Valentine Anantharaj is a Computational Climate Scientist with the Scientific Computing Group in the National Center for Computational Sciences (NCCS). Prior to joining ORNL, he was an Associate Research Professor at the Geosystems Research Institute (GRI) as well as Adjunct Faculty with the Department of Electrical and Computer Engineering in Mississippi State University. He holds a PhD in Computational Engineering, an MS in Meteorology, and BS in Physics. Valentine was a NASA Enterprise for Innovating Geospatial Solutions Graduate Fellow for two years during his graduate studies. Prior to his tenure at GRI, he started his scientific career as an Associate Scientist at the former Institute for Naval Oceanography, managed by University Corporation for Atmospheric Research.
Valentine has broad professional experience in the areas of scientific data management, machine learning applications of climate data, software engineering and applications development for operational implementation, decision support frameworks, integration of remote sensing data in numerical models, satellite precipitation estimation, and regional climate modeling. His recent research interests include land surface hydrology, land-atmosphere interactions, and characterization of uncertainties in global climate models, particularly shortwave radiation. Valentine’s focus is on advancing the leadership scale climate modeling activities at NCCS as well as the core competencies within CCSI.
R&D Activities Contributions
Big PanDA Workflow Management on Titan for High Energy and Nuclear Physics and for Future Extreme Scale Scientific Applications - This project will provide an important model for future exascale computing, increasing the coherence between the technology base used for high-performance computing and that used…
2008 - Takur, A., R. Vaughn, and V. Anantharaj, 2008: On the same page: Building stakeholder consensus. Design Principles and Practices. 2(1): 39-48.
2008 - Mostovoy, G. V., V. Anantharaj, R. L. King, and M. L. Filipova, 2008: Interpretation of the relationship between skin temperature and vegetation fraction: Effect of subpixel soil temperature variability. International Journal of Remote Sensing. 29(10), 2819-2831. DOI: 10.1080/01431160701395286
2008 - Mostovoy, G. V., and V. G. Anantharaj, 2008: Observed and simulated soil moisture variability over the Lower Mississippi Delta Region. Journal of Hydrometeorology. 9(6): 1125-1150. DOI: 10.1175/2008JHM999.1
2010 - Yilmaz, T., P. Houser, R. Shrestha, and V. Anantharaj, 2010: Optimally Merging Precipitation to minimize Land Surface Modeling Errors. Journal of Applied Meteorology and Climatology. DOI: 10.1175/2009JAMC2305.1
2010 - Turlapaty, A.C., V.G. Anantharaj, N.H. Younan, and F.J. Turk, 2010: Precipitation data fusion using vector space transformation and artificial neural networks. Pattern Recognition Letters. 31: 1184-1200. DOI: 10.1016/j.patrec.2009.12.033
2010 - Turlapaty, A.C., N.H. Younan, and V.G. Anantharaj, 2010: A pattern recognition based approach to consistency analysis of geophysical datasets. Computers and Geosciences. 36(4): 464-476. DOI: 10.1016/j.cageo.2009.10.002
2010 - Turk, F.J, G. Mostovoy and V. Anantharaj, 2010: The NRL-Blend High Resolution Precipitation Product and its Application to Land Surface Hydrology. Satellite Application for Surface Hydrology (F. Hossain and M. Gebremichael, Editors). Springer Verlag.
2010 - Turk, F.J., G.V. Mostovoy and V.G. Anantharaj, 2010: Soil Moisture Sensitivity to NRL-Blend High Resolution Precipitation Products: Analysis of Simulations With Two Land Surface Models. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS). 3: 32-48. DOI: 10.1109/JSTARS.2009.2034024
2010 - Anantharaj, V.G., U.S. Nair, P. Lawrence, T.N. Chase, S. Christopher, and T. Jones, 2010: Comparison of satellite-derived TOA shortwave fluxes to estimates from GCM simulations constrained by satellite observations of land surface characteristics. International Journal of Climatology. DOI: 10.1002/joc.2107
2011 - Shrestha, R., P.R. Houser, and V.G. Anantharaj, 2011: An optimal merging technique for high-resolution precipitation products. Journal of Advances in Modeling Earth Systems. 3(4), M12003. DOI:10.1029/2011MS000062.
2012 - Norman, M., J. Larkin, R.K. Archibald, I. Carpenter, V.G. Anantharaj, P. Micikevicius, and K.J. Evans, 2012: Porting the Community Atmosphere Model - Spectral Element Code to Utilize GPU Accelerators. International Journal of Cray User’s Group. [Best Paper Finalist]
2012 - Mahrooghy, M., N.H. Younan, V.G. Anantharaj, J. Aanstoos, and S. Yarahmadian, 2012: On The Use of a Cluster Ensemble Cloud Classification Technique in Satellite Precipitation Estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. DOI: 10.1109/JSTARS.2012.2201449
2012 - Mahrooghy, M., V.G. Anantharaj, N.H. Younan, J. Aanstoos, and K-L Hsu, 2012: On an Enhanced PERSIANN-CCS Algorithm for Precipitation Estimation, Journal of Atmospheric and Oceanic Technology. 29(7): 922-932. DOI:10.1175/JTECH-D-11-00146.1.
2012 - Mahrooghy, M., N.H. Younan, V.G. Anantharaj, J. Aanstoos, and S. Yarahmadian, 2012: On the Use of the Genetic Algorithm Filter-Based Feature Selection technique for Satellite Precipitation Estimation, IEEE Geoscience and Remote Sensing Letters. 9(5): 963-967.
2012 - Mahrooghy, M., N.H. Younan, and V.G. Anantharaj, and James Aanstoos, 2012: Enhancement of Satellite Precipitation Estimate via Unsupervised Dimensionality Reduction. IEEE Transactions on Geoscience and Remote Sensing, 50(10): 3931-3940. DOI: 10.1109/TGRS.2012.2189406.
2013 - Luo, Y., X. Feng, P.R. Houser, V.G. Anantharaj, X. Fan, G.D. Lannoy, X. Zhan, and L. Dabbiru, 2013: Potential Soil Moisture Products from the Aquarius Radiometer and Scatterometer Using an Observing System Simulation Experiment. Geoscientific Instrumentation, Methods and Data Systems. Copernicus Publications. 2: 113-120. DOI:10.5194/gi-2-113-2013.
2013 - Anantharaj, V.G., F.S. Foertter, W. Joubert, and J.C. Wells, 2013: Approaching Exascale: Application Requirements for OLCF Leadership Computing. Oak Ridge National Laboratory.