Q. J. Roy. Met. Soc., 125, 611633.
Goswami, B N, R.S Ajaya Mohan, Prince K Xavier and D. Sengupta, 2003:Clustering of
Low Pressure Systems During the Indian Summer Monsoon by Intraseasonal
Oscillations. Geophys. Res. Lett. 30(8),1431, doi:10.1029/2002GL016734, 2003.
B. N. Goswami, 2005: South Asian Monsoon: in Intraseasonal Variability of the
Atmosphere-Ocean Climate System, Eds. William K. M. Lau and Duane E.Waliser
Chapter 2, Praxis, Springer Berlin Heidelberg, 19-61 pp.
Goswami B.N., Wu G., Yasunari T. 2006: Annual cycle, Intraseasonal Oscillations and
Roadblock to seasonal predictability of the Asian summer monsoon, J. Climate, 19,50785099
Goswami B.B., Mukhopadhyay P., Mahanta R., Goswami B.N., 2010: Multiscale
interaction with Topography and Extreme Rainfall Events in the North-East Indian
region, J. Geophys. Res., 115, doi:10.1029/2009JD012275, D12114
Joseph S., Sahai A.K., Goswami B.N. 2010: Boreal summer intraseasonal oscillations
and seasonal Indian monsoon prediction in DEMETER coupled models, Climate
Dynamics, 35, pp.651-66
Joseph S., Sahai A.K., Chattopadhyay R., Goswami B.N., 2011: Can El-Nino and
Southern Oscillation (ENSO) events modulate intraseasonal oscillations of Indian
summer monsoon? , J. Geophys. Res.,116, D20123, doi:10.1029/2010JD015510
Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that
produces global precipitation estimates from passive microwave and infrared data at high
spatial and temporal resolution.. J. Hydromet., 5, 487-503.
Krishnamurthi, T. N. and H. N. Bhalme, 1976: Oscillations of a monsoon system.
Part I: Observational aspects. J. Atmos. Sci., 33, 1937–1954.
Jianyin Liang , Song Yang, Zeng-Zhen Hu, Bohua Huang, Arun Kumar, Zuqiang Zhang
2009: Predictable patterns of the Asian and Indo-Pacific summer precipitation in the
NCEP CFS, Climate Dynamics, DOI 10.1007/s00382-008-0420-8
Rajeevan, M., J. Bhate, J. D. Kale, and B. Lal, 2006: High‐resolution daily gridded
rainfall data for the Indian region: Analysis of break and active monsoon spells, Curr.
Sci., 91, 296–306
Rajeevan, M., A. Kesarkar, S. B. Thampi, T. N. Rao, B. Radhakrishna, and M.
Rajasekhar, 2010: Sensitivity of WRF cloud microphysics to simulations of a severe
thunderstorm event over Southeast India, Ann. Geophys., 28, 603–619.
Rienecker, M.M., M.J. Suarez, R. Gelaro, R. Todling, J. Bacmeister, E. Liu, M.G.
Bosilovich, S.D. Schubert, L. Takacs, G.-K. Kim, S. Bloom, J. Chen, D. Collins, A.
Conaty, A. da Silva, et al., 2011. MERRA - NASA's Modern-Era Retrospective Analysis
for Research and Applications. J. Climate, 24, 3624-3648, doi: 10.1175/JCLI-D-11
00015.
Routray, A., U. C. Mohanty, Dev Niyogi, S. R. H. Rizvi, Krishna K. Osuri, 2010:
Simulation of heavy rainfall events over Indian monsoon region using WRF-3DVAR
data assimilation system, Meteorol Atmos Phys ,106:107–125
DOI 10.1007/s00703-009-0054-3
Saha, Suranjana, and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis.
Bull. Amer. Meteor. Soc., 91, 1015–1057. doi: 10.1175/2010BAMS3001.11
J. E. Schemm, 2011: Introduction to the NCEP Climate Forecast System Version 2
Seminar at APEC Climate Center, available online at
www.apcc21.net/assets/812/20110608_APCC_CFSv2_intro.pdf
Sikka, D. R. and S. Gadgil, 1980: On the maximum cloud zone and the ITCZ over Indian
longitude during the southwest monsoon. Mon. Wea. Rev., 108, 1840–1853.
Taraphdar, S., P. Mukhopadhyay, and B. N. Goswami, 2010: Predictability of Indian
summer monsoon weather during active and break phases using a high resolution
regional model, Geophys. Res. Lett., 37, L21812, doi:10.1029/2010GL044969
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