- Articles & preprints
- Submission
- Policies
- Peer-review process
- Editorial board
- About
- EGU publications
- Manuscript tracking
Journal cover
Journal topic
Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
Journal topic
- Articles & preprints
- Submission
- Policies
- Peer-review process
- Editorial board
- About
- EGU publications
- Manuscript tracking
Journal metrics
IF5.240
IF 5-year
5.768
5.768
CiteScore
8.9
8.9
SNIP1.713
IPP5.53
SJR3.18
Scimago H
index71
index71
h5-index51
Abstracted/indexed
Abstracted/indexed
Volume 8, issue 11
Geosci. Model Dev., 8, 3579–3591, 2015
https://doi.org/10.5194/gmd-8-3579-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-3579-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Special issue: Community software to support the delivery of CMIP5
Geosci. Model Dev., 8, 3579–3591, 2015
https://doi.org/10.5194/gmd-8-3579-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-3579-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Development and technical paper 06 Nov 2015
Development and technical paper | 06 Nov 2015
An automatic and effective parameter optimization method for model tuning
T. Zhang et al.
Related authors
Li Wu, Tao Zhang, Yi Qin, and Wei Xue
Geosci. Model Dev., 13, 41–53, https://doi.org/10.5194/gmd-13-41-2020, https://doi.org/10.5194/gmd-13-41-2020, 2020
Short summary
Short summary
Uncertain parameters in physical parameterizations of general circulation models (GCMs) greatly impact model performance. In this study, an automated and efficient parameter optimization with the radiation balance constraint is presented and applied in the Community Atmospheric Model. Results show that the synthesized performance under the optimal parameters is 6.3 % better than the control run and the radiation imbalance is as low as 0.1 W m2.
Tao Zhang, Minghua Zhang, Wuyin Lin, Yanluan Lin, Wei Xue, Haiyang Yu, Juanxiong He, Xiaoge Xin, Hsi-Yen Ma, Shaocheng Xie, and Weimin Zheng
Geosci. Model Dev., 11, 5189–5201, https://doi.org/10.5194/gmd-11-5189-2018, https://doi.org/10.5194/gmd-11-5189-2018, 2018
Short summary
Short summary
Tuning of uncertain parameters in global atmospheric general circulation models has extreme computational cost. In this study, we provide an automatic tuning method by combining an auto-optimization algorithm with hindcasts to improve climate simulations in CAM5. The tuning improved the overall performance of a well-calibrated model by about 10 %. The computational cost of the entire auto-tuning procedure is just equivalent to a single 20-year simulation of CAM5.
Haoyu Xu, Tao Zhang, Yiqi Luo, Xin Huang, and Wei Xue
Geosci. Model Dev., 11, 3027–3044, https://doi.org/10.5194/gmd-11-3027-2018, https://doi.org/10.5194/gmd-11-3027-2018, 2018
Short summary
Short summary
This study proposes a new parameter calibration method based on surrogate optimization techniques to improve the prediction accuracy of soil organic carbon. Experiments on three popular global soil carbon cycle models show that the surrogate-based optimization method is effective and efficient in terms of both accuracy and cost. This research would help develop and improve the parameterization schemes of Earth climate systems.
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 Cheng, 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. Discuss., https://doi.org/10.5194/gmd-2020-18, https://doi.org/10.5194/gmd-2020-18, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Science advancement and societal needs require Earth system modeling with higher resolution that demands tremendous computing power. This work successfully scales the 10 km ocean and 25km 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 space resolution and time-varying frequency. Corresponding technical breakthroughs are of significance in modeling and HPC design communities.
Li Wu, Tao Zhang, Yi Qin, and Wei Xue
Geosci. Model Dev., 13, 41–53, https://doi.org/10.5194/gmd-13-41-2020, https://doi.org/10.5194/gmd-13-41-2020, 2020
Short summary
Short summary
Uncertain parameters in physical parameterizations of general circulation models (GCMs) greatly impact model performance. In this study, an automated and efficient parameter optimization with the radiation balance constraint is presented and applied in the Community Atmospheric Model. Results show that the synthesized performance under the optimal parameters is 6.3 % better than the control run and the radiation imbalance is as low as 0.1 W m2.
Tao Zhang, Minghua Zhang, Wuyin Lin, Yanluan Lin, Wei Xue, Haiyang Yu, Juanxiong He, Xiaoge Xin, Hsi-Yen Ma, Shaocheng Xie, and Weimin Zheng
Geosci. Model Dev., 11, 5189–5201, https://doi.org/10.5194/gmd-11-5189-2018, https://doi.org/10.5194/gmd-11-5189-2018, 2018
Short summary
Short summary
Tuning of uncertain parameters in global atmospheric general circulation models has extreme computational cost. In this study, we provide an automatic tuning method by combining an auto-optimization algorithm with hindcasts to improve climate simulations in CAM5. The tuning improved the overall performance of a well-calibrated model by about 10 %. The computational cost of the entire auto-tuning procedure is just equivalent to a single 20-year simulation of CAM5.
Qianyu Li, Xingjie Lu, Yingping Wang, Xin Huang, Peter M. Cox, and Yiqi Luo
Biogeosciences, 15, 6909–6925, https://doi.org/10.5194/bg-15-6909-2018, https://doi.org/10.5194/bg-15-6909-2018, 2018
Short summary
Short summary
Land-surface models have been widely used to predict the responses of terrestrial ecosystems to climate change. A better understanding of model mechanisms that govern terrestrial ecosystem responses to rising atmosphere [CO2] is needed. Our study for the first time shows that the expansion of leaf area under rising [CO2] is the most important response for the stimulation of land carbon accumulation by a land-surface model: CABLE. Processes related to leaf area should be better calibrated.
Haoyu Xu, Tao Zhang, Yiqi Luo, Xin Huang, and Wei Xue
Geosci. Model Dev., 11, 3027–3044, https://doi.org/10.5194/gmd-11-3027-2018, https://doi.org/10.5194/gmd-11-3027-2018, 2018
Short summary
Short summary
This study proposes a new parameter calibration method based on surrogate optimization techniques to improve the prediction accuracy of soil organic carbon. Experiments on three popular global soil carbon cycle models show that the surrogate-based optimization method is effective and efficient in terms of both accuracy and cost. This research would help develop and improve the parameterization schemes of Earth climate systems.
