Articles | Volume 13, issue 2
Geosci. Model Dev., 13, 841–858, 2020
https://doi.org/10.5194/gmd-13-841-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 13, 841–858, 2020
https://doi.org/10.5194/gmd-13-841-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper 03 Mar 2020
Model description paper | 03 Mar 2020
Reconstructing climatic modes of variability from proxy records using ClimIndRec version 1.0
Simon Michel et al.
Related authors
No articles found.
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
Short summary
Short summary
This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Samuel Tiéfolo Diabaté, Didier Swingedouw, Joël Jean-Marie Hirschi, Aurélie Duchez, Philip J. Leadbitter, Ivan D. Haigh, and Gerard D. McCarthy
Ocean Sci., 17, 1449–1471, https://doi.org/10.5194/os-17-1449-2021, https://doi.org/10.5194/os-17-1449-2021, 2021
Short summary
Short summary
The Gulf Stream and the Kuroshio are major currents of the North Atlantic and North Pacific, respectively. They transport warm water northward and are key components of the Earth climate system. For this study, we looked at how they affect the sea level of the coasts of Japan, the USA and Canada. We found that the inshore sea level
co-varies with the north-to-south shifts of the Gulf Stream and Kuroshio. In the paper, we discuss the physical mechanisms that could explain the agreement.
Margot Clyne, Jean-Francois Lamarque, Michael J. Mills, Myriam Khodri, William Ball, Slimane Bekki, Sandip S. Dhomse, Nicolas Lebas, Graham Mann, Lauren Marshall, Ulrike Niemeier, Virginie Poulain, Alan Robock, Eugene Rozanov, Anja Schmidt, Andrea Stenke, Timofei Sukhodolov, Claudia Timmreck, Matthew Toohey, Fiona Tummon, Davide Zanchettin, Yunqian Zhu, and Owen B. Toon
Atmos. Chem. Phys., 21, 3317–3343, https://doi.org/10.5194/acp-21-3317-2021, https://doi.org/10.5194/acp-21-3317-2021, 2021
Short summary
Short summary
This study finds how and why five state-of-the-art global climate models with interactive stratospheric aerosols differ when simulating the aftermath of large volcanic injections as part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP). We identify and explain the consequences of significant disparities in the underlying physics and chemistry currently in some of the models, which are problems likely not unique to the models participating in this study.
Ramdane Alkama, Patrick C. Taylor, Lorea Garcia-San Martin, Herve Douville, Gregory Duveiller, Giovanni Forzieri, Didier Swingedouw, and Alessandro Cescatti
The Cryosphere, 14, 2673–2686, https://doi.org/10.5194/tc-14-2673-2020, https://doi.org/10.5194/tc-14-2673-2020, 2020
Short summary
Short summary
The amount of solar energy absorbed by Earth is believed to strongly depend on clouds. Here, we investigate this relationship using satellite data and 32 climate models, showing that this relationship holds everywhere except over polar seas, where an increased reflection by clouds corresponds to an increase in absorbed solar radiation at the surface. This interplay between clouds and sea ice reduces by half the increase of net radiation at the surface that follows the sea ice retreat.
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.
Juliette Mignot, Carlos Mejia, Charles Sorror, Adama Sylla, Michel Crépon, and Sylvie Thiria
Geosci. Model Dev., 13, 2723–2742, https://doi.org/10.5194/gmd-13-2723-2020, https://doi.org/10.5194/gmd-13-2723-2020, 2020
Short summary
Short summary
The most robust representation of climate is usually obtained by averaging a large number of simulations, thereby cancelling individual model errors. Here, we work towards an objective way of selecting the least biased models over a certain region, based on physical parameters. This statistical method based on a neural classifier and multi-correspondence analysis is illustrated here for the Senegalo-Mauritanian region, but it could potentially be developed for any other region or process.
Angélique Hameau, Thomas L. Frölicher, Juliette Mignot, and Fortunat Joos
Biogeosciences, 17, 1877–1895, https://doi.org/10.5194/bg-17-1877-2020, https://doi.org/10.5194/bg-17-1877-2020, 2020
Short summary
Short summary
Ocean deoxygenation and warming are observed and projected to intensify under continued greenhouse gas emissions. Whereas temperature is considered the main climate change indicator, we show that in certain regions, thermocline doxygenation may be detectable before warming.
Pierre Sabatier, Marie Nicolle, Christine Piot, Christophe Colin, Maxime Debret, Didier Swingedouw, Yves Perrette, Marie-Charlotte Bellingery, Benjamin Chazeau, Anne-Lise Develle, Maxime Leblanc, Charlotte Skonieczny, Yoann Copard, Jean-Louis Reyss, Emmanuel Malet, Isabelle Jouffroy-Bapicot, Maëlle Kelner, Jérôme Poulenard, Julien Didier, Fabien Arnaud, and Boris Vannière
Clim. Past, 16, 283–298, https://doi.org/10.5194/cp-16-283-2020, https://doi.org/10.5194/cp-16-283-2020, 2020
Short summary
Short summary
High-resolution multiproxy analysis of sediment core from a high-elevation lake on Corsica allows us to reconstruct past African dust inputs to the western Mediterranean area over the last 3 millennia. Millennial variations of Saharan dust input have been correlated with the long-term southward migration of the Intertropical Convergence Zone, while short-term variations were associated with the North Atlantic Oscillation and total solar irradiance after and before 1070 cal BP, respectively.
Jérôme Sirven, Juliette Mignot, and Michel Crépon
Ocean Sci., 15, 1667–1690, https://doi.org/10.5194/os-15-1667-2019, https://doi.org/10.5194/os-15-1667-2019, 2019
Short summary
Short summary
In December 2002 and January 2003 satellite observations of chlorophyll showed a wavelike pattern with a wavelength of about 750 km south-west of the Cape Verde Peninsula. Such a pattern suggests the existence of a locally generated Rossby wave which slowly propagated westward. To verify this hypothesis a numerical study based on a simple model has been conducted. The numerical results are completed by an analytical study which evaluates the potential impact of the coastline shape.
Angélique Hameau, Juliette Mignot, and Fortunat Joos
Biogeosciences, 16, 1755–1780, https://doi.org/10.5194/bg-16-1755-2019, https://doi.org/10.5194/bg-16-1755-2019, 2019
Short summary
Short summary
The observed decrease of oxygen and warming in the ocean may adversely affect marine ecosystems and their services. We analyse results from an Earth system model for the last millennium and the 21st century. We find changes in temperature and oxygen due to fossil fuel burning and other human activities to exceed natural variations in many ocean regions already today. Natural variability is biased low in earlier studies neglecting forcing from past volcanic eruptions and solar change.
Nathaelle Bouttes, Didier Swingedouw, Didier M. Roche, Maria F. Sanchez-Goni, and Xavier Crosta
Clim. Past, 14, 239–253, https://doi.org/10.5194/cp-14-239-2018, https://doi.org/10.5194/cp-14-239-2018, 2018
Short summary
Short summary
Atmospheric CO2 is key for climate change. CO2 is lower during the oldest warm period of the last million years, the interglacials, than during the most recent ones (since 430 000 years ago). This difference has not been explained yet, but could be due to changes of ocean circulation. We test this hypothesis and the role of vegetation and ice sheets using an intermediate complexity model. We show that only small changes of CO2 can be obtained, underlying missing feedbacks or mechanisms.
