Articles | Volume 15, issue 17
https://doi.org/10.5194/gmd-15-6695-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-6695-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
05 Sep 2022
Methods for assessment of models |
| 05 Sep 2022
| 05 Sep 2022
Characterizing uncertainties of Earth system modeling with heterogeneous many-core architecture computing
Yangyang Yu
Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao
266100, China
College of Oceanic and Atmospheric Sciences, Ocean University of
China, Qingdao 266100, China
Shaoqing Zhang
CORRESPONDING AUTHOR
Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao
266100, China
College of Oceanic and Atmospheric Sciences, Ocean University of
China, Qingdao 266100, China
Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
Haohuan Fu
CORRESPONDING AUTHOR
Ministry of Education Key Laboratory for Earth System Modeling/Department of Earth System Science, Tsinghua University, Beijing 100084,
China
National Supercomputing Center in Wuxi, Wuxi 214072, China
Lixin Wu
CORRESPONDING AUTHOR
Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao
266100, China
College of Oceanic and Atmospheric Sciences, Ocean University of
China, Qingdao 266100, China
Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
Dexun Chen
CORRESPONDING AUTHOR
National Supercomputing Center in Wuxi, Wuxi 214072, China
Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education/Frontiers Science Center for Deep
Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao 266100, China
Zhiqiang Wei
Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
Dongning Jia
Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
Xiaopei Lin
Key Laboratory of Physical Oceanography, Ministry of Education/Institute for Advanced Ocean Study/Frontiers Science Center for Deep Ocean Multispheres and Earth System (DOMES), Ocean University of China, Qingdao
266100, China
College of Oceanic and Atmospheric Sciences, Ocean University of
China, Qingdao 266100, China
Pilot National Laboratory for Marine Science and Technology, Qingdao 266100, China
Related authors
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yang Gao, Xiaopei Lin, Zhao Liu, and Xiaojing Lv
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-10, https://doi.org/10.5194/gmd-2024-10, 2024
Preprint withdrawn
Short summary
Short summary
The hardware-related perturbations caused by the heterogeneous many-core architectures can blend with software or human errors, which can affect the accuracy of the model consistency verification. We develop a deep learning-based consistency test tool for ESMs on the heterogeneous systems (ESM-DCT) and evaluate it in CESM on new Sunway system. The ESM-DCT can detect the existence of software or human errors when taking hardware-related perturbations into account.
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
Short summary
Short summary
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.
Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
Short summary
Short summary
Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
Yujue Wang, Yizhe Yi, Wei Xu, Yiwen Zhang, Shubin Li, Hong-Hai Zhang, Mingliang Gu, Shibo Yan, Jialei Zhu, Chao Zhang, Jinhui Shi, Yang Gao, Xiaohong Yao, and Huiwang Gao
EGUsphere, https://doi.org/10.5194/egusphere-2025-3951, https://doi.org/10.5194/egusphere-2025-3951, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
Short summary
Short summary
Marine organic aerosols remain poorly quantified, which limits our understanding on the climate regulation of marine aerosols. Based on shipboard cruises over the Pacific Ocean, we proposed an observation-based parameterization approach to estimate the primary and secondary marine organic aerosols using sea surface chlorophyll a and sea salts in marine aerosols. The results highlight that the spatial distribution of marine organic aerosols was driven by the marine biological activities.
Wenbin Kou, Yang Gao, Dan Tong, Xiaojie Guo, Xiadong An, Wenyu Liu, Mengshi Cui, Xiuwen Guo, Shaoqing Zhang, Huiwang Gao, and Lixin Wu
Atmos. Chem. Phys., 25, 3029–3048, https://doi.org/10.5194/acp-25-3029-2025, https://doi.org/10.5194/acp-25-3029-2025, 2025
Short summary
Short summary
Unlike traditional numerical studies, we apply a high-resolution Earth system model, improving simulations of surface ozone and large-scale circulations such as atmospheric blocking. Besides local heat waves, we quantify the impact of atmospheric blocking on downstream ozone concentrations, which is closely associated with the blocking position. We identify three major pathways of Rossby wave propagation, stressing the critical role of large-scale circulation in regional air quality.