Related subject area
Climate and Earth System Modeling
The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500
HighResMIP versions of EC-Earth: EC-Earth3P and EC-Earth3P-HR – description, model computational performance and basic validation
Numerical study of the seasonal thermal and gas regimes of the largest artificial reservoir in western Europe using the LAKE 2.0 model
On the increased climate sensitivity in the EC-Earth model from CMIP5 to CMIP6
Earth System Model Evaluation Tool (ESMValTool) v2.0 – an extended set of large-scale diagnostics for quasi-operational and comprehensive evaluation of Earth system models in CMIP
Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management
WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model
The Sailor diagram – A new diagram for the verification of two-dimensional vector data from multiple models
Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2
The interactive global fire module pyrE (v1.0)
IPSL-CM5A2 – an Earth system model designed for multi-millennial climate simulations
Observations for Model Intercomparison Project (Obs4MIPs): status for CMIP6
Superparameterised cloud effects in the EMAC general circulation model (v2.50) – influences of model configuration
The Flexible Ocean and Climate Infrastructure version 1 (FOCI1): mean state and variability
Investigating the sensitivity to resolving aerosol interactions in downscaling regional model experiments with WRFv3.8.1 over Europe
Correcting a bias in a climate model with an augmented emulator
Improving climate model coupling through a complete mesh representation: a case study with E3SM (v1) and MOAB (v5.x)
Ocean biogeochemistry in the Norwegian Earth System Model version 2 (NorESM2)
Development of a sequential tool, LMDZ-NEMO-med-V1, to conduct global-to-regional past climate simulation for the Mediterranean basin: an Early Holocene case study
The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
Assessing the performance of climate change simulation results from BESM-OA2.5 compared with a CMIP5 model ensemble
Development of the MIROC-ES2L Earth system model and the evaluation of biogeochemical processes and feedbacks
Documenting numerical experiments in support of the Coupled Model Intercomparison Project Phase 6 (CMIP6)
The E3SM version 1 Single Column Model
Parallel I∕O in Flexible Modelling System (FMS) and Modular Ocean Model 5 (MOM5)
Mineral dust modelling with MADE3 in EMAC v2.54
COSMO-BEP-Tree v1.0: a coupled urban climate model with explicit representation of street trees
Statistical downscaling with the downscaleR package (v3.1.0): contribution to the VALUE intercomparison experiment
Lower boundary conditions in land surface models – effects on the permafrost and the carbon pools: a case study with CLM4.5
Simulating coupled surface–subsurface flows with ParFlow v3.5.0: capabilities, applications, and ongoing development of an open-source, massively parallel, integrated hydrologic model
HCLIM38: a flexible regional climate model applicable for different climate zones from coarse to convection-permitting scales
Including vegetation dynamics in an atmospheric chemistry-enabled general circulation model: linking LPJ-GUESS (v4.0) with the EMAC modelling system (v2.53)
Earth System Model Evaluation Tool (ESMValTool) v2.0 – diagnostics for emergent constraints and future projections from Earth system models in CMIP
Earth System Model Evaluation Tool (ESMValTool) v2.0 – technical overview
Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia
Replicability of the EC-Earth3 Earth system model under a change in computing environment
Implementation of Yale Interactive terrestrial Biosphere model v1.0 into GEOS-Chem v12.0.0: a tool for biosphere–chemistry interactions
The NExus Solutions Tool (NEST) v1.0: an open platform for optimizing multi-scale energy–water–land system transformations
JULES-BE: representation of bioenergy crops and harvesting in the Joint UK Land Environment Simulator vn5.1
An aerosol climatology for global models based on the tropospheric aerosol scheme in the Integrated Forecasting System of ECMWF
Beijing Climate Center Earth System Model version 1 (BCC-ESM1): model description and evaluation of aerosol simulations
HETEROFOR 1.0: a spatially explicit model for exploring the response of structurally complex forests to uncertain future conditions – Part 1: Carbon fluxes and tree dimensional growth
Can high-resolution GCMs reach the level of information provided by 12–50 km CORDEX RCMs in terms of daily precipitation distribution?
Reconstructing climatic modes of variability from proxy records using ClimIndRec version 1.0
Development and testing scenarios for implementing land use and land cover changes during the Holocene in Earth system model experiments
Coupling of a sediment diagenesis model (MEDUSA) and an Earth system model (CESM1.2): a contribution toward enhanced marine biogeochemical modelling and long-term climate simulations
Jena Soil Model (JSM v1.0; revision 1934): a microbial soil organic carbon model integrated with nitrogen and phosphorus processes
Evaluating Simulated Climate Patterns from theCMIP Archives Using Satellite and Reanalysis Datasets
A comprehensive assessment of tropical stratospheric upwelling in the specified dynamics Community Earth System Model 1.2.2 – Whole Atmosphere Community Climate Model (CESM (WACCM))
Evaluation of the University of Victoria Earth System Climate Model version 2.10 (UVic ESCM 2.10)
Malte Meinshausen, Zebedee R. J. Nicholls, Jared Lewis, Matthew J. Gidden, Elisabeth Vogel, Mandy Freund, Urs Beyerle, Claudia Gessner, Alexander Nauels, Nico Bauer, Josep G. Canadell, John S. Daniel, Andrew John, Paul B. Krummel, Gunnar Luderer, Nicolai Meinshausen, Stephen A. Montzka, Peter J. Rayner, Stefan Reimann, Steven J. Smith, Marten van den Berg, Guus J. M. Velders, Martin K. Vollmer, and Ray H. J. Wang
Geosci. Model Dev., 13, 3571–3605, https://doi.org/10.5194/gmd-13-3571-2020, https://doi.org/10.5194/gmd-13-3571-2020, 2020
Short summary
Short summary
This study provides the future greenhouse gas (GHG) concentrations under the new set of so-called SSP scenarios (the successors of the IPCC SRES and previous representative concentration pathway (RCP) scenarios). The projected CO2 concentrations range from 350 ppm for low-emission scenarios by 2150 to more than 2000 ppm under the high-emission scenarios. We also provide concentrations, latitudinal gradients, and seasonality for most of the other 42 considered GHGs.
Rein Haarsma, Mario Acosta, Rena Bakhshi, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Susanna Corti, Paolo Davini, Eleftheria Exarchou, Federico Fabiano, Uwe Fladrich, Ramon Fuentes Franco, Javier García-Serrano, Jost von Hardenberg, Torben Koenigk, Xavier Levine, Virna Loana Meccia, Twan van Noije, Gijs van den Oord, Froila M. Palmeiro, Mario Rodrigo, Yohan Ruprich-Robert, Philippe Le Sager, Etienne Tourigny, Shiyu Wang, Michiel van Weele, and Klaus Wyser
Geosci. Model Dev., 13, 3507–3527, https://doi.org/10.5194/gmd-13-3507-2020, https://doi.org/10.5194/gmd-13-3507-2020, 2020
Short summary
Short summary
HighResMIP is an international coordinated CMIP6 effort to investigate the improvement in climate modeling caused by an increase in horizontal resolution. This paper describes EC-Earth3P-(HR), which has been developed for HighResMIP. First analyses reveal that increasing resolution does improve certain aspects of the simulated climate but that many other biases still continue, possibly related to phenomena that are still not yet resolved and need to be parameterized.
Maksim Iakunin, Victor Stepanenko, Rui Salgado, Miguel Potes, Alexandra Penha, Maria Helena Novais, and Gonçalo Rodrigues
Geosci. Model Dev., 13, 3475–3488, https://doi.org/10.5194/gmd-13-3475-2020, https://doi.org/10.5194/gmd-13-3475-2020, 2020
Short summary
Short summary
The Alqueva reservoir, located in the southeast of Portugal, is the largest artificial reservoir in western Europe. It was established in 2002 to provide water and electrical resources to meet regional needs. Complex research of this reservoir is an essential scientific task in the scope of meteorology, hydrology, biology, and ecology. Two numerical models (namely, LAKE 2.0 and FLake) were used to assess the thermodynamic and biogeochemical regimes of the reservoir over 2 years of observations.
Klaus Wyser, Twan van Noije, Shuting Yang, Jost von Hardenberg, Declan O'Donnell, and Ralf Döscher
Geosci. Model Dev., 13, 3465–3474, https://doi.org/10.5194/gmd-13-3465-2020, https://doi.org/10.5194/gmd-13-3465-2020, 2020
Short summary
Short summary
The EC-Earth model used for CMIP6 is found to have a higher equilibrium climate sensitivity (ECS) than its predecessor used for CMIP5. In a series of sensitivity experiments, we investigate which model updates since CMIP5 have contributed to the increase in ECS. The main reason for the higher sensitivity in the EC-Earth model is the improved representation of the aerosol–radiation and aerosol–cloud interactions.
Veronika Eyring, Lisa Bock, Axel Lauer, Mattia Righi, Manuel Schlund, Bouwe Andela, Enrico Arnone, Omar Bellprat, Björn Brötz, Louis-Philippe Caron, Nuno Carvalhais, Irene Cionni, Nicola Cortesi, Bas Crezee, Edouard L. Davin, Paolo Davini, Kevin Debeire, Lee de Mora, Clara Deser, David Docquier, Paul Earnshaw, Carsten Ehbrecht, Bettina K. Gier, Nube Gonzalez-Reviriego, Paul Goodman, Stefan Hagemann, Steven Hardiman, Birgit Hassler, Alasdair Hunter, Christopher Kadow, Stephan Kindermann, Sujan Koirala, Nikolay Koldunov, Quentin Lejeune, Valerio Lembo, Tomas Lovato, Valerio Lucarini, François Massonnet, Benjamin Müller, Amarjiit Pandde, Núria Pérez-Zanón, Adam Phillips, Valeriu Predoi, Joellen Russell, Alistair Sellar, Federico Serva, Tobias Stacke, Ranjini Swaminathan, Verónica Torralba, Javier Vegas-Regidor, Jost von Hardenberg, Katja Weigel, and Klaus Zimmermann
Geosci. Model Dev., 13, 3383–3438, https://doi.org/10.5194/gmd-13-3383-2020, https://doi.org/10.5194/gmd-13-3383-2020, 2020
Short summary
Short summary
The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool designed to improve comprehensive and routine evaluation of earth system models (ESMs) participating in the Coupled Model Intercomparison Project (CMIP). It has undergone rapid development since the first release in 2016 and is now a well-tested tool that provides end-to-end provenance tracking to ensure reproducibility.