Lauren Marshall, Anja Schmidt, Matthew Toohey, Ken S. Carslaw, Graham W. Mann, Michael Sigl, Myriam Khodri, Claudia Timmreck, Davide Zanchettin, William T. Ball, Slimane Bekki, James S. A. Brooke, Sandip Dhomse, Colin Johnson, Jean-Francois Lamarque, Allegra N. LeGrande, Michael J. Mills, Ulrike Niemeier, James O. Pope, Virginie Poulain, Alan Robock, Eugene Rozanov, Andrea Stenke, Timofei Sukhodolov, Simone Tilmes, Kostas Tsigaridis, and Fiona Tummon
Atmos. Chem. Phys., 18, 2307–2328, https://doi.org/10.5194/acp-18-2307-2018, https://doi.org/10.5194/acp-18-2307-2018, 2018
Short summary
Short summary
We use four global aerosol models to compare the simulated sulfate deposition from the 1815 Mt. Tambora eruption to ice core records. Inter-model volcanic sulfate deposition differs considerably. Volcanic sulfate deposited on polar ice sheets is used to estimate the atmospheric sulfate burden and subsequently radiative forcing of historic eruptions. Our results suggest that deriving such relationships from model simulations may be associated with greater uncertainties than previously thought.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
Short summary
Short summary
Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Mélanie Wary, Frédérique Eynaud, Didier Swingedouw, Valérie Masson-Delmotte, Jens Matthiessen, Catherine Kissel, Jena Zumaque, Linda Rossignol, and Jean Jouzel
Clim. Past, 13, 729–739, https://doi.org/10.5194/cp-13-729-2017, https://doi.org/10.5194/cp-13-729-2017, 2017
Short summary
Short summary
The last glacial period was punctuated by abrupt climatic variations, whose cold atmospheric phases have been commonly associated with cold sea-surface temperatures and expansion of sea ice in the North Atlantic and adjacent seas. Here we provide direct evidence of a regional paradoxical see-saw pattern: cold Greenland and North Atlantic phases coincide with warmer sea-surface conditions and shorter seasonal sea-ice cover durations in the Norwegian Sea as compared to warm phases.
Davide Zanchettin, Myriam Khodri, Claudia Timmreck, Matthew Toohey, Anja Schmidt, Edwin P. Gerber, Gabriele Hegerl, Alan Robock, Francesco S. R. Pausata, William T. Ball, Susanne E. Bauer, Slimane Bekki, Sandip S. Dhomse, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Michael Mills, Marion Marchand, Ulrike Niemeier, Virginie Poulain, Eugene Rozanov, Angelo Rubino, Andrea Stenke, Kostas Tsigaridis, and Fiona Tummon
Geosci. Model Dev., 9, 2701–2719, https://doi.org/10.5194/gmd-9-2701-2016, https://doi.org/10.5194/gmd-9-2701-2016, 2016
Short summary
Short summary
Simulating volcanically-forced climate variability is a challenging task for climate models. The Model Intercomparison Project on the climatic response to volcanic forcing (VolMIP) – an endorsed contribution to CMIP6 – defines a protocol for idealized volcanic-perturbation experiments to improve comparability of results across different climate models. This paper illustrates the design of VolMIP's experiments and describes the aerosol forcing input datasets to be used.
K. Lohmann, J. Mignot, H. R. Langehaug, J. H. Jungclaus, D. Matei, O. H. Otterå, Y. Q. Gao, T. L. Mjell, U. S. Ninnemann, and H. F. Kleiven
Clim. Past, 11, 203–216, https://doi.org/10.5194/cp-11-203-2015, https://doi.org/10.5194/cp-11-203-2015, 2015
Short summary
Short summary
We use model simulations to investigate mechanisms of similar Iceland--Scotland overflow (outflow from the Nordic seas) and North Atlantic sea surface temperature variability, suggested from palaeo-reconstructions (Mjell et al., 2015). Our results indicate the influence of Nordic Seas surface temperature on the pressure gradient across the Iceland--Scotland ridge, not a large-scale link through the meridional overturning circulation, is responsible for the (simulated) co-variability.
J. Apaéstegui, F. W. Cruz, A. Sifeddine, M. Vuille, J. C. Espinoza, J. L. Guyot, M. Khodri, N. Strikis, R. V. Santos, H. Cheng, L. Edwards, E. Carvalho, and W. Santini
Clim. Past, 10, 1967–1981, https://doi.org/10.5194/cp-10-1967-2014, https://doi.org/10.5194/cp-10-1967-2014, 2014
Short summary
Short summary
In this paper we explore a speleothem δ18O record from Palestina cave, northwestern Peru, on the eastern side of the Andes cordillera, in the upper Amazon Basin. The δ18O record is interpreted as a proxy for South American Summer Monsoon (SASM) intensity and allows the reconstruction of its variability during the last 1600 years. Replicating regional climate signals from different sites and using different proxies is essential for a comprehensive understanding of past changes in SASM activity.
K. Lohmann, J. H. Jungclaus, D. Matei, J. Mignot, M. Menary, H. R. Langehaug, J. Ba, Y. Gao, O. H. Otterå, W. Park, and S. Lorenz
Ocean Sci., 10, 227–241, https://doi.org/10.5194/os-10-227-2014, https://doi.org/10.5194/os-10-227-2014, 2014
M. Kageyama, U. Merkel, B. Otto-Bliesner, M. Prange, A. Abe-Ouchi, G. Lohmann, R. Ohgaito, D. M. Roche, J. Singarayer, D. Swingedouw, and X Zhang
Clim. Past, 9, 935–953, https://doi.org/10.5194/cp-9-935-2013, https://doi.org/10.5194/cp-9-935-2013, 2013
R. Séférian, L. Bopp, D. Swingedouw, and J. Servonnat
Earth Syst. Dynam., 4, 109–127, https://doi.org/10.5194/esd-4-109-2013, https://doi.org/10.5194/esd-4-109-2013, 2013
M. Casado, P. Ortega, V. Masson-Delmotte, C. Risi, D. Swingedouw, V. Daux, D. Genty, F. Maignan, O. Solomina, B. Vinther, N. Viovy, and P. Yiou
Clim. Past, 9, 871–886, https://doi.org/10.5194/cp-9-871-2013, https://doi.org/10.5194/cp-9-871-2013, 2013
P. Ortega, M. Montoya, F. González-Rouco, H. Beltrami, and D. Swingedouw
Clim. Past, 9, 547–565, https://doi.org/10.5194/cp-9-547-2013, https://doi.org/10.5194/cp-9-547-2013, 2013
Related subject area
Climate and Earth system modeling
Effects of forcing differences and initial conditions on inter-model agreement in the VolMIP volc-pinatubo-full experiment
From emission scenarios to spatially resolved projections with a chain of computationally efficient emulators: coupling of MAGICC (v7.5.1) and MESMER (v0.8.3)
Global simulation of dissolved 231Pa and 230Th in the ocean and the sedimentary 231Pa∕230Th ratios with the ocean general circulation model COCO ver4.0
The linear feedback precipitation model (LFPM 1.0) – a simple and efficient model for orographic precipitation in the context of landform evolution modeling
Building a machine learning surrogate model for wildfire activities within a global Earth system model
Variability and extremes: statistical validation of the Alfred Wegener Institute Earth System Model (AWI-ESM)
Extreme events representation in CMCC-CM2 standard and high-resolution general circulation models
TopoCLIM: rapid topography-based downscaling of regional climate model output in complex terrain v1.1
CARDAMOM-FluxVal version 1.0: a FLUXNET-based validation system for CARDAMOM carbon and water flux estimates
Supporting hierarchical soil biogeochemical modeling: version 2 of the Biogeochemical Transport and Reaction model (BeTR-v2)
Using neural network ensembles to separate ocean biogeochemical and physical drivers of phytoplankton biogeography in Earth system models
GAN–argcPredNet v1.0: a generative adversarial model for radar echo extrapolation based on convolutional recurrent units
A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to-high latitudes
An automatic lake-model application using near-real-time data forcing: development of an operational forecast workflow (COASTLINES) for Lake Erie
ShellChron 0.4.0: a new tool for constructing chronologies in accretionary carbonate archives from stable oxygen isotope profiles
Comparison of ocean heat content estimated using two eddy-resolving hindcast simulations based on OFES1 and OFES2
Enhancing the accessibility of unified modeling systems: GFDL System for High-resolution prediction on Earth-to-Local Domains (SHiELD) v2021b in a container