Jiewen Shen, Bin Zhao, Shuxiao Wang, An Ning, Yuyang Li, Runlong Cai, Da Gao, Biwu Chu, Yang Gao, Manish Shrivastava, Jingkun Jiang, Xiuhui Zhang, and Hong He
Atmos. Chem. Phys., 24, 10261–10278, https://doi.org/10.5194/acp-24-10261-2024, https://doi.org/10.5194/acp-24-10261-2024, 2024
Short summary
Short summary
We extensively compare various cluster-dynamics-based parameterizations for sulfuric acid–dimethylamine nucleation and identify a newly developed parameterization derived from Atmospheric Cluster Dynamic Code (ACDC) simulations as being the most reliable one. This study offers a valuable reference for developing parameterizations of other nucleation systems and is meaningful for the accurate quantification of the environmental and climate impacts of new particle formation.
Lijing Cheng, Yuying Pan, Zhetao Tan, Huayi Zheng, Yujing Zhu, Wangxu Wei, Juan Du, Huifeng Yuan, Guancheng Li, Hanlin Ye, Viktor Gouretski, Yuanlong Li, Kevin E. Trenberth, John Abraham, Yuchun Jin, Franco Reseghetti, Xiaopei Lin, Bin Zhang, Gengxin Chen, Michael E. Mann, and Jiang Zhu
Earth Syst. Sci. Data, 16, 3517–3546, https://doi.org/10.5194/essd-16-3517-2024, https://doi.org/10.5194/essd-16-3517-2024, 2024
Short summary
Short summary
Observational gridded products are essential for understanding the ocean, the atmosphere, and climate change; they support policy decisions and socioeconomic developments. This study provides an update of an ocean subsurface temperature and ocean heat content gridded product, named the IAPv4 data product, which is available for the upper 6000 m (119 levels) since 1940 (more reliable after ~1955) for monthly and 1° × 1° temporal and spatial resolutions.
Ming Chu, Xing Wei, Shangfei Hai, Yang Gao, Huiwang Gao, Yujiao Zhu, Biwu Chu, Nan Ma, Juan Hong, Yele Sun, and Xiaohong Yao
Atmos. Chem. Phys., 24, 6769–6786, https://doi.org/10.5194/acp-24-6769-2024, https://doi.org/10.5194/acp-24-6769-2024, 2024
Short summary
Short summary
We used a 20-bin WRF-Chem model to simulate NPF events in the NCP during a three-week observational period in the summer of 2019. The model was able to reproduce the observations during June 29–July 6, which was characterized by a high frequency of NPF occurrence.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
Short summary
Short summary
To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Feifan Yan, Hang Su, Yafang Cheng, Rujin Huang, Hong Liao, Ting Yang, Yuanyuan Zhu, Shaoqing Zhang, Lifang Sheng, Wenbin Kou, Xinran Zeng, Shengnan Xiang, Xiaohong Yao, Huiwang Gao, and Yang Gao
Atmos. Chem. Phys., 24, 2365–2376, https://doi.org/10.5194/acp-24-2365-2024, https://doi.org/10.5194/acp-24-2365-2024, 2024
Short summary
Short summary
PM2.5 pollution is a major air quality issue deteriorating human health, and previous studies mostly focus on regions like the North China Plain and Yangtze River Delta. However, the characteristics of PM2.5 concentrations between these two regions are studied less often. Focusing on the transport corridor region, we identify an interesting seesaw transport phenomenon with stagnant weather conditions, conducive to PM2.5 accumulation over this region, resulting in large health effects.
Yangyang Yu, Shaoqing Zhang, Haohuan Fu, Dexun Chen, Yang Gao, Xiaopei Lin, Zhao Liu, and Xiaojing Lv
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-10, https://doi.org/10.5194/gmd-2024-10, 2024
Preprint withdrawn
Short summary
Short summary
The hardware-related perturbations caused by the heterogeneous many-core architectures can blend with software or human errors, which can affect the accuracy of the model consistency verification. We develop a deep learning-based consistency test tool for ESMs on the heterogeneous systems (ESM-DCT) and evaluate it in CESM on new Sunway system. The ESM-DCT can detect the existence of software or human errors when taking hardware-related perturbations into account.
