Articles | Volume 15, issue 10
Geosci. Model Dev., 15, 4055–4076, 2022
https://doi.org/10.5194/gmd-15-4055-2022
Geosci. Model Dev., 15, 4055–4076, 2022
https://doi.org/10.5194/gmd-15-4055-2022
Methods for assessment of models
25 May 2022
Methods for assessment of models | 25 May 2022

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

Shuaiqi Tang et al.

Related authors

The E3SM version 1 single-column model
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-Sheng Chen
Geosci. Model Dev., 13, 4443–4458, https://doi.org/10.5194/gmd-13-4443-2020,https://doi.org/10.5194/gmd-13-4443-2020, 2020
Short summary
Cloud characteristics, thermodynamic controls and radiative impacts during the Observations and Modeling of the Green Ocean Amazon (GoAmazon2014/5) experiment
Scott E. Giangrande, Zhe Feng, Michael P. Jensen, Jennifer M. Comstock, Karen L. Johnson, Tami Toto, Meng Wang, Casey Burleyson, Nitin Bharadwaj, Fan Mei, Luiz A. T. Machado, Antonio O. Manzi, Shaocheng Xie, Shuaiqi Tang, Maria Assuncao F. Silva Dias, Rodrigo A. F de Souza, Courtney Schumacher, and Scot T. Martin
Atmos. Chem. Phys., 17, 14519–14541, https://doi.org/10.5194/acp-17-14519-2017,https://doi.org/10.5194/acp-17-14519-2017, 2017
Short summary
Large-scale vertical velocity, diabatic heating and drying profiles associated with seasonal and diurnal variations of convective systems observed in the GoAmazon2014/5 experiment
Shuaiqi Tang, Shaocheng Xie, Yunyan Zhang, Minghua Zhang, Courtney Schumacher, Hannah Upton, Michael P. Jensen, Karen L. Johnson, Meng Wang, Maike Ahlgrimm, Zhe Feng, Patrick Minnis, and Mandana Thieman
Atmos. Chem. Phys., 16, 14249–14264, https://doi.org/10.5194/acp-16-14249-2016,https://doi.org/10.5194/acp-16-14249-2016, 2016
Short summary

Related subject area

Atmospheric sciences
Comparing Sentinel-5P TROPOMI NO2 column observations with the CAMS regional air quality ensemble
John Douros, Henk Eskes, Jos van Geffen, K. Folkert Boersma, Steven Compernolle, Gaia Pinardi, Anne-Marlene Blechschmidt, Vincent-Henri Peuch, Augustin Colette, and Pepijn Veefkind
Geosci. Model Dev., 16, 509–534, https://doi.org/10.5194/gmd-16-509-2023,https://doi.org/10.5194/gmd-16-509-2023, 2023
Short summary
Cross-evaluating WRF-Chem v4.1.2, TROPOMI, APEX, and in situ NO2 measurements over Antwerp, Belgium
Catalina Poraicu, Jean-François Müller, Trissevgeni Stavrakou, Dominique Fonteyn, Frederik Tack, Felix Deutsch, Quentin Laffineur, Roeland Van Malderen, and Nele Veldeman
Geosci. Model Dev., 16, 479–508, https://doi.org/10.5194/gmd-16-479-2023,https://doi.org/10.5194/gmd-16-479-2023, 2023
Short summary
Adapting a deep convolutional RNN model with imbalanced regression loss for improved spatio-temporal forecasting of extreme wind speed events in the short to medium range
Daan R. Scheepens, Irene Schicker, Kateřina Hlaváčková-Schindler, and Claudia Plant
Geosci. Model Dev., 16, 251–270, https://doi.org/10.5194/gmd-16-251-2023,https://doi.org/10.5194/gmd-16-251-2023, 2023
Short summary
ICLASS 1.1, a variational Inverse modelling framework for the Chemistry Land-surface Atmosphere Soil Slab model: description, validation, and application
Peter J. M. Bosman and Maarten C. Krol
Geosci. Model Dev., 16, 47–74, https://doi.org/10.5194/gmd-16-47-2023,https://doi.org/10.5194/gmd-16-47-2023, 2023
Short summary
Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM
Sudipta Ghosh, Sagnik Dey, Sushant Das, Nicole Riemer, Graziano Giuliani, Dilip Ganguly, Chandra Venkataraman, Filippo Giorgi, Sachchida Nand Tripathi, Srikanthan Ramachandran, Thazhathakal Ayyappen Rajesh, Harish Gadhavi, and Atul Kumar Srivastava
Geosci. Model Dev., 16, 1–15, https://doi.org/10.5194/gmd-16-1-2023,https://doi.org/10.5194/gmd-16-1-2023, 2023
Short summary

Cited articles

Albrecht, B. A.: Aerosols, Cloud Microphysics, and Fractional Cloudiness, Science, 245, 1227–1230, https://doi.org/10.1126/science.245.4923.1227, 1989. 
AMWG (Atmospheric Model Working Group): AMWG Diagnostic Package [data set], https://www.cesm.ucar.edu/working_groups/Atmosphere/amwg-diagnostics-package/, last access: 2 November 2021. 
ARM (Atmospheric Radiation Measurement): Intensive Operational Period (IOP) Data Browser [data set], https://iop.archive.arm.gov/arm-iop/2012/mag/magic/reynolds-marmet/ (last access: 2 November 2021), 2014. 
ARM (Atmospheric Radiation Measurement): Intensive Operational Period (IOP) Data Browser [data set], https://iop.archive.arm.gov/arm-iop/2016/sgp/hiscale/matthews-wcm (last access: 2 November 2021), 2016a. 
Download
Short summary
We developed an Earth system model (ESM) diagnostics package to compare various types of aerosol properties simulated in ESMs with aircraft, ship, and surface measurements from six field campaigns across spatial scales. The diagnostics package is coded and organized to be flexible and modular for future extension to other field campaign datasets and adapted to higher-resolution model simulations. Future releases will include comprehensive cloud and aerosol–cloud interaction diagnostics.