Minimal CMIP Emulator (MCE v1.2): a new simplified method for probabilistic climate projections
Influence of modifications (from AoB2015 to v0.5) in the Vegetation Optimality Model
C-LLAMA 1.0: a traceable model for food, agriculture, and land use
The Earth Model Column Collaboratory (EMC2) v1.1: an open-source ground-based lidar and radar instrument simulator and subcolumn generator for large-scale models
MPR 1.0: a stand-alone multiscale parameter regionalization tool for improved parameter estimation of land surface models
Description and evaluation of a secondary organic aerosol and new particle formation scheme within TM5-MP v1.2
PARASO, a circum-Antarctic fully coupled ice-sheet–ocean–sea-ice–atmosphere–land model involving f.ETISh1.7, NEMO3.6, LIM3.6, COSMO5.0 and CLM4.5
Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0
Assessment of the Finite-VolumE Sea ice–Ocean Model (FESOM2.0) – Part 2: Partial bottom cells, embedded sea ice and vertical mixing library CVMix
Evaluation and optimisation of the I/O scalability for the next generation of Earth system models: IFS CY43R3 and XIOS 2.0 integration as a case study
Coupling the Community Land Model version 5.0 to the parallel data assimilation framework PDAF: description and applications
Convolutional conditional neural processes for local climate downscaling
Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models
Modeling reservoir surface temperatures for regional and global climate models: a multi-model study on the inflow and level variation effects
Importance of radiative transfer processes in urban climate models: a study based on the PALM 6.0 model system
ChAP 1.0: a stationary tropospheric sulfur cycle for Earth system models of intermediate complexity
Non-Hydrostatic RegCM4 (RegCM4-NH): model description and case studies over multiple domains
Robustness of neural network emulations of radiative transfer parameterizations in a state-of-the-art general circulation model
NorCPM1 and its contribution to CMIP6 DCPP
ENSO-ASC 1.0.0: ENSO deep learning forecast model with a multivariate air–sea coupler
Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models
Decadal climate predictions with the Canadian Earth System Model version 5 (CanESM5)
CondiDiag1.0: A flexible online diagnostic tool for conditional sampling and budget analysis in the E3SM atmosphere model (EAM)
The Simplified Chemistry-Dynamical Model (SCDM V1.0)
Iodine chemistry in the chemistry–climate model SOCOL-AERv2-I
Coupling interactive fire with atmospheric composition and climate in the UK Earth System Model
On the impact of dropsondes on the EC IFS model (Cy47r1) analysis of convection during OTREC
Fast and accurate learned multiresolution dynamical downscaling for precipitation
A parameterization of sub-grid topographical effects on solar radiation in the E3SM Land Model (version 1.0): implementation and evaluation over the Tibetan Plateau
The Effects of Ocean Surface Waves on Global Intraseasonal Prediction: Case Studies with a Coupled CFSv2.0-WW3
WETMETH 1.0: a new wetland methane model for implementation in Earth system models
Better calibration of cloud parameterizations and subgrid effects increases the fidelity of E3SM Atmosphere Model version 1
Effect of horizontal resolution on the simulation of tropical cyclones in the Chinese Academy of Sciences FGOALS-f3 climate system model
Davide Zanchettin, Claudia Timmreck, Myriam Khodri, Anja Schmidt, Matthew Toohey, Manabu Abe, Slimane Bekki, Jason Cole, Shih-Wei Fang, Wuhu Feng, Gabriele Hegerl, Ben Johnson, Nicolas Lebas, Allegra N. LeGrande, Graham W. Mann, Lauren Marshall, Landon Rieger, Alan Robock, Sara Rubinetti, Kostas Tsigaridis, and Helen Weierbach
Geosci. Model Dev., 15, 2265–2292, https://doi.org/10.5194/gmd-15-2265-2022, https://doi.org/10.5194/gmd-15-2265-2022, 2022
Short summary
Short summary
This paper provides metadata and first analyses of the volc-pinatubo-full experiment of CMIP6-VolMIP. Results from six Earth system models reveal significant differences in radiative flux anomalies that trace back to different implementations of volcanic forcing. Surface responses are in contrast overall consistent across models, reflecting the large spread due to internal variability. A second phase of VolMIP shall consider both aspects toward improved protocol for volc-pinatubo-full.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
Short summary
Short summary
We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Yusuke Sasaki, Hidetaka Kobayashi, and Akira Oka
Geosci. Model Dev., 15, 2013–2033, https://doi.org/10.5194/gmd-15-2013-2022, https://doi.org/10.5194/gmd-15-2013-2022, 2022
Short summary
Short summary
For realistically simulating the recently observed distributions of dissolved 230Th and 231Pa in the ocean, we highlight the importance of the removal process of 231Pa and 230Th at the seafloor (bottom scavenging) and the dependence of scavenging efficiency on particle concentration. We show that consideration of these two processes can well reproduce not only the oceanic distribution of 231Pa and 230Th but also the sedimentary 231Pa/230Th ratios.
Stefan Hergarten and Jörg Robl
Geosci. Model Dev., 15, 2063–2084, https://doi.org/10.5194/gmd-15-2063-2022, https://doi.org/10.5194/gmd-15-2063-2022, 2022
Short summary
Short summary
The influence of climate on landform evolution has attracted great interest over the past decades. This paper presents a simple model for simulating the influence of topography on precipitation and the decrease in precipitation over large continental areas. The approach can be included in numerical models of large-scale landform evolution and causes only a moderate increase in the numerical complexity. It opens a door to investigating feedbacks between climate and landform evolution.
Qing Zhu, Fa Li, William J. Riley, Li Xu, Lei Zhao, Kunxiaojia Yuan, Huayi Wu, Jianya Gong, and James Randerson
Geosci. Model Dev., 15, 1899–1911, https://doi.org/10.5194/gmd-15-1899-2022, https://doi.org/10.5194/gmd-15-1899-2022, 2022
Short summary
Short summary
Wildfire is a devastating Earth system process that burns about 500 million hectares of land each year. It wipes out vegetation including trees, shrubs, and grasses and causes large losses of economic assets. However, modeling the spatial distribution and temporal changes of wildfire activities at a global scale is challenging. This study built a machine-learning-based wildfire surrogate model within an existing Earth system model and achieved high accuracy.
Justus Contzen, Thorsten Dickhaus, and Gerrit Lohmann
Geosci. Model Dev., 15, 1803–1820, https://doi.org/10.5194/gmd-15-1803-2022, https://doi.org/10.5194/gmd-15-1803-2022, 2022
Short summary
Short summary
Climate models are of paramount importance to predict future climate changes. Since many severe consequences of climate change are due to extreme events, the accurate behaviour of models in terms of extremes needs to be validated thoroughly. We present a method for model validation in terms of climate extremes and an algorithm to detect regions in which extremes tend to occur at the same time. These methods are applied to data from different climate models and to observational data.
Enrico Scoccimarro, Daniele Peano, Silvio Gualdi, Alessio Bellucci, Tomas Lovato, Pier Giuseppe Fogli, and Antonio Navarra
Geosci. Model Dev., 15, 1841–1854, https://doi.org/10.5194/gmd-15-1841-2022, https://doi.org/10.5194/gmd-15-1841-2022, 2022
Short summary
Short summary
This study evaluated the ability of the CMCC-CM2 climate model participating to the last CMIP6 effort, in representing extreme events of precipitation and temperature at the daily and 6-hourly frequencies. The 1/4° resolution version of the atmospheric model provides better results than the version at 1° resolution for temperature extremes, at both time frequencies. For precipitation extremes, especially at the daily time frequency, the higher resolution does not improve model results.
