Articles | Volume 15, issue 8
https://doi.org/10.5194/gmd-15-3205-2022
https://doi.org/10.5194/gmd-15-3205-2022
Development and technical paper
 | 
19 Apr 2022
Development and technical paper |  | 19 Apr 2022

CondiDiag1.0: a flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)

Hui Wan, Kai Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, Shixuan Zhang, and Ross Dixon

Related authors

Representing the effects of giant aerosol in droplet nucleation in E3SMv2
Yu Yao, Po-Lun Ma, Yi Qin, Matthew W. Christensen, Hui Wan, Kai Zhang, Balwinder Singh, Meng Huang, and Mikhail Ovchinnikov
EGUsphere, https://doi.org/10.5194/egusphere-2024-523,https://doi.org/10.5194/egusphere-2024-523, 2024
Short summary
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 1: Dust budget analyses and the impacts of a revised coupling scheme
Hui Wan, Kai Zhang, Christopher J. Vogl, Carol S. Woodward, Richard C. Easter, Philip J. Rasch, Yan Feng, and Hailong Wang
Geosci. Model Dev., 17, 1387–1407, https://doi.org/10.5194/gmd-17-1387-2024,https://doi.org/10.5194/gmd-17-1387-2024, 2024
Short summary
Numerical coupling of aerosol emissions, dry removal, and turbulent mixing in the E3SM Atmosphere Model version 1 (EAMv1) – Part 2: A semi-discrete error analysis framework for assessing coupling schemes
Christopher J. Vogl, Hui Wan, Carol S. Woodward, and Quan M. Bui
Geosci. Model Dev., 17, 1409–1428, https://doi.org/10.5194/gmd-17-1409-2024,https://doi.org/10.5194/gmd-17-1409-2024, 2024
Short summary
Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects
Shixuan Zhang, Kai Zhang, Hui Wan, and Jian Sun
Geosci. Model Dev., 15, 6787–6816, https://doi.org/10.5194/gmd-15-6787-2022,https://doi.org/10.5194/gmd-15-6787-2022, 2022
Short summary
Effective radiative forcing of anthropogenic aerosols in E3SM version 1: historical changes, causality, decomposition, and parameterization sensitivities
Kai Zhang, Wentao Zhang, Hui Wan, Philip J. Rasch, Steven J. Ghan, Richard C. Easter, Xiangjun Shi, Yong Wang, Hailong Wang, Po-Lun Ma, Shixuan Zhang, Jian Sun, Susannah M. Burrows, Manish Shrivastava, Balwinder Singh, Yun Qian, Xiaohong Liu, Jean-Christophe Golaz, Qi Tang, Xue Zheng, Shaocheng Xie, Wuyin Lin, Yan Feng, Minghuai Wang, Jin-Ho Yoon, and L. Ruby Leung
Atmos. Chem. Phys., 22, 9129–9160, https://doi.org/10.5194/acp-22-9129-2022,https://doi.org/10.5194/acp-22-9129-2022, 2022
Short summary

Related subject area

Climate and Earth system modeling
Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification
Hugo Banderier, Christian Zeman, David Leutwyler, Stefan Rüdisühli, and Christoph Schär
Geosci. Model Dev., 17, 5573–5586, https://doi.org/10.5194/gmd-17-5573-2024,https://doi.org/10.5194/gmd-17-5573-2024, 2024
Short summary
TorchClim v1.0: a deep-learning plugin for climate model physics
David Fuchs, Steven C. Sherwood, Abhnil Prasad, Kirill Trapeznikov, and Jim Gimlett
Geosci. Model Dev., 17, 5459–5475, https://doi.org/10.5194/gmd-17-5459-2024,https://doi.org/10.5194/gmd-17-5459-2024, 2024
Short summary
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024,https://doi.org/10.5194/gmd-17-5191-2024, 2024
Short summary
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024,https://doi.org/10.5194/gmd-17-5087-2024, 2024
Short summary
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024,https://doi.org/10.5194/gmd-17-4923-2024, 2024
Short summary

Cited articles

Bailey, A., Singh, H. K. A., and Nusbaumer, J.: Evaluating a Moist Isentropic Framework for Poleward Moisture Transport: Implications for Water Isotopes Over Antarctica, Geophys. Res. Lett., 46, 7819–7827, https://doi.org/10.1029/2019GL082965, 2019. a
Craig, A. P., Vertenstein, M., and Jacob, R.: A new flexible coupler for earth system modeling developed for CCSM4 and CESM1, Int. J. High Perform. C., 26, 31–42, https://doi.org/10.1177/1094342011428141, 2012. a
Craig, C., Bacmeister, J., Callaghan, P., Eaton, B., Gettelman, A., Goldhaber, S. N., Hannay, C., Herrington, A., Lauritzen, P. H., McInerney, J., Medeiros, B., Mills, M. J., Neale, R., Tilmes, S., Truesdale, J. E., Vertenstein, M., and Vitt, F. M.: CAM6.3 User's Guide, NCAR Technical Note NCAR/TN-571+EDD, National Center for Atmospheric Research, Boulder, Colorado, USA, https://doi.org/10.5065/Z953-ZC95, 2021. a, b
E3SM Project: Energy Exascale Earth System Model v1.0 [code], https://doi.org/10.11578/E3SM/dc.20180418.36, 2018. a
Eaton, B.: CAM Reference Manual, https://www.cesm.ucar.edu/models/cesm1.2/cam/docs/rm5_3/index.html (last access: 13 April 2022), 2015. a, b
Download
Short summary
This paper describes a tool embedded in a global climate model for sampling atmospheric conditions and monitoring physical processes as a numerical simulation is being carried out. The tool facilitates process-level model evaluation by allowing the users to select a wide range of quantities and processes to monitor at run time without having to do tedious ad hoc coding.