Peter Burek, Yusuke Satoh, Taher Kahil, Ting Tang, Peter Greve, Mikhail Smilovic, Luca Guillaumot, Fang Zhao, and Yoshihide Wada
Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, https://doi.org/10.5194/gmd-13-3267-2020, 2020
Short summary
Short summary
We present the new global hydrological model "Community Water Model" (CWatM), which can be used globally and regionally. The model is open source and written with the Python programming language. It uses global, freely available data in a smart and state-of-the-art format. It includes the major hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demand from the agriculture, domestic, and industrial sectors.
Haipeng Lin, Xu Feng, Tzung-May Fu, Heng Tian, Yaping Ma, Lijuan Zhang, Daniel J. Jacob, Robert M. Yantosca, Melissa P. Sulprizio, Elizabeth W. Lundgren, Jiawei Zhuang, Qiang Zhang, Xiao Lu, Lin Zhang, Lu Shen, Jianping Guo, Sebastian D. Eastham, and Christoph A. Keller
Geosci. Model Dev., 13, 3241–3265, https://doi.org/10.5194/gmd-13-3241-2020, https://doi.org/10.5194/gmd-13-3241-2020, 2020
Short summary
Short summary
Online coupling of meteorology and chemistry models often presents maintenance issues with hard-wired coding. We present WRF-GC, an one-way online coupling of the WRF meteorological model and GEOS-Chem atmospheric chemistry model for regional atmospheric chemistry and air quality modeling. Our coupling structure allows future versions of either parent model to be immediately integrated into WRF-GC. The WRF-GC model was able to well reproduce regional PM2.5 with greater computational efficiency.
Jon Sáenz, Sheila Carreno-Madinabeitia, Ganix Esnaola, Santos J. González-Rojí, Gabriel Ibarra-Berastegi, and Alain Ulazia
Geosci. Model Dev., 13, 3221–3240, https://doi.org/10.5194/gmd-13-3221-2020, https://doi.org/10.5194/gmd-13-3221-2020, 2020
Short summary
Short summary
A new diagram for the verification of vector variables (wind, current, etc.) generated by multiple models against a set of observations is presented in this package. It has been designed as a generalization of the Taylor diagram for two-dimensional quantities. It is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations, and it allows for an easy assessment of both bias and directional errors as well.
Lei Ma, George C. Hurtt, Louise P. Chini, Ritvik Sahajpal, Julia Pongratz, Steve Frolking, Elke Stehfest, Kees Klein Goldewijk, Donal O'Leary, and Jonathan C. Doelman
Geosci. Model Dev., 13, 3203–3220, https://doi.org/10.5194/gmd-13-3203-2020, https://doi.org/10.5194/gmd-13-3203-2020, 2020
Short summary
Short summary
Earth system models require information on historical land cover change. We present transition rules to generate land cover change from newly developed land use dataset (Land-use Harmonization, LUH2). The resulting forest cover, vegetation carbon, and emissions from land use and land cover change are simulated and evaluated against remote sensing data and other studies. The rules can guide the incorporation of land-cover information within earth system models for CMIP6.
Keren Mezuman, Kostas Tsigaridis, Gregory Faluvegi, and Susanne E. Bauer
Geosci. Model Dev., 13, 3091–3118, https://doi.org/10.5194/gmd-13-3091-2020, https://doi.org/10.5194/gmd-13-3091-2020, 2020
Short summary
Short summary
Fires affect the composition of the atmosphere and Earth’s radiation balance by emitting a suite of reactive gases and particles. An interactive fire module in an Earth system model (ESM) allows us to study the natural and anthropogenic drivers, feedbacks, and interactions of open fires. To do so, we have developed pyrE, the NASA GISS interactive fire emissions module.
The main motivation behind this work is to have fire emissions reacting to climate change and anthropogenic activities.
Pierre Sepulchre, Arnaud Caubel, Jean-Baptiste Ladant, Laurent Bopp, Olivier Boucher, Pascale Braconnot, Patrick Brockmann, Anne Cozic, Yannick Donnadieu, Jean-Louis Dufresne, Victor Estella-Perez, Christian Ethé, Frédéric Fluteau, Marie-Alice Foujols, Guillaume Gastineau, Josefine Ghattas, Didier Hauglustaine, Frédéric Hourdin, Masa Kageyama, Myriam Khodri, Olivier Marti, Yann Meurdesoif, Juliette Mignot, Anta-Clarisse Sarr, Jérôme Servonnat, Didier Swingedouw, Sophie Szopa, and Delphine Tardif
Geosci. Model Dev., 13, 3011–3053, https://doi.org/10.5194/gmd-13-3011-2020, https://doi.org/10.5194/gmd-13-3011-2020, 2020
Short summary
Short summary
Our paper describes IPSL-CM5A2, an Earth system model that can be integrated for long (several thousands of years) climate simulations. We describe the technical aspects, assess the model computing performance and evaluate the strengths and weaknesses of the model, by comparing pre-industrial and historical runs to the previous-generation model simulations and to observations. We also present a Cretaceous simulation as a case study to show how the model simulates deep-time paleoclimates.
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
Short summary
Short summary
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.
Harald Rybka and Holger Tost
Geosci. Model Dev., 13, 2671–2694, https://doi.org/10.5194/gmd-13-2671-2020, https://doi.org/10.5194/gmd-13-2671-2020, 2020
Short summary
Short summary
Simulating cloud processes and their interactions with their environment is one of the biggest challenges in atmospheric science. This study couples a cloud-resolving model with a global climate model to improve the representation of small-scale processes for climate simulations. Unlike conventional approaches, tropical precipitation is better simulated with the new model setup. However, the diurnal cycle of precipitation and cloud amounts can be significantly influenced by the chosen setup.
Katja Matthes, Arne Biastoch, Sebastian Wahl, Jan Harlaß, Torge Martin, Tim Brücher, Annika Drews, Dana Ehlert, Klaus Getzlaff, Fritz Krüger, Willi Rath, Markus Scheinert, Franziska U. Schwarzkopf, Tobias Bayr, Hauke Schmidt, and Wonsun Park
Geosci. Model Dev., 13, 2533–2568, https://doi.org/10.5194/gmd-13-2533-2020, https://doi.org/10.5194/gmd-13-2533-2020, 2020
Short summary
Short summary
A new Earth system model, the Flexible Ocean and Climate Infrastructure (FOCI), is introduced, consisting of a high-top atmosphere, an ocean model, sea-ice and land surface model components. A unique feature of FOCI is the ability to explicitly resolve small-scale oceanic features, for example, the Agulhas Current and the Gulf Stream. It allows to study the evolution of the climate system on regional and seasonal to (multi)decadal scales and bridges the gap to coarse-resolution climate models.
Vasileios Pavlidis, Eleni Katragkou, Andreas Prein, Aristeidis K. Georgoulias, Stergios Kartsios, Prodromos Zanis, and Theodoros Karacostas
Geosci. Model Dev., 13, 2511–2532, https://doi.org/10.5194/gmd-13-2511-2020, https://doi.org/10.5194/gmd-13-2511-2020, 2020
Short summary
Short summary
Our study investigates the role of aerosols in the climate of Europe by using a computer model and exploring different aerosol options available in this model as well as different aerosol datasets. Results show that aerosols can have a considerable impact on many aspects of the climate. Aerosols reduce solar radiation and temperature at the surface. Precipitation is not particularly affected in any specific direction. The cloudiness amount change is small. Also, changes in wind pattern are seen.
