Indian Institute of Tropical Meteorology

Scientist Profile

Prof. Ravi Shankar Nanjundiah

Designation

: Retired Scientist

Phone

:

Fax

:

Email ID

: ravisn[at]tropmet[dot]res[dot]in

Area of Expertise

Monsoon variability and predictability

Academic Records

Degree	University	Year	Stream
Ph.D.	Indian Institute of Science	1992	Atmospheric Sciences
M.E.	Indian Institute of Science	1986	Mechanical Engineering
B.E.	Rani Durgavati University, Jabalpur, India	1984	Mechanical Engineering

Research

Study of Monsoons and its variability using climate models

Application of High Performance Computing/Grid Computing for climate and weather-related studies

Use of Machine Learning Techniques for Monsoon prediction and downscaling

Awards & Honors

Award Name	Awarded By	Awarded For	Year
Fellow	Indian Meteorological Society (IMS)	Expert in the field	2018
Fellow	Indian Academy of Sciences (IAS)	Expert in the field	2018
Nvidia Innovation Award	Nvidia	Research	2013
Sir C V Raman Young Scientist Award	Indian Institute of Science	Research in Earth Sciences	2000

Scientific Careers

Year	Designation	Institute
2017 (Mar)-Present	Director	Indian Institute of Tropical Meteorology, Pune
2013 (Dec)-2017	Chairman	Centre for Atmospheric & Oceanic Sciences, Indian Institute of Science
2007 (Jul)-2017	Professor	Centre for Atmospheric & Oceanic Sciences, Indian Institute of Science
1995 (Jul)-2001 (Jul)	Associate Professor	Centre for Atmospheric & Oceanic Sciences, Indian Institute of Science
1993 (Feb)-1995 (Feb)	Post-Doctoral Fellow	CHAMMP, Project, Argonne National Laboratory, USA

Research Highlight

Linkage between global sea surface temperature and hydroclimatology of a major river basin of India before and after 1980

Global sea surface temperature (SST) linkage with the precipitation and surface temperature of the MRB was analyzed over the period 1950–2012. Significant changes in seasonal correlation patterns were witnessed from 1950–1980 (PR-80) to 1981–2012 (PO-80). The correlation was higher during PR-80 compared to PO-80 between the El Nino region SST versus the maximum temperature (Tmax) in all seasons except the pre-monsoon season and the minimum temperature (Tmin) in all seasons except the monsoon season.

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Honours

Adjunct Professor (Visiting Faculty), TIFR wef January 2019
Member, ISRO- Geosphere Biosphere Programme (GBP) PMB
Elected as Fellow of Indian Academy of Sciences (IAS) (2018)
Elected as Fellow of India Meteorological Society (IMS) (2018)
Member, Editorial Advisory Board, Dynamics and Statistics of the Climate System ( a new journal being launched by Oxford University Press), February 2016 - present.
Adjunct Faculty, ICTS-TIFR 2011-2014.
Co-author of paper titled "A Gradient- Based Comparison Measure for Visual Analysis of Multi eld Data" which won 3^rd Prize in the Best Paper Category at EuroVis 2011.
Associate Editor, Journal of Earth System Sciences (published jointly by the Indian Academy of Sciences, Bangalore and Springer), 2008-2014.

Selected Publications with Citations

(Complete List of Publications attached at the end)

1. Tripathi S, V. V. Srinivas and R S Nanjundiah 2006: Downscaling of Precipitation for Climate Change Scenarios: A Support Vector Machine Approach. Journal of Hydrology, 330, 621-640. (279 citations)

2. Sulochana Gadgil, M Rajeevan and R S Nanjundiah, 2005: Monsoon Prediction -Why yet another failure? Current Science, 88, 1389-1400. (140 citations)

3. Anandhi A , V V Srinivas, R S Nanjundiah and D Nagesh Kumar,2008: Downscaling Precipitation to River Basin in India for IPCC SRES Scenarios using Support Vector Machine. International Journal of Climatology, doi: 10.1002/joc.1529, 28, 401-420. (125 citations)

4. Gadgil S, J Srinivasan, R S Nanjundiah , K Krishna Kumar, A A Munot, and K. Rupa Kumar, 2002: On Forecasting the Indian Summer Monsoon :the Intriguing Season of 2002. Current Science,83, 394-403.(79 citations)

5. Chakraborty A , R S Nanjundiah and J Srinivasan, 2002: Role of Asian and African Orogra-phy on Indian Summer Monsoon. Geophysical Research Letters, 29, doi: 10.1029/2002GL015522.(51 citations)

6. Rajendran K , R S Nanjundiah, and J Srinivasan, 2002: Comparison of Seasonal and Intrasea-sonal Variation of Tropical Climate in NCAR CCM2 GCM With Two Di erent Cumulus schemes. Meteorology & Atmospheric Physics 79, 57-86.(35 citations)

7. Vinaychandran P N and R S Nanjundiah, 2009: Indian Ocean sea surface salinity variations in a coupled model. Climate Dynamics, doi:10.1007/s00382-008-0511-6, 33, 245-263.(28 citatons)

8. Bhat, G S, A Chakraborty , R S Nanjundiah and J Srinivasan, 2002: Vertical Thermal Structure of the Atmosphere over North Bay of Bengal: Observation and Model Results. Current Science, 83, 296-302 (24 citations)

9. Sahany S , V Venugopal and R S Nanjundiah, 2010: Diurnal Scale Signatures of Monsoon Rain-fall Over the Indian Region from TRMM Satellite Observations. Journal of Geophysical Research - Atmospheres, 115 D020103 doi:10.1029/2009JD012644, 2010. (22 citations)

10. Michalakes J and R S Nanjundiah, 1994: Computational Load in Model Physics of the parallel NCAR Community Climate Model. ANL/MCS-TM-186, February 1994. (21 citations)

Industry Interaction

I am currently involved in a project sponsored by Intel Inc. titled Intel Parallel Computing Centre for Modelling Monsoons and Tropical Climate (IPCC-MMTC)" for using computational accelerators such as Xeon-Phi for climate modelling. This research is being conducted in collaboration with National Centre for Atmospheric Research (NCAR) of USA.

Earlier I have been involved in projects sponsored by Microsoft and IBM on use of HPC for climate studies. I have also worked with India Meteorological Dept (which in our eld could be considered as a user industry) on using numerical models for forecasting monsoons.

Membership of Committees

1. Member, Project Monitoring Commitee, High-resolution Operational Ocean Forecast and reanalysis System (HOOFS) of Ministry of Earth Sciences, 2013-Present

2. Member, Project Advisory and Monitoring Committee for Hydrosphere and Cryosphere of Ministry of Earth Sciences, 2013-Present.

3. Member, Expert Committee on Application Development, National Supercomputing Mission, 2016-Present

4. Domain Co-ordinator for Environment and Climate Change, Imprint-India, 2015-Present.

Details of Research Experience of Ravi S. Nanjundiah

My research has been focussed on trying to understand Indian monsoon and its variability by investigations of a slew of atmospheric models including general circulation models (AGCMs), coupled AtmosphereOcean models (AOGCMs) as well as cloud system resolving models and on-line chemistry models , to assess the role of important factors and processes in the different observed facets of the monsoon. I have also assessed the performance of state of the art climate models in simulating/predicting the monsoon, its variability and its observed teleconnections so as to get an insight into how the skill in prediction could be improved . From the outset, I have also been deeply interested in the computational aspects and numerics of the models as well as use of machine learning methods. I have worked on improving the scalability of climate models, use of High Performance Computing, grid computing and computational accelerators for increasing computational throughput of climate models. All this has been achieved with successful collaboration with mathematicians, atmospheric scientists, oceanographers, hydrologists and computational scientists within and outside IISc, and with students.

A few of the investigations carried out are described briefly here to give a flavour of the problems addressed, the approach adopted and results obtained

I started research on the Indian Summer Monsoon in 1986 with the development of a simple climate model which could simulate realistically some of the most important features of the observed intraseasonal variability of the Indian monsoon such as the northward propagations of cloud-bands/rain-belts from the equatorial Indian Ocean onto the Indian monsoon zone at iintervals of 2-6 weeks throughout the summer monsoon season. We found that in the model the propagations occur due to gradient in vertical moist static instability (Nanjundiah et al,1992). This could potentially be useful for forecasting such propagations. While working on this model, I also began to use alternative computational techniques such as parallel computing so as to enable faster simulations on the available computers. I have continued work on monsoon modelling as well as on computational aspects and numerics of models throughout my career.

