Skip to main content
U.S. flag

An official website of the United States government

Tying in High Resolution E3SM with ARM Data (THREAD) – Project Overview and Recent Progress

PRESENTERS:
To attach your poster or presentation:

E-mail your file for upload
Authors

Lead Presenter

Abstract

Tying in High Resolution E3SM with ARM Data (THREAD) is a newly funded Science Focus Area project by the DOE BER Atmospheric System Research (ASR) program.  It is highly motivated by DOE’s two predominant developments of climate sciences: 1) long term ground-based observational data which has been collected for decades by Atmospheric Radiation Measurement (ARM) program and 2) the emerging global kilometer scale models such as Simplified Could Resolving E3SM Atmospheric Model (SCREAM, Caldwell et al. 2021). ARM samples clouds, aerosols, precipitation, turbulence, atmospheric states, surface fluxes and land properties at very high temporal frequencies, with continuous vertical profiling and additional scanning capabilities in recent years. Such measurements enable us on process-oriented mechanistic understanding of interaction and feedback between land surface, atmospheric boundary layer, clouds and precipitation. At the same time, it presents us a unique opportunity to take advantages of ground-based observations to help validate kilometer scale models, diagnose model biases, and constrain the sub-scale parameterized processes in these models such as boundary layer clouds and their transition into deep convection, and potential scale upgrowth into mesoscale convective systems (MCS).     

In this study, we focus on the assessment of SCREAM’s performance in representing mesoscale variabilities, such as mixed-phase boundary layer cloud transition, shallow to deep convection transition, convection aggregation, and their coupling with land surface using data from field campaigns and fixed sites supported by ARM, such GoAmazon, CATCI, COMBLE and SGP. We will demonstrate a pathway how ground-based observations such as ARM data can help with diagnosing model biases such as in SCREAM, establishing case studies for mechanistic understanding, and regulating sensitivity tests of error tracing, with the aids of modeling tools such as large-eddy simulations (LES), doubly periodic SCREAM (DP-SCREAM) and regionally refined SCREAM (RRM-SCREAM).

This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.   

P.S. In order to successfully submit this abstract, I chose "ESMD" as the funding program (which should be ASR instead) and "E3SM" as the sponsoring project (which should be THREAD instead).  Thanks for your consideration!

Category
Model Uncertainties, Model Biases, and Fit-for-Purpose
Funding Program Area(s)
Additional Resources:
NERSC (National Energy Research Scientific Computing Center)