Biography
Dr. Sujan Pal is a hydroclimatologist in the Environmental Science Division at Argonne National Laboratory. His research interests include investigating hydrometeorology, hydroclimatology and land-atmosphere interactions leveraging numerical modeling and field experiments. He monitors continuous measurements of surface fluxes (moisture, energy, CO2 and CH4) and near-surface soil moisture at the Argonne Testbed for Multiscale Observational Science (ATMOS). The overarching goal is to better understand the weather-climate extremes and heterogeneity at different spatio-temporal scales.
Dr. Pal is currently leading the high-resolution neighborhood scale inland flood modeling using WRF and WRF-Hydro for a project supported by AT&T on climate, risk, and resilience. He is also a Co-PI of US DOE funded Community Research on Climate and Urban Science (CROCUS) project which aims to study the impacts of urban climate change in Chicago area leveraging high-quality observations and modeling.
Education:
Ph.D. (2017 - 2021) University of Illinois at Urbana-Champaign, USA
M.S (2015 - 2017) The University of Arizona, Tucson, USA
B.E (2010 - 2014) Jadavpur University, Kolkata, India
Honors and Awards:
2023: Argonne IMPACT Award for Enhancing Argonne’s Reputation
2022: Argonne IMPACT Award for Extraordinary Effort.
Associate Editor: Frontiers in Water: Spatiotemporal Modelling and Assessment of Water-related Multi-hazards
Publications:
Pal, S., Wang, J., Feinstein J., Yan E., Kotamarthi, V. R., 2023. Projected changes in extreme streamflow and inland flooding in the mid-21st century over Northeastern United States using ensemble WRF-Hydro simulations, Journal of Hydrology: Regional Studies, 47, 101371, https://doi.org/10.1016/j.ejrh.2023.101371
Pal, Sujan, Dominguez, Francina, Bollatti, Pablo, Oncley, Steven P., Yang, Yi, Alvarez, Javier, and Garcia, Carlos M., 2021. Investigating the Effects of Land Use Change on Subsurface, Surface, and Atmospheric Branches of the Hydrologic Cycle in Central Argentina , Water Resources Research, Vol. 57, No. 11, 1944-7973 https://doi.org/10.1029/2021WR029704
Pal, Sujan and Sharma, Prateek, 2021. A Review of Machine Learning Applications in Land Surface Modeling, Earth, Vol. 2, No. 1, pp 174, 2673-4834 https://doi.org/10.3390/earth2010011
Pal, S., Dominguez, F., Dillon, M. E., Alvarez, J., Garcia, C. M., Nesbitt, S. W., & Gochis, D., 2021. Hydrometeorological observations and modeling of an extreme rainfall event using WRF and WRF-Hydro during the RELAMPAGO field campaign in Argentina, Journal of Hydrometeorology, 22(2), 331–351. https://doi.org/10.1175/JHM-D-20-0133.1
Pal, S., H.-I. Chang, C. L. Castro, and F. Dominguez, 2019. Credibility of convection-permitting modeling to improve seasonal precipitation forecasting in the southwestern United States. Front Earth Sci., 7, 11, https://doi.org/10.3389/feart.2019.00011