I. Studies of the simulation of the mean monsoon

Role of the spectacular mountain ranges of the Indian subcontinent and Myanmar in the mean monsoon has been emphasized in one of the early theories of the monsoon in the beginning of the last century. A special feature of the Bay of Bengal which sustains the monsoon with cloud systems from the region moving onto the Indian landmass, is the low salinity water near the surface due to river runoff and rainfall. River runoff could decrease due to increased impounding of river-waters. It is thus important to understand the role of river runoff on the monsoon. It has been suggested that increasing aerosols, particularly, black carbon, may decrease the monsoon rainfall and the importance of considering the impact of aerosols, clouds and their interaction has been pointed out.

a. Impact of orography

Our investigation of what happens to the monsoon when the mountains over different parts of the globe are removed in an AGCM (the NCMRWF GCM) showed that, with the exception of African orography, removal of orography in any other part of the world including remote regions such as the Rockies and the Andes reduced the monsoon rainfall and delayed its onset, these effects being largest for Western Himalayas (Chakraborty et al 2002, 2006). The absence of African orography strengthened the low level westerly jet and the rainfall over the Indian monsoon region because of non-linear feedbacks between rainfall and circulation that had been ignored in previous studies

b. Monsoon & Ocean-Land-Atmosphere interaction

Comparison of a 100 year run of the Community Climate System Model (CCSM3) in which the river runoff is included with another similar run in which there is no river runoff showed that when the river discharge was shut off, global average sea surface temperature (SST) rose by about 0.5C and the monsoon rainfall increased by about 10% with a large increase in the eastern Bay of Bengal and along the west coast of India. In addition, the frequency of occurrence of La Nia-like cooling events in the equatorial Pacific increased and the correlation between ISMR and Pacific SST anomalies became stronger. The teleconnection between 4 the SST anomalies in the Pacific and monsoon was effected via upper tropospheric meridional temperature gradient and a shift of the North African Asian Jet axis (Vinayachandran et al, 2015).

c. Monsoons, Aerosols & Clouds

Aerosols and their interaction with atmosphere especially in modulating radiative heating can have a significant impact on monsoons. Over India black carbon aerosols (from vehicular emissions) and dust can play a significant role in modulating monsoons.

When we incorporated the atmospheric heating effect of black carbon aerosols (and cooling effect on the ground) we found that the strength of the mean monsoon actually increased. However, the regions where significant changes in precipitation occurred were sensitive to the cumulus parameterization used. (Chakraborty et al, 2004, Chakraborty et al 2012). Our studies have also shown that aerosol radiative forcing over geographically remote regions such as Eastern China could impact the Indian Monsoon (Chakraborty et al 2014). We have also assessed the simulation of aerosol concentrations over India in an on-line chemistry model (Govardhan et al 2015, 2016)

Cloud related processes are important for monsoons and its simulation. We examined cumulus closure in two AGCMs and found that simulation of tropical rainfall in general, and Indian summer monsoon in particular , were sensititve to the rate at which clouds reduce moist instability. Lower rates of instability reduction gave more realistic simulations (Jain et al 2013, Mishra et al 2008) . We are studying convection over Bay of Bengal using a cloud system resolving model and are now attempting LES of convection over a tropical ocean.

II Assessment of the performance of climate models in monsoon simulation and prediction

An analysis of the retrospective predictions by seven coupled oceanatmosphere models from major forecasting centres of Europe and USA showed that they had reasonable skill in predicting the extremes of the Indian summer monsoon rainfall, particularly those associated with ENSO. However, despite large inter-model differences in the parameterizations, numerics etc., there was also a remarkable coherence between the failures of the models to predict the Equatorial Indian Ocean Oscillation (EQUINOO) and the monsoon in years in which EQUINOO played an important role. It was found that models were able to simulate ENSOmonsoon link realistically, whereas the link of monsoon rainfall with EQUINOO was simulated realis-tically by only one model the ECMWF model. Furthermore, in most models the simulated link is opposite to the observed, suggesting that prediction of EQUINOO and its links with the monsoon need to be improved for improving monsoon predictions by these models (Nanjundiah et al, 2013). We found that while the CGCMs used in IPCC AR4 were also able to simulate the ENSO-Monsoon relationship realistically, almost all models failed to simulate the EQUINOO-Indian monsoon relationship (Rajeevan and Nanjundiah, 2009).

III Machine Learning Techniques for Climate Change & Seasonal Prediction:

We have studied the impact of possible anthropogenic climate on smaller scales (such as that of a river basin or a meteorological subdivision) than those that can be resolved by IPCC scenario models by using statistical downscaling techniques ( e g Tripathi et al, 2006, Anandhi et al, 2012). We have shown that forecasts of the Indian summer monsoon rainfall on the seasonal scale using similar machine learning techniques have skills comparable to the operational statistical models (Saha et al, 2016)

IV Numerical Techniques for AGCMs:

We have investigated the impact of numerics and developed a framework for deriving splitting methods for semi-linear ordinary differential equations and partial differential equations (Murthy and Nanjundiah, 2000). We developed a technique for grid refinement for spectral technique using reparameterisation maps tailored for studying tropical convection and teleconnections. Grid refinement in spectral models is a much more challenging task than in grid-point models and only a handful of such efforts have been attempted (Janakiraman et al, 2012). We have developed a technique for analysis of space-time variation of tropical precipitation (Shanker and Nanjundiah, 2004, Chakraborty and Nanjundiah, 2012).

V HPC & Climate Modelling:

Scalability and throughput are important issues while using High Performance Computing. Any increase in these in effect implies a faster and more efficient computer at no additional cost. My research (in collaboration with computational scientists) has shown that these can be improved through load-balancing, message compression and use of computational accelerators. Our work on load balancing (Sundari et al, 2009) for a climate-system model showed that moving high computational load related to radiation to less-loaded processors computing ocean and other components leads to 15% improvement in overall throughput. This was perhaps the first of its kind for a multi-component climate system model.

The trend in computational architecture is to move towards accelerators such as GPUs (for lowering of energy requirement). I have worked on exploiting GPUs for climate modelling (Korwar et al, 2014). Radiation computations can be a significant part of a climate models execution time. By offloading the most time-consuming routines of radiation onto GPUs and exploiting asynchronous computing due to the fact that it is a slowly varying function of time, we could completely offset the time consumed in this part of execution. In the process these parts of the codes could be called more frequently and hence could result in higher accuracy.

Interprocessor communication is one of the biggest bottlenecks in parallel computing. Bigger the size of the communicated message higher could be the overhead. My work (Kumar et al ,2008) on messagecompression exploits the fact that the model state does not change significantly between two consecutive timesteps and this could be exploited to reduce inter-processor communication. By sending information only about the changed parts of the message the speedup increases by about 18%. This was the first application of message-compression to a climate model.

VI Grid Computing for Climate Modelling

Grid computing helps to agglomerate resources at geographically distinct locations. In a resources-starved country like India it is a good alternative to installing a large computer at a single location. We built a computational grid consisting of clusters at CAOS and SERC that could be used for climate-system model simulations (Sundari et al 2012, 2011) . This grid exploited the feature that a climate-system model consists of loosely coupled sub-components running concurrently with inter-component communication being low (in contrast to intra-component communication which could be much higher). The middleware for this purpose could reconfigure computations whenever new/existing systems became available/unavailable. The ideas thus developed can also be used on future exa-scale computers which could consist of loosely-coupled computers (to prevent frequent failure).

VII Climate & Big Data

Datasets related to climate are now getting bigger due to higher availability of data from satellite and conventional observations, and due to higher resolution of simulations. Analysisng this data is now considered as one of the biggest challenges in Big Data. It is no longer possible for a researcher to manually search for a pattern within such large datasets. Hence automated techniques are a necessity. I have worked on developing algorithms (Doraiswamy et al, 2013) based on computational topology for tracking cloudsystems such as cyclones and the eastward moving cloudbands in the equator related to Madden Julian oscillations. It could also resolve movement of clouds within such cloudsystems . Another automated method using gradient based multi-field comparison measure could identify hurricanes and its tracks in a large dataset such as a multi-century simulation from a climate model (Nagaraj et al 2011).

