Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 1: assessing E3SM aerosol predictions using aircraft, ship, and surface measurements

Journal Article
Geoscientific Model Development, vol. 15, iss. 10, pp. 4055-4076, 2022
Shuaiqi Tang, Jerome D. Fast, Kai Zhang, Joseph C. Hardin, Adam C. Varble, John E. Shilling, Fan Mei, Maria A. Zawadowicz, Po-Lun Ma
Abstract. An Earth system model (ESM) aerosol–cloud diagnostics package is developed to facilitate the routine evaluation of aerosols, clouds, and aerosol–cloud interactions simulated by the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). The first version focuses on comparing simulated aerosol properties with aircraft, ship, and surface measurements, which are mostly measured in situ. The diagnostics currently cover six field campaigns in four geographical regions: eastern North Atlantic (ENA), central US (CUS), northeastern Pacific (NEP), and Southern Ocean (SO). These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the Atmospheric Radiation Measurement (ARM) program and other agencies. Various types of diagnostics and metrics are performed for aerosol number, size distribution, chemical composition, cloud condensation nuclei (CCN) concentration, and various meteorological quantities to assess how well E3SM represents observed aerosol properties across spatial scales. Overall, E3SM qualitatively reproduces the observed aerosol number concentration, size distribution, and chemical composition reasonably well, but it overestimates Aitken-mode aerosols and underestimates accumulation-mode aerosols over the CUS and ENA regions, suggesting that processes related to particle growth or coagulation might be too weak in the model. The current version of E3SM struggles to reproduce the new particle formation events frequently observed over both the CUS and ENA regions, indicating missing processes in current parameterizations. The diagnostics package is coded and organized in a way that can be extended to other field campaign datasets and adapted to higher-resolution model simulations.