Xing Wei, Yanjie Shen, Xiao-Ying Yu, Yang Gao, Huiwang Gao, Ming Chu, Yujiao Zhu, and Xiaohong Yao
Atmos. Chem. Phys., 23, 15325–15350, https://doi.org/10.5194/acp-23-15325-2023, https://doi.org/10.5194/acp-23-15325-2023, 2023
Short summary
Short summary
We investigate the contribution of grown new particles to Nccn at a rural mountain site in the North China Plain. The total particle number concentrations (Ncn) observed on 8 new particle formation (NPF) days were higher compared to non-NPF days. The Nccn at 0.2 % supersaturation (SS) and 0.4 % SS on the NPF days was significantly lower than on non-NPF days. Only one of eight NPF events had detectable net contributions to Nccn at 0.4 % SS and 1.0 % SS with increased κ values.
Jiangyu Li, Shaoqing Zhang, Qingxiang Liu, Xiaolin Yu, and Zhiwei Zhang
Geosci. Model Dev., 16, 6393–6412, https://doi.org/10.5194/gmd-16-6393-2023, https://doi.org/10.5194/gmd-16-6393-2023, 2023
Short summary
Short summary
Ocean surface waves play an important role in the air–sea interface but are rarely activated in high-resolution Earth system simulations due to their expensive computational costs. To alleviate this situation, this paper designs a new wave modeling framework with a multiscale grid system. Evaluations of a series of numerical experiments show that it has good feasibility and applicability in the WAVEWATCH III model, WW3, and can achieve the goals of efficient and high-precision wave simulation.
Chupeng Zhang, Shangfei Hai, Yang Gao, Yuhang Wang, Shaoqing Zhang, Lifang Sheng, Bin Zhao, Shuxiao Wang, Jingkun Jiang, Xin Huang, Xiaojing Shen, Junying Sun, Aura Lupascu, Manish Shrivastava, Jerome D. Fast, Wenxuan Cheng, Xiuwen Guo, Ming Chu, Nan Ma, Juan Hong, Qiaoqiao Wang, Xiaohong Yao, and Huiwang Gao
Atmos. Chem. Phys., 23, 10713–10730, https://doi.org/10.5194/acp-23-10713-2023, https://doi.org/10.5194/acp-23-10713-2023, 2023
Short summary
Short summary
New particle formation is an important source of atmospheric particles, exerting critical influences on global climate. Numerical models are vital tools to understanding atmospheric particle evolution, which, however, suffer from large biases in simulating particle numbers. Here we improve the model chemical processes governing particle sizes and compositions. The improved model reveals substantial contributions of newly formed particles to climate through effects on cloud condensation nuclei.
Yuyang Li, Jiewen Shen, Bin Zhao, Runlong Cai, Shuxiao Wang, Yang Gao, Manish Shrivastava, Da Gao, Jun Zheng, Markku Kulmala, and Jingkun Jiang
Atmos. Chem. Phys., 23, 8789–8804, https://doi.org/10.5194/acp-23-8789-2023, https://doi.org/10.5194/acp-23-8789-2023, 2023
Short summary
Short summary
We set up a new parameterization for 1.4 nm particle formation rates from sulfuric acid–dimethylamine (SA–DMA) nucleation, fully including the effects of coagulation scavenging and cluster stability. Incorporating the new parameterization into 3-D chemical transport models, we achieved better consistencies between simulation results and observation data. This new parameterization provides new insights into atmospheric nucleation simulations and its effects on atmospheric pollution or health.
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
Short summary
Short summary
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.
Yu Lin, Leiming Zhang, Qinchu Fan, He Meng, Yang Gao, Huiwang Gao, and Xiaohong Yao
Atmos. Chem. Phys., 22, 16073–16090, https://doi.org/10.5194/acp-22-16073-2022, https://doi.org/10.5194/acp-22-16073-2022, 2022
Short summary
Short summary
In this study, we analyzed 7-year (from May 2014 to April 2021) concentration data of six criteria air pollutants (PM2.5, PM10, O3, NO2, CO and SO2) as well as the sum of NO2 and O3 in six cities in South China. Three different analysis methods were used to identify emission-driven interannual variations and perturbations from varying weather conditions. In addition, a self-developed method was further introduced to constrain analysis uncertainties.