Papers Published in Peer reviewed Journals

2021

99. Mukhopadhyay P., Bechtold P., Zhu Y., Krishna R.P.M., Kumar Siddharth, Ganai M., Tirkey S., Goswami T., Mahakur M., Deshpande M., Prasad V.S., Johny C.J., Mitra A., Ashrit R., Sarkar A., Sarkar Sahadat, Roy Kumar, Andrews E., Kanase R., Malviya S., Abhilash S., Domkawle M., Pawar S.D., Mamgain A., Durai V.R., Nanjundiah R.S., Mitra A.K., Rajagopal E.N., Mohapatra M., Rajeevan M., Unravelling the mechanism of extreme (more than 30 sigma) precipitation during August 2018 and 2019 over Kerala, India, Weather and Forecasting, 36, August 2021, DOI:10.1175/WAF-D-20-0162.1, 1253-1273

98. Mukhopadhyay P., Bechtold P., Zhu Y., Krishna R.P.M., … , Nanjundiah R.S., Mitra A.K., Rajagopal E.N., Mohapatra M., Rajeevan M., Unravelling the mechanism for extreme rain events in Kerala, India, Bulletin of the American Meteorological Society, May 2021, 400-401 (NOWCAST: Papers of Note)

97. Mohan G.M., Vani K.G., Hazra A., Mallick C., Chaudhari H.S., Pokhrel S., Pawar S.D., Konwar M., Saha Subodh K., Das S.K., Deshpande S., Ghude S., Barth M.C., Rao Suryachandra A., Nanjundiah R.S., Rajeevan M., Evaluating different lightning parameterization schemes to simulate lightning flash counts over Maharashtra, India, Atmospheric Research, 255: 105532, June 2021, DOI:DOI:10.1016/j.atmosres.2021.105532, 1-22

96. Jena C., Ghude S.D., Kumar Rajesh, Debnath S., Govardhan G., Soni V.K., Kulkarni S.H., Beig G., Nanjundiah R.S., Rajeevan M., Performance of high resolution (400 m) PM2.5 forecast over Delhi, Scientific Reports, 11: 4104, February 2021, DOI:DOI:10.1038/s41598-021-83467-8, 1-9 (Impact Factor 3.998)

95. Arushi P.V., Chakraborty A., Nanjundiah R.S., Recent weakening in MJO-related convective activity over the equatorial Indian Ocean and Maritime Continent, Theoretical and Applied Climatology, 143, January 2021, DOI:10.1007/s00704-020-03423-w, 267-278

2020

94. Pathak H.S., Satheesh S.K., Moorthy K.K., Nanjundiah R.S., Assessment of regional aerosol radiative effects under the SWAAMI campaign – Part 2: Clear-sky direct shortwave radiative forcing using multi-year assimilated data over the Indian subcontinent, Atmospheric Chemistry and Physics, 20, November 2020, DOI:10.5194/acp-20-14237-2020, 14237-14252

93. Kumar R., Ghude S.D., Biswas M., Jena C., Alessandrini S., Debnath S., Kulkarni S., Sperati S., Soni V.K., Nanjundiah R.S., Rajeevan M., Enhancing accuracy of air quality and temperature forecasts during paddy crop residue burning season in Delhi via chemical data assimilation, Journal of Geophysical Research: Atmospheres, 125: e2020JD033019, September 2020, DOI: 10.1029/2020JD033019, 1-16

92. Kumar Bipin, Nanjudiah R.S., Bhowmik M., Prospective applications of artificial intelligence/machine learning techniques in earth sciences, Current Science, 119, August 2020, 424-425

91. Mukhopadhyay P., Krishnan R., Nanjundiah R.S., Mohapatra M., Prediction of Extreme Events: Current status and future pathways against the backdrop of climate change, Bulletin of the American Meteorological Society, 101, July 2020, DOI:10.1175/BAMS-D-20-0037.1, E1137–E1141

90. Ghude S.D., Rajesh Kumar, Jena C., Debnath S., Kulkarni R.G., Alessandrini S., Biswas M., Kulkrani S., Pithani P., Kelkar S., Sajjan V., Chate D.M., Soni V.K., Singh S., Nanjundiah R.S., Rajeevan M., Evaluation of PM2.5 forecast using chemical data assimilation in the WRF-Chem model: A novel initiative under the Ministry of Earth Sciences air quality early warning system for Delhi, Current Science, 118, June 2020, DO:I10.18520/cs/v118/i11/, 1-13

89. Jahfer S., Vinayachandran P.N., Nanjundiah R.S., The role of Amazon river runoff on the multidecadal variability of the Atlantic ITCZ, Environmental Research Letters, 15: 054013, May 2020, DOI:10.1088/1748-9326/ab7c8a, 1-10

88. Srivastava G., Chakraborty A., Nanjundiah, R.S., Multidecadal variations in ENSO-Indian summer monsoon relationship at sub-seasonal timescales, Theoretical and Applied Climatology, 140, May 2020, DOI:10.1007/s00704-020-03122-6, 1299–1314

87. Pithani P., Ghude S.D., Jenamani R.K., Biswas M., Naidu C.V., Debnath S., Kulkarni R., Dhangar N.G., Jena C., Hazra A., Phani R., Mukhopadhyay P., Prabhakaran Thara, Nanjundiah R.S., Rajeevan M., Real-Time forecast of dense fog events over Delhi: The performance of the WRF model during the WiFEX field campaign, Weather and Forecasting, 35, April 2020, DOI:10.1175/WAF-D-19-0104.1, 739-756

86. Karmakar N., Chakraborty A., Nanjundiah R.S., Influence of global sea surface temperature on ultra-low frequency variability in the Indian summer monsoon rainfall, Quarterly Journal of Royal Meteorological Society, 146, February 2020, Part B, DOI:10.1002/qj.3715, 904-921

85. Saha M., Nanjundiah R.S., Prediction of ENSO and EQUINOO Indices during June to September using Deep Learning Method, Meteorological Applications, 27, February 2020, DOI:10.1002/met.1826, 1-13

2019

84. Rao S.A., Goswami B.N., Sahai A.K., Rajagopal E.N., Mukhopadhyay P., Rajeevan M., Nayak S., Rathore L.S., Shenoi S.S.C., Ramesh K.J., Nanjundiah R.S., Ravichandran M., Mitra A.K., Pai D.S., Bhowmik S.K.R., Hazra A., Mahapatra S., Saha S.K., Chaudhari H.S., Joseph S., Pentakota S., Pokhrel S., Pillai P.A., Chattopadhay R., Deshpande M., Krishna R.P.M., Siddharth Renu, Prasad V.S., Abhilash S., Pani, Monsoon Mission : A targeted activity to improve monsoon prediction across scales, Bulletin of the American Meteorological Society, 100, December 2019, DOI:10.1175/BAMS-D-17-0330.1, 2509-2532

83. Pathak H.S., Satheesh S.K., Nanjundiah R.S., Moorthy K.K., Lakshmivarahan S., Babu S.N.S., 2019: Assessment of regional aerosol radiative effects under the SWAAMI campaign – Part 1: Quality-enhanced estimation of columnar aerosol extinction and absorption over the Indian subcontinent. Atmospheric Chemistry and Physics, 19, September 2019, DOI:10.5194/acp-19-11865-2019, 11865–11886

82. Srivastava G., Chakraborty A.,Nanjundiah R.S., 2019:Multidecadal see-saw of the impact of ENSO on Indian and West African summer monsoon rainfall, Climate Dynamics, 52, June 2019, DOI:10.1007/s00382-018-4535-2, 6633-6649

81. Govardhan G., Sateesh S.K., Krishna Moorty K., Nanjundiah R., 2019: Simulations of black carbon over the Indian region: improvements and implications of diurnality in emissions, Atmospheric Chemistry and Physics, 19, June 2019, DOI:10.5194/acp-19-8229-2019, 8229–8241

80. Banerjee P., Satheesh S.K., Krishna Moorthy K., Nanjundiah R.S., Nair V.S., 2019: Long-range transport of mineral dust to the Northeast Indian Ocean: Regional versus remote sources and the implications, Journal of Climate, 32, March 2019, DOI:10.1175/JCLI-D-18-0403.1, 1525-1549