Doug McNeall, Jonny Williams, Richard Betts, Ben Booth, Peter Challenor, Peter Good, and Andy Wiltshire
Geosci. Model Dev., 13, 2487–2509, https://doi.org/10.5194/gmd-13-2487-2020, https://doi.org/10.5194/gmd-13-2487-2020, 2020
Short summary
Short summary
In the climate model FAMOUS, matching the modelled Amazon rainforest to observations required different land surface parameter settings than for other forests. It was unclear if this discrepancy was due to a bias in the modelled climate or an error in the land surface component of the model. Correcting the climate of the model with a statistical model corrects the simulation of the Amazon forest, suggesting that the land surface component of the model is not the source of the discrepancy.
Vijay S. Mahadevan, Iulian Grindeanu, Robert Jacob, and Jason Sarich
Geosci. Model Dev., 13, 2355–2377, https://doi.org/10.5194/gmd-13-2355-2020, https://doi.org/10.5194/gmd-13-2355-2020, 2020
Short summary
Short summary
Accurate climate modeling of coupled Earth systems requires mapping of solution field data between dependent components that use non-matching discrete meshes. While existing workflows provide a pathway to generate the projection weights as an offline step, severe bottlenecks impede flexible setup of high-resolution models. In this paper, we present new algorithmic approaches to simplify the E3SM computational workflow using a scalable software infrastructure to generate the remapping operators.
Jerry F. Tjiputra, Jörg Schwinger, Mats Bentsen, Anne L. Morée, Shuang Gao, Ingo Bethke, Christoph Heinze, Nadine Goris, Alok Gupta, Yan-Chun He, Dirk Olivié, Øyvind Seland, and Michael Schulz
Geosci. Model Dev., 13, 2393–2431, https://doi.org/10.5194/gmd-13-2393-2020, https://doi.org/10.5194/gmd-13-2393-2020, 2020
Short summary
Short summary
Ocean biogeochemistry plays an important role in determining the atmospheric carbon dioxide concentration. Earth system models, which are regularly used to study and project future climate change, generally include an ocean biogeochemistry component. Prior to their application, such models are rigorously validated against real-world observations. In this study, we evaluate the ability of the ocean biogeochemistry in the Norwegian Earth System Model version 2 to simulate various datasets.
Tristan Vadsaria, Laurent Li, Gilles Ramstein, and Jean-Claude Dutay
Geosci. Model Dev., 13, 2337–2354, https://doi.org/10.5194/gmd-13-2337-2020, https://doi.org/10.5194/gmd-13-2337-2020, 2020
Short summary
Short summary
This article aims to reproduce the Early Holocene climate over the Mediterranean basin, characterized with a large reorganization of the Mediterranean thermohaline circulation. In order to reduce the demand of strong computation resources, a comprehensive global-to-regional model architecture is developed and validated against paleo data. Beyond the case study shown here, this platform may be applied to a large number of paleoclimate contexts.
James A. Franke, Christoph Müller, Joshua Elliott, Alex C. Ruane, Jonas Jägermeyr, Juraj Balkovic, Philippe Ciais, Marie Dury, Pete D. Falloon, Christian Folberth, Louis François, Tobias Hank, Munir Hoffmann, R. Cesar Izaurralde, Ingrid Jacquemin, Curtis Jones, Nikolay Khabarov, Marian Koch, Michelle Li, Wenfeng Liu, Stefan Olin, Meridel Phillips, Thomas A. M. Pugh, Ashwan Reddy, Xuhui Wang, Karina Williams, Florian Zabel, and Elisabeth J. Moyer
Geosci. Model Dev., 13, 2315–2336, https://doi.org/10.5194/gmd-13-2315-2020, https://doi.org/10.5194/gmd-13-2315-2020, 2020
Short summary
Short summary
Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Crop models, which represent plant biology, are necessary tools for this purpose since they allow representing future climate, farmer choices, and new agricultural geographies. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, under the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to evaluate and improve crop models.
Vinicius Buscioli Capistrano, Paulo Nobre, Sandro F. Veiga, Renata Tedeschi, Josiane Silva, Marcus Bottino, Manoel Baptista da Silva Jr., Otacílio Leandro Menezes Neto, Silvio Nilo Figueroa, José Paulo Bonatti, Paulo Yoshio Kubota, Julio Pablo Reyes Fernandez, Emanuel Giarolla, Jessica Vial, and Carlos A. Nobre
Geosci. Model Dev., 13, 2277–2296, https://doi.org/10.5194/gmd-13-2277-2020, https://doi.org/10.5194/gmd-13-2277-2020, 2020
Short summary
Short summary
This work represents the product of our recent efforts to develop a Brazilian climate model and helps address some scientific issues on the frontier of knowledge (e.g., cloud feedback studies). The BESM results show climate sensitivity and thermodynamical responses similar to a CMIP5 ensemble. More than that, BESM has the objective of being an additional climate model with the ability to reproduce changes that are physically understood in order to study the global climate system.
Tomohiro Hajima, Michio Watanabe, Akitomo Yamamoto, Hiroaki Tatebe, Maki A. Noguchi, Manabu Abe, Rumi Ohgaito, Akinori Ito, Dai Yamazaki, Hideki Okajima, Akihiko Ito, Kumiko Takata, Koji Ogochi, Shingo Watanabe, and Michio Kawamiya
Geosci. Model Dev., 13, 2197–2244, https://doi.org/10.5194/gmd-13-2197-2020, https://doi.org/10.5194/gmd-13-2197-2020, 2020
Short summary
Short summary
We developed a new Earth system model (ESM) named MIROC-ES2L. This model is based on a state-of-the-art climate model and includes carbon–nitrogen cycles for the land and multiple biogeochemical cycles for the ocean. The model's performances on reproducing historical climate and biogeochemical changes are confirmed to be reasonable, and the new model is likely to be an
optimisticmodel in projecting future climate change among ESMs in the Coupled Model Intercomparison Project Phase 6.
Charlotte Pascoe, Bryan N. Lawrence, Eric Guilyardi, Martin Juckes, and Karl E. Taylor
Geosci. Model Dev., 13, 2149–2167, https://doi.org/10.5194/gmd-13-2149-2020, https://doi.org/10.5194/gmd-13-2149-2020, 2020
Short summary
Short summary
We present a methodology for documenting numerical experiments in the context of an information sharing ecosystem which allows the weather, climate, and earth system modelling community to accurately document and share information about their modelling workflow. We describe how through iteration with a range of stakeholders, we rationalized multiple sources of information and improved the clarity of experimental definitions for the Coupled Model Intercomparison Project Phase 6 (CMIP6).
Peter A. Bogenschutz, Shuaiqi Tang, Peter M. Caldwell, Shaocheng Xie, Wuyin Lin, and Yao-sheng Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-27, https://doi.org/10.5194/gmd-2020-27, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
This paper documents a tool that has been developed that can be used to accelerate the development and understanding of climate models. This version of the model, known as a the single column model, is much faster to run than the full climate model and we demonstrate that this tool can be used to quickly exploit model biases that arise due to physical processes. We show examples of how this single column model can directly benefit the field.
Rui Yang, Marshall Ward, and Ben Evans
Geosci. Model Dev., 13, 1885–1902, https://doi.org/10.5194/gmd-13-1885-2020, https://doi.org/10.5194/gmd-13-1885-2020, 2020
Short summary
Short summary
Parallel I/O is implemented in the Modular Ocean Model (MOM) with optimal performance over a range of tuning parameters of model configuration, netCDF, MPI-IO and Lustre filesystem. The scalable parallel I/O performance is observed at 0.1° resolution global model, and it could achieve up to 60 times faster in write speed relative to serial single-file I/O running on 960 PEs.