Joel Fiddes, Kristoffer Aalstad, and Michael Lehning
Geosci. Model Dev., 15, 1753–1768, https://doi.org/10.5194/gmd-15-1753-2022, https://doi.org/10.5194/gmd-15-1753-2022, 2022
Short summary
Short summary
This study describes and evaluates a new downscaling scheme that addresses the need for hillslope-scale atmospheric forcing time series for modelling the local impact of regional climate change on the land surface in mountain areas. The method has a global scope and is able to generate all model forcing variables required for hydrological and land surface modelling. This is important, as impact models require high-resolution forcings such as those generated here to produce meaningful results.
Yan Yang, A. Anthony Bloom, Shuang Ma, Paul Levine, Alexander Norton, Nicholas C. Parazoo, John T. Reager, John Worden, Gregory R. Quetin, T. Luke Smallman, Mathew Williams, Liang Xu, and Sassan Saatchi
Geosci. Model Dev., 15, 1789–1802, https://doi.org/10.5194/gmd-15-1789-2022, https://doi.org/10.5194/gmd-15-1789-2022, 2022
Short summary
Short summary
Global carbon and water have large uncertainties that are hard to quantify in current regional and global models. Field observations provide opportunities for better calibration and validation of current modeling of carbon and water. With the unique structure of CARDAMOM, we have utilized the data assimilation capability and designed the benchmarking framework by using field observations in modeling. Results show that data assimilation improves model performance in different aspects.
Jinyun Tang, William J. Riley, and Qing Zhu
Geosci. Model Dev., 15, 1619–1632, https://doi.org/10.5194/gmd-15-1619-2022, https://doi.org/10.5194/gmd-15-1619-2022, 2022
Short summary
Short summary
We here describe version 2 of BeTR, a reactive transport model created to help ease the development of biogeochemical capability in Earth system models that are used for quantifying ecosystem–climate feedbacks. We then coupled BeTR-v2 to the Energy Exascale Earth System Model to quantify how different numerical couplings of plants and soils affect simulated ecosystem biogeochemistry. We found that different couplings lead to significant uncertainty that is not correctable by tuning parameters.
Christopher Holder, Anand Gnanadesikan, and Marie Aude-Pradal
Geosci. Model Dev., 15, 1595–1617, https://doi.org/10.5194/gmd-15-1595-2022, https://doi.org/10.5194/gmd-15-1595-2022, 2022
Short summary
Short summary
It can be challenging to understand why Earth system models (ESMs) produce specific results because one can arrive at the same result simply by changing the values of the parameters. In our paper, we demonstrate that it is possible to use machine learning to figure out how and why particular components of an ESM (such as biology or ocean circulations) affect the output. This work could be applied to observations to improve the accuracy of the formulations used in ESMs.
Kun Zheng, Yan Liu, Jinbiao Zhang, Cong Luo, Siyu Tang, Huihua Ruan, Qiya Tan, Yunlei Yi, and Xiutao Ran
Geosci. Model Dev., 15, 1467–1475, https://doi.org/10.5194/gmd-15-1467-2022, https://doi.org/10.5194/gmd-15-1467-2022, 2022
Short summary
Short summary
In extrapolation methods, there is a phenomenon that causes the extrapolated image to be blurred and unrealistic. The paper proposes the GAN–argcPredNet v1.0 network model, which aims to solve this problem through GAN's ability to strengthen the characteristics of multi-modal data modeling. GAN–argcPredNet v1.0 has achieved excellent results. Our model can reduce the prediction loss in a small-scale space so that the prediction results have more detailed features.
Swen Brands
Geosci. Model Dev., 15, 1375–1411, https://doi.org/10.5194/gmd-15-1375-2022, https://doi.org/10.5194/gmd-15-1375-2022, 2022
Short summary
Short summary
The present study evaluates the last two global climate model generations in terms of their capability to reproduce recurrent regional atmospheric circulation patterns in the Northern Hemisphere mid-to-high latitudes under present climate conditions. These patterns are linked with many environmental variables on the local scale and thus provide an overarching concept for model verification. The results are expected to be of interest for model developers and regional climate scientists.
Shuqi Lin, Leon Boegman, Shiliang Shan, and Ryan Mulligan
Geosci. Model Dev., 15, 1331–1353, https://doi.org/10.5194/gmd-15-1331-2022, https://doi.org/10.5194/gmd-15-1331-2022, 2022
Short summary
Short summary
An operational hydrodynamics forecast system, COASTLINES, using the Windows Task Scheduler, Python, and MATLAB scripts, to automate application of a 3-D model (AEM3D) in Lake Erie was developed. The system predicted storm-surge and up-/downwelling events that are important for flood water and drinking water/fishery management. This example of the successful development of an operational forecast system can be adapted to simulate aquatic systems as required for management and public safety.
Niels J. de Winter
Geosci. Model Dev., 15, 1247–1267, https://doi.org/10.5194/gmd-15-1247-2022, https://doi.org/10.5194/gmd-15-1247-2022, 2022
Short summary
Short summary
ShellChron is a tool for determining the relative age of samples in carbonate (climate) archives based on the seasonal variability in temperature and salinity or precipitation recorded in stable oxygen isotope measurements. The model allows dating of fossil archives within a year, which is important for climate reconstructions on the sub-seasonal to decadal scale. In this paper, I introduce ShellChron and test it on a range of real and virtual datasets to demonstrate its use.
Fanglou Liao, Xiao Hua Wang, and Zhiqiang Liu
Geosci. Model Dev., 15, 1129–1153, https://doi.org/10.5194/gmd-15-1129-2022, https://doi.org/10.5194/gmd-15-1129-2022, 2022
Short summary
Short summary
The ocean heat content (OHC) estimated using two eddying hindcast simulations, OFES1 and OFES2, was compared from 1960 to 2016, with observation-based results as a reference. Marked differences were found, especially in the Atlantic Ocean. These were related to the differences in the net surface heating, heat advection, and vertical heat diffusion. These documented differences may help the community better understand and use these quasi-global high-resolution datasets for their own purposes.
Kai-Yuan Cheng, Lucas M. Harris, and Yong Qiang Sun
Geosci. Model Dev., 15, 1097–1105, https://doi.org/10.5194/gmd-15-1097-2022, https://doi.org/10.5194/gmd-15-1097-2022, 2022
Short summary
Short summary
This paper presents the implementation of container technology for the System for High‐resolution prediction on Earth‐to‐Local Domains (SHiELD), a unified atmospheric model that can be used as a global, a global–nest, and a regional model for weather-to-seasonal prediction. Container technology makes SHiELD cross-platform and easy to use, which opens opportunities for collaborative research and development. The performance and scalability of the containerized SHiELD are evaluated and discussed.
Junichi Tsutsui
Geosci. Model Dev., 15, 951–970, https://doi.org/10.5194/gmd-15-951-2022, https://doi.org/10.5194/gmd-15-951-2022, 2022
Short summary
Short summary
A new simple climate model, MCE, was developed. It can emulate the basic behavior of comprehensive climate models in a minimal way with sufficient accuracy, providing a reasonable way to assess climate change mitigation scenarios in terms of consistency with long-term temperature goals. The model's simple structure is suitable for building probability distributions of key model parameters such that they reflect uncertainty ranges of multiple climate projections and observed warming trends.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Geosci. Model Dev., 15, 883–900, https://doi.org/10.5194/gmd-15-883-2022, https://doi.org/10.5194/gmd-15-883-2022, 2022
Short summary
Short summary
The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.
Thomas S. Ball, Naomi E. Vaughan, Thomas W. Powell, Andrew Lovett, and Timothy M. Lenton
Geosci. Model Dev., 15, 929–949, https://doi.org/10.5194/gmd-15-929-2022, https://doi.org/10.5194/gmd-15-929-2022, 2022
Short summary
Short summary
C-LLAMA is a simple model of the global food system operating at a country level from 2013 to 2050. The model begins with projections of diet composition and populations for each country, producing a demand for each food commodity and finally an agricultural land use in each country. The model can be used to explore the sensitivity of agricultural land use to various drivers within the food system at country, regional, and continental spatial aggregations.
