The GFDL Global Atmosphere and Land Model AM4.0/LM4.0: 2. Model Description, Sensitivity Studies, and Tuning Strategies

Abstract

In Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.

Formation of Tropical Anvil Clouds by Slow Evaporation

“…A promising starting point is the prognostic Tiedtke (1993) scheme, which includes a sink for cloud fraction that is proportional to the saturation deficit; this scheme is already in use in modified form at GFDL (Zhao et al, 2018) and elsewhere. A promising starting point is the prognostic Tiedtke (1993) scheme, which includes a sink for cloud fraction that is proportional to the saturation deficit; this scheme is already in use in modified form at GFDL (Zhao et al, 2018) and elsewhere.…”

Improved Surface Layer Simulation Using Refined Vertical Resolution in the GFDL Atmospheric General Circulation Model

“…The two models (L32 and L33) are integrated for 11 years with the same monthly SST and sea ice climatologies every year. This type of AGCM simulations driven by the climatological SST and sea ice extent produces mean climatology and subseasonal and seasonal variability that are very similar to corresponding AMIP simulations, which are driven by annually varying monthly SST and sea ice (Zhao et al, ). The climatologies obtained by averaging the model results for the last 10‐year period are evaluated against a reanalysis ensemble data set (Shin et al, ), which is generated by combining the four reanalysis data sets of ERA‐20C (Poli et al, ), ERA‐Interim (Berrisford et al, ; Dee et al, ), NCEP‐CFSR (Saha et al, ), and NASA‐MERRA (Rienecker et al, ).…”

Improved Simulations of Tropical Pacific Annual‐Mean Climate in the GFDL FLOR and HiFLOR Coupled GCMs

“…It is conceivable that some of the tropical Pacific climate improvements seen in the 55‐km FLOR could also have been attained with a 100‐km grid (midway between LOAR1 and FLOR), though we have not tested this in the FLOR lineage which has focused on improving simulations of regional and extreme phenomena that clearly benefit from higher atmospheric resolution. However, analyses of the 100‐km GFDL‐AM4 atmosphere model (Zhao et al, ; ) and its coupled counterpart GFDL‐Coupled Model version 4 confirm that excellent simulations of tropical Pacific climate are indeed possible with a 100‐km atmosphere grid.…”

“…Beyond its utility for the present study, LOAR1 has also contributed to the development of a new GFDL coupled model (Seamless system for Prediction and EArth system Research [SPEAR]) which is optimized for seasonal‐to‐decadal applications and forecasting. SPEAR leverages the new technology and parameterizations developed for the Coupled Model version 4 CGCM (Zhao et al, , ) that is GFDL's main model contribution to Coupled Model Intercomparison Project phase 6. SPEAR will be documented in a future study.…”