Robert Nystrom

Introduction

I am currently a Project Scientist I at the National Center for Atmospheric Research (NCAR), following an Advanced Study Program (ASP) Postdoctoral Fellowship. Before arriving at NCAR I received my PhD in Meteorology and Atmospheric Science from Penn State University (#WeAre) and my BS in Atmospheric Science from the University of Illinois at Urbana-Champaign (#ILL). 

My research interests lie at the intersection of Earth system predictability, extreme weather events, numerical weather prediction, data assimilation, and atmospheric dynamics. My work has specifically focused on improving the predictability of extreme weather events, such as tropical cyclones, and understanding their dynamics through the use of ensemble data assimilation and ensemble forecasts. I am also actively working to better understand the air-sea interactions which fuel hurricanes and better represent these physical processes in numerical models.

When I am not working hard on my research, I enjoy participating in community outreach activities to educate the public and students on a variety of topics in meteorology. 

Research Directions

My overarching research goal is to better understand Earth system predictability and improve predictions of TCs and extreme weather events across timescales.

   

One focus of my research has been understanding the practical and intrinsic predictability of tropical cyclones (TCs) using high resolution numerical weather prediction (NWP) models, a crucial first step toward improving predictions. I am also actively working to establish how uncertainty in the model representation of TC air-sea interactions limit TC predictability. 

With increased resolution of global NWP models (e.g., top left), opportunities for subseasonal-to-seasonal predictions of TCs and extreme weather events are on the horizon. In addition to the potentially high reward of subseasonal TC predictions, this research direction has the potential to also bridge the gap between high impact weather events and climate by improving our understanding of subseasonal drivers of TC activity.   


DA is a powerful tool routinely used to provide initial conditions for NWP models. Improvements in DA methodologies and new observations can have significant positive influences on predictions of high impact weather events. My research focuses on using to novel observations, such as those from satellites and radars, to improve predictions of extreme weather events. 

In addition, DA can also be used to estimate unknown model physics. On this front, I have been actively working to develop methods to estimate unknown model physics related to the air-sea momentum and enthalpy fluxes under high winds, a longstanding issue in TC prediction.

In the future I am excited to explore questions such how coupled data assimilation can improve subseasonal TC predictability and bridge the current weather-climate gap. 

About Me

My Journey:

Born on π-day in the western suburbs of Chicago, an initial fear of severe weather quickly transitioned into a fascination, and I was hooked. Since then, I've had the opportunity to chase supercell thunderstorms throughout the Great Plains, travel to the Arctic, lecture abroad, and even fly through Hurricane Arthur (2010). I am lucky to be living out my childhood dreams and I look forward to seeing where my passion for atmospheric science takes me next.  

In my free time you are likely to find me outside either golfing, running, hiking, or skiing–a new hobby I've enjoyed the past few years while working and living near the Rockies. I also enjoy cooking (ask me about my Quiche Lorraine recipe), photography, cheering on my favorite sports teams, and will never turn down a locally brewed stout or IPA. 

Additional information:

Google Scholar Profile

|Curriculum Vitale|

Robert_Nystrom_CV_web.pdf

Publications

Nystrom, R. G., C. Snyder, and M. Gharamti, 2023: An Ensemble Kalman Smoother Approach Toward Estimating the Tropical Cyclone Surface-Exchange Coefficients. Mon. Wea. Rev., https://doi.org/10.1175/MWR-D-22-0147.1.

Nystrom, R. G. and F. Judt, 2022: The consequences of surface-exchange coefficient uncertainty on an otherwise highly predictable major hurricane. Mon. Wea. Rev., 150, 2073–2089, https://doi.org/10.1175/MWR-D-21-0320.1.

Q. Zhao, N. L. Baker, Y. Jin, and R. G. Nystrom, 2021: Scale Analysis of Infrared Water Vapor Brightness Temperatures for Tropical Cyclone All-Sky Radiance Assimilation. Geophys. Res. Lett., 48, e2021GL095458, https://doi.org/10.1029/2021GL095458.