2018

79. Kumar Bipin, Bhowmik Moumita, Nanjundiah R.S., 2018: Clouds, microphysical processes and small-scale simulations. Current Science, 115, November 2018, 1636-1637

78. Sonali P, R S Nanjundiah and D N Kumar, 2018: Detection and attribution of climate change signal in South India temperature. Climate Research Vol. 76: 145–160, 2018 https://doi.org/10.3354/cr01530

77. Mukhopadhyay P., Nanjundiah R.S., 2018: Representation of physical processes in weather and climate models, Current Science, 114, March 2018, 1155-1155

76. Jain D K , A Chakraborty and R S Nanjundiah, 2018: A Mechanism for the Southward Propa-gation of Mesoscale Convective Systems Over the Bay of Bengal. Journal of Geophysical Research - Atmospheres doi:10.1002/2017JD027470

2017

75. Sonali P, R S Nanjundiah and D N Kumar, 2017: Linkage between global sea surface temperature and hydroclimatology of a major river basin of India before and after 1980. Environmental Research Letters, 12, 124002

74. Govardhan G., Satheesh S.K., Nanjundiah R., Moorthy K.K., Babu S.S., 2017: Possible climatic implications of high-altitude black carbon emissions. Atmospheric Chemistry and Physics. 17, DOI:10.5194/acp-17-9623-2017, 9623–9644

73. Karmarkar N., Chakraborty A., Nanjundiah R.S., 2017: Increased sporadic extremes decrease the intraseasonal variability in the Indian summer monsoon rainfall. Scientific Reports. 7:7824, DOI:10.1038/s41598-017-07529-6, 1-7

72. Arushi P V , A Chakraborty and R S Nanjundiah, 2017: Orographic Control of the Bay of Bengal Cold Pool Rainfall. Journal of Earth System Sciences, 126: 111, https://doi.org/10.1007/s12040-017-0892-1

71. Saha M , P Mitra and R S Nanjundiah, 2017: Deep learning for predicting the monsoon over the ho-mogeneous regions of India Journal of Earth System Science, 126: 54, https://doi.org/ 10.1007/s12040-017-0838-7

70. Jahfer S., Vinaychandran P.N., Nanjundiah R.S., 2017: Long-term impact of Amazon river runoff on northern hemispheric climate. Scientific Reports. 7:10989, DOI:10.1038/s41598-017-10750-y, 1-9

69. Karmakar N, A Chakraborty and R S Nanjundiah, 2017: The Spatio-Temporal Structures and Relative Roles of Low- and High-Frequency Intraseasonal Modes in Indian Summer Monsoon Rainfall. Monthly Weather Review, 145 413-435.

68. Kashyap, A, S S Vadhiyar, R S Nanjundiah, P N Vinayachandran, 2017: Asynchronous and Synchronous Models of Executions on Intel Xeon Phi Coprocessor Systems for High Performance of Long Wave Radiation Calculations in Atmosphere models. Journal of Parallel and Distributed Computing, 102, 199-212

67. Anandhi A, N Omani, I Chaubey, R Horton, D Bader and R S Nanjundiah, 2017: Synthetic Scenarios from CMIP5 Model Simulations for Climate Change Impact Assessments in Managed Ecosystems and Water Resources: Case Study in South Asian Countries Transactions of the ASABE 59(6) 1715-1731. doi: 10.13031/trans.59.11585

2016

66. Ghosh R , A Chakraborty and R S Nanjundiah, 2016: Relative Role of Pre-monsoon Conditions and Intraseasonal Oscillations in Determining Early-vs-Late Indian Monsoon Intensity in a GCM.Theoretical & Applied Climatology DOI 10.1007/s00704-016-1970-z

65. Sonali P , D N Kumar and R S Nanjundiah, 2016: Intercomparison of CMIP5 and CMIP3 sim-ulations of the late 20th century temperature extremes over India and detection of climatic trends.Theoretical & Applied Climatology DOI:10.1007/s00704-015-1716-3

64. Saha M , P Mitra and R S Nanjundiah, 2016: Autoencoder Based Climatic Index Discovery for Prediction of Indian Monsoon. Meteorology & Atmospheric Physics DOI: 10.1007/s00703-016-0431-7

63. Govardhan G , R S Nanjundiah, S K Satheesh, K Krishnamoorthy and T Takemura, 2016: Inter-comparison and performance evaluation of chemistry transport models over Indian region. Atmospheric Environment, 125, 486-504.

2015

62. Das Gupta A , A S V Murthy and R S Nanjundiah, 2015: A study of singularities in the inviscid linear theory of sea breezes. Int J Adv Eng Sci Appl Math, DOI 10.1007/s12572-015-0129-y

61. Vinaychandran P N, J Sharief and R S Nanjundiah, 2015: Impact of River Runo into the Ocean on Indian Summer Monsoon. Environmental Research Letters, 10 doi:10.1088/1748-9326/10/5/054008

60. Karmakar N , A Chakraborty and R S Nanjundiah, 2015: Decreasing intensity of monsoon low-frequency intraseasonal variability over India. Environmental Research Letters, 10, doi:10.1088/1748-9326/10/5/054018.

59. Govardhan G , R S Nanjundiah, S K Satheesh, K K Moorthy and V R Kotamurthi,2015: Perfor-mance of WRF-Chem over Indian region: Comparison with measurements Journal of Earth System Science, 124, 875-896.

2014

58. Venkatesh T N, J Mathew and R S Nanjundiah, 2014: Secondary instability as a mechanism for severe clear-air turbulence in the atmosphere. Meteorology & Atmospheric Physics, 126, 139-160

57. Anandhi A and R S Nanjundiah, 2014: Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores. Theoretical and Applied Climatology doi:10.1007/s00704-013-1043-5..

56. Chakraborty A, R S Nanjundiah and J Srinivasan, 2014: Radiative Impacts of Carbon Aerosols on South and East Asian Summer Monsoon: Proximate vs Remote. International Journal of Climatology, 34, 2108-2121.

55. Anandhi A, V V Srinivas, D N Kumar, R S Nanjundiah and P H Gowda, 2014: Estimating future climate change scenarios of surface solar radiation in data sparse regions: a case study in Malaprabha river basin, India. Climate Research, 59 , pp. 259-270.

54. Chakraborty A and R S Nanjundiah, 2014: Role of Orography in Modulating Space-time Scales of Convection over South Asia. Theoretical and Applied Climatology 116, 549-564.

2013

53. Doraiswamy H , V Natarajan and R S Nanjundiah, 2013: An Exploration Framework to Identify and Track Movement of Cloud systems. IEEE Transactions on Visualization and Computer Graphics,19(12), 2896-2905.

52. Jain D K , A Chakraborty and R S Nanjundiah, 2013: Role of Cloud Adjustment Time Scale on Simulation of Interannual Variability of Indian Summer Monsoon. Meteorology and Atmospheric Physics, 122, 159-173.

51. Nanjundiah R S, P A Francis, M Ved and S Gadgil, 2013: Predicting the extremes of Indian summer monsoon rainfall with coupled ocean-atmosphere models. Current Science 104, 1380-1393

50. Das Gupta A J , A S V Murthy, R S Nanjundiah and C V Srinivas, 2013: A linear model for the sea breeze circulation relevant to the tropical regions. International Journal of Geomathematics 4, 97-135 (doi:10.1007/s13137-013-0047-8).

2012

49. Chakraborty A and R S Nanjundiah, 2012: Space-time Scales of Northward Propagation of Convec-tion During Boreal Summer. in Monthly Weather Review, 140, 3857-3866.

48. Sajani S, K Krishna Moorthy, K Rajendran and R S Nanjundiah, 2012: Monsoon sensitivity to aerosol direct radiative forcing in the Community Climate Model. Journal of Earth System Sciences, 121, 867-889.

47. Sundari S M , S S Vadhiyar and R S Nanjundiah, 2012: Large Improvements in Application throughput of Long-running Multi-Component Applications using Batch Grids. Concurrency and Computation: Practice and Experience, 24, 1775-1791 .

46. Rajendran K, R S Nanjundiah, S Gadgil and J Srinivasan, 2012: On simulation of the tropical SST-rainfall relationship by atmospheric and coupled models. Journal of Earth System Sciences, 121, 595-610.

