Earth system model parameter adjustment using a Green's functions approach

Abstract

Abstract. We demonstrate the practicality and effectiveness of using a Green's functions estimation approach for adjusting uncertain parameters in an Earth system model (ESM). This estimation approach has previously been applied to an intermediate-complexity climate model and to individual ESM components, e.g., ocean, sea ice, or carbon cycle components. Here, the Green's functions approach is applied to a state-of-the-art ESM that comprises a global atmosphere/land configuration of the Goddard Earth Observing System (GEOS) coupled to an ocean and sea ice configuration of the Massachusetts Institute of Technology general circulation model (MITgcm). Horizontal grid spacing is approximately 110 km for GEOS and 37–110 km for MITgcm. In addition to the reference GEOS-MITgcm simulation, we carried out a series of model sensitivity experiments, in which 20 uncertain parameters are perturbed. These “control” parameters can be used to adjust sea ice, microphysics, turbulence, radiation, and surface schemes in the coupled simulation. We defined eight observational targets: sea ice fraction, net surface shortwave radiation, downward longwave radiation, near-surface temperature, sea surface temperature, sea surface salinity, and ocean temperature and salinity at 300 m. We applied the Green's functions approach to optimize the values of the 20 control parameters so as to minimize a weighted least-squares distance between the model and the eight observational targets. The new experiment with the optimized parameters resulted in a total cost reduction of 9 % relative to a simulation that had already been adjusted using other methods. The optimized experiment attained a balanced cost reduction over most of the observational targets. We also report on results from a set of sensitivity experiments that are not used in the final optimized simulation but helped explore options and guided the optimization process. These experiments include an assessment of sensitivity to the number of control parameters and to the selection of observational targets and weights in the cost function. Based on these sensitivity experiments, we selected a specific definition for the cost function. The sensitivity experiments also revealed a decreasing overall cost as the number of control variables was increased. In summary, we recommend using the Green's functions estimation approach as an additional fine-tuning step in the model development process. The method is not a replacement for modelers' experience in choosing and adjusting sensitive model parameters. Instead, it is an additional practical and effective tool for carrying out final adjustments of uncertain ESM parameters.

The Nonlinear Northern Hemisphere Stratospheric Temperature Response to External Radiative Forcing in Decadal Climate Simulations

“…To understand the sensitivity of external radiative forcing due to CO 2 and ODSs, we used the Goddard Earth System-MITgcm (GEOS-MITgcm) coupled earth system model at a nominal 1-degree horizontal resolution in the atmosphere and ocean, with 72 vertical levels in the atmosphere (top lid 0.01 hPa) and 50 levels in the ocean. Details of the model can be found in (Strobach et al, 2022), but some aspects relevant to this study are described here. The atmospheric model includes the finite volume dynamical core on a cubed sphere grid (Putman and Lin, 2007), a full suite of physical parameterizations including the two-moment cloud microphysics (which includes the aerosol indirect effect) of Barahona et al (2014), the land model of Koster et al (2000), and is coupled to the the Goddard Chemistry Aerosol Radiation and Transport (GOCART) interactive aerosol model Chin et al (2002); Colarco et al (2010).…”

Resonant Diurnal Internal Tides in the North Atlantic: 2. Modeling

“…The model used in this study was the GEOS infrastructure and atmospheric model coupled to an ocean configuration of the MITgcm, hereinafter GEOS‐MITgcm (see Light et al., 2022; Strobach et al., 2020; Strobach, Klein, et al., 2022; Strobach, Molod, et al., 2022). We used the so‐called C1440‐LLC2160 simulation, in which the GEOS atmosphere has 72 vertical layers and nominal horizontal grid spacing of 7 km, the MITgcm ocean has 90 vertical levels and horizontal grid spacing of 2–4‐km, and the simulated ocean includes full lunisolar tidal forcing (see Supporting Information and Torres et al., 2022).…”

Impact of the TAO/TRITON Array on Reanalyses and Predictions of the 2015 El Niño

“…• Atmosphere Model: The atmospheric model is now the "Icarus generation" Goddard Earth Observing System (GEOS) atmospheric general circulation model with 72 layers and approximately 0.5° resolution (Molod et al, 2015;Rienecker et al, 2008). Although the suite of atmospheric physical parameterizations does not include any fundamental changes relative to the previous version coupled model, the behavior of the current model was adjusted substantially as a result of a Green's Functions tuning procedure (Strobach et al, 2022).…”

“…The horizontal viscosity uses the anisotropic scheme of (Large et al., 2001) for better representation of equatorial currents, upwelling and mixing. Atmosphere Model: The atmospheric model is now the “Icarus generation” Goddard Earth Observing System (GEOS) atmospheric general circulation model with 72 layers and approximately 0.5° resolution (Molod et al., 2015; Rienecker et al., 2008). Although the suite of atmospheric physical parameterizations does not include any fundamental changes relative to the previous version coupled model, the behavior of the current model was adjusted substantially as a result of a Green's Functions tuning procedure (Strobach et al., 2022). In contrast to the more conventional tuning procedure (Schmidt et al., 2017) used during the development of GEOS‐S2S‐2 that was essentially developed using atmosphere‐only experiments, the Green's functions method used during the S2S‐3 development was performed using a series of coupled model experiments. Weakly Coupled Assimilation: Largely similar to the schematic in Figure 1 (Molod et al., 2020) for GEOS‐S2S‐2 (our previous coupled model), two new features of the weakly coupled assimilation were implemented in our latest GEOS‐S2S‐3 coupled system.…”