Articles | Volume 13, issue 10
Geosci. Model Dev., 13, 4831–4843, 2020
https://doi.org/10.5194/gmd-13-4831-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: The Model Intercomparison Project on the climatic response...
Model experiment description paper
09 Oct 2020
Model experiment description paper
| 09 Oct 2020
Quantifying CanESM5 and EAMv1 sensitivities to Mt. Pinatubo volcanic forcing for the CMIP6 historical experiment
Landon A. Rieger et al.
Related authors
Jennifer Schallock, Christoph Brühl, Christine Bingen, Michael Höpfner, Landon Rieger, and Jos Lelieveld
Atmos. Chem. Phys., 23, 1169–1207, https://doi.org/10.5194/acp-23-1169-2023, https://doi.org/10.5194/acp-23-1169-2023, 2023
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We characterized the influence of volcanic aerosols for the period 1990–2019 and established a volcanic SO2 emission inventory that includes more than 500 eruptions. From limb-based satellite observations of SO2 and extinction, we derive 3D plumes of SO2 perturbations and injected mass by a novel method. We calculate instantaneous radiative forcing with a comprehensive chemisty climate model. Our results show that smaller eruptions can also contribute to the stratospheric aerosol forcing.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
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This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
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This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Larry W. Thomason, Mahesh Kovilakam, Anja Schmidt, Christian von Savigny, Travis Knepp, and Landon Rieger
Atmos. Chem. Phys., 21, 1143–1158, https://doi.org/10.5194/acp-21-1143-2021, https://doi.org/10.5194/acp-21-1143-2021, 2021
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Measurements of the impact of volcanic eruptions on stratospheric aerosol loading by space-based instruments show show a fairly well-behaved relationship between the magnitude and the apparent changes to aerosol size over several orders of magnitude. This directly measured relationship provides a unique opportunity to verify the performance of interactive aerosol models used in climate models.
Elizaveta Malinina, Alexei Rozanov, Landon Rieger, Adam Bourassa, Heinrich Bovensmann, John P. Burrows, and Doug Degenstein
Atmos. Meas. Tech., 12, 3485–3502, https://doi.org/10.5194/amt-12-3485-2019, https://doi.org/10.5194/amt-12-3485-2019, 2019
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This paper covers the problems related to the derivation of aerosol extinction coefficients and Ångström exponents from space-borne instruments working in limb and occultation viewing geometries. Aerosol extinction coefficients and Ångström exponents were calculated from the SCIAMACHY aerosol particle size data set. The results were compared with the data from SAGE II and OSIRIS. The Ångström exponent in the tropical regions and its dependency on particle size parameters are discussed.
Christoph Brühl, Jennifer Schallock, Klaus Klingmüller, Charles Robert, Christine Bingen, Lieven Clarisse, Andreas Heckel, Peter North, and Landon Rieger
Atmos. Chem. Phys., 18, 12845–12857, https://doi.org/10.5194/acp-18-12845-2018, https://doi.org/10.5194/acp-18-12845-2018, 2018
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Use of multi-instrument satellite data is important to get consistent simulations of aerosol radiative forcing by a complex chemistry climate model, here with a main focus on the lower stratosphere. The satellite data at different wavelengths together with the patterns in the simulated size distribution point to a significant contribution from moist mineral dust lifted to the tropopause region by the Asian summer monsoon.
Landon A. Rieger, Elizaveta P. Malinina, Alexei V. Rozanov, John P. Burrows, Adam E. Bourassa, and Doug A. Degenstein
Atmos. Meas. Tech., 11, 3433–3445, https://doi.org/10.5194/amt-11-3433-2018, https://doi.org/10.5194/amt-11-3433-2018, 2018
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This paper compares aerosol extinction records from two limb scattering instruments, OSIRIS and SCIAMACHY, to that from the occultation instrument SAGE II. Differences are investigated through modelling and retrieval studies and important sources of systematic errors are quantified. It is found that the largest biases come from uncertainties in the aerosol size distribution and the aerosol particle concentration at altitudes above 30 km.
Daniel J. Zawada, Landon A. Rieger, Adam E. Bourassa, and Douglas A. Degenstein
Atmos. Meas. Tech., 11, 2375–2393, https://doi.org/10.5194/amt-11-2375-2018, https://doi.org/10.5194/amt-11-2375-2018, 2018
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The Ozone Mapping and Profiler Suite Limb Profiler measures scattered sunlight, which is then inverted to obtain vertical profiles of ozone in the atmosphere. We have developed a new algorithm for inverting the data which is better suited for areas with large horizontal ozone gradients, such as the polar vortex. Data from the full currently 5-year mission have been processed and are publicly available.
Larry W. Thomason, Nicholas Ernest, Luis Millán, Landon Rieger, Adam Bourassa, Jean-Paul Vernier, Gloria Manney, Beiping Luo, Florian Arfeuille, and Thomas Peter
Earth Syst. Sci. Data, 10, 469–492, https://doi.org/10.5194/essd-10-469-2018, https://doi.org/10.5194/essd-10-469-2018, 2018
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We describe the construction of a continuous 38-year record of stratospheric aerosol optical properties. The Global Space-based Stratospheric Aerosol Climatology, or GloSSAC, provided the input data to the construction of the Climate Model Intercomparison Project stratospheric aerosol forcing data set (1979 to 2014) and is now extended through 2016. GloSSAC focuses on the the SAGE series of instruments through mid-2005 and on OSIRIS and CALIPSO after that time.
Adam E. Bourassa, Chris Z. Roth, Daniel J. Zawada, Landon A. Rieger, Chris A. McLinden, and Douglas A. Degenstein
Atmos. Meas. Tech., 11, 489–498, https://doi.org/10.5194/amt-11-489-2018, https://doi.org/10.5194/amt-11-489-2018, 2018
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OSIRIS satellite measurements of ozone in the stratosphere are corrected for slowly varying errors. These changes make the OSIRIS data compare better with other satellite measurements over the long term and make an impact on our understanding of the recovery of the ozone layer.
Cristen Adams, Adam E. Bourassa, Chris A. McLinden, Chris E. Sioris, Thomas von Clarmann, Bernd Funke, Landon A. Rieger, and Douglas A. Degenstein
Atmos. Chem. Phys., 17, 8063–8080, https://doi.org/10.5194/acp-17-8063-2017, https://doi.org/10.5194/acp-17-8063-2017, 2017
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We measured the relationship between volcanic aerosol and trace gases in the stratosphere using the OSIRIS and MIPAS satellite instruments between 2002 and 2014. We found that levels of stratospheric NO2 and N2O5 both decreased significantly in the presence of volcanic aerosol. These decreases were consistent with the modeling results.
Christopher E. Sioris, Landon A. Rieger, Nicholas D. Lloyd, Adam E. Bourassa, Chris Z. Roth, Douglas A. Degenstein, Claude Camy-Peyret, Klaus Pfeilsticker, Gwenaël Berthet, Valéry Catoire, Florence Goutail, Jean-Pierre Pommereau, and Chris A. McLinden
Atmos. Meas. Tech., 10, 1155–1168, https://doi.org/10.5194/amt-10-1155-2017, https://doi.org/10.5194/amt-10-1155-2017, 2017
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A new OSIRIS NO2 retrieval algorithm is described and validated using > 40 balloon-based profile measurements. The validation results indicate a slight improvement relative to the existing operational algorithm in terms of the bias versus the balloon data, particularly in the lower stratosphere. The implication is that this new algorithm should replace the operational one. The motivation was to combine spectral fitting and the SaskTRAN radiative transfer model to achieve an improved product.
Sergey M. Khaykin, Sophie Godin-Beekmann, Philippe Keckhut, Alain Hauchecorne, Julien Jumelet, Jean-Paul Vernier, Adam Bourassa, Doug A. Degenstein, Landon A. Rieger, Christine Bingen, Filip Vanhellemont, Charles Robert, Matthew DeLand, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, https://doi.org/10.5194/acp-17-1829-2017, 2017
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The article is devoted to the long-term evolution and variability of stratospheric aerosol, which plays an important role in climate change and the ozone layer. We use 22-year long continuous observations using laser radar soundings in southern France and satellite-based observations to distinguish between natural aerosol variability (caused by volcanic eruptions) and human-induced change in aerosol concentration. An influence of growing pollution above Asia on stratospheric aerosol is found.
