Understanding Bulk Surface Flux Algorithm Contributions to Climate Projection Uncertainties

Modern Earth System models (ESMs) utilize a variety of bulk surface flux algorithms to compute the transfer of heat, water, and momentum across the air-sea interface. When compared to direct covariance flux measurements from research ships, fluxes estimated from many bulk algorithms are biased by about 10%-20%, with the majority of algorithms overestimating the flux. Surface flux biases lead to erroneous exchanges of energy between the ocean and atmosphere. For the ocean, flux biases can contribute to biases in circulations and sea surface temperature (SST). In the atmosphere, flux biases can affect the frequency, intensity, and vertical structure of convection, its radiative feedbacks, and the large-scale circulation response to its heating. The surface flux bias of a given model will imprint onto its estimated equilibrium climate sensitivity (ECS) through the the response of ocean circulations and cloud properties to the flux bias. The COARE3.5 bulk flux algorithm is the most recent version of the COARE bulk flux algorithm, originally developed in 1992 as part of the TOGA COARE field campaign. Its predecessor, the COARE3.0 algorithm, has been shown to produce some of the smallest flux biases when compared to other bulk algorithms; it is the basis for nearly all modern satellite-derived surface flux products. In this study, we will investigate surface flux feedbacks in observations, and leverage the COARE3.5 bulk flux algorithm to assess biases in surface fluxes and their feedbacks for models participating in CMIP6. Our work plan will:
1. Demonstrate flux algorithm diversity in CMIP6 models through average fluxes
conditionally sampled by wind speed and near-surface vertical humidity gradients. Estimate
model-dependent surface biases attributable to bulk flux algorithm by comparison of fluxes
computed using model input variables to the COARE3.5 algorithm.
2. Characterize observed and simulated surface flux feedbacks to diabatic heating associated
with clouds as a function of tropical circulation and global cloud regimes, and estimate
“theoretical” feedbacks for model fluxes computed with the COARE3.5 algorithm.
3. Assess the impact of improved surface flux calculations on cloud distributions and radiative
effects, and ECS in the CESM2 by replacing the native flux algorithm with the COARE3.5
algorithm and repeating pre-industrial control and 4xCO2 simulations.
4. Contribute surface flux diagnostics to NOAA MAPP Process-Oriented Diagnostic library.

The proposed work is relevant to Competition 5 (MAPP: Constraining Models’ Climate
Sensitivity) because: 1) it targets improved understanding of the clouds and convection coupling
with the ocean surface through improved in surface flux estimates, and 2) it aims to reduce the
uncertainty of cloud radiative effects and future climate projections arising from biases in
simulated fluxes. Our proposal targets Priority Areas B (defining key process-level metrics and
diagnostics) and C (using observations to develop constraints on models’ climate sensitivity).
This research will advance core capabilities in Earth system science and modeling. It
addresses NOAA Climate Adaptation and Mitigation objectives for “Improved scientific
understanding of the changing climate system” and “Assessments of current and future states of
the climate system.”

Award Announcement: https://engr.source.colostate.edu/atmospheric-scientist-aims-to-better-connect-climate-models-with-evaporation-observations-through-noaa-funded-research/