Christof G. Beer, Johannes Hendricks, Mattia Righi, Bernd Heinold, Ina Tegen, Silke Groß, Daniel Sauer, Adrian Walser, and Bernadett Weinzierl
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-82, https://doi.org/10.5194/gmd-2020-82, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Mineral dust aerosol plays an important role in the climate system. Previously, dust emissions have often been represented in global models by prescribed monthly-mean emission fields representative of a specific year. We now apply an online calculation of wind-driven dust emissions. This results in an improved agreement with observations, due to a better representation of the highly variable dust emissions. Increasing the model resolution led to an additional performance gain.
Gianluca Mussetti, Dominik Brunner, Stephan Henne, Jonas Allegrini, E. Scott Krayenhoff, Sebastian Schubert, Christian Feigenwinter, Roland Vogt, Andreas Wicki, and Jan Carmeliet
Geosci. Model Dev., 13, 1685–1710, https://doi.org/10.5194/gmd-13-1685-2020, https://doi.org/10.5194/gmd-13-1685-2020, 2020
Short summary
Short summary
Street trees are regarded as a powerful measure to reduce excessive heat in cities. To enable city-wide studies of the cooling effect of street trees, we developed a coupled urban climate model with explicit representation of street trees (COSMO-BEP-Tree). The model compares well with surface, flux and satellite observations and responds realistically to changes in tree characteristics. Street trees largely impact energy fluxes and wind speed, while air temperatures are only slightly reduced.
Joaquín Bedia, Jorge Baño-Medina, Mikel N. Legasa, Maialen Iturbide, Rodrigo Manzanas, Sixto Herrera, Ana Casanueva, Daniel San-Martín, Antonio S. Cofiño, and José Manuel Gutiérrez
Geosci. Model Dev., 13, 1711–1735, https://doi.org/10.5194/gmd-13-1711-2020, https://doi.org/10.5194/gmd-13-1711-2020, 2020
Short summary
Short summary
We introduce downscaleR, an open-source tool for statistical downscaling (SD) of climate information, implementing the most popular approaches and state-of-the-art techniques. It makes possible the development of end-to-end downscaling applications, from data retrieval to model building, validation, and prediction, bringing to climate scientists and practitioners a unique comprehensive framework for the development of complex and fully reproducible SD experiments.
Ignacio Hermoso de Mendoza, Hugo Beltrami, Andrew H. MacDougall, and Jean-Claude Mareschal
Geosci. Model Dev., 13, 1663–1683, https://doi.org/10.5194/gmd-13-1663-2020, https://doi.org/10.5194/gmd-13-1663-2020, 2020
Short summary
Short summary
We study the impact that the thickness of the subsurface and the geothermal gradient have in land models for climate simulations. To do this, we modify the Community Land Model version 4.5. In a scenario of rising atmospheric temperatures, the temperature of an insufficiently deep subsurface rises faster than it would in the real land. For the model, this produces faster permafrost thawing and increased emissions of land carbon to the atmosphere.
Benjamin N. O. Kuffour, Nicholas B. Engdahl, Carol S. Woodward, Laura E. Condon, Stefan Kollet, and Reed M. Maxwell
Geosci. Model Dev., 13, 1373–1397, https://doi.org/10.5194/gmd-13-1373-2020, https://doi.org/10.5194/gmd-13-1373-2020, 2020
Short summary
Short summary
Integrated hydrologic models (IHMs) were developed in order to allow for more accurate simulations of real-world ecohydrologic conditions. Many IHMs exist, and the literature can be dense, so it is often difficult to understand what a specific model can and cannot do. We provide a review of the current core capabilities, solution techniques, communication structure with other models, some limitations, and potential future improvements of one such open-source integrated model called ParFlow.
Danijel Belušić, Hylke de Vries, Andreas Dobler, Oskar Landgren, Petter Lind, David Lindstedt, Rasmus A. Pedersen, Juan Carlos Sánchez-Perrino, Erika Toivonen, Bert van Ulft, Fuxing Wang, Ulf Andrae, Yurii Batrak, Erik Kjellström, Geert Lenderink, Grigory Nikulin, Joni-Pekka Pietikäinen, Ernesto Rodríguez-Camino, Patrick Samuelsson, Erik van Meijgaard, and Minchao Wu
Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, https://doi.org/10.5194/gmd-13-1311-2020, 2020
Short summary
Short summary
A new regional climate modelling system, HCLIM38, is presented and shown to be applicable in different regions ranging from the tropics to the Arctic. The main focus is on climate simulations at horizontal resolutions between 1 and 4 km, the so-called convection-permitting scales, even though the model can also be used at coarser resolutions. The benefits of simulating climate at convection-permitting scales are shown and are particularly evident for climate extremes.
Matthew Forrest, Holger Tost, Jos Lelieveld, and Thomas Hickler
Geosci. Model Dev., 13, 1285–1309, https://doi.org/10.5194/gmd-13-1285-2020, https://doi.org/10.5194/gmd-13-1285-2020, 2020
Short summary
Short summary
We have integrated the LPJ-GUESS dynamic global vegetation model into the EMAC atmospheric chemistry-enabled GCM (general circulation model). This combined framework will enable the investigation of many land–atmosphere interactions and feedbacks with state-of-the-art simulation models. Initial results show that using the climate produced by EMAC together with LPJ-GUESS produces an acceptable representation of the global vegetation.
Axel Lauer, Veronika Eyring, Omar Bellprat, Lisa Bock, Bettina K. Gier, Alasdair Hunter, Ruth Lorenz, Núria Pérez-Zanón, Mattia Righi, Manuel Schlund, Daniel Senftleben, Katja Weigel, and Sabrina Zechlau
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-60, https://doi.org/10.5194/gmd-2020-60, 2020
Revised manuscript accepted for GMD
Mattia Righi, Bouwe Andela, Veronika Eyring, Axel Lauer, Valeriu Predoi, Manuel Schlund, Javier Vegas-Regidor, Lisa Bock, Björn Brötz, Lee de Mora, Faruk Diblen, Laura Dreyer, Niels Drost, Paul Earnshaw, Birgit Hassler, Nikolay Koldunov, Bill Little, Saskia Loosveldt Tomas, and Klaus Zimmermann
Geosci. Model Dev., 13, 1179–1199, https://doi.org/10.5194/gmd-13-1179-2020, https://doi.org/10.5194/gmd-13-1179-2020, 2020
Short summary
Short summary
This paper describes the second major release of ESMValTool, a community diagnostic and performance metrics tool for the evaluation of Earth system models. This new version features a brand new design, with an improved interface and a revised preprocessor. It takes advantage of state-of-the-art computational libraries and methods to deploy efficient and user-friendly data processing, improving the performance over its predecessor by more than a factor of 30.
Miguel Nogueira, Clément Albergel, Souhail Boussetta, Frederico Johannsen, Isabel F Trigo, Sofia L Ermida, João P A Martins, and Emanuel Dutra
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-49, https://doi.org/10.5194/gmd-2020-49, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
We used earth observations to evaluate and improve the representation of Land Surface Temperature (LST) and vegetation coverage over Iberia in CHTESSEL and SURFEX Land Surface Models. We demonstrate the added value of updating the vegetation types and fractions together with the representation of vegetation coverage seasonality. Results show a large reduction of daily maximum LST systematic error during warm months, with neutral impacts in other seasons.
François Massonnet, Martin Ménégoz, Mario Acosta, Xavier Yepes-Arbós, Eleftheria Exarchou, and Francisco J. Doblas-Reyes
Geosci. Model Dev., 13, 1165–1178, https://doi.org/10.5194/gmd-13-1165-2020, https://doi.org/10.5194/gmd-13-1165-2020, 2020
Short summary
Short summary
Earth system models (ESMs) are one of the cornerstones of modern climate science. They are usually run on high-performance computers (HPCs). Whether the choice of HPC can affect the model results is a question of importance for optimizing the design of scientific studies. Here, we introduce a protocol for testing the replicability of the EC-Earth3 ESM across different HPCs. We find the simulation results to be replicable only if specific precautions are taken at the compilation stage.