D. J. Zawada, S. R. Dueck, L. A. Rieger, A. E. Bourassa, N. D. Lloyd, and D. A. Degenstein
Atmos. Meas. Tech., 8, 2609–2623, https://doi.org/10.5194/amt-8-2609-2015, https://doi.org/10.5194/amt-8-2609-2015, 2015
L. A. Rieger, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 7, 777–780, https://doi.org/10.5194/amt-7-777-2014, https://doi.org/10.5194/amt-7-777-2014, 2014
L. A. Rieger, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 7, 507–522, https://doi.org/10.5194/amt-7-507-2014, https://doi.org/10.5194/amt-7-507-2014, 2014
Jennifer Schallock, Christoph Brühl, Christine Bingen, Michael Höpfner, Landon Rieger, and Jos Lelieveld
Atmos. Chem. Phys., 23, 1169–1207, https://doi.org/10.5194/acp-23-1169-2023, https://doi.org/10.5194/acp-23-1169-2023, 2023
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We characterized the influence of volcanic aerosols for the period 1990–2019 and established a volcanic SO2 emission inventory that includes more than 500 eruptions. From limb-based satellite observations of SO2 and extinction, we derive 3D plumes of SO2 perturbations and injected mass by a novel method. We calculate instantaneous radiative forcing with a comprehensive chemisty climate model. Our results show that smaller eruptions can also contribute to the stratospheric aerosol forcing.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Chengzhu Zhang, Jean-Christophe Golaz, Ryan Forsyth, Tom Vo, Shaocheng Xie, Zeshawn Shaheen, Gerald L. Potter, Xylar S. Asay-Davis, Charles S. Zender, Wuyin Lin, Chih-Chieh Chen, Chris R. Terai, Salil Mahajan, Tian Zhou, Karthik Balaguru, Qi Tang, Cheng Tao, Yuying Zhang, Todd Emmenegger, Susannah Burrows, and Paul A. Ullrich
Geosci. Model Dev., 15, 9031–9056, https://doi.org/10.5194/gmd-15-9031-2022, https://doi.org/10.5194/gmd-15-9031-2022, 2022
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Earth system model (ESM) developers run automated analysis tools on data from candidate models to inform model development. This paper introduces a new Python package, E3SM Diags, that has been developed to support ESM development and use routinely in the development of DOE's Energy Exascale Earth System Model. This tool covers a set of essential diagnostics to evaluate the mean physical climate from simulations, as well as several process-oriented and phenomenon-based evaluation diagnostics.
Ulla Wandinger, Athena Augusta Floutsi, Holger Baars, Moritz Haarig, Albert Ansmann, Anja Hünerbein, Nicole Docter, David Donovan, Gerd-Jan van Zadelhoff, Shannon Mason, and Jason Cole
EGUsphere, https://doi.org/10.5194/egusphere-2022-1241, https://doi.org/10.5194/egusphere-2022-1241, 2022
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We introduce an aerosol classification model that has been developed for the Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The model provides a consistent description of microphysical, optical, and radiative properties of common aerosol types such as dust, sea salt, pollution, and smoke. It is used for aerosol classification and assessment of radiation effects based on the synergy of active and passive observations with lidar, imager, and radiometer of the multi-instrument platform.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-262, https://doi.org/10.5194/gmd-2022-262, 2022
Preprint under review for GMD
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High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes, and thus increasingly important. However, uniformly reducing the grid size of global Earth system model is too computationally expensive. We overview the fully coupled Regionally Refined Model (RRM) of E3SMv2 and document a first-of-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid timestep strategy.
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
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Here we analyze the effective aerosol forcing simulated by E3SM version 1 using both century-long free-running and short nudged simulations. The aerosol forcing in E3SMv1 is relatively large compared to other models, mainly due to the large indirect aerosol effect. Aerosol-induced changes in liquid and ice cloud properties in E3SMv1 have a strong correlation. The aerosol forcing estimates in E3SMv1 are sensitive to the parameterization changes in both liquid and ice cloud processes.
Xue Zheng, Qing Li, Tian Zhou, Qi Tang, Luke P. Van Roekel, Jean-Christophe Golaz, Hailong Wang, and Philip Cameron-Smith
Geosci. Model Dev., 15, 3941–3967, https://doi.org/10.5194/gmd-15-3941-2022, https://doi.org/10.5194/gmd-15-3941-2022, 2022
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We document the model experiments for the future climate projection by E3SMv1.0. At the highest future emission scenario, E3SMv1.0 projects a strong surface warming with rapid changes in the atmosphere, ocean, sea ice, and land runoff. Specifically, we detect a significant polar amplification and accelerated warming linked to the unmasking of the aerosol effects. The impact of greenhouse gas forcing is examined in different climate components.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard B. Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Michael S. Pritchard, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev., 15, 2881–2916, https://doi.org/10.5194/gmd-15-2881-2022, https://doi.org/10.5194/gmd-15-2881-2022, 2022
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An alternative set of parameters for E3SM Atmospheric Model version 1 has been developed based on a tuning strategy that focuses on clouds. When clouds in every regime are improved, other aspects of the model are also improved, even though they are not the direct targets for calibration. The recalibrated model shows a lower sensitivity to anthropogenic aerosols and surface warming, suggesting potential improvements to the simulated climate in the past and future.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
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This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Trevor J. McDougall, Paul M. Barker, Ryan M. Holmes, Rich Pawlowicz, Stephen M. Griffies, and Paul J. Durack
Geosci. Model Dev., 14, 6445–6466, https://doi.org/10.5194/gmd-14-6445-2021, https://doi.org/10.5194/gmd-14-6445-2021, 2021
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We show that the way that the air–sea heat flux is treated in ocean models means that the model's temperature variable should be interpreted as being Conservative Temperature, irrespective of whether the equation of state used in an ocean model is EOS-80 or TEOS-10.
John G. Virgin, Christopher G. Fletcher, Jason N. S. Cole, Knut von Salzen, and Toni Mitovski
Geosci. Model Dev., 14, 5355–5372, https://doi.org/10.5194/gmd-14-5355-2021, https://doi.org/10.5194/gmd-14-5355-2021, 2021
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Equilibrium climate sensitivity, or the amount of warming the Earth would exhibit a result of a doubling of atmospheric CO2, is a common metric used in assessments of climate models. Here, we compare climate sensitivity between two versions of the Canadian Earth System Model. We find the newest iteration of the model (version 5) to have higher climate sensitivity due to reductions in low-level clouds, which reflect radiation and cool the planet, as the surface warms.
Yongkang Xue, Tandong Yao, Aaron A. Boone, Ismaila Diallo, Ye Liu, Xubin Zeng, William K. M. Lau, Shiori Sugimoto, Qi Tang, Xiaoduo Pan, Peter J. van Oevelen, Daniel Klocke, Myung-Seo Koo, Tomonori Sato, Zhaohui Lin, Yuhei Takaya, Constantin Ardilouze, Stefano Materia, Subodh K. Saha, Retish Senan, Tetsu Nakamura, Hailan Wang, Jing Yang, Hongliang Zhang, Mei Zhao, Xin-Zhong Liang, J. David Neelin, Frederic Vitart, Xin Li, Ping Zhao, Chunxiang Shi, Weidong Guo, Jianping Tang, Miao Yu, Yun Qian, Samuel S. P. Shen, Yang Zhang, Kun Yang, Ruby Leung, Yuan Qiu, Daniele Peano, Xin Qi, Yanling Zhan, Michael A. Brunke, Sin Chan Chou, Michael Ek, Tianyi Fan, Hong Guan, Hai Lin, Shunlin Liang, Helin Wei, Shaocheng Xie, Haoran Xu, Weiping Li, Xueli Shi, Paulo Nobre, Yan Pan, Yi Qin, Jeff Dozier, Craig R. Ferguson, Gianpaolo Balsamo, Qing Bao, Jinming Feng, Jinkyu Hong, Songyou Hong, Huilin Huang, Duoying Ji, Zhenming Ji, Shichang Kang, Yanluan Lin, Weiguang Liu, Ryan Muncaster, Patricia de Rosnay, Hiroshi G. Takahashi, Guiling Wang, Shuyu Wang, Weicai Wang, Xu Zhou, and Yuejian Zhu
Geosci. Model Dev., 14, 4465–4494, https://doi.org/10.5194/gmd-14-4465-2021, https://doi.org/10.5194/gmd-14-4465-2021, 2021
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The subseasonal prediction of extreme hydroclimate events such as droughts/floods has remained stubbornly low for years. This paper presents a new international initiative which, for the first time, introduces spring land surface temperature anomalies over high mountains to improve precipitation prediction through remote effects of land–atmosphere interactions. More than 40 institutions worldwide are participating in this effort. The experimental protocol and preliminary results are presented.
Robin D. Lamboll, Chris D. Jones, Ragnhild B. Skeie, Stephanie Fiedler, Bjørn H. Samset, Nathan P. Gillett, Joeri Rogelj, and Piers M. Forster
Geosci. Model Dev., 14, 3683–3695, https://doi.org/10.5194/gmd-14-3683-2021, https://doi.org/10.5194/gmd-14-3683-2021, 2021
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Lockdowns to avoid the spread of COVID-19 have created an unprecedented reduction in human emissions. We can estimate the changes in emissions at a country level, but to make predictions about how this will affect our climate, we need more precise information about where the emissions happen. Here we combine older estimates of where emissions normally occur with very recent estimates of sector activity levels to enable different groups to make simulations of the climatic effects of lockdown.
Ben Kravitz, Douglas G. MacMartin, Daniele Visioni, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Andy Jones, Thibaut Lurton, Pierre Nabat, Ulrike Niemeier, Alan Robock, Roland Séférian, and Simone Tilmes
Atmos. Chem. Phys., 21, 4231–4247, https://doi.org/10.5194/acp-21-4231-2021, https://doi.org/10.5194/acp-21-4231-2021, 2021
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This study investigates multi-model response to idealized geoengineering (high CO2 with solar reduction) across two different generations of climate models. We find that, with the exception of a few cases, the results are unchanged between the different generations. This gives us confidence that broad conclusions about the response to idealized geoengineering are robust.
Yong Wang, Guang J. Zhang, Shaocheng Xie, Wuyin Lin, George C. Craig, Qi Tang, and Hsi-Yen Ma
Geosci. Model Dev., 14, 1575–1593, https://doi.org/10.5194/gmd-14-1575-2021, https://doi.org/10.5194/gmd-14-1575-2021, 2021
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A stochastic deep convection parameterization is implemented into the US Department of Energy Energy Exascale Earth System Model Atmosphere Model version 1 (EAMv1). Compared to the default model, the well-known problem of
too much light rain and too little heavy rainis largely alleviated over the tropics with the stochastic scheme. Results from this study provide important insights into the model performance of EAMv1 when stochasticity is included in the deep convective parameterization.
