Bithi De

Climate Dynamics

Climate Change, Large-scale atmospheric dynamics, Clouds and Radiation, Arctic sea ice loss, Troposphere-Stratosphere interaction

GISS perturbed parameter ensemble (PPE) project

Atmospheric Dynamics

• I am currently leveraging GISS E2.1 perturbed parameter ensemble (PPE) as a testbed to determine to what extent large-scale dynamical variability is explained by physics settings in clouds and convection parameterizations. PPE members are characterized by a different parameter setting in the clouds or convection parameterization (with a second setting modified to re-balance the members radiation). This unique approach, given the same dynamical core and parameterizations, allows us to learn to what extent jet location is a parameter problem.

De, B., G. Elsaesser, A. N. LeGrande and K. Grise (2024) Leveraging a radiatively-balanced climate model PPE to better understand how cloud and convective processes affect the southern hemisphere jet stream location (to be submitted soon)

• I contributed to a collaborative project that leverages machine learning techniques to generate a calibrated physics ensemble for the GISS model. My tasks included identifying optimal simulation periods for dynamical variables.

Elsaesser, G, M. van Lier-Walqui, Q. Yang, M. Kelley, A. S. Ackerman, A. M. Fridlind, G. V. Cesana, G. A. Schmidt, J. Wu, A. Behrangi, S. J. Camargo, B. De, K. Inoue, N. Leitmann-Niimi, J D. O. Strong (2024): Using Machine Learning to Generate a Calibrated Physics Ensemble for GISS Model E3 (to be submitted soon)

Cloud-dynamical interactions

• We examined the influence of the climate models' present-day atmospheric circulation climatologies, and the accompanying climatological cloud radiative effects, in explaining the inter-model spread in response of global-mean surface temperature to increased CO2 (known as the "Equilibrium Climate Sensitivity", or "ECS").

-B. De, G. Tselioudis and L.M. Polvani, 2022: Improved representation of atmospheric dynamics in CMIP6 models removes climate sensitivity dependence on Hadley Cell climatological extent, Atmos. Sci. Lett, doi:10.1002/asl.1073 (https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/asl.1073)

• The accuracy in how the models show cloud-dynamical changes are crucial as it can help us to understand how global climate change affects regional and global temperature patterns. We explored influence of cloud radiative properties on the positioning of the Southern Hemisphere’s midlatitude jet utilizing CMIP6 models.

-L.M. Polvani, B. De, K. Grise and G. Tselioudis, 2024: Little evidence of a causal link between shortwave cloud radiative effects and the latitude of the Southern Hemisphere jet in the CMIP6 Models, 2024 (to be submitted soon)

Arctic-midlatitude interactions

I investigated the impact of Arctic Sea ice loss on atmospheric circulation and extreme winter weather across Europe and North America. Through the study lens of troposphere-stratosphere coupling, we found that regional sea ice anomalies can influence inter-annual variations in regional circulation and weather patterns, ultimately enhancing winter weather predictions. The findings are published as below:

1. Zhang et al. 2018 https://www.science.org/doi/10.1126/sciadv.aat6025
2. De et al. 2020 https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020GL088057#
3. De and Wu 2019 https://link.springer.com/article/10.1007/s00382-018-4576-6

I co-mentored a student intern (spring and summer 2021) to investigate the combined influence of Arctic warming and ENSO on the potential changes in atmospheric circulation in association with persistent extreme temperature/precipitation events across Northern Hemisphere winter. Details can be found https://stemgateway.nasa.gov/s/course-offering/a0Bt0000004lAnnEAE/arcticel-ni%C3%B1o-teleconnection-its-impacts-on-extreme-weather-events-virtual

AGU

member

2014 - Present

EGU

2022 - Present