Abstract
Abstract. Climate models are essential for our comprehensive understanding of Earth's atmosphere and can provide critical insights on future changes decades ahead. Because of these critical roles, today's climate models are continuously being developed and evaluated using constraining observations and measurements obtained by satellites, airborne, and ground-based instruments. Instrument simulators can provide a bridge between the measured or retrieved quantities and their sampling in models and field observations while considering instrument sensitivity limitations. Here we present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar instrument simulator and subcolumn generator, specifically designed for large-scale models, in particular climate models, but also applicable to high-resolution model output. EMC2 provides a flexible framework enabling direct comparison of model output with ground-based observations, including generation of subcolumns that may statistically represent finer model spatial resolutions. In addition, EMC2 emulates ground-based (and air- or space-borne) measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. The simulator uses either single particle or bulk particle size distribution lookup tables, depending on the selected scheme approach, to perform the forward calculations. To facilitate model evaluation, EMC2 also includes three hydrometeor classification methods, namely, radar- and sounding-based cloud and precipitation detection and classification, lidar-based phase classification, and a Cloud Feedback Model Intercomparison Project Observational Simulator Package (COSP) lidar simulator emulator. The software is written in Python, is easy to use, and can be straightforwardly customized for different models, radars, and lidars. Following the description of the logic, functionality, features, and software structure of EMC2, we present a case study of highly supercooled mixed-phase cloud based on measurements from the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) West Antarctic Radiation Experiment (AWARE). We compare observations with the application of EMC2 to outputs from four configurations of the NASA Goddard Institute for Space Studies (GISS) climate model (ModelE3) in single-column model (SCM) mode and from a large-eddy simulation (LES) model. We show that two of the four ModelE3 configurations can form and maintain highly supercooled precipitating cloud for several hours, consistent with observations and LES. While our focus is on one of these ModelE3 configurations, which performed slightly better in this case study, both of these configurations and the LES results post-processed with EMC2 generally provide reasonable agreement with observed lidar and radar variables. As briefly demonstrated here, EMC2 can provide a lightweight and flexible framework for comparing the results of both large-scale and high-resolution models directly with observations, with relatively little overhead and multiple options for achieving consistency with model microphysical or radiation scheme physics.
Highlights
The representation of cloud processes in large-scale models is continuously advancing, conceptually, and in the level of details and complexity implemented in the micro- and macro-physical schemes (e.g., Lin et al, 2019; Cesana et al, 2019)
When the radiation approach is selected in EMC2, forward radar calculations using bulk lookup tables (LUTs) are limited to the zeroth radar moment (Ze) due to a set of limitations: 1. Large-scale model radiation schemes are not informed with hydrometeor fall velocities
Based on Lagrangian simulations constrained by the remotesensing observations, Silber et al (2019a) postulated that the activated ice-nucleating particle (INP) and cloud condensation nuclei (CCN) concentrations during the event were on the order of 0.2 L−1 and 20 cm−3, respectively, to enable drizzle to be produced and precipitate along with ice precipitation below the highly supercooled cloud base
Summary
The representation of cloud processes in large-scale models is continuously advancing, conceptually, and in the level of details and complexity implemented in the micro- and macro-physical schemes (e.g., Lin et al, 2019; Cesana et al, 2019) These improvements are reflected in the accuracy of the resulting model output (e.g., Klein et al, 2013; Lin et al, 2019; Myers et al, 2021; Wang et al, 2019), yet results still show large inter-model variability (e.g., Zelinka et al, 2020). We present the Earth Model Column Collaboratory (EMC2), an open-source ground-based lidar and radar simulator and subcolumn generator, which is designed to operate over large-scale model output while being faithful to the physics implemented in models’ microphysics or radiation schemes but can be applied to high-resolution model output.
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