Jingzhe Sun, Yingjing Jiang, Shaoqing Zhang, Weimin Zhang, Lv Lu, Guangliang Liu, Yuhu Chen, Xiang Xing, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev., 15, 4805–4830, https://doi.org/10.5194/gmd-15-4805-2022, https://doi.org/10.5194/gmd-15-4805-2022, 2022
Short summary
Short summary
An online ensemble coupled data assimilation system with the Community Earth System Model is designed and evaluated. This system uses the memory-based information transfer approach which avoids frequent I/O operations. The observations of surface pressure, sea surface temperature, and in situ temperature and salinity profiles can be effectively assimilated into the coupled model. That will facilitate a long-term high-resolution climate reanalysis once the algorithm efficiency is much improved.
Lu Yang, Hongli Fu, Xiaofan Luo, Shaoqing Zhang, and Xuefeng Zhang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-92, https://doi.org/10.5194/tc-2022-92, 2022
Revised manuscript not accepted
Short summary
Short summary
During the melting season in Arctic, sea ice thickness is difficult to detect directly by the satellite remote sensing. A bivariate regression model is put forward in this study to construct sea ice thickness. Comparisons with observations show that the new sea ice thickness data has some advantages over other data sets. The experiment shows that the model is expected to provide an available data for improving the forecast accuracy of sea ice variables in the Arctic sea ice melting season.
Xiajie Yang, Qiaoqiao Wang, Nan Ma, Weiwei Hu, Yang Gao, Zhijiong Huang, Junyu Zheng, Bin Yuan, Ning Yang, Jiangchuan Tao, Juan Hong, Yafang Cheng, and Hang Su
Atmos. Chem. Phys., 22, 3743–3762, https://doi.org/10.5194/acp-22-3743-2022, https://doi.org/10.5194/acp-22-3743-2022, 2022
Short summary
Short summary
We use the GEOS-Chem model with additional anthropogenic and biomass burning chlorine emissions combined with updated parameterizations for N2O5 ＋ Cl chemistry to investigate the impacts of chlorine chemistry on air quality in China. Our study not only significantly improves the model's performance but also demonstrates the importance of non-sea-salt chlorine sources as well as an appropriate parameterization for N2O5 ＋ Cl chemistry to the impact of chlorine chemistry in China.
Yating Gao, Dihui Chen, Yanjie Shen, Yang Gao, Huiwang Gao, and Xiaohong Yao
Atmos. Chem. Phys., 22, 1515–1528, https://doi.org/10.5194/acp-22-1515-2022, https://doi.org/10.5194/acp-22-1515-2022, 2022
Short summary
Short summary
This study focuses on spatiotemporal heterogeneity of observed gaseous amines, NH3, their particulate counterparts in PM2.5 over different sea zones, and the disproportional release of alkaline gases and corresponding particulate counterparts from seawater in the sea zones in terms of different extents of enrichment of TMAH+ and DMAH+ in the sea surface microlayer (SML). A novel hypothesis is delivered.
Ying Zhou, Simo Hakala, Chao Yan, Yang Gao, Xiaohong Yao, Biwu Chu, Tommy Chan, Juha Kangasluoma, Shahzad Gani, Jenni Kontkanen, Pauli Paasonen, Yongchun Liu, Tuukka Petäjä, Markku Kulmala, and Lubna Dada
Atmos. Chem. Phys., 21, 17885–17906, https://doi.org/10.5194/acp-21-17885-2021, https://doi.org/10.5194/acp-21-17885-2021, 2021
Short summary
Short summary
We characterized the connection between new particle formation (NPF) events in terms of frequency, intensity and growth at a near-highway location in central Beijing and at a background mountain site 80 km away. Due to the substantial contribution of NPF to the global aerosol budget, identifying the conditions that promote the occurrence of regional NPF events could help understand their contribution on a large scale and would improve their implementation in global models.
Dihui Chen, Yanjie Shen, Juntao Wang, Yang Gao, Huiwang Gao, and Xiaohong Yao
Atmos. Chem. Phys., 21, 16413–16425, https://doi.org/10.5194/acp-21-16413-2021, https://doi.org/10.5194/acp-21-16413-2021, 2021
Short summary
Short summary
The study provides solid evidence to demonstrate that atmospheric trimethylamine (TMAgas) and particulate trimethylaminium in PM2.5 (TMAH+) observed in marine atmospheres were uniquely derived from seawater emissions. As sea-derived TMAgas correlated significantly with DMAgas and NH3gas, sea-derived DMAgas and NH3gas can be estimated and can quantify the contribution to the observed species in the marine atmosphere. Similarly, the contributions of primary DMAH+ have also been estimated.
