The Forced Trends in the Tropical Pacific and Global Tropical Cyclones in Earth System Models

Lead PI: Chia-Ying Lee , Prof. Adam Sobel , Dr. Suzana J. Camargo , Seager, Richard; Reed, Kevin; Fosu, Boniface; Wehner, Michael

Unit Affiliation: Ocean and Climate Physics, Lamont-Doherty Earth Observatory (LDEO)

September 2022 - August 2025
Active
North America ; United States
Project Type: Research

DESCRIPTION: This project studies the forced trend in global TC and how it is influenced by forced trends in the tropical Pacific sea surface temperature (SST) field using DOE’s Energy Exascale Earth System Model (E3SM). In recent years we have learned that TCs are becoming more disastrous as Earth’s climate warms, with stronger intensity, more rain, and more widespread storm surge. However, we know little about some other respects of TC activity, even in sign (e.g., TC frequency). One limiting factor is the uncertainties in the tropical Pacific zonal SST gradient, characterized by the western Pacific warm pool and eastern Pacific cold tongue. This SST gradient strongly influences global TC activity, as is apparent on the interannual time scale in the responses of TCs to the El Niño-Southern Oscillation (ENSO). Many Earth System Models (ESMs) project this gradient to weaken in response to anthropogenic forcing, leading to a more El Niño-like future climate. Observations, in contrast, show a strengthening of the zonal SST gradient, leading to a more La Niña climate, over the past several decades. While it is possible that the observed trend is due to natural variability, recent research provides compelling evidence suggesting that the projected El Niño-like future in models is erroneous, and a consequence of the climatological cold tongue bias in the models. This cold tongue bias and the weakening trend in the SST gradient persist in the latest generations of ESMs, including the E3SM, and are likely to affect E3SM’s TC projections, especially in the near-term future.

Using DOE’s E3SM, this project aims to understand the physical processes through which this cold tongue bias influences simulated global TC activity projection, quantify this influence, and develop novel projections, based on appropriate bias corrections, that are more consistent with recent historical observations. Specifically, we design a suite of E3SM experiments with and without the cold tongue bias through flux adjustment. Global TC activity in these simulations will be examined using directly-simulated TC from additional high-resolution simulations and synthetic TCs downscaled from the Columbia HAZard TC model (CHAZ). The robustness of the findings will be assessed by examining the climate and TCs simulations from existing climate projections as well as numerical experiments leveraged from proposal team members’ ongoing projects.

TCs can cause severe damage to the energy sectors and other infrastructures in regions exposed to them while their precipitation is an important element of the Earth’s water cycle. How TC activity evolves with climate is thus directly related to DOE’s overall science goals as well as those of the E3SM in particular. Furthermore, as tropical Pacific SST is a pacemaker of the rate of global warming, the proposed project also has important implications for climate change more broadly, beyond TCs. Through collaboration with the E3SM team, our findings will inform future model development efforts.

SPONSOR:

Department of Energy

FUNDED AMOUNT:

$897,789

RESEARCH TEAM:

Haibo Liu, Gus Correa

EXTERNAL COLLABORATORS:

Mississippi State University, Stony Brook, Lawrence Livermore National Lab

WEBSITE:

https://climatemodeling.science.energy.gov/projects/forced-trends-tropical-pacific-and-global-tropical-cyclones-earth-system-models

PUBLICATIONS:

Sobel, Adam H., Chia-Ying Lee, Steven G. Bowen, Suzana J. Camargo, Mark A. Cane, Amy Clement, Boniface Fosu, et al. 2023. “Near-Term Tropical Cyclone Risk And Coupled Earth System Model Biases”. Proceedings Of The National Academy Of Sciences 120 (33). DOI:10.1073/pnas.2209631120.

KEYWORDS

natural disaster climate modeling