Qi Tang, Michael J. Prather, Juno Hsu, Daniel J. Ruiz, Philip J. Cameron-Smith, Shaocheng Xie, and Jean-Christophe Golaz
Geosci. Model Dev., 14, 1219–1236, https://doi.org/10.5194/gmd-14-1219-2021, https://doi.org/10.5194/gmd-14-1219-2021, 2021
Claudia Tebaldi, Kevin Debeire, Veronika Eyring, Erich Fischer, John Fyfe, Pierre Friedlingstein, Reto Knutti, Jason Lowe, Brian O'Neill, Benjamin Sanderson, Detlef van Vuuren, Keywan Riahi, Malte Meinshausen, Zebedee Nicholls, Katarzyna B. Tokarska, George Hurtt, Elmar Kriegler, Jean-Francois Lamarque, Gerald Meehl, Richard Moss, Susanne E. Bauer, Olivier Boucher, Victor Brovkin, Young-Hwa Byun, Martin Dix, Silvio Gualdi, Huan Guo, Jasmin G. John, Slava Kharin, YoungHo Kim, Tsuyoshi Koshiro, Libin Ma, Dirk Olivié, Swapna Panickal, Fangli Qiao, Xinyao Rong, Nan Rosenbloom, Martin Schupfner, Roland Séférian, Alistair Sellar, Tido Semmler, Xiaoying Shi, Zhenya Song, Christian Steger, Ronald Stouffer, Neil Swart, Kaoru Tachiiri, Qi Tang, Hiroaki Tatebe, Aurore Voldoire, Evgeny Volodin, Klaus Wyser, Xiaoge Xin, Shuting Yang, Yongqiang Yu, and Tilo Ziehn
Earth Syst. Dynam., 12, 253–293, https://doi.org/10.5194/esd-12-253-2021, https://doi.org/10.5194/esd-12-253-2021, 2021
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We present an overview of CMIP6 ScenarioMIP outcomes from up to 38 participating ESMs according to the new SSP-based scenarios. Average temperature and precipitation projections according to a wide range of forcings, spanning a wider range than the CMIP5 projections, are documented as global averages and geographic patterns. Times of crossing various warming levels are computed, together with benefits of mitigation for selected pairs of scenarios. Comparisons with CMIP5 are also discussed.
Ghassan Taha, Robert Loughman, Tong Zhu, Larry Thomason, Jayanta Kar, Landon Rieger, and Adam Bourassa
Atmos. Meas. Tech., 14, 1015–1036, https://doi.org/10.5194/amt-14-1015-2021, https://doi.org/10.5194/amt-14-1015-2021, 2021
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This work describes the newly released OMPS LP aerosol extinction profile multi-wavelength Version 2.0 algorithm and dataset. It is shown that the V2.0 aerosols exhibit significant improvements in OMPS LP retrieval performance in the Southern Hemisphere and at lower altitudes. The new product is compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies.
Larry W. Thomason, Mahesh Kovilakam, Anja Schmidt, Christian von Savigny, Travis Knepp, and Landon Rieger
Atmos. Chem. Phys., 21, 1143–1158, https://doi.org/10.5194/acp-21-1143-2021, https://doi.org/10.5194/acp-21-1143-2021, 2021
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Measurements of the impact of volcanic eruptions on stratospheric aerosol loading by space-based instruments show show a fairly well-behaved relationship between the magnitude and the apparent changes to aerosol size over several orders of magnitude. This directly measured relationship provides a unique opportunity to verify the performance of interactive aerosol models used in climate models.
Kine Onsum Moseid, Michael Schulz, Trude Storelvmo, Ingeborg Rian Julsrud, Dirk Olivié, Pierre Nabat, Martin Wild, Jason N. S. Cole, Toshihiko Takemura, Naga Oshima, Susanne E. Bauer, and Guillaume Gastineau
Atmos. Chem. Phys., 20, 16023–16040, https://doi.org/10.5194/acp-20-16023-2020, https://doi.org/10.5194/acp-20-16023-2020, 2020
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In this study we compare solar radiation at the surface from observations and Earth system models from 1961 to 2014. We find that the models do not reproduce the so-called
global dimmingas found in observations. Only model experiments with anthropogenic aerosol emissions display any dimming at all. The discrepancies between observations and models are largest in China, which we suggest is in part due to erroneous aerosol precursor emission inventories in the emission dataset used for CMIP6.
Christopher J. Smith, Ryan J. Kramer, Gunnar Myhre, Kari Alterskjær, William Collins, Adriana Sima, Olivier Boucher, Jean-Louis Dufresne, Pierre Nabat, Martine Michou, Seiji Yukimoto, Jason Cole, David Paynter, Hideo Shiogama, Fiona M. O'Connor, Eddy Robertson, Andy Wiltshire, Timothy Andrews, Cécile Hannay, Ron Miller, Larissa Nazarenko, Alf Kirkevåg, Dirk Olivié, Stephanie Fiedler, Anna Lewinschal, Chloe Mackallah, Martin Dix, Robert Pincus, and Piers M. Forster
Atmos. Chem. Phys., 20, 9591–9618, https://doi.org/10.5194/acp-20-9591-2020, https://doi.org/10.5194/acp-20-9591-2020, 2020
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The spread in effective radiative forcing for both CO2 and aerosols is narrower in the latest CMIP6 (Coupled Model Intercomparison Project) generation than in CMIP5. For the case of CO2 it is likely that model radiation parameterisations have improved. Tropospheric and stratospheric radiative adjustments to the forcing behave differently for different forcing agents, and there is still significant diversity in how clouds respond to forcings, particularly for total anthropogenic forcing.
Prodromos Zanis, Dimitris Akritidis, Aristeidis K. Georgoulias, Robert J. Allen, Susanne E. Bauer, Olivier Boucher, Jason Cole, Ben Johnson, Makoto Deushi, Martine Michou, Jane Mulcahy, Pierre Nabat, Dirk Olivié, Naga Oshima, Adriana Sima, Michael Schulz, Toshihiko Takemura, and Konstantinos Tsigaridis
Atmos. Chem. Phys., 20, 8381–8404, https://doi.org/10.5194/acp-20-8381-2020, https://doi.org/10.5194/acp-20-8381-2020, 2020
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In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014.
Duane Waliser, Peter J. Gleckler, Robert Ferraro, Karl E. Taylor, Sasha Ames, James Biard, Michael G. Bosilovich, Otis Brown, Helene Chepfer, Luca Cinquini, Paul J. Durack, Veronika Eyring, Pierre-Philippe Mathieu, Tsengdar Lee, Simon Pinnock, Gerald L. Potter, Michel Rixen, Roger Saunders, Jörg Schulz, Jean-Noël Thépaut, and Matthias Tuma
Geosci. Model Dev., 13, 2945–2958, https://doi.org/10.5194/gmd-13-2945-2020, https://doi.org/10.5194/gmd-13-2945-2020, 2020
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This paper provides an update to an international research activity whose objective is to facilitate access to satellite and other types of regional and global datasets for evaluating global models used to produce 21st century climate projections.
Zhipeng Qu, Yi Huang, Paul A. Vaillancourt, Jason N. S. Cole, Jason A. Milbrandt, Man-Kong Yau, Kaley Walker, and Jean de Grandpré
Atmos. Chem. Phys., 20, 2143–2159, https://doi.org/10.5194/acp-20-2143-2020, https://doi.org/10.5194/acp-20-2143-2020, 2020
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This study aims to better understand the mechanism of transport of water vapour through the mid-latitude tropopause. The results affirm the strong influence of overshooting convection on lower-stratospheric water vapour and highlight the importance of both dynamics and cloud microphysics in simulating water vapour distribution in the region of the upper troposphere–lower stratosphere.
Martin Juckes, Karl E. Taylor, Paul J. Durack, Bryan Lawrence, Matthew S. Mizielinski, Alison Pamment, Jean-Yves Peterschmitt, Michel Rixen, and Stéphane Sénési
Geosci. Model Dev., 13, 201–224, https://doi.org/10.5194/gmd-13-201-2020, https://doi.org/10.5194/gmd-13-201-2020, 2020
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The data request of the Coupled Model Intercomparison Project Phase 6 (CMIP6) defines all the quantities
from CMIP6 simulations that should be archived. The building blocks and structure of the CMIP6 Data Request, which has been constructed to meet these challenges, are described in this paper.
Joelle Dionne, Knut von Salzen, Jason Cole, Rashed Mahmood, W. Richard Leaitch, Glen Lesins, Ian Folkins, and Rachel Y.-W. Chang
Atmos. Chem. Phys., 20, 29–43, https://doi.org/10.5194/acp-20-29-2020, https://doi.org/10.5194/acp-20-29-2020, 2020
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Low clouds persist in the summer Arctic, with important consequences for the radiation budget. We found that the ability of precipitation parameterizations to reproduce observed cloud properties was more variable than their ability to represent radiative effects. Our results show that cloud properties and their parameterizations affect the radiative effects of clouds.