45. Janakiraman S , R S Nanjundiah and A S Vasudevamurthy, 2012: A novel variable resolution global spectral method on the sphere. J of Computational Physics, 231, 2794-2810.

44. Jain D K , A Chakraborty and R S Nanjundiah, 2012: On the role of cloud adjustment time scale in simulating precipitation with relaxed Arakawa-Schubert Convection scheme. Meteorology and Atmospheric Physics 115 1-13.

2011

43. Sundari S M , S S Vadhiyar and R S Nanjundiah, 2011: Adaptive Executions of Multi-Physics Coupled Applications on Batch Grids. Journal of Grid Computing, 9(4), 455-478.

42. Anandhi A, V V Srinivas, D Nagesh Kumar and R S Nanjundiah, 2011: Daily Relative Humidity Projections in an Indian River Basin for IPCC SRES Scenarios. Theoretical and Applied Climatology DOI 10.1007/s00704-011-0511-z

41. Vialard J, P Terray, J-P Duvel, R S Nanjundiah, S S C Shenoi and D Shankar,2011: Factors Controlling January-April rainfall over southern India and Sri Lanka. Climate Dynamics 37, 493-507.

40. Nagaraj, S , V Natarajan and R S Nanjundiah, 2011: A Gradient- Based Comparison Measure for Visual Analysis of Multi eld Data. Computer Graphics Forum, 30(3), 2011, 1101-1110.

2010

39. Sahany S , V Venugopal and R S Nanjundiah, 2010: The 26 July 2005 heavy rainfall event over Mumbai: numerical modeling aspects Meteorology & Atmospheric Physics 109, 115-128

38. Sahany S , V Venugopal and R S Nanjundiah, 2010: Diurnal Scale Signatures of Monsoon Rain-fall Over the Indian Region from TRMM Satellite Observations. Journal of Geophysical Research - Atmospheres, 115 D020103 doi:10.1029/2009JD012644, 2010.

37. Sundari S M , S S Vadhidyar and R S Nanjundiah, 2010: Grids with Multiple Batch Systems for Performance Enhancement of Multi-Component and Parameter Sweep Parallel Applications. Future Generation Computing Systems, vol 26, 217-227.

2009

36. Vinaychandran P N and R S Nanjundiah, 2009: Indian Ocean sea surface salinity variations in a coupled model. Climate Dynamics, doi:10.1007/s00382-008-0511-6, 33, 245-263.

35. Anandhi A , V V Srinivas, D N Kumar and R S Nanjundiah, 2009: Role of Predictors in Downscaling Surface Temperature to River Basin in India for IPCC SRES Scenarios using Support Vector Machine.International Journal of Climatology, 29, 583-603.

34. Chakraborty A, R S Nanjundiah and J Srinivasan, 2009: Impact of African Orography and the Indian Summer Monsoon on the low-level Somali Jet. Intl. Journal of Climatology, 29, 983-992.

33. Sundari S M , S S Vadhiyar and R S Nanjundiah, 2009: Dynamic Component Extension: A Strategy for Performance Improvement in Multi-Component Applications. International Journal of High Performance Computing Applications 23, pages 84-98.

2008

32. Mishra S, J Srinivasan and R S Nanjundiah, 2008: Impact of temporal resolution on ITCZ rainfall. Monthly Weather Review, 136, 4077-4091.

31. Sahaney S and R S Nanjundiah, 2008 : Impact of Convective Downdraft on Rainfall in an Aqua-planet model. Annales Geophysicae, 26, 1877-1887.

30. Nanjundiah R S, 2008: HPC: Its application in Climate Modelling. Computer Modelling in Engi-neering & Sciences, 27, 1-23.

29. Kumar S V , R S Nanjundiah, M J Thazhuthaveetil, and R Govindrajan , 2008: Impact of Message Compression on the Scalability of an Atmospheric Modelling. Application on Clusters. Journal of Parallel Computing, doi:10.1016/j.parco-2007.10.0.002, 34, 1-16.

28. Anandhi A , V V Srinivas, R S Nanjundiah and D Nagesh Kumar,2008: Downscaling Precipitation to River Basin in India for IPCC SRES Scenarios using Support Vector Machine. International Journal of Climatology, doi: 10.1002/joc.1529, 28, 401-420.

2007

27. Nanjundiah R S and T.N. Krishnamurti, 2007: Intraseasonal Variations of Tropical Convergence Zones: Theory and Predictions. Current Science, 93, 173-181.

2006

26. Chakraborty A , R S Nanjundiah, and J Srinivasan 2006: Theoritical Aspects of the Onset of Indian Summer Monsoon From Perturbed Orography Simulations in a GCM Annales Geophysicae, 24, 2075-2089.

25. Tripathi S , V. V. Srinivas and R S Nanjundiah, 2006: Downscaling of Precipitation for Climate Change Scenarios: A Support Vector Machine Approach. Journal of Hydrology, 330, 621-640.

24. Maity R , D N Kumar and R S Nanjundiah, 2006: Review Of Hydroclimatic Teleconnection Between Hydrologic Variables And Large-Scale Atmospheric Circulation Patterns With Indian Perspective. Journal of Indian Hydrological Society, 13, 77-92.

23. M P Sudheer , R S Nanjundiah and A S V Murthy, 2006: Revisiting the Slow Manifold of Lorenz-Krishnamurthy Quintet. Discrete and Continous Dynamical Systems - Series B, 6, 1403-1416.

22. Vidyunmala V , R S Nanjundiah and J Srinivasan, 2006: The E ect of Variation in SST and its Meridional gradient on the Equatorial and O -equatorial ITCZ in AGCM. Meteorology and Atmo-spheric Physics, 95, 239-253

2005

21. Nanjundiah R S , V Vidyunmala and J Srinivasan, 2005: The impact of increase in CO2 on the simulation of tropical biennial oscillations (TBO) in 12 coupled general circulation models Atmospheric Science Letters, 6, 183-191 doi: 10.1002/asl.113.

20. Janakiraman S , R S Nanjundiah, and P Vinaychandran 2005: Simulations of the Monsoons with a Coupled Ocean-Atmospheric Model on the Param Padma. Current Science, 89, 1555-1562.

19. Nanjundiah R S , V Vidyunmala and J Srinivasan, 2005: On the di erence in the seasonal cycle of rainfall over India in the Community Climate System Model( CCSM2) and Community Atmospheric Model(CAM2). Geophysical Res. Letters, 32, doi: 10.1029/2005GL024278.

18. Gadgil S, M Rajeevan and R S Nanjundiah, 2005: Monsoon Prediction -Why yet another failure? Current Science, 88, 1389-1400.

2004

17. Chakraborty A , S K Satheesh, R S Nanjundiah and J. Srinivasan, 2004: Impact of Absorbing Aerosols on the Simulation of Climate in the Indian Region using an atmospheric GCM. Annales Geophysicae, 22, 1421-1434.

16. Shanker A P , and R S Nanjundiah , 2004: Morlet Wavelet Analysis in Space and Time: Study of Poleward Propagations of Intertropical Convergence Zones. Geophysical Research Letters, 31, doi:10.1029/2003GL018150

2002

15. Chakraborty A , R S Nanjundiah and J Srinivasan, 2002: Role of Asian and African Orography on Indian Summer Monsoon. Geophysical Research Letters, 29, doi: 10.1029/2002GL015522.

14. Gadgil S, J Srinivasan, R S Nanjundiah , K Krishna Kumar, A A Munot, and K. Rupa Kumar, 2002: On Forecasting the Indian Summer Monsoon :the Intriguing Season of 2002. Current Science, 83, 394-403.

13. Rajendran K , R S Nanjundiah and J Srinivasan, 2002: The Impact of Surface Hydrology on the Simulation of Tropical Intraseasonal Oscillation in NCAR (CCM2) Atmospheric GCM. Journal of Meteorological Society of Japan, 80, 1357-1381

12. Bhat G S, A Chakraborty , R S Nanjundiah and J Srinivasan, 2002: Vertical Thermal Structure of the Atmosphere over North Bay of Bengal: Observation and Model Results. Current Science, 83, 296-302

11. Srinivasan, J and R S Nanjundiah, 2002: The Evolution of Indian Summer monsoon in 1997 and 1983. Meteorology and Atmospheric Physics, 79, 243-257

10. Rajendran K , R S Nanjundiah, and J Srinivasan, 2002: Comparison of Seasonal and Intrasea-sonal Variation of Tropical Climate in NCAR CCM2 GCM With Two Di erent Cumulus schemes. Meteorology & Atmospheric Physics 79, 57-86.