Yadong Lei, Xu Yue, Hong Liao, Cheng Gong, and Lin Zhang
Geosci. Model Dev., 13, 1137–1153, https://doi.org/10.5194/gmd-13-1137-2020, https://doi.org/10.5194/gmd-13-1137-2020, 2020
Short summary
Short summary
We coupled a dynamic vegetation model YIBs with the chemical transport model GEOS-Chem to develop a new tool for studying interactions between atmospheric chemistry and biosphere. Within this framework, leaf area index and stomatal conductance are predicted for chemical simulations. In turn, surface ozone causes negative impacts to plant growth and the consequent dry deposition. Such interactions are important for air pollution prediction but ignored in most of current chemical models.
Adriano Vinca, Simon Parkinson, Edward Byers, Peter Burek, Zarrar Khan, Volker Krey, Fabio A. Diuana, Yaoping Wang, Ansir Ilyas, Alexandre C. Köberle, Iain Staffell, Stefan Pfenninger, Abubakr Muhammad, Andrew Rowe, Roberto Schaeffer, Narasimha D. Rao, Yoshihide Wada, Ned Djilali, and Keywan Riahi
Geosci. Model Dev., 13, 1095–1121, https://doi.org/10.5194/gmd-13-1095-2020, https://doi.org/10.5194/gmd-13-1095-2020, 2020
Short summary
Short summary
This article describes a newly developed numerical model that can assess impacts of long-term policies for the energy, water and land (WEL) sectors at the scale of a river basin. We show the importance of having an integrated method when jointly considering multiple policies as opposed to conventional sectoral analysis. This model can be useful for studying river basins, such as the Indus basin, that are exposed to challenges over WEL sectors, like water scarcity or food and energy access.
Emma W. Littleton, Anna B. Harper, Naomi E. Vaughan, Rebecca J. Oliver, Maria Carolina Duran-Rojas, and Timothy M. Lenton
Geosci. Model Dev., 13, 1123–1136, https://doi.org/10.5194/gmd-13-1123-2020, https://doi.org/10.5194/gmd-13-1123-2020, 2020
Short summary
Short summary
This study presents new functionality to represent bioenergy crops and harvests in JULES, a land surface model. Such processes must be explicitly represented before the environmental effects of large-scale bioenergy production can be fully evaluated, using Earth system modelling. This new functionality allows for many types of bioenergy plants and harvesting regimes to be simulated, such as perennial grasses, short rotation coppicing, and forestry rotations.
Alessio Bozzo, Angela Benedetti, Johannes Flemming, Zak Kipling, and Samuel Rémy
Geosci. Model Dev., 13, 1007–1034, https://doi.org/10.5194/gmd-13-1007-2020, https://doi.org/10.5194/gmd-13-1007-2020, 2020
Short summary
Short summary
Aerosols are tiny particles of natural and anthropogenic origin transported by the winds in the Earth's atmosphere. These particles play a key role in the energy budget of our planet. In numerical models of the Earth's atmosphere, aerosols spatial distribution are often represented by conditions averaged over several years. We prepared a new aerosol climatology and used it in a numerical weather model. We show that in certain regions aerosols can affect the quality of numerical weather forecast.
Tongwen Wu, Fang Zhang, Jie Zhang, Weihua Jie, Yanwu Zhang, Fanghua Wu, Laurent Li, Jinghui Yan, Xiaohong Liu, Xiao Lu, Haiyue Tan, Lin Zhang, Jun Wang, and Aixue Hu
Geosci. Model Dev., 13, 977–1005, https://doi.org/10.5194/gmd-13-977-2020, https://doi.org/10.5194/gmd-13-977-2020, 2020
Short summary
Short summary
This paper describes the first version of the Beijing Climate Center (BCC) fully coupled Earth System Model with interactive atmospheric chemistry and aerosols (BCC-ESM1). It is one of the models at the BCC for the Coupled Model Intercomparison Project Phase 6 (CMIP6). The CMIP6 Aerosol Chemistry Model Intercomparison Project (AerChemMIP) experiment using BCC-ESM1 has been finished. The evaluations show an overall good agreement between BCC-ESM1 simulations and observations in the 20th century.
Mathieu Jonard, Frédéric André, François de Coligny, Louis de Wergifosse, Nicolas Beudez, Hendrik Davi, Gauthier Ligot, Quentin Ponette, and Caroline Vincke
Geosci. Model Dev., 13, 905–935, https://doi.org/10.5194/gmd-13-905-2020, https://doi.org/10.5194/gmd-13-905-2020, 2020
Short summary
Short summary
To explore the forest response to new forestry practices under a changing environment, one needs models combining a process-based approach with a detailed spatial representation, which is very rare. We decided to develop our own model according to a spatially explicit approach describing individual tree growth based on resource sharing (light, water and nutrients). A first evaluation showed that HETEROFOR predicts well individual radial growth and is able to reproduce size–growth relationships.
Marie-Estelle Demory, Ségolène Berthou, Silje L. Sørland, Malcolm J. Roberts, Urs Beyerle, Jon Seddon, Rein Haarsma, Christoph Schär, Ole B. Christensen, Rowan Fealy, Jesus Fernandez, Grigory Nikulin, Daniele Peano, Dian Putrasahan, Christopher D. Roberts, Christian Steger, Claas Teichmann, and Robert Vautard
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-370, https://doi.org/10.5194/gmd-2019-370, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
Now that Global Climate Models (GCM) can run at similar resolutions than Regional Climate Models (RCM), one may wonder whether GCMs and RCMs provide similar regional climate information. We perform such evaluation for daily precipitation distribution in PRIMAVERA GCMs (25–50 km resolution) and CORDEX RCMs (12–50 km resolution) over Europe. We show that PRIMAVERA and CORDEX simulate similar distributions. Considering both datasets at such resolution results in large benefits for impact studies.
Simon Michel, Didier Swingedouw, Marie Chavent, Pablo Ortega, Juliette Mignot, and Myriam Khodri
Geosci. Model Dev., 13, 841–858, https://doi.org/10.5194/gmd-13-841-2020, https://doi.org/10.5194/gmd-13-841-2020, 2020
Short summary
Short summary
Natural archives such as sediments, ice, tree rings or speleothems provide indirect observations of past climate at local and regional scales. In this paper, we provide a computational device to properly make evaluated reconstructions of climate indices using these paleo-data. It provides optimizing cross-validation algorithms and four regression methods that are applied to the reconstruction of the North Atlantic Oscillation index and compared in this study.
Sandy P. Harrison, Marie-José Gaillard, Benjamin D. Stocker, Marc Vander Linden, Kees Klein Goldewijk, Oliver Boles, Pascale Braconnot, Andria Dawson, Etienne Fluet-Chouinard, Jed O. Kaplan, Thomas Kastner, Francesco S. R. Pausata, Erick Robinson, Nicki J. Whitehouse, Marco Madella, and Kathleen D. Morrison
Geosci. Model Dev., 13, 805–824, https://doi.org/10.5194/gmd-13-805-2020, https://doi.org/10.5194/gmd-13-805-2020, 2020
Short summary
Short summary
The Past Global Changes LandCover6k initiative will use archaeological records to refine scenarios of land use and land cover change through the Holocene to reduce the uncertainties about the impacts of human-induced changes before widespread industrialization. We describe how archaeological data are used to map land use change and how the maps can be evaluated using independent palaeoenvironmental data. We propose simulations to test land use and land cover change impacts on past climates.
Takasumi Kurahashi-Nakamura, André Paul, Guy Munhoven, Ute Merkel, and Michael Schulz
Geosci. Model Dev., 13, 825–840, https://doi.org/10.5194/gmd-13-825-2020, https://doi.org/10.5194/gmd-13-825-2020, 2020
Short summary
Short summary
Chemical processes in ocean-floor sediments have a large influence on the marine carbon cycle, hence the global climate, at long timescales. We developed a new coupling scheme for a chemical sediment model and a comprehensive climate model. The new coupled model outperformed the original uncoupled climate model in reproducing the global distribution of sediment properties. The sediment model will also act as a
bridgebetween the ocean model and paleoceanographic data.
