Scientist Profile

Mrs. Shikha Singh

Designation
: Scientist C

Phone
:  +91 94222 72531

Fax
: 

Email ID
: shikha[dot]cat[at]tropmet[dot]res[dot]in

Ocean Modeling
Degree University Year Stream
Ph.D. Indian Institute of Technology, Mumbai 2016 IDP in Climate Studies
Induction Training Indian Institute of Tropical Meteorology, Pune, India 2013 Atmosphere and Ocean Science
B.Tech. Motilal Nehru National Institute of Technology, Allahabad 2012 Chemical Engineering

 Understanding the role of subsurface biases in coupled models

 Mixing parameterizations in the ocean models

 Numerical modelling of oceans

 Turbulence modeling

Award Name Awarded By Awarded For Year
Fulbright Kalam Doctoral Fellowship The J. William Fulbright Foreign Scholarships Board (FSB), Washington D.C., U.S.A. and Department of Science & Technology, Ministry of Science & Technology, Government of India Excellence in scientific research 2019-20
AGU Travel Grant American Geophysical Union To attend AGU Fall Meeting 2019 2019
Best Poster Award National Oceanography Workshop, INCOIS, Hyderabad, India Best Poster presentation 2018
Best Poster Award National Science Conference, Indian Institute of Science, Bengaluru, India Best Poster presentation 2015
Best Project Award Centre for Advanced Training, IITM, Pune, India Best dissertation 2013
Merit Scholarship Award Motilal Nehru National Institute of Technology, Allahabad Best performing student of the year 2009-2012
Year Designation Institute
2019-Present Fulbright Scholar (Visiting Researcher) University of Massachusetts, Dartmouth, USA
2018-2019 Scientist C Indian Institute of Tropical Meteorology, Pune
2014-2017 Scientist B Indian Institute of Tropical Meteorology, Pune
2012-2013 Trainee Scientist Indian Institute of Tropical Meteorology, Pune
2011- Outreach Student Indian Institute of Science, Bengaluru, India

Research Highlight


Possible impact of subsurface biases in coupled models

The CMIP-5 models develop internal warm and saline biases between a depth range of ~100 and ~800m in long term simulations. These internal biases are found to have implications in large scale ocean dynamics via their linkage through baroclinicity of the ocean. The role of internal biases in the ensuing dynamics is quantified via relations between Brunt Vaisala frequency (N2) and baroclinic wave speeds using both Sturm-Loiuville theorem and WKBJ approximation. The CMIP-5 models are found to have a higher baroclinic speed compared to that of observations (figure). The study suggests that faster wave propagation in climate models due to subsurface biases has potential to change lifecycle and periodicity of simulated planetary scale events. A corollary being a cautionary outlook on climate projections made by coupled models as long as the biases are persistent.

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