Neil C. Swart, Jason N. S. Cole, Viatcheslav V. Kharin, Mike Lazare, John F. Scinocca, Nathan P. Gillett, James Anstey, Vivek Arora, James R. Christian, Sarah Hanna, Yanjun Jiao, Warren G. Lee, Fouad Majaess, Oleg A. Saenko, Christian Seiler, Clint Seinen, Andrew Shao, Michael Sigmond, Larry Solheim, Knut von Salzen, Duo Yang, and Barbara Winter
Geosci. Model Dev., 12, 4823–4873, https://doi.org/10.5194/gmd-12-4823-2019, https://doi.org/10.5194/gmd-12-4823-2019, 2019
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The Canadian Earth System Model version 5 (CanESM5) is a global model developed to simulate historical climate change and variability, to make centennial-scale projections of future climate, and to produce initialized seasonal and decadal predictions. This paper describes the model components and quantifies the model performance. CanESM5 simulations contribute to the Coupled Model Intercomparison Project phase 6 (CMIP6) and will be employed for climate science applications in Canada.
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
Geosci. Model Dev., 12, 4375–4385, https://doi.org/10.5194/gmd-12-4375-2019, https://doi.org/10.5194/gmd-12-4375-2019, 2019
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Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.
Qi Tang, Stephen A. Klein, Shaocheng Xie, Wuyin Lin, Jean-Christophe Golaz, Erika L. Roesler, Mark A. Taylor, Philip J. Rasch, David C. Bader, Larry K. Berg, Peter Caldwell, Scott E. Giangrande, Richard B. Neale, Yun Qian, Laura D. Riihimaki, Charles S. Zender, Yuying Zhang, and Xue Zheng
Geosci. Model Dev., 12, 2679–2706, https://doi.org/10.5194/gmd-12-2679-2019, https://doi.org/10.5194/gmd-12-2679-2019, 2019
Elizaveta Malinina, Alexei Rozanov, Landon Rieger, Adam Bourassa, Heinrich Bovensmann, John P. Burrows, and Doug Degenstein
Atmos. Meas. Tech., 12, 3485–3502, https://doi.org/10.5194/amt-12-3485-2019, https://doi.org/10.5194/amt-12-3485-2019, 2019
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This paper covers the problems related to the derivation of aerosol extinction coefficients and Ångström exponents from space-borne instruments working in limb and occultation viewing geometries. Aerosol extinction coefficients and Ångström exponents were calculated from the SCIAMACHY aerosol particle size data set. The results were compared with the data from SAGE II and OSIRIS. The Ångström exponent in the tropical regions and its dependency on particle size parameters are discussed.
Toni Mitovski, Jason N. S. Cole, Norman A. McFarlane, Knut von Salzen, and Guang J. Zhang
Geosci. Model Dev., 12, 2107–2117, https://doi.org/10.5194/gmd-12-2107-2019, https://doi.org/10.5194/gmd-12-2107-2019, 2019
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Changes in the large-scale environment during convective precipitation events simulated by the Canadian Atmospheric Model (CanAM4.3) are compared against those simulated by the super-parameterized Community Atmosphere Model (spCAM5). Compared to spCAM5, CanAM4.3 underestimates the frequency of extreme convective precipitation and the duration of convective events are 50 % shorter. The dependence of precipitation on changes in the large-scale environment differs between CanAM4.3 and spCAM5.
Doug M. Smith, James A. Screen, Clara Deser, Judah Cohen, John C. Fyfe, Javier García-Serrano, Thomas Jung, Vladimir Kattsov, Daniela Matei, Rym Msadek, Yannick Peings, Michael Sigmond, Jinro Ukita, Jin-Ho Yoon, and Xiangdong Zhang
Geosci. Model Dev., 12, 1139–1164, https://doi.org/10.5194/gmd-12-1139-2019, https://doi.org/10.5194/gmd-12-1139-2019, 2019
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The Polar Amplification Model Intercomparison Project (PAMIP) is an endorsed contribution to the sixth Coupled Model Intercomparison Project (CMIP6). It will investigate the causes and global consequences of polar amplification through coordinated multi-model numerical experiments. This paper documents the experimental protocol.
Ben Kravitz, Philip J. Rasch, Hailong Wang, Alan Robock, Corey Gabriel, Olivier Boucher, Jason N. S. Cole, Jim Haywood, Duoying Ji, Andy Jones, Andrew Lenton, John C. Moore, Helene Muri, Ulrike Niemeier, Steven Phipps, Hauke Schmidt, Shingo Watanabe, Shuting Yang, and Jin-Ho Yoon
Atmos. Chem. Phys., 18, 13097–13113, https://doi.org/10.5194/acp-18-13097-2018, https://doi.org/10.5194/acp-18-13097-2018, 2018
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Marine cloud brightening has been proposed as a means of geoengineering/climate intervention, or deliberately altering the climate system to offset anthropogenic climate change. In idealized simulations that highlight contrasts between land and ocean, we find that the globe warms, including the ocean due to transport of heat from land. This study reinforces that no net energy input into the Earth system does not mean that temperature will necessarily remain unchanged.
Venkatramani Balaji, Karl E. Taylor, Martin Juckes, Bryan N. Lawrence, Paul J. Durack, Michael Lautenschlager, Chris Blanton, Luca Cinquini, Sébastien Denvil, Mark Elkington, Francesca Guglielmo, Eric Guilyardi, David Hassell, Slava Kharin, Stefan Kindermann, Sergey Nikonov, Aparna Radhakrishnan, Martina Stockhause, Tobias Weigel, and Dean Williams
Geosci. Model Dev., 11, 3659–3680, https://doi.org/10.5194/gmd-11-3659-2018, https://doi.org/10.5194/gmd-11-3659-2018, 2018
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We present recommendations for the global data infrastructure needed to support CMIP scientific design and its future growth and evolution. We follow a dataset-centric design less prone to systemic failure. Scientific publication in the digital age is evolving to make data a primary scientific output, alongside articles. We design toward that future scientific data ecosystem, informed by the need for reproducibility, data provenance, future data technologies, and measures of costs and benefits.
Christoph Brühl, Jennifer Schallock, Klaus Klingmüller, Charles Robert, Christine Bingen, Lieven Clarisse, Andreas Heckel, Peter North, and Landon Rieger
Atmos. Chem. Phys., 18, 12845–12857, https://doi.org/10.5194/acp-18-12845-2018, https://doi.org/10.5194/acp-18-12845-2018, 2018
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Use of multi-instrument satellite data is important to get consistent simulations of aerosol radiative forcing by a complex chemistry climate model, here with a main focus on the lower stratosphere. The satellite data at different wavelengths together with the patterns in the simulated size distribution point to a significant contribution from moist mineral dust lifted to the tropopause region by the Asian summer monsoon.
Duoying Ji, Songsong Fang, Charles L. Curry, Hiroki Kashimura, Shingo Watanabe, Jason N. S. Cole, Andrew Lenton, Helene Muri, Ben Kravitz, and John C. Moore
Atmos. Chem. Phys., 18, 10133–10156, https://doi.org/10.5194/acp-18-10133-2018, https://doi.org/10.5194/acp-18-10133-2018, 2018
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We examine extreme temperature and precipitation under climate-model-simulated solar dimming and stratospheric aerosol injection geoengineering schemes. Both types of geoengineering lead to lower minimum temperatures at higher latitudes and greater cooling of minimum temperatures and maximum temperatures over land compared with oceans. Stratospheric aerosol injection is more effective in reducing tropical extreme precipitation, while solar dimming is more effective over extra-tropical regions.
Landon A. Rieger, Elizaveta P. Malinina, Alexei V. Rozanov, John P. Burrows, Adam E. Bourassa, and Doug A. Degenstein
Atmos. Meas. Tech., 11, 3433–3445, https://doi.org/10.5194/amt-11-3433-2018, https://doi.org/10.5194/amt-11-3433-2018, 2018
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This paper compares aerosol extinction records from two limb scattering instruments, OSIRIS and SCIAMACHY, to that from the occultation instrument SAGE II. Differences are investigated through modelling and retrieval studies and important sources of systematic errors are quantified. It is found that the largest biases come from uncertainties in the aerosol size distribution and the aerosol particle concentration at altitudes above 30 km.
Kai Zhang, Philip J. Rasch, Mark A. Taylor, Hui Wan, Ruby Leung, Po-Lun Ma, Jean-Christophe Golaz, Jon Wolfe, Wuyin Lin, Balwinder Singh, Susannah Burrows, Jin-Ho Yoon, Hailong Wang, Yun Qian, Qi Tang, Peter Caldwell, and Shaocheng Xie
Geosci. Model Dev., 11, 1971–1988, https://doi.org/10.5194/gmd-11-1971-2018, https://doi.org/10.5194/gmd-11-1971-2018, 2018
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The conservation of total water is an important numerical feature for global Earth system models. Even small conservation problems in the water budget can lead to systematic errors in century-long simulations for sea level rise projection. This study quantifies and reduces various sources of water conservation error in the atmosphere component of the Energy Exascale Earth System Model.