Israel Silber, Robert C. Jackson, Ann M. Fridlind, Andrew S. Ackerman, Scott Collis, Johannes Verlinde, and Jiachen Ding
Geosci. Model Dev., 15, 901–927, https://doi.org/10.5194/gmd-15-901-2022, https://doi.org/10.5194/gmd-15-901-2022, 2022
Short summary
Short summary
The Earth Model Column Collaboratory (EMC2) is an open-source ground-based (and air- or space-borne) lidar and radar simulator and subcolumn generator designed for large-scale models, in particular climate models, applicable also for high-resolution models. EMC2 emulates measurements while remaining faithful to large-scale models' physical assumptions implemented in their cloud or radiation schemes. We demonstrate the use of EMC2 to compare AWARE measurements with the NASA GISS ModelE3 and LES.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
Short summary
Short summary
The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Tommi Bergman, Risto Makkonen, Roland Schrödner, Erik Swietlicki, Vaughan T. J. Phillips, Philippe Le Sager, and Twan van Noije
Geosci. Model Dev., 15, 683–713, https://doi.org/10.5194/gmd-15-683-2022, https://doi.org/10.5194/gmd-15-683-2022, 2022
Short summary
Short summary
We describe in this paper the implementation of a process-based secondary organic aerosol and new particle formation scheme within the chemistry transport model TM5-MP version 1.2. The performance of the model simulations for the year 2010 is evaluated against in situ observations, ground-based remote sensing and satellite retrievals. Overall, the simulated aerosol fields are improved, although in some areas the model shows a decline in performance.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
Short summary
Short summary
We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
Katherine V. Calvin, Abigail Snyder, Xin Zhao, and Marshall Wise
Geosci. Model Dev., 15, 429–447, https://doi.org/10.5194/gmd-15-429-2022, https://doi.org/10.5194/gmd-15-429-2022, 2022
Short summary
Short summary
Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. We identify parameter combinations that best replicate historical land use in the United States.
Patrick Scholz, Dmitry Sidorenko, Sergey Danilov, Qiang Wang, Nikolay Koldunov, Dmitry Sein, and Thomas Jung
Geosci. Model Dev., 15, 335–363, https://doi.org/10.5194/gmd-15-335-2022, https://doi.org/10.5194/gmd-15-335-2022, 2022
Short summary
Short summary
Structured-mesh ocean models are still the most mature in terms of functionality due to their long development history. However, unstructured-mesh ocean models have acquired new features and caught up in their functionality. This paper continues the work by Scholz et al. (2019) of documenting the features available in FESOM2.0. It focuses on the following two aspects: (i) partial bottom cells and embedded sea ice and (ii) dealing with mixing parameterisations enabled by using the CVMix package.
Xavier Yepes-Arbós, Gijs van den Oord, Mario C. Acosta, and Glenn D. Carver
Geosci. Model Dev., 15, 379–394, https://doi.org/10.5194/gmd-15-379-2022, https://doi.org/10.5194/gmd-15-379-2022, 2022
Short summary
Short summary
Climate prediction models produce a large volume of simulated data that sometimes might not be efficiently managed. In this paper we present an approach to address this issue by reducing the computing time and storage space. As a case study, we analyse the output writing process of the ECMWF atmospheric model called IFS, and we integrate into it a data writing tool called XIOS. The results suggest that the integration between the two components achieves an adequate computational performance.
Lukas Strebel, Heye R. Bogena, Harry Vereecken, and Harrie-Jan Hendricks Franssen
Geosci. Model Dev., 15, 395–411, https://doi.org/10.5194/gmd-15-395-2022, https://doi.org/10.5194/gmd-15-395-2022, 2022
Short summary
Short summary
We present the technical coupling between a land surface model (CLM5) and the Parallel Data Assimilation Framework (PDAF). This coupling enables measurement data to update simulated model states and parameters in a statistically optimal way. We demonstrate the viability of the model framework using an application in a forested catchment where the inclusion of soil water measurements significantly improved the simulation quality.
Anna Vaughan, Will Tebbutt, J. Scott Hosking, and Richard E. Turner
Geosci. Model Dev., 15, 251–268, https://doi.org/10.5194/gmd-15-251-2022, https://doi.org/10.5194/gmd-15-251-2022, 2022
Short summary
Short summary
We develop a new method for climate downscaling, i.e. transforming low-resolution climate model output to high-resolution projections, using a deep-learning model known as a convolutional conditional neural process. This model is shown to outperform an ensemble of baseline methods for downscaling daily maximum temperature and precipitation and provides a powerful new downscaling framework for climate impact studies.
Eduardo Moreno-Chamarro, Louis-Philippe Caron, Saskia Loosveldt Tomas, Javier Vegas-Regidor, Oliver Gutjahr, Marie-Pierre Moine, Dian Putrasahan, Christopher D. Roberts, Malcolm J. Roberts, Retish Senan, Laurent Terray, Etienne Tourigny, and Pier Luigi Vidale
Geosci. Model Dev., 15, 269–289, https://doi.org/10.5194/gmd-15-269-2022, https://doi.org/10.5194/gmd-15-269-2022, 2022
Short summary
Short summary
Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Manuel C. Almeida, Yurii Shevchuk, Georgiy Kirillin, Pedro M. M. Soares, Rita M. Cardoso, José P. Matos, Ricardo M. Rebelo, António C. Rodrigues, and Pedro S. Coelho
Geosci. Model Dev., 15, 173–197, https://doi.org/10.5194/gmd-15-173-2022, https://doi.org/10.5194/gmd-15-173-2022, 2022
Short summary
Short summary
In this study, we have evaluated the importance of the input of energy conveyed by river inflows into lakes and reservoirs when modeling surface water energy fluxes. Our results suggest that there is a strong correlation between water residence time and the surface water temperature prediction error and that the combined use of process-based physical models and machine-learning models will considerably improve the modeling of air–lake heat and moisture fluxes.
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
Short summary
Short summary
Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
Alexey V. Eliseev, Rustam D. Gizatullin, and Alexandr V. Timazhev
Geosci. Model Dev., 14, 7725–7747, https://doi.org/10.5194/gmd-14-7725-2021, https://doi.org/10.5194/gmd-14-7725-2021, 2021
Short summary
Short summary
A stationary, computationally efficient scheme, ChAP 1.0 (Chemical and Aerosol Processes, version 1.0), is developed for the sulfur cycle in the troposphere. This scheme is designed for Earth system models of intermediate complexity (EMICs). The scheme model reasonably reproduces characteristics of the tropospheric sulfur cycle. Despite its simplicity, ChAP may be successfully used to simulate anthropogenic sulfur pollution in the atmosphere at coarse spatial scales and timescales.
Erika Coppola, Paolo Stocchi, Emanuela Pichelli, Jose Abraham Torres Alavez, Russell Glazer, Graziano Giuliani, Fabio Di Sante, Rita Nogherotto, and Filippo Giorgi
Geosci. Model Dev., 14, 7705–7723, https://doi.org/10.5194/gmd-14-7705-2021, https://doi.org/10.5194/gmd-14-7705-2021, 2021
Short summary
Short summary
In this work we describe the development of a non-hydrostatic version of the regional climate model RegCM4-NH, implemented to allow simulations at convection-permitting scales of <4 km for climate applications. The new core is described, and three case studies of intense convection are carried out to illustrate the model performances. Comparison with observations is much improved with respect to with coarse grid runs. RegCM4-NH offers a promising tool for climate investigations at a local scale.