1992-2000

9. Murthy A S V, and R S Nanjundiah, 2000: Splitting Errors in Explicit and Implicit Methods. Monthly Weather Review, 128, 3921-3926.

8. Nanjundiah R S, 2000: Impact of Moisture Transport on the Simulated Tropical Rainfall in a General Circulation Model. Climate Dynamics, 16, 303-317.

7. Nanjundiah R S, 2000: Seasonal Simulation of the Monsoon with the NCMRWF Model. Current Science, 78, 869-875.

6. Sinha, U N, R S Nanjundiah , and T N Venkatesh, 1999: Computational Weather Modelling. Current Science, 77, 1333-1342.

5. Jagadheesha D , R S Nanjundiah and R Ramesh, 1999: Orbital Forcing of Monsoonal Climates in NCAR CCM2 with Two Horizontal Resolutions. Paleoclimatology, 3, 279-301.

4. Nanjundiah R S and J Srinivasan, 1999: Anomalies of Precipitable Water-Vapor and Vertical Sta-bility During El-Nino. Geophysical Research Letters, 26, 95-98.

3. Nanjundiah R S, and U N Sinha 1999: Impact of Modern Software Engineering Practices on the Capabilities of an Atmospheric General Circulation Model. Current Science, 76, 1114-1116.

2. Sinha U N and R S Nanjundiah , 1998: Usability of Parallel Processing Computers in Numerical Weather Prediciton. Current Science, 74, 1045-1048.

1. Nanjundiah R S , J Srinivasan and S Gadgil, 1992: Intraseasonal Variation of the Indian Summer Monsoon. II : Theoritical Aspects. J of Japanese Meteorological Society, 70, 529-550. (Special issue on Asian Monsoons).

Book Chapters

Randall D.A., Srinivasan J., Nanjundiah R.S., Mukhopadhyay P., Current Trends in the Representation of Physical Processes in Weather and Climate Models, Nature Springer, ISBN 978-981-13-3395-8, https://doi.org/10.1007/978-981-13-3396-5
Rajeevan M and R S Nanjundiah, 2009: Coupled Model Simulations of Twentieth Century Climate of the Indian Summer Monsoon. In Current Trends in Science, Platinum Jubilee Special Publication of Indian Academy of Sciences, pages 537-561 Ed: A Bhattacharyya, S R Shetye and V K Gaur.
Vinaychandran P N and R S Nanjundiah, 2007: Association between Indonesian Rainfall and the Indian Ocean dipole in Understanding and Forecasting of Monsoons. P N Vinaychandran (Ed). Centre for Science and Technology of the Non- Aligned and Other Developing Countries (NAM S & T Centre), New Delhi.

Conferences

2016

72. Saha M , P Mitra and R S Nanjundiah: Predictor Discovery for Early-late Indian Summer Monsoon Using Stacked Autoencoder. International Conference on Computational Science 2016, ICCS 2016, 6-8 June 2016, San Diego, California, USA. Procedia Computer Science, doi:10.1016/j.procs.2016.05.337

71. Sharif J , P N Vinayachandran, R S Nanjundiah: Impact of global river runo into the ocean on cli-mate. SPIE Conference on Remote Sensing and Modeling of the Atmosphere, Oceans and Interactions, New Delhi 6 April, 2016.

70. Karmakar N , A Chakraborty and R S Nanjundiah: The spatio-temporal structures and role of low-and high-frequency intraseasonal modes in Indian Summer monsoon rainfall observed in TRMM data. SPIE Conference on Remote Sensing and Modeling of the Atmosphere, Oceans and Interactions, New Delhi, 4 April 2016.

69. Nanjundiah R S, G Govardhan and S K Satheesh: Aerosol simulations over the Indian region: comparison with ground and satellite-derived observations. SPIE Conference on Remote Sensing and Modeling of the Atmosphere, Oceans, and Interactions, New Delhi 7 April, 2016.

68. Nanjundiah R S: Forecasting of Monsoons: Challenges & Opportunities. IMS Workshop, IITM Pune, 23-24 February 2016

2015

67. Nanjundiah R S, G Govardhan , S K Satheesh and K Krishnamoorthy: Aerosol simulations over Indian region in o -line and on-line chemistry transport models. Lorri Workshop, Imperial College, London, UK, 9th July 2015.

2014

66. Nanjundiah R S and A P Gunasekaran: Modelling Planetary Atmospheres: Challenges. The Second Indian Venus Workshop, NGRI, Hyderabad 28-29 October, 2014 (Invited Talk).

65. Nanjundiah R S, 2014: Use of Computational Accelerators in Climate Modelling. IRUS Workshop, HiPC, Goa, 18 Dec 2014. (Invited Talk)

64. Nanjundiah R S, 2014: Monsoons: Intraseasonal Variability & Seasonal Mean. Workshop on Clouds Convection and Data, Abu Dhabi, UAE, 4-6 March 2014 (Invited Talk).

2013

63. Korwar S K , S S Vadhiyar and R S Nanjundiah, 2013: GPU-enabled E cient Executions of Radiation Calculations in Climate Modeling. In the proceedings of International Conference on High Performance Computing (HiPC), December 2013, Bangalore, India.

62. Nanjundiah R S, 2013: Monsoon Prediction and Simulation: The HPC Challenge. Indo-US Work-shop on High Performance Computing, Applications, Big Data and Analytics. IISc Bangalore, 16-18 December 2013.

61. Nanjundiah R S, 2013: Seasonal Prediction of Indian Monsoon: Role of Teleconnections. Indo-French Meeting, CEFPRA, New Delhi, 3-5 October 2013.

60. Malakar P , V Natarajan, S S Vadhiyar and R S Nanjundiah, 2013: A Di usion-Based Processor Reallocation Strategy for Tracking Multiple Dynamically Varying Weather Phenomena. In the pro-ceedings of the International Conference on Parallel Processing (ICPP), October 2013, Lyon, France.

59. Nanjundiah R S, 2013: Parallel Computational Environments for Modelling Atmospheric & Oceanic Flows. ICTS Workshop on Advanced Dynamical Core Modeling for Atmospheric and Oceanic Circu-lations. National Atmospheric Research Laboratory, Tirupati, 18-23 February 2013.

58. Nanjundiah R S, 2013: Climate and Weather over Borneo. HPC Workshop, University of Brunei Dar-us-salaam, Brunei, 7^th February 2013

57. Nanjundiah R S, 2013: Seasonal Prediction of Indian Monsoon: Role of Ocean-Atmosphere Coupling. ICTS Workshop on Clouds, Convection and Tropical Meteorology, International Centre for Theoritical Studies, TIFR, Bangalore, 21-26 January 2013

2012

56. Govardhan G , R S Nanjundiah, S K Satheesh, K Krishnamoorthy and V R Kotarmurthi, 2012: Simulations of aerosols during pre-monsoon and post-monsoon periods, over Indian region. AGU Fall Meeting, San Francisco, 3-7 December 2012.

55. Nanjundiah R S, 2012: Indian Monsoon-Indian Ocean Linkages in Coupled Models: Its relevance to Seasonal Forecasts of Indian Monsoons. PORSEC 2012, Kochi, 6-9 Nov 2012 (Invited Talk).

54. Nanjundiah R S and M Ved, 2012: Interannual Variability in Retrospective CFS Forecasts. MMICM, IITM, Pune, 10-12 September 2012.

53. Nanjundiah R S 2012: Monsoons: Interplay of Fluid Mechanics and Thermodynamics. ICCOMIM-2012, MSRIT, Bangalore, 11-13 July 2012 (Invited Talk).

52. Nanjundiah R S, 2012: Monsoons Impact of Oceans and Orography. Workshop on Extra-tropical Tropical Interactions, NYU, Abu Dhabi (UAE), 19-22 March, 2012 (Invited Talk).