Zhao Liu, Shaoqing Zhang, Yang Shen, Yuping Guan, and Xiong Deng
Nonlin. Processes Geophys., 28, 481–500, https://doi.org/10.5194/npg-28-481-2021, https://doi.org/10.5194/npg-28-481-2021, 2021
Short summary
Short summary
A general methodology is introduced to capture regime transitions of the Atlantic meridional overturning circulation (AMOC). The assimilation models with different parameters simulate different paths for the AMOC to switch between equilibrium states. Constraining model parameters with observations can significantly mitigate the model deviations, thus capturing AMOC regime transitions. This simple model study serves as a guideline for improving coupled general circulation models.
Liya Ma, Yujiao Zhu, Mei Zheng, Yele Sun, Lei Huang, Xiaohuan Liu, Yang Gao, Yanjie Shen, Huiwang Gao, and Xiaohong Yao
Atmos. Chem. Phys., 21, 183–200, https://doi.org/10.5194/acp-21-183-2021, https://doi.org/10.5194/acp-21-183-2021, 2021
Short summary
Short summary
In this study, we investigate three patterns of new particles growing to CCN (cloud condensation nuclei) size, i.e., one-stage growth and two-stage growth-A and growth-B patterns. Combining the observations of gaseous pollutants and measured or modeled particulate chemical species, the three growth patterns were discussed regarding the spatial heterogeneity, formation of secondary aerosols, and evaporation of semivolatile particulates as was the survival probability of new particles to CCN size.
Shaoqing Zhang, Haohuan Fu, Lixin Wu, Yuxuan Li, Hong Wang, Yunhui Zeng, Xiaohui Duan, Wubing Wan, Li Wang, Yuan Zhuang, Hongsong Meng, Kai Xu, Ping Xu, Lin Gan, Zhao Liu, Sihai Wu, Yuhu Chen, Haining Yu, Shupeng Shi, Lanning Wang, Shiming Xu, Wei Xue, Weiguo Liu, Qiang Guo, Jie Zhang, Guanghui Zhu, Yang Tu, Jim Edwards, Allison Baker, Jianlin Yong, Man Yuan, Yangyang Yu, Qiuying Zhang, Zedong Liu, Mingkui Li, Dongning Jia, Guangwen Yang, Zhiqiang Wei, Jingshan Pan, Ping Chang, Gokhan Danabasoglu, Stephen Yeager, Nan Rosenbloom, and Ying Guo
Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, https://doi.org/10.5194/gmd-13-4809-2020, 2020
Short summary
Short summary
Science advancement and societal needs require Earth system modelling with higher resolutions that demand tremendous computing power. We successfully scale the 10 km ocean and 25 km atmosphere high-resolution Earth system model to a new leading-edge heterogeneous supercomputer using state-of-the-art optimizing methods, promising the solution of high spatial resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modelling and HPC design communities.
Cited articles
Andrysco, M., Jhala, R., and Lerner, S.: Printing floating-point numbers: a
faster, always correct method, Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, 51, 555–567,
https://doi.org/10.1145/2837614.2837654, 2016.
Arteaga, A., Fuhrer, O., and Hoefler, T.: Designing Bit-Reproducible
Portable High-Performance Applications, 2014 IEEE International Parallel
& Distributed Processing Symposium (IPDPS), USA, 1235–1244,
https://doi.org/10.1109/IPDPS.2014.127, 2014.
Bailey, D. H.: Resolving numerical anomalies in scientific computation,
Lawrence Berkeley National Laboratory, University of California, USA, https://escholarship.org/uc/item/2qf8v4bn (last access: 30 August 2022), 2008.
Baker, A. H., Hammerling, D. M., Levy, M. N., Xu, H., Dennis, J. M., Eaton, B. E., Edwards, J., Hannay, C., Mickelson, S. A., Neale, R. B., Nychka, D., Shollenberger, J., Tribbia, J., Vertenstein, M., and Williamson, D.: A new ensemble-based consistency test for the Community Earth System Model (pyCECT v1.0), Geosci. Model Dev., 8, 2829–2840, https://doi.org/10.5194/gmd-8-2829-2015, 2015.