Alexei Belochitski and Vladimir Krasnopolsky
Geosci. Model Dev., 14, 7425–7437, https://doi.org/10.5194/gmd-14-7425-2021, https://doi.org/10.5194/gmd-14-7425-2021, 2021
Short summary
Short summary
There is a lot interest in using machine learning (ML) techniques to improve environmental models by replacing physically based model components with ML-derived ones. The latter ordinarily demonstrate excellent results when tested in a stand-alone setting but can break their host model either outright when coupled to it or eventually when the model changes. We built an ML component that not only does not destabilize its host model but is also robust with respect to substantial changes in it.
Ingo Bethke, Yiguo Wang, François Counillon, Noel Keenlyside, Madlen Kimmritz, Filippa Fransner, Annette Samuelsen, Helene Langehaug, Lea Svendsen, Ping-Gin Chiu, Leilane Passos, Mats Bentsen, Chuncheng Guo, Alok Gupta, Jerry Tjiputra, Alf Kirkevåg, Dirk Olivié, Øyvind Seland, Julie Solsvik Vågane, Yuanchao Fan, and Tor Eldevik
Geosci. Model Dev., 14, 7073–7116, https://doi.org/10.5194/gmd-14-7073-2021, https://doi.org/10.5194/gmd-14-7073-2021, 2021
Short summary
Short summary
The Norwegian Climate Prediction Model version 1 (NorCPM1) is a new research tool for performing climate reanalyses and seasonal-to-decadal climate predictions. It adds data assimilation capability to the Norwegian Earth System Model version 1 (NorESM1) and has contributed output to the Decadal Climate Prediction Project (DCPP) as part of the sixth Coupled Model Intercomparison Project (CMIP6). We describe the system and evaluate its baseline, reanalysis and prediction performance.
Bin Mu, Bo Qin, and Shijin Yuan
Geosci. Model Dev., 14, 6977–6999, https://doi.org/10.5194/gmd-14-6977-2021, https://doi.org/10.5194/gmd-14-6977-2021, 2021
Short summary
Short summary
Considering the sophisticated energy exchanges and multivariate coupling in ENSO, we subjectively incorporate the prior physical knowledge into the modeling process and build up an ENSO deep learning forecast model with a multivariate air–sea coupler, named ENSO-ASC, the performance of which outperforms the other state-of-the-art models. The extensive experiments indicate that ENSO-ASC is a powerful tool for both the ENSO prediction and for the analysis of the underlying complex mechanisms.
Luan F. Santos and Pedro S. Peixoto
Geosci. Model Dev., 14, 6919–6944, https://doi.org/10.5194/gmd-14-6919-2021, https://doi.org/10.5194/gmd-14-6919-2021, 2021
Short summary
Short summary
The Andes act as a wall in atmospheric flows and play an important role in the weather of South America but are currently underrepresented in weather and climate models. In this work, we propose grids that better capture the mountains and, using idealized dynamical models, study the effects caused by the use of such grids. While possibly improving forecasts for short periods, the grids introduce spurious numerical (nonphysical) effects, which can demand added caution from model developers.
Reinel Sospedra-Alfonso, William J. Merryfield, George J. Boer, Viatsheslav V. Kharin, Woo-Sung Lee, Christian Seiler, and James R. Christian
Geosci. Model Dev., 14, 6863–6891, https://doi.org/10.5194/gmd-14-6863-2021, https://doi.org/10.5194/gmd-14-6863-2021, 2021
Short summary
Short summary
CanESM5 decadal predictions that started from observed climate states represent the observed evolution of upper-ocean temperatures, surface climate, and the carbon cycle better than ones not started from observed climate states for several years into the forecast. This is due both to better representations of climate internal variability and to corrections of the model response to external forcing including changes in GHG emissions and aerosols.
Hui Wan, Kai Zhang, Philip J. Rasch, Vincent E. Larson, Xubin Zeng, Shixuan Zhang, and Ross Dixon
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-331, https://doi.org/10.5194/gmd-2021-331, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
This paper describes a tool embedded in a global climate model for sampling atmospheric conditions and monitoring physical processes as a numerical simulation is being carried out. The tool facilitates process-level model evaluation by allowing the users to select a wide range of quantities and processes to monitor at run time without having to do tedious ad hoc coding.
Hao-Jhe Hong and Thomas Reichler
Geosci. Model Dev., 14, 6647–6660, https://doi.org/10.5194/gmd-14-6647-2021, https://doi.org/10.5194/gmd-14-6647-2021, 2021
Short summary
Short summary
The Arctic wintertime circulation of the stratosphere has pronounced impacts on the troposphere and surface climate. Changes in the stratospheric circulation can lead to either increases or decreases in Arctic ozone. Understanding the interactions between ozone and the circulation will have the benefit of model prediction for the climate. This study introduces an economical and fast simplified model that represents the realistic distribution of ozone and its interaction with the circulation.
Arseniy Karagodin-Doyennel, Eugene Rozanov, Timofei Sukhodolov, Tatiana Egorova, Alfonso Saiz-Lopez, Carlos A. Cuevas, Rafael P. Fernandez, Tomás Sherwen, Rainer Volkamer, Theodore K. Koenig, Tanguy Giroud, and Thomas Peter
Geosci. Model Dev., 14, 6623–6645, https://doi.org/10.5194/gmd-14-6623-2021, https://doi.org/10.5194/gmd-14-6623-2021, 2021
Short summary
Short summary
Here, we present the iodine chemistry module in the SOCOL-AERv2 model. The obtained iodine distribution demonstrated a good agreement when validated against other simulations and available observations. We also estimated the iodine influence on ozone in the case of present-day iodine emissions, the sensitivity of ozone to doubled iodine emissions, and when considering only organic or inorganic iodine sources. The new model can be used as a tool for further studies of iodine effects on ozone.
João C. Teixeira, Gerd A. Folberth, Fiona M. O'Connor, Nadine Unger, and Apostolos Voulgarakis
Geosci. Model Dev., 14, 6515–6539, https://doi.org/10.5194/gmd-14-6515-2021, https://doi.org/10.5194/gmd-14-6515-2021, 2021
Short summary
Short summary
Fire constitutes a key process in the Earth system, being driven by climate as well as affecting climate. However, studies on the effects of fires on atmospheric composition and climate have been limited to date. This work implements and assesses the coupling of an interactive fire model with atmospheric composition, comparing it to an offline approach. This approach shows good performance at a global scale. However, regional-scale limitations lead to a bias in modelling fire emissions.
Stipo Sentić, Peter Bechtold, Željka Fuchs-Stone, Mark Rodwell, and David J. Raymond
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-354, https://doi.org/10.5194/gmd-2021-354, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
The OTREC field campaign focuses on studying convection in the east Pacific and the Caribbean. Observations obtained from dropsondes have been assimilated in the ECMWF model, and compared to a model run in which sondes have not been assimilated. The model performs well in both simulations, but assimilation of sondes helps to reduce the departure for pre-tropical storm conditions. Variables important for studying convection are also studied.
Jiali Wang, Zhengchun Liu, Ian Foster, Won Chang, Rajkumar Kettimuthu, and V. Rao Kotamarthi
Geosci. Model Dev., 14, 6355–6372, https://doi.org/10.5194/gmd-14-6355-2021, https://doi.org/10.5194/gmd-14-6355-2021, 2021
Short summary
Short summary
Downscaling, the process of generating a higher spatial or time dataset from a coarser observational or model dataset, is a widely used technique. Two common methodologies for performing downscaling are to use either dynamic (physics-based) or statistical (empirical). Here we develop a novel methodology, using a conditional generative adversarial network (CGAN), to perform the downscaling of a model's precipitation forecasts and describe the advantages of this method compared to the others.
Dalei Hao, Gautam Bisht, Yu Gu, Wei-Liang Lee, Kuo-Nan Liou, and L. Ruby Leung
Geosci. Model Dev., 14, 6273–6289, https://doi.org/10.5194/gmd-14-6273-2021, https://doi.org/10.5194/gmd-14-6273-2021, 2021
Short summary
Short summary
Topography exerts significant influence on the incoming solar radiation at the land surface. This study incorporated a well-validated sub-grid topographic parameterization in E3SM land model (ELM) version 1.0. The results demonstrate that sub-grid topography has non-negligible effects on surface energy budget, snow cover, and surface temperature over the Tibetan Plateau and that the ELM simulations are sensitive to season, elevation, and spatial scale.