Daniel J. Zawada, Landon A. Rieger, Adam E. Bourassa, and Douglas A. Degenstein
Atmos. Meas. Tech., 11, 2375–2393, https://doi.org/10.5194/amt-11-2375-2018, https://doi.org/10.5194/amt-11-2375-2018, 2018
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The Ozone Mapping and Profiler Suite Limb Profiler measures scattered sunlight, which is then inverted to obtain vertical profiles of ozone in the atmosphere. We have developed a new algorithm for inverting the data which is better suited for areas with large horizontal ozone gradients, such as the polar vortex. Data from the full currently 5-year mission have been processed and are publicly available.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
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Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Larry W. Thomason, Nicholas Ernest, Luis Millán, Landon Rieger, Adam Bourassa, Jean-Paul Vernier, Gloria Manney, Beiping Luo, Florian Arfeuille, and Thomas Peter
Earth Syst. Sci. Data, 10, 469–492, https://doi.org/10.5194/essd-10-469-2018, https://doi.org/10.5194/essd-10-469-2018, 2018
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We describe the construction of a continuous 38-year record of stratospheric aerosol optical properties. The Global Space-based Stratospheric Aerosol Climatology, or GloSSAC, provided the input data to the construction of the Climate Model Intercomparison Project stratospheric aerosol forcing data set (1979 to 2014) and is now extended through 2016. GloSSAC focuses on the the SAGE series of instruments through mid-2005 and on OSIRIS and CALIPSO after that time.
Adam E. Bourassa, Chris Z. Roth, Daniel J. Zawada, Landon A. Rieger, Chris A. McLinden, and Douglas A. Degenstein
Atmos. Meas. Tech., 11, 489–498, https://doi.org/10.5194/amt-11-489-2018, https://doi.org/10.5194/amt-11-489-2018, 2018
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OSIRIS satellite measurements of ozone in the stratosphere are corrected for slowly varying errors. These changes make the OSIRIS data compare better with other satellite measurements over the long term and make an impact on our understanding of the recovery of the ozone layer.
Camilla W. Stjern, Helene Muri, Lars Ahlm, Olivier Boucher, Jason N. S. Cole, Duoying Ji, Andy Jones, Jim Haywood, Ben Kravitz, Andrew Lenton, John C. Moore, Ulrike Niemeier, Steven J. Phipps, Hauke Schmidt, Shingo Watanabe, and Jón Egill Kristjánsson
Atmos. Chem. Phys., 18, 621–634, https://doi.org/10.5194/acp-18-621-2018, https://doi.org/10.5194/acp-18-621-2018, 2018
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Marine cloud brightening (MCB) has been proposed to help limit global warming. We present here the first multi-model assessment of idealized MCB simulations from the Geoengineering Model Intercomparison Project. While all models predict a global cooling as intended, there is considerable spread between the models both in terms of radiative forcing and the climate response, largely linked to the substantial differences in the models' representation of clouds.
Cristen Adams, Adam E. Bourassa, Chris A. McLinden, Chris E. Sioris, Thomas von Clarmann, Bernd Funke, Landon A. Rieger, and Douglas A. Degenstein
Atmos. Chem. Phys., 17, 8063–8080, https://doi.org/10.5194/acp-17-8063-2017, https://doi.org/10.5194/acp-17-8063-2017, 2017
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We measured the relationship between volcanic aerosol and trace gases in the stratosphere using the OSIRIS and MIPAS satellite instruments between 2002 and 2014. We found that levels of stratospheric NO2 and N2O5 both decreased significantly in the presence of volcanic aerosol. These decreases were consistent with the modeling results.
Christopher E. Sioris, Landon A. Rieger, Nicholas D. Lloyd, Adam E. Bourassa, Chris Z. Roth, Douglas A. Degenstein, Claude Camy-Peyret, Klaus Pfeilsticker, Gwenaël Berthet, Valéry Catoire, Florence Goutail, Jean-Pierre Pommereau, and Chris A. McLinden
Atmos. Meas. Tech., 10, 1155–1168, https://doi.org/10.5194/amt-10-1155-2017, https://doi.org/10.5194/amt-10-1155-2017, 2017
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A new OSIRIS NO2 retrieval algorithm is described and validated using > 40 balloon-based profile measurements. The validation results indicate a slight improvement relative to the existing operational algorithm in terms of the bias versus the balloon data, particularly in the lower stratosphere. The implication is that this new algorithm should replace the operational one. The motivation was to combine spectral fitting and the SaskTRAN radiative transfer model to achieve an improved product.
Hiroki Kashimura, Manabu Abe, Shingo Watanabe, Takashi Sekiya, Duoying Ji, John C. Moore, Jason N. S. Cole, and Ben Kravitz
Atmos. Chem. Phys., 17, 3339–3356, https://doi.org/10.5194/acp-17-3339-2017, https://doi.org/10.5194/acp-17-3339-2017, 2017
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This study analyses shortwave radiation (SW) in the G4 experiment of the Geoengineering Model Intercomparison Project. G4 involves stratospheric injection of 5 Tg yr−1 of SO2 against the RCP4.5 scenario. The global mean forcing of the sulphate geoengineering has an inter-model variablity of −3.6 to −1.6 W m−2, implying a high uncertainty in modelled processes of sulfate aerosols. Changes in water vapour and cloud amounts due to the SO2 injection weaken the forcing at the surface by around 50 %.
Daniel Mitchell, Krishna AchutaRao, Myles Allen, Ingo Bethke, Urs Beyerle, Andrew Ciavarella, Piers M. Forster, Jan Fuglestvedt, Nathan Gillett, Karsten Haustein, William Ingram, Trond Iversen, Viatcheslav Kharin, Nicholas Klingaman, Neil Massey, Erich Fischer, Carl-Friedrich Schleussner, John Scinocca, Øyvind Seland, Hideo Shiogama, Emily Shuckburgh, Sarah Sparrow, Dáithí Stone, Peter Uhe, David Wallom, Michael Wehner, and Rashyd Zaaboul
Geosci. Model Dev., 10, 571–583, https://doi.org/10.5194/gmd-10-571-2017, https://doi.org/10.5194/gmd-10-571-2017, 2017
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This paper provides an experimental design to assess impacts of a world that is 1.5 °C warmer than at pre-industrial levels. The design is a new way to approach impacts from the climate community, and aims to answer questions related to the recent Paris Agreement. In particular the paper provides a method for studying extreme events under relatively high mitigation scenarios.
Sergey M. Khaykin, Sophie Godin-Beekmann, Philippe Keckhut, Alain Hauchecorne, Julien Jumelet, Jean-Paul Vernier, Adam Bourassa, Doug A. Degenstein, Landon A. Rieger, Christine Bingen, Filip Vanhellemont, Charles Robert, Matthew DeLand, and Pawan K. Bhartia
Atmos. Chem. Phys., 17, 1829–1845, https://doi.org/10.5194/acp-17-1829-2017, https://doi.org/10.5194/acp-17-1829-2017, 2017
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The article is devoted to the long-term evolution and variability of stratospheric aerosol, which plays an important role in climate change and the ozone layer. We use 22-year long continuous observations using laser radar soundings in southern France and satellite-based observations to distinguish between natural aerosol variability (caused by volcanic eruptions) and human-induced change in aerosol concentration. An influence of growing pollution above Asia on stratospheric aerosol is found.
Nathan P. Gillett, Hideo Shiogama, Bernd Funke, Gabriele Hegerl, Reto Knutti, Katja Matthes, Benjamin D. Santer, Daithi Stone, and Claudia Tebaldi
Geosci. Model Dev., 9, 3685–3697, https://doi.org/10.5194/gmd-9-3685-2016, https://doi.org/10.5194/gmd-9-3685-2016, 2016
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Detection and attribution of climate change is the process of determining the causes of observed climate changes, which has underpinned key conclusions on the role of human influence on climate in the reports of the Intergovernmental Panel on Climate Change (IPCC). This paper describes a coordinated set of climate model experiments that will form part of the Sixth Coupled Model Intercomparison Project and will support improved attribution of climate change in the next IPCC report.
Stephen M. Griffies, Gokhan Danabasoglu, Paul J. Durack, Alistair J. Adcroft, V. Balaji, Claus W. Böning, Eric P. Chassignet, Enrique Curchitser, Julie Deshayes, Helge Drange, Baylor Fox-Kemper, Peter J. Gleckler, Jonathan M. Gregory, Helmuth Haak, Robert W. Hallberg, Patrick Heimbach, Helene T. Hewitt, David M. Holland, Tatiana Ilyina, Johann H. Jungclaus, Yoshiki Komuro, John P. Krasting, William G. Large, Simon J. Marsland, Simona Masina, Trevor J. McDougall, A. J. George Nurser, James C. Orr, Anna Pirani, Fangli Qiao, Ronald J. Stouffer, Karl E. Taylor, Anne Marie Treguier, Hiroyuki Tsujino, Petteri Uotila, Maria Valdivieso, Qiang Wang, Michael Winton, and Stephen G. Yeager
Geosci. Model Dev., 9, 3231–3296, https://doi.org/10.5194/gmd-9-3231-2016, https://doi.org/10.5194/gmd-9-3231-2016, 2016
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The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This document defines OMIP and details a protocol both for simulating global ocean/sea-ice models and for analysing their output.
M. Namazi, K. von Salzen, and J. N. S. Cole
Atmos. Chem. Phys., 15, 10887–10904, https://doi.org/10.5194/acp-15-10887-2015, https://doi.org/10.5194/acp-15-10887-2015, 2015
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A new parameterization of black carbon in snow in the Canadian Atmospheric Global Climate Model provides realistic simulations of radiative forcings. BC emissions and simulated BC concentrations in snow have changed substantially in recent decades. However, simulated impacts of changes in BC concentrations in snow from 1950-1959 to 2000-2009 on snow reflectivity and snow extent in the Northern Hemisphere are very small, with few regional exceptions, in contrast to results from earlier studies.