Lin Yu, Bernhard Ahrens, Thomas Wutzler, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 13, 783–803, https://doi.org/10.5194/gmd-13-783-2020, https://doi.org/10.5194/gmd-13-783-2020, 2020
Short summary
Short summary
In this paper, we have developed a new soil organic carbon model that describes the formation and turnover of soil organic matter in a more mechanistic manner. With this model, we are able to better represent how microorganisms and nutrient processes influence the below-ground carbon storage and better explain some observed features of soil organic matter. We hope this model can increase our confidence in predictions of future climate change, particularly on how soil can mitigate the process.
John T. Fasullo
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-1, https://doi.org/10.5194/gmd-2020-1, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
The fidelity of climate model simulations included in the WCRP Coupled Model Intercomparison Project Versions 3 through 6 is evaluated using best-estimates of fields considered by the community to be critical for climate change projections. The analysis benchmarks patterns of the mean state and variability (seasonal/interannual) both within and across model generations, highlighting progress and quantifying persisting biases across models.
Nicholas A. Davis, Sean M. Davis, Robert W. Portmann, Eric Ray, Karen H. Rosenlof, and Pengfei Yu
Geosci. Model Dev., 13, 717–734, https://doi.org/10.5194/gmd-13-717-2020, https://doi.org/10.5194/gmd-13-717-2020, 2020
Short summary
Short summary
Large-scale waves drive upward motion in the tropical stratosphere, with major impacts on stratospheric chemistry and climate. However, some of the modeling methods which attempt to simulate the past evolution of the stratosphere do not seem to be able to recreate important trends. We believe this is due to disagreements between the basic climate of the model and observations, but if the method is constructed more carefully, the disagreement becomes smaller and the trends become more realistic.
Nadine Mengis, David P. Keller, Andrew MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, H. Damon Matthews, and Kirsten Zickfeld
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-373, https://doi.org/10.5194/gmd-2019-373, 2020
Revised manuscript accepted for GMD
Short summary
Short summary
In this manuscript we evaluate the newest version of the University of Victoria Earth System Climate Model (UVic ESCM 2.10). Combining recent model developments as a joint effort, this version is to be used the next phase of model inter-comparison and climate change studies. The UVic ESCM 2.10 is capable of reproducing well changes in historical temperature and carbon fluxes, as well as the distribution of many ocean tracers.
Cited articles
Adler, R. F., Huffman, G. J., Chang, A., Ferraro, R., Xie, P.-P., Janowiak, J., Rudolf, B., Schneider, U., Curtis, S., Bolvin, D., Gruber, A., Susskind, J., Arkin, P., and Nelkin, E.: The version-2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979–present), J. Hydrometeorol., 4, 1147–1167, 2003.
Aksoy, A., Zhang, F., and Nielsen-Gammon, J. W.: Ensemble-based simultaneous state and parameter estimation with MM5, Geophys. Res. Lett., 33, L12801, https://doi.org/10.1029/2006GL026186, 2006.
Allen, M. R., Stott, P. A., Mitchell, J. F., Schnur, R., and Delworth, T. L.: Quantifying the uncertainty in forecasts of anthropogenic climate change, Nature, 407, 617–620, 2000.
Arulampalam, M., Maskell, S., Gordon, N., and Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking, Signal Processing, IEEE T., 50, 174–188, 2002.
Bardenet, R., Brendel, M., Kégl, B., and Sebag, M.: Collaborative hyperparameter tuning, in: Proceedings of the 30th International Conference on Machine Learning (ICML-13), 16–21 June 2013, Atlanta, Georgia, USA, 199–207, 2013.
Barkstrom, B. R.: The earth radiation budget experiment (ERBE), B. Am. Meteorol. Soc., 65, 1170–1185, 1984.
Beven, K. and Binley, A.: The future of distributed models: model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Cameron, D., Beven, K. J., Tawn, J., Blazkova, S., and Naden, P.: Flood frequency estimation by continuous simulation for a gauged upland catchment (with uncertainty), J. Hydrol., 219, 169–187, 1999.
Campolongo, F., Cariboni, J., and Saltelli, A.: An effective screening design for sensitivity analysis of large models, Environ. Modell. Softw., 22, 1509–1518, 2007.
Chen, T.-Y., Wei, W.-J., and Tsai, J.-C.: Optimum design of headstocks of precision lathes, Int. J. Mach. Tool. Manu., 39, 1961–1977, 1999.
Eldred, M., Agarwal, H., Perez, V., Wojtkiewicz Jr., S., and Renaud, J.: Investigation of reliability method formulations in DAKOTA/UQ, Struct. Infrastruct. E., 3, 199–213, 2007.
Elkinton, C. N., Manwell, J. F., and McGowan, J. G.: Algorithms for offshore wind farm layout optimization, Wind Engineering, 32, 67–84, 2008.
Evensen, G.: The ensemble Kalman filter: Theoretical formulation and practical implementation, Ocean Dynam., 53, 343–367, 2003.
Gan, Y., Duan, Q., Gong, W., Tong, C., Sun, Y., Chu, W., Ye, A., Miao, C., and Di, Z.: A comprehensive evaluation of various sensitivity analysis methods: a case study with a hydrological model, Environ. Modell. Softw., 51, 269–285, 2014.
Gilks, W. R.: Markov Chain Monte Carloin Practice, Chapman and Hall/CRC, London, UK, 1995.
Gill, M. K., Kaheil, Y. H., Khalil, A., McKee, M., and Bastidas, L.: Multiobjective particle swarm optimization for parameter estimation in hydrology, Water Resour. Res., 42, W07417, https://doi.org/10.1029/2005WR004528, 2006.
Gleckler, P. J., Taylor, K. E., and Doutriaux, C.: Performance metrics for climate models, J. Geophys. Res.-Atmos., 113, D06104, https://doi.org/10.1029/2007JD008972, 2008.
Golaz, J., Salzmann, M., Donner, L. J., Horowitz, L. W., Ming, Y., and Zhao, M.: Sensitivity of the aerosol indirect effect to subgrid variability in the cloud parameterization of the GFDL atmosphere general circulation model AM3, J. Climate, 24, 3145–3160, 2011.
Goldberg, D. E., Korb, B., and Deb, K.: Messy genetic algorithms: motivation, analysis, and first results, Complex systems, 3, 493–530, 1989.
Grell, G. A., Dudhia, J., and Stauffer, D.: A description of the fifthgeneration Penn State/NCAR Mesoscale Model (MM5), NCAR Tech. Note NCAR/TN-3981STR, 122 pp., 1994.
Hack, J. J., Boville, B., Kiehl, J., Rasch, P., and Williamson, D.: Climate statistics from the National Center for Atmospheric Research Community Climate Model CCM2, J. Geophys. Res.-Atmos., 99, 20785–20813, 1994.
Hader, R. and Park, S. H.: Slope-rotatable central composite designs, Technometrics, 20, 413–417, 1978.
Hakkarainen, J., Ilin, A., Solonen, A., Laine, M., Haario, H., Tamminen, J., Oja, E., and Järvinen, H.: On closure parameter estimation in chaotic systems, Nonlin. Processes Geophys., 19, 127–143, https://doi.org/10.5194/npg-19-127-2012, 2012.
Hararuk, O., Xia, J., and Luo, Y.: Evaluation and improvement of a global land model against soil carbon data using a Bayesian Markov chain Monte Carlo method, J. Geophys. Res.-Biogeo., 119, 403–417, 2014.
Hegerty, B., Hung, C.-C., and Kasprak, K.: A comparative study on differential evolution and genetic algorithms for some combinatorial problems, in: Proceedings of 8th Mexican International Conference on Artificial Intelligence, 9–13 November 2009, Guanajuato, Mexico, 88, 2009.