Ruizi Shi, Fanghua Xu, Li Liu, Zheng Fan, Hao Yu, Hong Li, Xiang Li, and Yunfei Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-322, https://doi.org/10.5194/gmd-2021-322, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
To better understand the effects of surface waves on global intraseasonal prediction, we incorporated the WW3 model into the CFSv2.0. Processes of Langmuir mixing, Stokes-Coriolis force with entrainment, air-sea fluxes modified by Stokes drift and momentum roughness length, were considered. Results from two groups of 56-day experiments show that overestimated sea surface temperature, 2-m air temperature, 10-m wind, wave height, and underestimated mixed layer from original CFSv2.0 are improved.
Claude-Michel Nzotungicimpaye, Kirsten Zickfeld, Andrew H. MacDougall, Joe R. Melton, Claire C. Treat, Michael Eby, and Lance F. W. Lesack
Geosci. Model Dev., 14, 6215–6240, https://doi.org/10.5194/gmd-14-6215-2021, https://doi.org/10.5194/gmd-14-6215-2021, 2021
Short summary
Short summary
In this paper, we describe a new wetland methane model (WETMETH) developed for use in Earth system models. WETMETH consists of simple formulations to represent methane production and oxidation in wetlands. We also present an evaluation of the model performance as embedded in the University of Victoria Earth System Climate Model (UVic ESCM). WETMETH is capable of reproducing mean annual methane emissions consistent with present-day estimates from the regional to the global scale.
Po-Lun Ma, Bryce E. Harrop, Vincent E. Larson, Richard Neale, Andrew Gettelman, Hugh Morrison, Hailong Wang, Kai Zhang, Stephen A. Klein, Mark D. Zelinka, Yuying Zhang, Yun Qian, Jin-Ho Yoon, Christopher R. Jones, Meng Huang, Sheng-Lun Tai, Balwinder Singh, Peter A. Bogenschutz, Xue Zheng, Wuyin Lin, Johannes Quaas, Hélène Chepfer, Michael A. Brunke, Xubin Zeng, Johannes Mülmenstädt, Samson Hagos, Zhibo Zhang, Hua Song, Xiaohong Liu, Hui Wan, Jingyu Wang, Qi Tang, Peter M. Caldwell, Jiwen Fan, Larry K. Berg, Jerome D. Fast, Mark A. Taylor, Jean-Christophe Golaz, Shaocheng Xie, Philip J. Rasch, and L. Ruby Leung
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-298, https://doi.org/10.5194/gmd-2021-298, 2021
Revised manuscript accepted for GMD
Short summary
Short summary
We developed alternative parameters settings for E3SM Atmospheric Model version 1. We study the impact of parameter changes on the fidelity of model climate, and implications for climate change studies. The recalibration reduces common and longstanding biases across cloud regimes in the model and produces weaker aerosol-cloud interactions and cloud feedbacks.
Jinxiao Li, Qing Bao, Yimin Liu, Lei Wang, Jing Yang, Guoxiong Wu, Xiaofei Wu, Bian He, Xiaocong Wang, Xiaoqi Zhang, Yaoxian Yang, and Zili Shen
Geosci. Model Dev., 14, 6113–6133, https://doi.org/10.5194/gmd-14-6113-2021, https://doi.org/10.5194/gmd-14-6113-2021, 2021
Short summary
Short summary
The configuration and simulated performance of tropical cyclones (TCs) in FGOALS-f3-L/H will be introduced firstly. The results indicate that the simulated performance of TC activities is improved globally with the increased horizontal resolution especially in TC counts, seasonal cycle, interannual variabilities and intensity aspects. It is worth establishing a high-resolution coupled dynamic prediction system based on FGOALS-f3-H (~ 25 km) to improve the prediction skill of TCs.
Cited articles
Andersen, K., Ditlevsen, P., Rasmussen, S., Clausen, H., Vinther, B., Johnsen, S., and Steffensen, J.: Retrieving a comon accumulation record from Greenland ice cores for the past 1800 years, J. Geophys. Res., 111, D15106, https://doi.org/10.1029/2005JD006765, 2006.
Andersen, K. K., Bigler, M., Buchardt, S. L., Clausen, H. B., Dahl-Jensen, D., Davies, S. M., Fischer, H., Goto-Azuma, K., Hansson, M. E., Heinemeier, J., Johnsen, S. J., Larsen, L. B., Mischeler, R., Olsen, G. J., Rasmussen, S. O., Röthlisberger, R., Ruth, U., Seierstad, I. K., Siggaard-Andersen, M.-L., Steffense, J. P., Svensson, A. M., and Vinther, B. M.: Greenland Ice Core Chronology 2005 (GICC05) and 20 year means of oxygen isotope data from ice core NGRIP, PANGAEA, https://doi.org/10.1594/PANGAEA.586838, 2007.
Björklund, J. A., Gunnarson, B. E., Seftigen, K., Esper, J., and Linderholm, H. W.: Blue intensity and density from northern Fennoscandian tree rings, exploring the potential to improve summer temperature reconstructions with earlywood information, Clim. Past, 10, 877–885, https://doi.org/10.5194/cp-10-877-2014, 2014.
Booth, B. B. B., Dunstone, N. J., Halloran, P. R., Andrews, T., and Bellouin, N.: Aerosols implicated as a prime driver of twentieth-century North Atlantic climate variability, Nature, 484, 228–233, https://doi.org/10.1038/nature10946, 2012. a
Browne, M. W.: Cross-Validation Methods, Astron. Astrophys., 44, 108–132, 2000. a
Bunn, A. G., Graumlich, L. J., and Urban, D. L.: Trends in twentieth-century tree growth at high elevations
in the Sierra Nevada and White Mountains, USA, The Holocene, 15, 481–488, https://doi.org/10.1191/0959683605hl827rp, 2005.
Büntgen, U., Franck, D. C., Nievergelt, D., and Esper, J.: Summer Temperature Variations in the European Alps, A.D. 755–2004, J. Climate, 19, 5606–5623, 2006.
Cahill, N., Kemp, A. C., Horton, B. P., and Parnell, A. C.: A Bayesian hierarchical model for reconstructing relative sea level: from raw data to rates of change, Clim. Past, 12, 525–542, https://doi.org/10.5194/cp-12-525-2016, 2016. a
Casado, M., Ortega, P., Masson-Delmotte, V., Risi, C., Swingedouw, D., Daux, V., Genty, D., Maignan, F., Solomina, O., Vinther, B., Viovy, N., and Yiou, P.: Impact of precipitation intermittency on NAO-temperature signals in proxy records, Clim. Past, 9, 871–886, https://doi.org/10.5194/cp-9-871-2013, 2013. a
Dickson, R., Lazier, J., Meincke, J., Rhines, P., and Swift, J.: Long-term coordinated changes in the convective activity of the North Atlantic, Prog. Oceanogr., 38, 241–295, https://doi.org/10.1016/S0079-6611(97)00002-5, 1996. a
Drinkwater, K. F., Belgrano, A., Borja, A., Conversi, A., Edwards, M., Greene, C. H., Ottersen, A., Pershing, J., and Walker, H. A.: The North Atlantic Oscillation: Climate significance and environmental impacts, The response of marine ecosystems to climate variability with the North Atlantic Oscillation, edited by: Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M., Geoph. Monog. Series, 134, 211–234, 2003. a
Esper, J., Büntgen, U., Frank, D., Verstege, A., Nievergelt, D., and Liebhold, A.: 1200 years of regular outbreaks in alpine insects, P. Roy. Soc. B-Biol. Sci., 274, 671–679, 2006.