D. J. Zawada, S. R. Dueck, L. A. Rieger, A. E. Bourassa, N. D. Lloyd, and D. A. Degenstein
Atmos. Meas. Tech., 8, 2609–2623, https://doi.org/10.5194/amt-8-2609-2015, https://doi.org/10.5194/amt-8-2609-2015, 2015
P. Hess, D. Kinnison, and Q. Tang
Atmos. Chem. Phys., 15, 2341–2365, https://doi.org/10.5194/acp-15-2341-2015, https://doi.org/10.5194/acp-15-2341-2015, 2015
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Using a series of model simulations, we find that at widespread NH extratropical locations, interannual tropospheric ozone variability is largely determined by the transport of ozone from the stratosphere. This has implications in the interpretation of measured tropospheric ozone variability in light of changes in the emissions of ozone precursors and in the response of tropospheric ozone to climate change.
L. A. Rieger, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 7, 777–780, https://doi.org/10.5194/amt-7-777-2014, https://doi.org/10.5194/amt-7-777-2014, 2014
L. A. Rieger, A. E. Bourassa, and D. A. Degenstein
Atmos. Meas. Tech., 7, 507–522, https://doi.org/10.5194/amt-7-507-2014, https://doi.org/10.5194/amt-7-507-2014, 2014
Ø. Hodnebrog, T. K. Berntsen, O. Dessens, M. Gauss, V. Grewe, I. S. A. Isaksen, B. Koffi, G. Myhre, D. Olivié, M. J. Prather, F. Stordal, S. Szopa, Q. Tang, P. van Velthoven, and J. E. Williams
Atmos. Chem. Phys., 12, 12211–12225, https://doi.org/10.5194/acp-12-12211-2012, https://doi.org/10.5194/acp-12-12211-2012, 2012
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ICON-Sapphire: simulating the components of the Earth system and their interactions at kilometer and subkilometer scales
Ocean Modeling with Adaptive REsolution (OMARE; version 1.0) – refactoring the NEMO model (version 4.0.1) with the parallel computing framework of JASMIN – Part 1: Adaptive grid refinement in an idealized double-gyre case
Monthly-scale extended predictions using the atmospheric model coupled with a slab ocean
stoPET v1.0: a stochastic potential evapotranspiration generator for simulation of climate change impacts
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1
Evaluation of native Earth system model output with ESMValTool v2.6.0
WRF–ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer
The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system
Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2
Accelerated photosynthesis routine in LPJmL4
Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system
Temperature forecasting by deep learning methods
Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios
Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro
Implementation and evaluation of the GEOS-Chem chemistry module version 13.1.2 within the Community Earth System Model v2.1
Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2
Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)
Impact of increased resolution on the representation of the Canary upwelling system in climate models
Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations
Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)
Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at planetary boundary layer gray-zone resolution: a case study over the coastal regions of North China
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
SURFER v2.0: a flexible and simple model linking anthropogenic CO2 emissions and solar radiation modification to ocean acidification and sea level rise
Analysis of Systematic Biases in Tropospheric Hydrostatic Delay Models and Construction of Correction Model
A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data
Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics
Impacts of the ice-particle size distribution shape parameter on climate simulations with the Community Atmosphere Model Version 6 (CAM6)
A modeling framework to understand historical and projected ocean climate change in large coupled ensembles
TriCCo v1.1.0 – a cubulation-based method for computing connected components on triangular grids
Estimation of missing building height in OpenStreetMap data: a French case study using GeoClimate 0.0.1
The Moist Quasi-Geostrophic Coupled Model: MQ-GCM 2.0
Transport parameterization of the Polar SWIFT model (version 2)
Analog data assimilation for the selection of suitable general circulation models
Uncertainty and sensitivity analysis for probabilistic weather and climate-risk modelling: an implementation in CLIMADA v.3.1.0
Grid refinement in ICON v2.6.4
Simulating marine neodymium isotope distributions using ND v1.0 coupled to the ocean component of the FAMOUS-MOSES1 climate model: sensitivities to reversible scavenging efficiency and benthic source distributions
Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset
The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)
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
HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor
LPJ-GUESS/LSMv1.0: a next-generation land surface model with high ecological realism
Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44
Intercomparison of four algorithms for detecting tropical cyclones using ERA5
Inland lake temperature initialization via coupled cycling with atmospheric data assimilation
wavetrisk-2.1: an adaptive dynamical core for ocean modelling
Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime
AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model
Fa Li, Qing Zhu, William J. Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James T. Randerson
Geosci. Model Dev., 16, 869–884, https://doi.org/10.5194/gmd-16-869-2023, https://doi.org/10.5194/gmd-16-869-2023, 2023
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We developed an interpretable machine learning model to predict sub-seasonal and near-future wildfire-burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 months) of local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning models results in highly accurate predictions of wildfire-burned areas; this will also help develop relevant early-warning and management systems for tropical wildfires.
Edmund P. Meredith, Uwe Ulbrich, and Henning W. Rust
Geosci. Model Dev., 16, 851–867, https://doi.org/10.5194/gmd-16-851-2023, https://doi.org/10.5194/gmd-16-851-2023, 2023
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Cell-tracking algorithms allow for the study of properties of a convective cell across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm's criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Cathy Hohenegger, Peter Korn, Leonidas Linardakis, René Redler, Reiner Schnur, Panagiotis Adamidis, Jiawei Bao, Swantje Bastin, Milad Behravesh, Martin Bergemann, Joachim Biercamp, Hendryk Bockelmann, Renate Brokopf, Nils Brüggemann, Lucas Casaroli, Fatemeh Chegini, George Datseris, Monika Esch, Geet George, Marco Giorgetta, Oliver Gutjahr, Helmuth Haak, Moritz Hanke, Tatiana Ilyina, Thomas Jahns, Johann Jungclaus, Marcel Kern, Daniel Klocke, Lukas Kluft, Tobias Kölling, Luis Kornblueh, Sergey Kosukhin, Clarissa Kroll, Junhong Lee, Thorsten Mauritsen, Carolin Mehlmann, Theresa Mieslinger, Ann Kristin Naumann, Laura Paccini, Angel Peinado, Divya Sri Praturi, Dian Putrasahan, Sebastian Rast, Thomas Riddick, Niklas Roeber, Hauke Schmidt, Uwe Schulzweida, Florian Schütte, Hans Segura, Radomyra Shevchenko, Vikram Singh, Mia Specht, Claudia Christine Stephan, Jin-Song von Storch, Raphaela Vogel, Christian Wengel, Marius Winkler, Florian Ziemen, Jochem Marotzke, and Bjorn Stevens
Geosci. Model Dev., 16, 779–811, https://doi.org/10.5194/gmd-16-779-2023, https://doi.org/10.5194/gmd-16-779-2023, 2023
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Models of the Earth system used to understand climate and predict its change typically employ a grid spacing of about 100 km. Yet, many atmospheric and oceanic processes occur on much smaller scales. In this study, we present a new model configuration designed for the simulation of the components of the Earth system and their interactions at kilometer and smaller scales, allowing an explicit representation of the main drivers of the flow of energy and matter by solving the underlying equations.
Yan Zhang, Xuantong Wang, Yuhao Sun, Chenhui Ning, Shiming Xu, Hengbin An, Dehong Tang, Hong Guo, Hao Yang, Ye Pu, Bo Jiang, and Bin Wang
Geosci. Model Dev., 16, 679–704, https://doi.org/10.5194/gmd-16-679-2023, https://doi.org/10.5194/gmd-16-679-2023, 2023
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We construct a new ocean model, OMARE, that can carry out multi-scale ocean simulation with adaptive mesh refinement. OMARE is based on the refactorization of NEMO with a third-party, high-performance piece of middleware. We report the porting process and experiments of an idealized western-boundary current system. The new model simulates turbulent and temporally varying mesoscale and submesoscale processes via adaptive refinement. Related topics and future work with OMARE are also discussed.
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 16, 705–717, https://doi.org/10.5194/gmd-16-705-2023, https://doi.org/10.5194/gmd-16-705-2023, 2023
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To improve the numerical model predictability of monthly extended-range scales, we use the simplified slab ocean model (SOM) to restrict the complicated sea surface temperature (SST) bias from a 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have better performance than the WRF-ROMS, which has a significant impact on the atmosphere. For extreme weather events such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.
Dagmawi Teklu Asfaw, Michael Bliss Singer, Rafael Rosolem, David MacLeod, Mark Cuthbert, Edisson Quichimbo Miguitama, Manuel F. Rios Gaona, and Katerina Michaelides
Geosci. Model Dev., 16, 557–571, https://doi.org/10.5194/gmd-16-557-2023, https://doi.org/10.5194/gmd-16-557-2023, 2023
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stoPET is a new stochastic potential evapotranspiration (PET) generator for the globe at hourly resolution. Many stochastic weather generators are used to generate stochastic rainfall time series; however, no such model exists for stochastically generating plausible PET time series. As such, stoPET represents a significant methodological advance. stoPET generate many realizations of PET to conduct climate studies related to the water balance, agriculture, water resources, and ecology.
Markus Köhli, Martin Schrön, Steffen Zacharias, and Ulrich Schmidt
Geosci. Model Dev., 16, 449–477, https://doi.org/10.5194/gmd-16-449-2023, https://doi.org/10.5194/gmd-16-449-2023, 2023
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In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev., 16, 335–352, https://doi.org/10.5194/gmd-16-335-2023, https://doi.org/10.5194/gmd-16-335-2023, 2023
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Models that are used to simulate and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper, we develop a novel framework that increases the horizontal and vertical resolutions only for areas of the globe that contain stratocumulus, hence reducing the model runtime while providing better results.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev., 16, 315–333, https://doi.org/10.5194/gmd-16-315-2023, https://doi.org/10.5194/gmd-16-315-2023, 2023
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool was designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows for reading and processing native climate model output, i.e., data that have not been reformatted before.