Donahue, A. S. and Caldwell, P. M.: Impact of Physics Parameterization
Ordering in A Global Atmosphere Model, J. Adv. Model. Earth Sy., 10, 481–499,
https://doi.org/10.1002/2017MS001067, 2018.
Düben, P. D., Joven, J., Lingamneni, A., McNamara, H., Micheli, G. D.,
Palem, K. V., and Palmer, T. N.: On the use of inexact, pruned hardware in
atmospheric modelling, Phil. Trans. R. Soc. A, 372, 20130276, https://doi.org/10.1098/rsta.2013.0276, 2014.
Düben, P. D., Subramanian, A., Dawson, A., and Palmer T. N.: A study of
reduced numerical precision to make superparametrisation more competitive using a hardware emulator in the
OpenIFS model, J. Adv. Model. Earth Sy., 9, 566–584,
https://doi.org/10.1002/2016MS000862, 2017.
Emanuel, K. A. and Živković-Rothman, M.: Development and evaluation
of a convection scheme for use in climate models, J. Atmos. Sci., 56,
1766–1782, https://doi.org/10.1175/1520-0469(1999)056<1766:DAEOAC>2.0.CO;2, 1999.
Flato, G. M.: Earth system models: an overview, WIREs Clim. Change, 2,
783–800, https://doi.org/10.1002/wcc.148, 2011.
Fu, H., Liao, J., Yang, J., Wang, L., Song, Z., Huang, X., Yang, C., Xue,
W., Liu, F., Qiao, F., Zhao, W., Yin, X., Hou, C., Zhang, C., Ge, W., Zhang,
J., Wang, Y., Zhou, C., and Yang, G.: The sunway TaihuLight supercomputer:
system and applications, Sci. China Inf. Sci., 59, 072001,
https://doi.org/10.1007/s11432-016-5588-7, 2016.
Fu, H., Liao, J., Ding, N., Duan, X., Gan, L., Liang, Y., Wang, X., Yang,
J., Zheng, Y., Liu, W., Wang, L., and Yang, G.: Redesigning cam-se for
peta-scale climate modeling performance and ultra-high resolution on sunway
taihulight, In Proceedings of the international conference for high
performance computing, networking, storage and analysis, Association for Computing Machinery, https://doi.org/10.1145/3126908.3126909, 2017a.
Fu, H., Liao, J., Xue, W., Wang, L., Chen, D., Gu, L., Xu, J., Ding, N.,
Wang, X., He, C., Xu, S., Liang, Y., Fang, J., Xu, Y., Zheng, W., Xu, J.,
Zheng, Z., Wei, W., Ji, X., Zhang, H., Chen, B., Li, K., Huang, X., Chen,
W., and Yang, G.: Refactoring and optimizing the community atmosphere model
(CAM) on the sunway taihu-light supercomputer, in: High performance
computing, networking, storage and analysis, International Conference for High Performance Computing, Networking, Storage and Analysis, https://doi.org/10.1109/SC.2016.82, 2017b.
Fuhrer, O., Chadha, T., Hoefler, T., Kwasniewski, G., Lapillonne, X., Leutwyler, D., Lüthi, D., Osuna, C., Schär, C., Schulthess, T. C., and Vogt, H.: Near-global climate simulation at 1 km resolution: establishing a performance baseline on 4888 GPUs with COSMO 5.0, Geosci. Model Dev., 11, 1665–1681, https://doi.org/10.5194/gmd-11-1665-2018, 2018.
Goff, J. and Gratch, S: List 1947, Smithsonian Meteorological Tables, Trans.
Am. Soc., 52, 95, 1946.
Kara, A. B., Rochford P. A., and Hurlburt H. E.: An optimal definition for
ocean mixed layer depth, J. Geophys. Res.-Oceans, 105, 16803–16821,
https://doi.org/10.1029/2000JC900072, 2000.
Kelly, R. C.: GPU Computing for Atmospheric Modeling, Comput. Sci. Eng., 12,
26–33, https://doi.org/10.1109/MCSE.2010.26, 2010.
Li, S., Zhang, S., Liu, Z., Yang, X. Rosati, A., Golaz, J. C., and Zhao, M.:
The Role of Large-scale Feedbacks in Cumulus Convection Parameter
Estimation, J. Climate, 29, 4099–4119, https://doi.org/10.1175/JCLI-D-15-0117.1,
2016.