51. Nanjundiah R S, 2012: HPC: A Useful Tool to Study and Understand Monsoon. HPC Symposium, IIT Kanpur, 13-14 March 2012 (Invited Talk).

2011

50. Nanjundiah R S, 2011: Challenges in Predicting and Simulating the Monsoon. HiPC User Sympo-sium, Bangalore, 19-21 Dec 2011 (Invited Talk).

49. Nanjundiah R S, 2011: Turbulence in Climate Studies. ICTS-TIFR Discussion Meeting on Turbu-lence, 12-16 December, IISc Bangalore (Invited Talk)

48. Nanjundiah R S, 2011: Do Coupled Models Simulate the EQUINOO-ISMR Relationship? Workshop on Monsoon Variability, 17-19 August 2011, IISc Bangalore.

47. Nagaraj S , V Natarajan and R S Nanjundiah, 2011: A Gradient- Based Comparison Measure for Visual Analysis of Multi eld Data. EuroVis 2011, Bergen, Norway (3rd Prize in the Best Paper Category).

2010

46. Sundari S M , S S Vadhiyar and R S Nanjundiah, 2010: Morco: Middleware Framework for Long-Running Multi-Component Applications on Batch Grids. HPDC 2010, June 20-25 2010, Chicago, USA.

45. Nanjundiah R S, 2010: Modeling of Monsoons: A Challenge in Climate and Computational Sciences. The 12^th International Specialist Meeting on The Next Generation Models on Climate Change and Sustainability for Advanced High Performance Computing Facilities, 23-25 March 2010, Tsukuba, Japan (Invited Talk).

2009

44. Malakar P , V Natarajan, S S Vadhiyar and R S Nanjundiah, 2009: An integrated simulation and visualization framework for Tracking cyclone Aila. International Conference on High Performance Computig, HiPC, 16-19 December 2009, Kochi, India. (Best Student paper award)

43. Sundari S M , S S Vadhiyar and R S Nanjundiah, 2009: Middleware for Long-Running Applications on Batch Grids. International Conference on High Performance Computing, HiPC, 16-19 December 2009, Kochi, India

42. Nanjundiah R S, S S Vadhiyar and S M Sundari , 2009: Computational Challenges for Monsoon Studies in India. ATIP 1^st Workshop on HPC in India, Supercomputing 2009, 20 November 2009, Portland USA. (invited talk)

2008

41. Nanjundiah R S, 2008: Impact of coupling on simulation of seasonal cycle in atmosphere and ocean over Indian region. International Conference on Progress in Weather prediciton and Climate Modelling over the Indian Region, December 9-12, 2008, Noida, India.(invited talk)

40. Nanjundiah R S, 2008: Climate system modelling: Challenges in Load Balancing and Grid Enabling a Multi-Component System, International Conference on High Performance Computing (HiPC), User Industry Symposium, December 17-19, 2008, Bangalore, India. (invited talk)

39. Anandhi A , Srinivas V V, Kumar, D N, Nanjundiah R S, 2008. Downscaling climate variables to river basin scale in India for IPCC SRES scenarios using support vector machine. Proceedings of Water Down Under Conference. 15-17 April, Adelaide, Australia, ISBN 0-858-25735-1, pp.449-458.

2007

38. Sundari M S , S S Vadhiyar and R S Nanjundiah: Coupled Climate Models on Grids. HiPC 2007, Goa, 18-21 December 2007.

37. Nanjundiah R S, 2007: Grid Computing and HPC for Climate Studies. Eu-India Grid Computing Workshop. Pune 27-28 September 2007 (invited talk).

36. S Janakiraman , R S Nanjundiah and A S V Murthy, 2007: A variable resolution global spectral model on the sphere with ner resolution over tropics. 2007 Workshop on Solution of Partial Di erential Equations on the Sphere. UK Met. O ce, Exeter, UK, 24-27 September 2007.

35. Nanjundiah R S, 2007: Simulation of Indian Summer Monsoon: Role of Oceans, Mountains and Aerosols. Celebrating the Monsoon, International Conference on Monsoons, Indian Institute of Science, Bangalore, 24-28 July 2007.

34. Vidyunmala V , R S Nanjundiah and J Srinivasan, 2007: Errors in Simulation of Oceanic ITCZ and Indian Summer Monsoon Rainfall in IPCC AR4 20c3m and AMIP simulations. Celebrating the Monsoon, International conference on Monsoons, Indian Institute of Science, Bangalore 24-28 July 2007.

33. Nanjundiah R S, 2007: Monsoons, Climate System Models and HPC: A User's Perspective. Invited Talk at International HPC Users Forum Conference. IIT New Delhi, 28 Feb -1 March 2007.

32. Srinivasan J, R S Nanjundiah and V Vidyunmala , 2007: Analysis of the Errors in the Simulation of Indian Monsoon Rainfall in IPCC AR4 Simulations of the 20th Century Climate. WGNE/PCMDI Systematic Errors Workshop February 12-16 2007, San Francisco, USA.

2006

31. M P Sudheer , R S Nanjundiah and A S V Murthy,2006: Slow-Manifolds for Use in Weather Forecasting, International Congress on Computational Mechanics and Simulation (ICCMS 06) Dec 8-10, 2006, IIT Guwahati, India

30. Nanjundiah R S, 2006: HPC and Climate Systems Modelling: A User's Perspective. Invited Talk HiPC 2006, Bangalore 19-22 Dec 2006.

29. Mishra S K , J Srinivasan and R S Nanjundiah, 2006:The Impact of Timestep Size in The Simulation of Rainfall in a GCM. AGU Fall Meeting 2006, San Francisco,USA.

28. Nanjundiah R S, 2006: AGCMS, Monsoons and Interannual Variability: Is SST-Rainfall Relationship the Culprit? Invited talk at 3^rd Annual meeting of Asia Oceania Geophysical Society, Singapore, 10-14 July 2006.

27. Nanjundiah R S, 2006, A Chakraborty and J Srinivasan, 2006: Impact of African Orography on the Low Level Westerly Jet During the Monsoon Season. 11^th Asian Congress of Fluid Mechanics, Kuala Lumpur, Malaysia, 22-25 May 2006.

26. Sahaney S and R S Nanjundiah, 2006: Impact of Convective Downdrafts on The Simulation of Interannual Variability of Indian Summer Monsoon Rainfall in a GCM. IMPA 2006, IIT Delhi, February 14-16 2006.

25. Mishra S , R S Nanjundiah and J Srinivasan, 2006: Impact of Temporal Resolution on ITCZ Simulation In An Aquaplanet GCM. IMPA 2006, IIT Delhi, February 14-16 2006.

24. Tripathi S , V V Srinivas , R S Nanjundiah, 2006. Support Vector Machine Approach to Downscale Precipitation in Climate Change Scenarios. In: Randall Graham, (Ed.), Examining the Con uence of Environmental and Water Concerns, Proceedings of the 2006 World Environmental and Water Resources Congress (CD-ROM), May 21-25, 2006, Omaha, Nebraska, USA.

2005

23. Nanjundiah R S, 2005: Monsoon Simulations and High Peroformance Computing. Brainstorming workshop on High Performance Computing for Weather and Climate. Indian Institute of Technology, New Delhi, March 10-13 2005

22. Nanjundiah R S, 2005: Monsoon Simulation on Param Padma. NRB Workshop on Recent Trends in IT and Computing. National Physical and Oceanographic Laboratory, Kochi, January 10 and 11, 2005.

2004

21. Shanker A P and R S Nanjundiah, 2004: 2-D Complex Wavelet Transforms for Identi cation of Wave-like features in Geophysical Data. SPCOM 2004, IISc Bangalore, December 11-14, 2004.

20. Janakiraman S , R S Nanjundiah and A S V Murthy, 2004: High Resolution Tropical Belt Trans-formation for Variable Resolution Spectral Models PDEs on a Sphere 2004, Yokohoma, Japan, July 17-19, 2004.

1989-2003

19. Nanjundiah R S and S Janakiraman , 2003: Impact of Water Mass forcing on simulation of Indian Summer Monsoon. HPC SE 2003, Moscow June 16-20, 2003. (Invited talk)

18. Venkatesh T N, R S Nanjundiah, and U N Sinha, 2000: Building A Scalable Parallel Architecture for Spectral GCMs. In 9^th Symposium on Use of MPPs i for Weather Forecasting, ECMWF, Reading, U K, November 13-17 2000.