Xiaohui Zhong, Zhijian Ma, Yichen Yao, Lifei Xu, Yuan Wu, and Zhibin Wang
Geosci. Model Dev., 16, 199–209, https://doi.org/10.5194/gmd-16-199-2023, https://doi.org/10.5194/gmd-16-199-2023, 2023
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More and more researchers use deep learning models to replace physics-based parameterizations to accelerate weather simulations. However, embedding the ML models within the weather models is difficult as they are implemented in different languages. This work proposes a coupling framework to allow ML-based parameterizations to be coupled with the Weather Research and Forecasting (WRF) model. We also demonstrate using the coupler to couple the ML-based radiation schemes with the WRF model.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
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Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Ming Yin, Yilun Han, Yong Wang, Wenqi Sun, Jianbo Deng, Daoming Wei, Ying Kong, and Bin Wang
Geosci. Model Dev., 16, 135–156, https://doi.org/10.5194/gmd-16-135-2023, https://doi.org/10.5194/gmd-16-135-2023, 2023
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All global climate models (GCMs) use the grid-averaged surface heat fluxes to drive the atmosphere, and thus their horizontal variations within the grid cell are averaged out. In this regard, a novel scheme considering the variation and partitioning of the surface heat fluxes within the grid cell is developed. The scheme reduces the long-standing rainfall biases on the southern and eastern margins of the Tibetan Plateau. The performance of key variables at the global scale is also evaluated.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
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In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Geosci. Model Dev., 15, 8931–8956, https://doi.org/10.5194/gmd-15-8931-2022, https://doi.org/10.5194/gmd-15-8931-2022, 2022
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Inspired by the success of deep learning in various domains, we test the applicability of video prediction methods by generative adversarial network (GAN)-based deep learning to predict the 2 m temperature over Europe. Our video prediction models have skill in predicting the diurnal cycle of 2 m temperature up to 12 h ahead. Complemented by probing the relevance of several model parameters, this study confirms the potential of deep learning in meteorological forecasting applications.
Thomas Bossy, Thomas Gasser, and Philippe Ciais
Geosci. Model Dev., 15, 8831–8868, https://doi.org/10.5194/gmd-15-8831-2022, https://doi.org/10.5194/gmd-15-8831-2022, 2022
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We developed a new simple climate model designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: calibration using Bayesian inference, the possibility of coupling with integrated assessment models, and the capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model and its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022, https://doi.org/10.5194/gmd-15-8809-2022, 2022
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In this study, we implement a hardening mortality scheme into CTSM5.0-FATES-Hydro and evaluate how it impacts plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Rainer Schneck, Veronika Gayler, Julia E. M. S. Nabel, Thomas Raddatz, Christian H. Reick, and Reiner Schnur
Geosci. Model Dev., 15, 8581–8611, https://doi.org/10.5194/gmd-15-8581-2022, https://doi.org/10.5194/gmd-15-8581-2022, 2022
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The versions of ICON-A and ICON-Land/JSBACHv4 used for this study constitute the first milestone in the development of the new ICON Earth System Model ICON-ESM. JSBACHv4 is the successor of JSBACHv3, and most of the parameterizations of JSBACHv4 are re-implementations from JSBACHv3. We assess and compare the performance of JSBACHv4 and JSBACHv3. Overall, the JSBACHv4 results are as good as JSBACHv3, but both models reveal the same main shortcomings, e.g. the depiction of the leaf area index.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
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We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Adama Sylla, Emilia Sanchez Gomez, Juliette Mignot, and Jorge López-Parages
Geosci. Model Dev., 15, 8245–8267, https://doi.org/10.5194/gmd-15-8245-2022, https://doi.org/10.5194/gmd-15-8245-2022, 2022
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Increasing model resolution depends on the subdomain of the Canary upwelling considered. In the Iberian Peninsula, the high-resolution (HR) models do not seem to better simulate the upwelling indices, while in Morocco to the Senegalese coast, the HR models show a clear improvement. Thus increasing the resolution of a global climate model does not necessarily have to be the only way to better represent the climate system. There is still much work to be done in terms of physical parameterizations.
Jadwiga H. Richter, Daniele Visioni, Douglas G. MacMartin, David A. Bailey, Nan Rosenbloom, Brian Dobbins, Walker R. Lee, Mari Tye, and Jean-Francois Lamarque
Geosci. Model Dev., 15, 8221–8243, https://doi.org/10.5194/gmd-15-8221-2022, https://doi.org/10.5194/gmd-15-8221-2022, 2022
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Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI).
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Entao Yu, Rui Bai, Xia Chen, and Lifang Shao
Geosci. Model Dev., 15, 8111–8134, https://doi.org/10.5194/gmd-15-8111-2022, https://doi.org/10.5194/gmd-15-8111-2022, 2022
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A large number of simulations are conducted to investigate how different physical parameterization schemes impact surface wind simulations under stable weather conditions over the coastal regions of North China using the Weather Research and Forecasting model with a horizontal grid spacing of 0.5 km. Results indicate that the simulated wind speed is most sensitive to the planetary boundary layer schemes, followed by short-wave/long-wave radiation schemes and microphysics schemes.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Marina Martínez Montero, Michel Crucifix, Victor Couplet, Nuria Brede, and Nicola Botta
Geosci. Model Dev., 15, 8059–8084, https://doi.org/10.5194/gmd-15-8059-2022, https://doi.org/10.5194/gmd-15-8059-2022, 2022
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We present SURFER, a lightweight model that links CO2 emissions and geoengineering to ocean acidification and sea level rise from glaciers, ocean thermal expansion and Greenland and Antarctic ice sheets. The ice sheet module adequately describes the tipping points of both Greenland and Antarctica. SURFER is understandable, fast, accurate up to several thousands of years, capable of emulating results obtained by state of the art models and well suited for policy analyses.
Haopeng Fan, Siran Li, Zhongmiao Sun, Guorui Xiao, Xinxing Li, and Xiaogang Liu
EGUsphere, https://doi.org/10.5194/egusphere-2022-898, https://doi.org/10.5194/egusphere-2022-898, 2022
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The bias of traditional tropospheric zenith hydrostatic delay (ZHD) model is usually thought negligible, yet it still reaches 10 mm sometimes and would lead to mm-level position errors for space geodetic observations. Therefore, We analyzed the bias’ characteristics and present a grid model to correct the traditional ZHD formula. When we verified the efficiency based on data from ECMWF (European Centre for Medium-Range Weather Forecasts), it turned out that ZHD biases were rectified by ~50 %.
Francisco José Cuesta-Valero, Hugo Beltrami, Stephan Gruber, Almudena García-García, and J. Fidel González-Rouco
Geosci. Model Dev., 15, 7913–7932, https://doi.org/10.5194/gmd-15-7913-2022, https://doi.org/10.5194/gmd-15-7913-2022, 2022
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Inversions of subsurface temperature profiles provide past long-term estimates of ground surface temperature histories and ground heat flux histories at timescales of decades to millennia. Theses estimates complement high-frequency proxy temperature reconstructions and are the basis for studying continental heat storage. We develop and release a new bootstrap method to derive meaningful confidence intervals for the average surface temperature and heat flux histories from any number of profiles.
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, https://doi.org/10.5194/gmd-15-7879-2022, 2022
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We develop a model that integrates an Earth system model with a three-dimensional hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local-scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.
Wentao Zhang, Xiangjun Shi, and Chunsong Lu
Geosci. Model Dev., 15, 7751–7766, https://doi.org/10.5194/gmd-15-7751-2022, https://doi.org/10.5194/gmd-15-7751-2022, 2022
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The two-moment bulk cloud microphysics scheme used in CAM6 was modified to consider the impacts of the ice-crystal size distribution shape parameter (μi). After that, how the μi impacts cloud microphysical processes and then climate simulations is clearly illustrated by offline tests and CAM6 model experiments. Our results and findings are useful for the further development of μi-related parameterizations.
Yona Silvy, Clément Rousset, Eric Guilyardi, Jean-Baptiste Sallée, Juliette Mignot, Christian Ethé, and Gurvan Madec
Geosci. Model Dev., 15, 7683–7713, https://doi.org/10.5194/gmd-15-7683-2022, https://doi.org/10.5194/gmd-15-7683-2022, 2022
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A modeling framework is introduced to understand and decompose the mechanisms causing the ocean temperature, salinity and circulation to change since the pre-industrial period and into 21st century scenarios of global warming. This framework aims to look at the response to changes in the winds and in heat and freshwater exchanges at the ocean interface in global climate models, throughout the 1850–2100 period, to unravel their individual effects on the changing physical structure of the ocean.
Aiko Voigt, Petra Schwer, Noam von Rotberg, and Nicole Knopf
Geosci. Model Dev., 15, 7489–7504, https://doi.org/10.5194/gmd-15-7489-2022, https://doi.org/10.5194/gmd-15-7489-2022, 2022
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In climate science, it is helpful to identify coherent objects, for example, those formed by clouds. However, many models now use unstructured grids, which makes it harder to identify coherent objects. We present a new method that solves this problem by moving model data from an unstructured triangular grid to a structured cubical grid. We implement the method in an open-source Python package and show that the method is ready to be applied to climate model data.