Liao, X., Xiao, L., Yang, C., and Lu, Y.: Milkyway-2 supercomputer: system
and application, Front. Comput. Sci., 8, 345–356,
https://doi.org/10.1007/s11704-014-3501-3, 2014.
Linford, J. C., Michalakes, J., Vachharajani, M., and Sandu, A.: Multi-core
acceleration of chemical kinetics for simulation and prediction, in: High
performance computing networking, storage and analysis, International Conference for High Performance Computing Networking, Storage and Analysis, 1–11, https://doi.org/10.1145/1654059.1654067, 2009.
Mielikainen, J., Huang, B., Wang, J., Huang, H.-L. A., and Goldberg, M. D.:
Compute unified device architecture (CUDA)-based parallelization of WRF
Kessler cloud microphysics scheme, Comput. Geosci.-UK, 52, 292–299,
https://doi.org/10.1016/j.cageo.2012.10.006, 2013.
Milroy, D. J., Baker, A. H., Hammerling, D. M., Dennis, J. M., Mickelson, S.
A., and Jessup, E. R.: Towards Characterizing the Variability of
Statistically Consistent Community Earth System Model Simulations, Pro.
Comput. Sci., 80, 1589–1600, https://doi.org/10.1016/j.procs.2016.05.489,
2016.
Morrison, H. and Gettelman, A.: A new two-moment bulk stratiform cloud
microphysics scheme in the Community Atmosphere Model, version 3 (CAM3).
Part I: Description and numerical tests, J. Climate, 21, 3642–3659,
https://doi.org/10.1175/2008JCLI2105.1, 2008.
Neale, R. B., Richter, J. H., and Jochum, M.: The impact of convection on
ENSO: From a delayed oscillator to a series of events, J. Climate, 21,
5904–5924, https://doi.org/10.1175/2008JCLI2244.1, 2008.
Palem, K. and Lingamneni, A.: Ten Years of Building Broken Chips: The
Physics and Engineering of Inexact Computing, ACM T. Embed.
Comput. S., 12, 1–23, https://doi.org/10.1145/2465787.2465789,
2013.
Park, S., Bretherton, C. S., and Rasch, P. J.: Integrating Cloud Processes
in the Community Atmosphere Model, Version 5, J. Climate, 27, 6821–6856,
https://doi.org/10.1175/JCLI-D-14-00087.1, 2014.
Rosinski, J. M. and Williamson, D. L.: The accumulation of rounding errors
and port validation for global atmospheric models, SIAM J. Sci. Comput., 18,
552–564, https://doi.org/10.1137/S1064827594275534, 1997.
Sansom, P. G., Stephenson, D. B., Ferro, C. A. T., Zappa, G., and Shaffery,
L.: Simple uncertainty frameworks for selecting weighting schemes and
interpreting multimodel ensemble climate change experiments, J. Climate, 26,
4017–4037, https://doi.org/10.1175/JCLI-D-12-00462.1, 2013.
Stephenson, M., Hari, S. K. S., Lee, Y., Ebrahimi, E., Johnson, D. R.,
Nellans, D., O'Connor, M., and Keckler, S. W.: Flexible Software Profiling
of GPU Architectures, ACM SIGARCH Comp. Architecture News, 43, 185–197, 2015.
Sun, W. Y. and Ogura, Y.: Modeling the Evolution of the Convective Planetary
Boundary Layer, J. Atmos. Sci., 37, 1558–1572,
https://doi.org/10.1175/1520-0469(1980)037<1558:MTEOTC>2.0.CO;2, 1980.
Tintó Prims, O., Acosta, M. C., Moore, A. M., Castrillo, M., Serradell, K., Cortés, A., and Doblas-Reyes, F. J.: How to use mixed precision in ocean models: exploring a potential reduction of numerical precision in NEMO 4.0 and ROMS 3.6, Geosci. Model Dev., 12, 3135–3148, https://doi.org/10.5194/gmd-12-3135-2019, 2019.