 

Zhang, Y., S. B. Sieron, Y. Liu, X. C. Chen, R. G. Nystrom, M. Minamide, M.-Y. Chan, C. Hartman, Z. Yao, J. H. Ruppert, A. Okazaki, S. J. Greybush, E. E. Clothiaux, and F. Zhang, 2021: Ensemble-Based Assimilation of Satellite All-Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017). Geophys. Res. Lett., 48, e2021GL096419, https://doi.org/10.1029/2021GL096410. 

Nystrom, R. G., S. J. Greybush, X. Chen, and F. Zhang, 2021: Potential for new constraints on tropical cyclone surface-exchange coefficients through simultaneous ensemble-based state and parameter estimation, Mon. Wea. Rev., 149, 2213–2230, https://doi.org/10.1175/MWR-D-20-0259.1.

 

Chen, X., R. G. Nystrom, C. A. Davis, C. Zarzycki, 2021: Dynamical Structures of Cross-Domain Forecast Error Covariance of a Simulated Tropical Cyclone Using a Convection-Permitting Coupled Atmosphere-Ocean Ensemble, Mon. Wea. Rev., 149, 41–63, https://doi-org./10.1175/MWR-D-20-0116.1.

 

Yu, C.-L., A. C. Didlake Jr., F. Zhang, and R. G. Nystrom, 2021: Asymmetric Rainband Processes Leading to Secondary Eyewall Formation in a Model Simulation of Hurricane Matthew (2016), J. Atmos. Sci., 78, 29–49, https://doi-org/10.1175/JAS-D-20-0061.1.

 

Nystrom, R. G., R. Rotunno, C. A. Davis, and F. Zhang, 2020: Consistent impacts of surface enthalpy and drag coefficient uncertainty between an analytical model and simulated tropical cyclone maximum intensity and storm structure. J. Atmos. Sci., 77, 3059–3080, https://doi.org/10.1175/JAS-D-19-0357.1.

 

Nystrom, R. G., X. Chen, F. Zhang, and C. A. Davis, 2020: Nonlinear Impacts of Surface Exchange Coefficient Uncertainty on Tropical Cyclone Air-Sea Interactions and Intensification. Geophys. Res. Lett., https://doi.org/10.1029/2019GL085783.

 

Nystrom, R. G. and F. Zhang, 2019: Practical Uncertainties and Underlying Dynamics in the Limited Predictability of the Record-Breaking Intensification of Hurricane Patricia (2015). Mon. Wea. Rev., 147, 3535–3556, https://doi.org/10.1175/MWR-D-18-0450.1.

 

Zhang F., M. Minamide, R. G. Nystrom, X. Chen, S.-J. Lin, and L. M. Harris, 2019: Improving Harvey forecasts with next-generation weather satellites. Bull. Amer. Meteor. Soc., 100, 1217–1222, https://doi.org/10.1175/BAMS-D-18-0149.1.

 

Tao. D., K. A. Emanuel, F. Zhang, R. Rotunno, M. M. Bell, and R. G. Nystrom, 2019: Evaluation of the assumptions in the steady-state tropical cyclone self-stratified outflow using three-dimensional convection-allowing simulations. J. Atmos. Sci., 76, 2995–3009, https://doi.org/10.1175/JAS-D-19-0033.1.

 

Nystrom, R. G., F. Zhang, E. B. Munsell, S. A. Braun, J. A. Sippel, Y. Weng, and K. A. Emanuel, 2018: Predictability and dynamics of Hurricane Joaquin (2015) explored through convection-permitting ensemble sensitivity experiments. J. Atmos. Sci., 75, 401–424, https://doi.org/10.1175/JAS-D-17-0137.1.


Contact Info

Email: nystrom [at] ucar [dot] edu

LinkedIn: https://www.linkedin.com/in/robert-nystrom-56138a7a/