Jérémy Bernard, Erwan Bocher, Elisabeth Le Saux Wiederhold, François Leconte, and Valéry Masson
Geosci. Model Dev., 15, 7505–7532, https://doi.org/10.5194/gmd-15-7505-2022, https://doi.org/10.5194/gmd-15-7505-2022, 2022
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OpenStreetMap is a collaborative project aimed at creaing a free dataset containing topographical information. Since these data are available worldwide, they can be used as standard data for geoscience studies. However, most buildings miss the height information that constitutes key data for numerous fields (urban climate, noise propagation, air pollution). In this work, the building height is estimated using statistical modeling using indicators that characterize the building's environment.
Sergey Kravtsov, Ilijana Mastilovic, Andrew McC. Hogg, William K. Dewar, and Jeffrey R. Blundell
Geosci. Model Dev., 15, 7449–7469, https://doi.org/10.5194/gmd-15-7449-2022, https://doi.org/10.5194/gmd-15-7449-2022, 2022
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Climate is a complex system whose behavior is shaped by multitudes of processes operating on widely different spatial scales and timescales. In hierarchical modeling, one goes back and forth between highly idealized process models and state-of-the-art models coupling the entire range of climate subsystems to identify specific phenomena and understand their dynamics. The present contribution highlights an intermediate climate model focussing on midlatitude ocean–atmosphere interactions.
Ingo Wohltmann, Daniel Kreyling, and Ralph Lehmann
Geosci. Model Dev., 15, 7243–7255, https://doi.org/10.5194/gmd-15-7243-2022, https://doi.org/10.5194/gmd-15-7243-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Juan Ruiz, Pierre Ailliot, Thi Tuyet Trang Chau, Pierre Le Bras, Valérie Monbet, Florian Sévellec, and Pierre Tandeo
Geosci. Model Dev., 15, 7203–7220, https://doi.org/10.5194/gmd-15-7203-2022, https://doi.org/10.5194/gmd-15-7203-2022, 2022
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We present a new approach to validate numerical simulations of the current climate. The method can take advantage of existing climate simulations produced by different centers combining an analog forecasting approach with data assimilation to quantify how well a particular model reproduces a sequence of observed values. The method can be applied with different observations types and is implemented locally in space and time significantly reducing the associated computational cost.
Chahan M. Kropf, Alessio Ciullo, Laura Otth, Simona Meiler, Arun Rana, Emanuel Schmid, Jamie W. McCaughey, and David N. Bresch
Geosci. Model Dev., 15, 7177–7201, https://doi.org/10.5194/gmd-15-7177-2022, https://doi.org/10.5194/gmd-15-7177-2022, 2022
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Mathematical models are approximations, and modellers need to understand and ideally quantify the arising uncertainties. Here, we describe and showcase the first, simple-to-use, uncertainty and sensitivity analysis module of the open-source and open-access climate-risk modelling platform CLIMADA. This may help to enhance transparency and intercomparison of studies among climate-risk modellers, help focus future research, and lead to better-informed decisions on climate adaptation.
Günther Zängl, Daniel Reinert, and Florian Prill
Geosci. Model Dev., 15, 7153–7176, https://doi.org/10.5194/gmd-15-7153-2022, https://doi.org/10.5194/gmd-15-7153-2022, 2022
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This article describes the implementation of grid refinement in the ICOsahedral Nonhydrostatic (ICON) model, which has been jointly developed at several German institutions and constitutes a unified modeling system for global and regional numerical weather prediction and climate applications. The grid refinement allows using a higher resolution in regional domains and transferring the information back to the global domain by means of a feedback mechanism.
Suzanne Robinson, Ruza Ivanovic, Lauren Gregoire, Julia Tindall, Tina van de Flierdt, Yves Plancherel, Frerk Pöppelmeier, Kazuyo Tachikawa, and Paul Valdes
EGUsphere, https://doi.org/10.5194/egusphere-2022-606, https://doi.org/10.5194/egusphere-2022-606, 2022
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We present the implementation of neodymium (Nd) isotopes into the ocean model of FAMOUS (ND v1.0). Nd fluxes from seafloor sediment alongside incorporation of Nd onto sinking particles represent the major global sources and sinks. However, model-data mismatch in the North Pacific and northern North Atlantic suggest that certain reactive components of the sediment interact the most with seawater. Our results are important for interpreting Nd isotopes in terms of ocean circulation.
Sébastien Gardoll and Olivier Boucher
Geosci. Model Dev., 15, 7051–7073, https://doi.org/10.5194/gmd-15-7051-2022, https://doi.org/10.5194/gmd-15-7051-2022, 2022
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Tropical cyclones (TCs) are one of the most devastating natural disasters, which justifies monitoring and prediction in the context of a changing climate. In this study, we have adapted and tested a convolutional neural network (CNN) for the classification of reanalysis outputs (ERA5 and MERRA-2 labeled by HURDAT2) according to the presence or absence of TCs. We tested the impact of interpolation and of "mixing and matching" the training and test sets on the performance of the CNN.
Marco A. Giorgetta, William Sawyer, Xavier Lapillonne, Panagiotis Adamidis, Dmitry Alexeev, Valentin Clément, Remo Dietlicher, Jan Frederik Engels, Monika Esch, Henning Franke, Claudia Frauen, Walter M. Hannah, Benjamin R. Hillman, Luis Kornblueh, Philippe Marti, Matthew R. Norman, Robert Pincus, Sebastian Rast, Daniel Reinert, Reiner Schnur, Uwe Schulzweida, and Bjorn Stevens
Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022, https://doi.org/10.5194/gmd-15-6985-2022, 2022
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This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
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
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This study investigates the nudging implementation in the EAMv1 model. We find that (1) revising the sequence of calculations and using higher-frequency constraining data to improve the performance of a simulation nudged to EAMv1’s own meteorology, (2) using the relocated nudging tendency and 3-hourly ERA5 reanalysis to obtain a better agreement between nudged simulations and observations, and (3) using wind-only nudging are recommended for the estimates of global mean aerosol effects.
Christian R. Steger, Benjamin Steger, and Christoph Schär
Geosci. Model Dev., 15, 6817–6840, https://doi.org/10.5194/gmd-15-6817-2022, https://doi.org/10.5194/gmd-15-6817-2022, 2022
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Terrain horizon and sky view factor are crucial quantities for many geoscientific applications; e.g. they are used to account for effects of terrain on surface radiation in climate and land surface models. Because typical terrain horizon algorithms are inefficient for high-resolution (< 30 m) elevation data, we developed a new algorithm based on a ray-tracing library. A comparison with two conventional methods revealed both its high performance and its accuracy for complex terrain.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Jorge Baño-Medina, Rodrigo Manzanas, Ezequiel Cimadevilla, Jesús Fernández, Jose González-Abad, Antonio S. Cofiño, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 6747–6758, https://doi.org/10.5194/gmd-15-6747-2022, https://doi.org/10.5194/gmd-15-6747-2022, 2022
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Deep neural networks are used to produce downscaled regional climate change projections over Europe for temperature and precipitation for the first time. The resulting dataset, DeepESD, is analyzed against state-of-the-art downscaling methodologies, reproducing more accurately the observed climate in the historical period and showing plausible future climate change signals with low computational requirements.
Stella Bourdin, Sébastien Fromang, William Dulac, Julien Cattiaux, and Fabrice Chauvin
Geosci. Model Dev., 15, 6759–6786, https://doi.org/10.5194/gmd-15-6759-2022, https://doi.org/10.5194/gmd-15-6759-2022, 2022
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When studying tropical cyclones in a large dataset, one needs objective and automatic procedures to detect their specific pattern. Applying four different such algorithms to a reconstruction of the climate, we show that the choice of the algorithm is crucial to the climatology obtained. Mainly, the algorithms differ in their sensitivity to weak storms so that they provide different frequencies and durations. We review the different options to consider for the choice of the tracking methodology.
Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, and Sean G. T. Kelley
Geosci. Model Dev., 15, 6659–6676, https://doi.org/10.5194/gmd-15-6659-2022, https://doi.org/10.5194/gmd-15-6659-2022, 2022
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Application of 1-D lake models coupled within earth-system prediction models will improve accuracy but requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within a weather prediction model to constrain lake temperature evolution. We compared these lake temperature values with other estimates and found much reduced errors (down to 1-2 K). The lake cycling initialization is now applied to two operational US NOAA weather models.
Nicholas K.-R. Kevlahan and Florian Lemarié
Geosci. Model Dev., 15, 6521–6539, https://doi.org/10.5194/gmd-15-6521-2022, https://doi.org/10.5194/gmd-15-6521-2022, 2022
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WAVETRISK-2.1 is an innovative climate model for the world's oceans. It uses state-of-the-art techniques to change the model's resolution locally, from O(100 km) to O(5 km), as the ocean changes. This dynamic adaptivity makes optimal use of available supercomputer resources, and allows two-dimensional global scales and three-dimensional submesoscales to be captured in the same simulation. WAVETRISK-2.1 is designed to be coupled its companion global atmosphere model, WAVETRISK-1.x.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
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The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
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Short summary
Recently, the stratospheric aerosol forcing dataset used as an input to the Coupled Model Intercomparison Project phase 6 was updated. This work explores the impact of those changes on the modelled historical climates in the CanESM5 and EAMv1 models. Temperature differences in the stratosphere shortly after the Pinatubo eruption are found to be significant, but surface temperatures and precipitation do not show a significant change.
Recently, the stratospheric aerosol forcing dataset used as an input to the Coupled Model...