Vazhkudai, S. S., de Supinski, B. R., Bland, A. S., Geist, A., Sexton, J.,
Kahle, J., Zimmer, C. J., Atchley, S., Oral, S., Maxwell, D. E., Vergara
Larrea, V. G., Bertsch, A., Goldstone, R., Joubert, W., Chambreau, C.,
Appelhans, D., Blackmore, R., Casses, B., Chochia, G., Davison, G., Ezell,
M. A., Gooding, T., Gonsiorowski, E., Grinberg, L., Hanson, B., Hartner, B.,
Karlin, I., Leininger, M. L., Leverman, D., Marroquin, C., Moody, A.,
Ohmacht, M., Pankajakshan, R., Pizzano, F., Rogers, J. H., Rosenburg, B.,
Schmidt, D., Shankar, M., Wang, F., Watson, P., Walkup, B., Weems, L. D.,
and Yin, J.: The design, deployment, and evaluation of the coral
pre-exascale systems, in: International Conference for High Performance Computing, Networking, Storage and Analysis, USA, https://doi.org/10.1109/SC.2018.00055, 2018.
Wang, M. and Zhang, G. J.: Improving the Simulation of Tropical Convective
Cloud-Top Heights in CAM5 with CloudSat Observations, J. Climate, 31, 5189–5204,
https://doi.org/10.1175/JCLI-D-18-0027.1, 2018.
Whitehead, N. and Fit-Florea, A.: Precision & Performance: Floating
Point and IEEE 754 Compliance for NVIDIA GPUs,
https://developer.nvidia.com/sites/default/files/akamai/cuda/files/NVIDIA-CUDA-Floating-Point.pdf (last access: 27 August 2022),
2011.
Xiao, H., Sun, J., Bian, X., and Dai, Z.: GPU acceleration of the WSM6 cloud
microphysics scheme in GRAPES model, Comput. Geosci., 59, 156–162,
https://doi.org/10.1016/j.cageo.2013.06.016, 2013.
Xu, S., Huang, X., Oey, L.-Y., Xu, F., Fu, H., Zhang, Y., and Yang, G.: POM.gpu-v1.0: a GPU-based Princeton Ocean Model, Geosci. Model Dev., 8, 2815–2827, https://doi.org/10.5194/gmd-8-2815-2015, 2015.
Yano, J. I.: Subgrid-scale physical parameterization in atmospheric
modeling: How can we make it consistent?, J. Phys. A-Math. Theor., 49, 284001,
https://doi.org/10.1088/1751-8113/49/28/284001, 2016.
Yu, Y., Zhang, S., Fu, H., Wu, L., Chen, D., Gao, Y., Wei, Z., Jia, D., and Lin, X.: Data and Codes of Characterizing Uncertainties of Earth System Modeling with Heterogeneous Many-core Architecture Computing, Zenodo [data set], https://doi.org/10.5281/zenodo.6481868, 2022.
Zhang, G. J. and McFarlane, N. A.: Sensitivity of climate simulations to
the parameterization of cumulus convection in the Canadian climate centre
general circulation model, Atmos. Ocean, 33, 407–446,
https://doi.org/10.1080/07055900.1995.9649539, 1995.
Zhang, S., Fu, H., Wu, L., Li, Y., Wang, H., Zeng, Y., Duan, X., Wan, W., Wang, L., Zhuang, Y., Meng, H., Xu, K., Xu, P., Gan, L., Liu, Z., Wu, S., Chen, Y., Yu, H., Shi, S., Wang, L., Xu, S., Xue, W., Liu, W., Guo, Q., Zhang, J., Zhu, G., Tu, Y., Edwards, J., Baker, A., Yong, J., Yuan, M., Yu, Y., Zhang, Q., Liu, Z., Li, M., Jia, D., Yang, G., Wei, Z., Pan, J., Chang, P., Danabasoglu, G., Yeager, S., Rosenbloom, N., and Guo, Y.: Optimizing high-resolution Community Earth System Model on a heterogeneous many-core supercomputing platform, Geosci. Model Dev., 13, 4809–4829, https://doi.org/10.5194/gmd-13-4809-2020, 2020.
Short summary
To understand the scientific consequence of perturbations caused by slave cores in heterogeneous computing environments, we examine the influence of perturbation amplitudes on the determination of the cloud bottom and cloud top and compute the probability density function (PDF) of generated clouds. A series of comparisons of the PDFs between homogeneous and heterogeneous systems show consistently acceptable error tolerances when using slave cores in heterogeneous computing environments.
To understand the scientific consequence of perturbations caused by slave cores in heterogeneous...