17. Semeena V S and R S Nanjundiah, 2000: Impact of Surface Hydrological Modelling on Simulation of the Indian Monsoon. Tropmet, Cochin, February 2000.

16. Nanjundiah R S, 2000: Importance of Modelling Moisture Advection in Simulation of tropical Rain-fall in GCMs. National Space Science Symposium, Puri, 1-4 March 2000.

15. Nanjundiah R S, 1999: Reengineering Issues for the Spectral GCM. Symposium on Advances in Numerical Weather Prediction Techniques for the Tropics. IBM SRC, IIT Delhi, 10 Dec 1999.

14. Nanjundiah R S, 1999: Application of Parallel Computing to Atmospheric Modelling Studies. PCAA'99, CDAC Pune, 23-26 June 1999.

13. Nanjundiah R S, 1998: Numerical Methods for Atmospheric Models. International Symposium on Cyclones. Dhaka, Dec 12-16 1998.

12. Bali M , Nanjundiah, R S and Kusuma G Rao, 1998: Impact of Surface Layer Processes in Modelling of Indian summer Monsoon by CCM2. National Seminar on Numerical Weather Prediction with emphasis on Boundary Layer Modelling and Meso-scale Modelling, Jadavpur University, Calcutta, Dec 3-5, 1998.

11. Nanjundiah R S, 1998: Use of High Computing for Weather & Climate Related Problems. Workshop on Modern Trends in Computing Technologies, Centre for Advanced Techonology, Indore, Nov 9-10, 1998.

10. Nanjundiah R S and A Raju, 1997: Experiment In Parallel Implementation of the NCMRWF model. Intromet, IIT Delhi, 2-5 December 1997.

9. Jagadheesha D , R S Nanjundiah and R Ramesh, 1997: Paleoclimatological Studies On South Asian Monsoon Using CCM2 GCM. Intromet, IIT Delhi, 2-5 December 1997.

8. Rajendran K , R S Nanjundiah, and J. Srinivasan, 1997. Impact of Surface Hydrology on Monsoon Simulation. VIIth Asian Conference of Fluid Mechanics, December 8-12, 1997, Madras, India

7. Raju A and R S Nanjundiah, 1997: Development of a Parallel Climate Version of the NCMRWF T-80 Model. Tropmet '97, Bangalore, India, 10-14 February 1997.

6. Nanjundiah R S, K Rajendran, and J Srinivasan, 1997: Impact of Orography on the Simulation of Asian Summer Monsoon Rainfall in NCAR CCM2 GCM. Workshop on Monsoon Studies (IWM-I), Bali, Indonesia, 24-28 February 1997.

5. Asha G, K Rajendran and R S Nanjundiah, 1997: Intraseasonal Variations of the Asian Monsooon: CCM2 Simulations. Tropmet '97, Bangalore, India, 10-14 February 1997.

4. Sinha U N and R S Nanjundiah 1996 : A Decade of Parallel Meteorological Computing on Flosolver. In 7^th Symposium of Use of MPPs for Weather Forecasting, ECMWF, Reading December 3-4 1996. (50%)

3. Michalakes J, T Can eld, R S Nanjundiah and S Hammond : MPMM A Massively Parallel Meso-Scale Model for Weather Forecasting. In 5^th Symposium on Use of MPPs for Weather Forecasting, ECMWF, Reading. Nov 1994.

2. Nanjundiah R S, J Srinivasan and S Gadgil,1992: E ect of Cumulus Parameterization on Modelling the Intraseasonal Variation of Tropical Convergence Zones. In Physical Proceses in Atmospheric Models". Ed: D R Sikka and S S Singh. Pp: 480-491. Wiley Eastern Limited New Delhi.

1. Nanjundiah R S, 1989: Monsoon Simulation on Flosolver. Second Indo-Soviet Symposium on Me-chanics, NAL, Bangalore, February 1989.

Reports

15. Deshpande M., Johny C.J., Kanase R., Tirkey S., Sarkar S., Goswami T., Roy Kumar, Ganai M., Krishna R.P.M., Prasad V.S., Mukhopadhyay P., Durai V.R., Nanjundiah R.S., Rajeevan M., Implementation of Global Ensemble Forecast System (GEFS) at 12km Resolution, August, 2020, ISSN 0252-1075, IITM Technical Report No.TR-06, ESSO/IITM/MM/TR/02(2020)/200

14. Jena C., Ghude S., Kumar R., Debnath S., Soni V.K., Nanjundiah R.S., Rajeevan M., 2020, High-resolution (400 m) operational air quality early warning system for Delhi, India, IGAC News, 66, 25-26

13. Venkatesh T N, J Mathew and R S Nanjundiah, 2011: Exploring a Mechanism for Severe Clear Air Turbulence. Fluid Mechanics report-2011-FM2, Dept of Aerospace Engineering, IISC, Bangalore.

12. Nanjundiah R S, 2009: A Quick Assessment of Forecasts for the Indian Summer Monsoon Rainfall in 2009. CAOS Report No 2009 AS 02, CAOS, IISc, Bangalore.

11. Vivek S and R S Nanjundiah, 2009: Forecasting Indian Summer Monsoon using support vector machine approach. CAOS Report No. 2009 AS 01.

10. Sundari M S , V S Sathish and R S Nanjundiah: Loadbalancing of longwave calculations in CCSM. CAOS Report No. 2007 AS 01.

9. Shanker A P , and R S Nanjundiah, 2003: Two-Dimensional Morlet Wavelet Analysis of Atmo-spheric Data. CAOS Report No. 2003 AS 01

8. Venkatesh T N, and R S Nanjundiah, 1999: Cyclone Track Prediction: International Status. NAL Report PDFS9919. Flosolver Unit, National Aerospace Laboratory.

7. Nanjundiah R S, and V S Semeena , 1998: Behaviour of Atmospheric Anamolies During May over Asia-Paci c Region. CAOS (IISc) Report 98AS8.

6. Nanjundiah R S, A Raju and U N Sinha, 1996: Implementation of the T-80 NCMRWF Model on Power2 Architecture. Part III: Validation of Sequential and Parallel Implementation. CAOS (IISc) Report 96AS3.

5. Nanjundiah R S, A Raju and U N Sinha, 1996: Implementation of the T-80 NCMRWF Model on Power2 Architecture. Part II: Coarse Grain Parallel Implementation. CAOS (IISc) Report 96AS2.

4. Nanjundiah R S, A Raju and U N Sinha, 1996: Implementation of the T-80 NCMRWF Model on Power2 Architecture. Part I: Sequential Implementation. CAOS (IISc) Report 96AS2.

3. Michalakes J and R S Nanjundiah, 1994: Computational Load in Model Physics of the parallel NCAR Community Climate Model. ANL/MCS-TM-186, February 1994.

2. Nanjundiah R S and U N Sinha, 1992: Implementation of A Three-Dimensional Global Climate Model on Flosolver Mk3 Parallel Computer. CAS (Indian Institute of Science) Report No. 92-AS-3.

1. Nanjundiah R S, 1988: Simulation of Monsoon on Flosolver. NAL Report PDAE8803. National Aeronautical Laboratory, Bangalore, India February 1988.

*****

Guidance of students

Degree	No of Students Graduated	Currently Guiding
Ph D.	8	7
M.Sc. (Engg)	4	0
M.Tech	8	1

आईआईटीएम
IITM

भारतीय उष्णदेशीय मौसम विज्ञान संस्थान
Indian Institute of Tropical Meteorology

Scientist Profile

Prof. Ravi Shankar Nanjundiah

Designation

: Retired Scientist

Phone

:

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:

Email ID

: ravisn[at]tropmet[dot]res[dot]in

Area of Expertise

Academic Records

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Scientific Careers

Research Highlight

Scientist Profile

Prof. Ravi Shankar Nanjundiah

Designation : Retired Scientist

Phone :

Fax :

Email ID : ravisn[at]tropmet[dot]res[dot]in

Area of Expertise

Academic Records

Research

Awards & Honors

Scientific Careers

Research Highlight

Designation

: Retired Scientist

Phone

:

Fax

:

Email ID

: ravisn[at]tropmet[dot]res[dot]in