Sciences and Exploration Directorate

Priyanka Yadav

(Assistant Research Scientist)

Priyanka Yadav's Contact Card & Information.
Email: priyanka.yadav@nasa.gov
Org Code: 610.1
Address:
NASA/GSFC
Mail Code 610.1
Greenbelt, MD 20771
Employer: UNIV OF MARYLAND COLLEGE PARK

Brief Bio


Priyanka Yadav is an Assistant Research Scientist with the University of Maryland Earth System Science Interdisciplinary Center and the Global Modeling and Assimilation Office at NASA Goddard Space Flight Center.

She is currently working on seamless prediction and predictability from weather to subseasonal, and that from subseasonal to seasonal timescales. Her research focuses on improving predictability on subseasonal to seasonal (S2S) timescales using reanalysis datasets, climate models, and advanced statistical techniques.


Priyanka successfully demonstrated that the phase speed of the MJO controls the strength and duration of the tropospheric and stratospheric pathway in MJO teleconnections. In addition, she has contributed to various national and international research community projects. Her scientific contributions span across a wide range of research projects, including studying the dynamical predictability due to teleconnections arising from fast and slow MJO episodes via tropospheric and stratospheric pathways, stratosphere-troposphere coupling in S2S models, the North American monsoon, the South Asian monsoon and its links to the ENSO and IOD, air pollutant dispersion modeling, and studying the stratospheric ozone depletion using TOMS data.

Research Interests


Seamless predictability and prediction from weather to subseasonal lead times and that from subseasonal to seasonal lead times.

Earth Science: Analysis


Subseasonal-to-seasonal (S2S) tropical variability and its remote impacts.

Earth Science: Seasonal Dynamics

The modes of tropical variability (e.g. Madden-Julian Oscillation (MJO), Indian Ocean Dipole (IOD), and ENSO) can influence the global weather across different timescales via tropospheric and stratospheric teleconnection pathways. These tropical modes are the sources of subseasonal predictability of midlatitude weather regimes such as the North Atlantic Oscillation (NAO), Pacific North American Pattern (PNA), weather regimes (Scandinavian Blocking, Atlantic ridge, Pacific Blocking).


South Asian monsoon, The North and South American monsoon systems.

Earth Science: Atmospheric Dynamics

Current Projects


Seamless Prediction and Predictability across weather-seasonal timescales.

Positions/Employment


Assistant Research Scientist

University of Maryland (ESSIC) - Maryland

2023 - Present

Teaching Experience


Teaching Assistant, Introduction to the Fundamentals of Atmospheric Sciences, George Mason University.

Education


Ph.D., George Mason University, Department of Atmospheric, Oceanic & Earth Sciences, USA

Dissertation: The character of the mid-latitude response to the fast and slow cycles of the Madden-Julian Oscillation heating.

M.Tech., Atmospheric Sciences, University of Pune, India

Thesis: Effects of meteorological inputs on air pollutant dispersion modeling over Pune City using AERMOD model.

M.Sc., Space Sciences, University of Pune, India

Thesis: Satellite Data Analysis of Stratospheric Ozone using TOMS data

B.Sc., Electronics, India

Professional Societies


American Meteorological Society

2018 - Present


American Geophysical Union

2019 - Present

Other Professional Information


Google Scholar

ORCID: 0000-0003-0277-8142

Web of Science ResearcherID: N-4272-2019

Publications


Refereed

2024. "The Role of the Stratosphere in Teleconnections Arising From Fast and Slow MJO Episodes." Geophysical Research Letters 51 (1): [10.1029/2023gl104826] [Journal Article/Letter]

2023. "Intrinsic Predictability Limits arising from Indian Ocean MJO Heating: Effects on tropical and extratropical teleconnections." Weather and Climate Dynamics 4 1001-1018 [10.5194/wcd-4-1001-2023] [Journal Article/Letter]

2022. "The Winter North Pacific Teleconnection in Response to ENSO and the MJO in Operational Subseasonal Forecasting Models Is Too Weak." Journal of Climate 35 (24): 8013-8030 [10.1175/jcli-d-22-0179.1] [Journal Article/Letter]

2022. "Stationary wave biases and their effect on upward troposphere– stratosphere coupling in sub-seasonal prediction models." Weather and Climate Dynamics 3 (2): 679-692 [10.5194/wcd-3-679-2022] [Journal Article/Letter]

2022. "Advances in the prediction of MJO-Teleconnections in the S2S forecast systems." Bulletin of the American Meteorological Society 103 (6): E1426-E1447 [https://doi.org/10.1175/BAMS-D-21-0130.1] [Journal Article/Letter]

2019. "The Euro-Atlantic Circulation Response to the Madden-Julian Oscillation Cycle of Tropical Heating: Coupled GCM Intervention Experiments." Atmosphere-Ocean 57 (3): 161-181 [10.1080/07055900.2019.1626214] [Journal Article/Letter]

2018. "Systematic Errors in Weather and Climate Models: Nature, Origins, and Ways Forward." Bulletin of the American Meteorological Society 99 (4): ES67-ES70 [10.1175/bams-d-17-0287.1] [Journal Article/Letter]

2017. "Circulation Response to Fast and Slow MJO Episodes." Monthly Weather Review 145 (5): 1577-1596 [10.1175/mwr-d-16-0352.1] [Journal Article/Letter]