Jackson, C., Sen, M. K., and Stoffa, P. L.: An efficient stochastic Bayesian approach to optimal parameter and uncertainty estimation for climate model predictions, J. Climate, 17, 2828–2841, 2004.
Jackson, C. S., Sen, M. K., Huerta, G., Deng, Y., and Bowman, K. P.: Error reduction and convergence in climate prediction, J. Climate, 21, 6698–6709, 2008.
Jakumeit, J., Herdy, M., and Nitsche, M.: Parameter optimization of the sheet metal forming process using an iterative parallel Kriging algorithm, Struct. Multidiscip. O., 29, 498–507, 2005.
Kennedy, J.: Particle swarm optimization, in: Encyclopedia of Machine Learning, Springer, New York, USA, 760–766, 2010.
Li, L., Wang, B., Dong, L., Liu, L., Shen, S., Hu, N., Sun, W., Wang, Y., Huang, W., Shi, X., Pu, Y., and Yang, G.: Evaluation of grid-point atmospheric model of IAP LASG version 2 (GAMIL2), Adv. Atmos. Sci., 30, 855–867, 2013.
Li, J., Duan, Q. Y., Gong, W., Ye, A., Dai, Y., Miao, C., Di, Z., Tong, C., and Sun, Y.: Assessing parameter importance of the Common Land Model based on qualitative and quantitative sensitivity analysis, Hydrol. Earth Syst. Sci., 17, 3279–3293, https://doi.org/10.5194/hess-17-3279-2013, 2013.
Liang, F., Cheng, Y., and Lin, G.: Simulated stochastic approximation annealing for global optimization with a square-root cooling schedule, J. Am. Stat. Assoc., 109, 847–863, 2013.
Lin, Y. L., Zhao, M., Ming, Y., Golaz, J., Donner, L. J., Klein, S. A., Ramaswamy, V., and Xie, S.: Precipitation partitioning, tropical clouds, and intraseasonal variability in GFDL AM2, J. Climate, 26, 5453–5466, 2013.
McKay, M. D., Beckman, R. J., and Conover, W. J.: Comparison of three methods for selecting values of input variables in the analysis of output from a computer code, Technometrics, 21, 239–245, 1979.
Morris, M. D.: Factorial sampling plans for preliminary computational experiments, Technometrics, 33, 161–174, 1991.
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, 2008.
Murphy, J. M., Sexton, D. M., Barnett, D. N., Jones, G. S., Webb, M. J., Collins, M., and Stainforth, D. A.: Quantification of modelling uncertainties in a large ensemble of climate change simulations, Nature, 430, 768–772, 2004.
Nelder, J. A. and Mead, R.: A simplex method for function minimization, Computer J., 7, 308–313, 1965.
Poterjoy, J., Zhang, F., and Weng, Y.: The effects of sampling errors on the EnKF assimilation of inner-core hurricane observations, Mon. Weather Rev., 142, 1609–1630, 2014.
Press, W., Teukolsky, S., Vetterling, W., and Flannery, B.: Numerical Recipes in Fortran, Cambridge Univ. Press, Cambridge, 70 pp., 1992.
Raktoe, B. L., Hedayat, A., and Federer, W. T.: Factorial Designs, John Wiley & Sons, Hoboken, New Jersey, USA, 1981.
Reichler, T. and Kim, J.: How well do coupled models simulate today's climate?, B. Am. Meteorol. Soc., 89, 303–311, 2008.
Santitissadeekorn, N. and Jones, C.: Two-stage filtering for joint state-parameter estimation, Mon. Weather Rev., 143, 2028–2042, https://doi.org/10.1175/MWR-D-14-00176.1, 2015.
Severijns, C. and Hazeleger, W.: Optimizing parameters in an atmospheric general circulation model, J. Climate, 18, 3527–3535, 2005.
Shi, Y. and Eberhart, R. C.: Empirical study of particle swarm optimization, in: Proceedings of the 1999 Congress on Evolutionary Computation, CEC 99, Vol. 3, IEEE, 6–9 July 1999, Washington, DC, USA, 1945–1950, 1999.
Simmons, A., Uppala, S., Dee, D., and Kobayashi, S.: ERA-interim: new ECMWF reanalysis products from 1989 onwards, ECMWF Newsl., 110, 25–35, 2007.
Sobol, I. M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates, Math. Comput. Simulat., 55, 271–280, 2001.
Storn, R. and Price, K.: Differential Evolution – a Simple and Efficient Adaptive Scheme for Global Optimization over Continuous Spaces, ICSI Berkeley, Berkeley, California, USA, 1995.
Sun, Y., Hou, Z., Huang, M., Tian, F., and Ruby Leung, L.: Inverse modeling of hydrologic parameters using surface flux and runoff observations in the Community Land Model, Hydrol. Earth Syst. Sci., 17, 4995–5011, https://doi.org/10.5194/hess-17-4995-2013, 2013.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, 2001.
Tong, C.: PSUADE User's Manual, Lawrence Livermore National Laboratory (LLNL), Livermore, CA, 109 pp., 2005.
Van Laarhoven, P. J. and Aarts, E. H.: Simulated Annealing, Springer, Dordrecht, Netherlands, 1987.
Wang, B., Wan, H., Ji, Z., Zhang, X., Yu, R., Yu, Y., and Liu, H.: Design of a new dynamical core for global atmospheric models based on some efficient numerical methods, S. China Ser. A, 47, 4–21, 2004.
Warren, S. G. and Schneider, S. H.: Seasonal simulation as a test for uncertainties in the parameterizations of a Budyko-Sellers zonal climate model, J. Atmos. Sci., 36, 1377–1391, 1979.
Williams, P. D.: Modelling climate change: the role of unresolved processes, Philos. T. R. Soc. A, 363, 2931–2946, 2005.
Xu, K.-M. and Krueger, S. K.: Evaluation of cloudiness parameterizations using a cumulus ensemble model, Mon. Weather Rev., 119, 342–367, 1991.
Yang, B., Qian, Y., Lin, G., Leung, L. R., Rasch, P. J., Zhang, G. J., McFarlane, S. A., Zhao, C., Zhang, Y., Wang, H., Wang, M., and Liu, X.: Uncertainty quantification and parameter tuning in the CAM5 Zhang-McFarlane convection scheme and impact of improved convection on the global circulation and climate, J. Geophys. Res.-Atmos., 118, 395–415, 2013.
Yang, B., Zhang, Y., Qian, Y., Huang, A., and Yan, H.: Calibration of a convective parameterization scheme in the WRF model and its impact on the simulation of East Asian summer monsoon precipitation, Clim. Dynam., 1, 1–24, 2014.
Yu, R.: A two-step shape-preserving advection scheme, Adv. Atmos. Sci., 11, 479–490, 1994.
Zhang, G. J. and Mu, M.: Effects of modifications to the Zhang-McFarlane convection parameterization on the simulation of the tropical precipitation in the National Center for Atmospheric Research Community Climate Model, version 3, J. Geophys. Res.-Atmos., 110, D09109, https://doi.org/10.1029/2004JD005617, 2005.
Zhang, M., Lin, W., Bretherton, C. S., Hack, J. J., and Rasch, P. J.: A modified formulation of fractional stratiform condensation rate in the NCAR Community Atmospheric Model (CAM2), J. Geophys. Res.-Atmos., 108, 4035, https://doi.org/10.1029/2002jd002523, 2003.
Search articles
Special issue
Download
Short summary
A “three-step” methodology is proposed to effectively obtain the optimum combination of some key parameters in cloud and convective parameterizations according to a comprehensive objective evaluation metrics. The optimal results improve the metrics performance by 9%. A software framework can automatically execute any part of the “three-step” calibration strategy. The proposed methodology and framework can easily be applied to other GCMs to speed up the model development process.
A “three-step” methodology is proposed to effectively obtain the optimum combination of some...
Geoscientific Model Development
An interactive open-access journal of the European Geosciences Union
All site content, except where otherwise noted, is licensed under the Creative Commons Attribution 4.0 License.