Esper, J., Frank, D., Büntgen, U., Verstege, A., Luterbacher, J., and Xoplaki, E.: Long-term drought severity variations in Morocco, Geophys. Res. Lett., 34, L17702, https://doi.org/10.1029/2007GL030844, 2007.
Etheridge, D. M., Steele, L. P., Langenfelds, R. L., and Francey, R. J.: Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years from air in Antarctic ice and firn, J. Geophys. Res., 101, 4115–4128, 1996. a
Evan, A. T., Vimont, D. J., Heidinger, A. K., Kossin, J. P., and Bennartz, R.: The Role of Aerosols in the Evolution of Tropical North Atlantic Ocean Temperature Anomalies, Science, 324, 778–781, https://doi.org/10.1126/science.1167404, 2009. a
Evan, A. T., Foltz, G. R., Zhang, D., and Vimont, D. J.: Influence of African dust on ocean–atmosphere variability in the tropical Atlantic, Nat. Geosci., 4, 762–765, https://doi.org/10.1038/NGEO1276, 2011. a
Gneiting, T. and Raftery, A. E.: Strictly Proper Scoring Rules, Prediction, and Estimation, J. Am. Stat. Assoc., 102, 359–378, 2007. a
Fisher, D. A., Koerner, R. M., and Reeh, N.: Holocene climatic records from Agassiz Ice Cap, Ellesmere Island, NWT, Canada, The Holocene, 5, 19–24, 1995.
Friedman, J., Hastie, T., and Tibshirani, R.: Regularization Paths for Generalized Linear Models via Coordinate Descent, J. Stat. Softw., 33, 1–22, 2010.
George, S. S. and Nielsen, E.: Hydroclimatic Change in Southern Manitoba Since A.D. 1409 Inferred from Tree Rings, Quaternary Res., 58, 103–111, https://doi.org/10.1006/qres.2002.2343, 2002.
Gray, S. T., Graumlich, L. J., Betancourt, J. L., and Pederson, G. T.: A tree-ring based reconstruction of the Atlantic Multidecadal Oscillation since 1567 A.D., Geophys. Res. Lett., 31, L12205, https://doi.org/10.1029/2004GL019932, 2004. a, b, c
Graybill, D. A.: International Tree-ring Data Bank NV516, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1994a.
Graybill, D. A.: International Tree-ring Data Bank NV517, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1994b.
Graybill, D. A.: International Tree-ring Data Bank UT508, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1994c.
Graybill, D. A.: International Tree-ring Data Bank UT509, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1994d.
Guillot, D., Rajaratnam, B., and Emile-Geay, J.: Statistical paleoclimate reconstructions via Markov random fields, Ann. Appl. Stat., 9, 324–352, https://doi.org/10.1214/14-AOAS794, 2015. a
Hakim, G. J., Emile-Geay, J., Steig, E. J., Tardif, R., Steiger, N., and Perkins, W. A.: The last millennium climate reanalysis project: Framework and first results, J. Geophys. Res.-Atmos., 121, 6745–6764, 2016. a
Hawkins, E. and Sutton, R.: The potential to narrow uncertainty in regional climate predictions, B. Am. Meteorol. Soc., 90, 1095–1108, https://doi.org/10.1175/2009BAMS2607.1, 2009. a
Helama, S., Holopainen, J., Timonen, M., and Mielikäinen, K.: An 854-Year Tree-ring chronology of Scots Pine for South-West Finland, Studia Quaternaria, 31, 61–68, https://doi.org/10.2478/squa-2014-0006, 2014.
Homrighausen, D. and McDonald, D. J.: Leave-one-out cross-validation is risk consistent for lasso, Mach. Learn., 97, 65–78, https://doi.org/10.1007/s10994-014-5438-z, 2014. a
Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M.: An overview of the North Atlantic Oscillation, Geoph. Monog. Series, 134, 1–35, https://doi.org/10.1029/134GM01, 2003. a
Isobe, T., Feigelson, E. D., Akritas, M. G., and Babu, G. J.: Linear regression in astronomy, I, Astrophys. J., 364, 104–113, 1990. a
Jones, P. D., Jonsson, T., and Wheeler, D.: Extension to the North Atlantic Oscillation using early instrumental pressure observations from Gibraltar and south-west Iceland, Int. J. Climatol., 17, 1433–1450, https://doi.org/10.1002/(SICI)1097-0088(19971115)17:13<1433::AID-JOC203>3.0.CO;2-P, 1997. a, b, c, d, e
Karspeck, A. R., Stammer, D., Köhl, A., Danabasoglu, G., Balmaseda, M., Smith, D. M., Fujii, Y., Zhang, S., Giese, B., Tsujino, H., and Rosati, A.: Comparison of the Atlantic meridional overturning circulation between 1960 and 2007 in six ocean reanalysis products, J. Climate, 26, 7392–7413, 2015. a
Khodri, M., Izumo, T., Vialard, J., Janicot, S., Cassou, C., Lengaigne, M., Mignot, J., Gastineau, G., Guilyardi, E., Lebas, N., Robock, A., and McPhaden, M. J.: Tropical explosive volcanic eruptions can trigger El Niño by cooling tropical Africa, Nat. Commun., 8, 778, https://doi.org/10.1038/s41467-017-00755-6, 2017. a
Kohavi, R.: A study of Cross-Validation and Boostrap for Accuracy Estimation and Model Selection, Proceedings of the 14th International Joint Conferences on Artificial Intelligence, 2, 1137–1143, 1995. a
Kosaka, Y. and Xie, S.-P.: Recent global-warming hiatus tied to equatorial Pacific surface cooling, Nature, 501, 403–407, https://doi.org/10.1038/nature12534, 2013. a
Lehner, F., Raible, C. C., and Stocker, T. F.: Testing the robustness of a precipitation proxy-based North Atlantic Oscillation reconstruction, Quaternary Sci. Rev., 45, 85–94, 2012. a
Li, J., Xie, S., Cook, E. R., Morales, M. S., Christie, N. C. J., Chen, F., D'Arrigo, R., Fowler, A. M., and Gou, X.: El Niño modulations over the
past seven centuries, Nat. Clim. Change, 3, 822–826, 2013. a
Liaw, A. and Wiener, M.: Classification and Regression by randomForest, R News, 2, 18–22, 2002.
Lindholm, M. and Jalkanen, R.: Subcentury scale variability in height-increment and tree-ring width chronologies of Scots pine since AD 745 in northern Finland, The Holocene, 22, 571–577, https://doi.org/10.1177/0959683611427332, 2011.
Mann, M. E., Zhang, Z., Hughes, M. K., Bradley, R. S., Miller, S. K., Rutherford, S., and Ni, F.: Proxy-based reconstructions of hemispheric and global surface temperature variations over the past two millennia, P. Natl. Acad. Sci. USA, 35, 13252–13257, 2008. a
McCarthy, G. D., Haigh, I. D., Hirshi, J. J.-M., Grist, J. P., and Smeed, D. A.: Ocean impact on decadal Atlantic climate variability revealed by sea-level observations, Nature, 521, 508–512, 2015.
McCornack, R. L.: An evaluation of two methods of cross-validation, Psychol. Rep., 5, 127–130, 1959. a
Meeker, L. D. and Mayewski, P. A.: A 1400-year high-resolution record of atmospheric circulation over the North Atlantic and Asia, The Holocene, 12, 257–266, 2002.
Mevik, B., Wehrens, R., and Liland, K. H.: The pls Package: Principal Component and Partial Least Squares Regression in R, J. Stat. Softw., 18, 1–23, 2007.
Michel, S.: ClimIndRec 1.0, Version 1.0, Zenodo, https://doi.org/10.5281/zenodo.3464293, 2019. a
Mignot, J., Khodri, M., Frankignoul, C., and Servonnat, J.: Volcanic impact on the Atlantic Ocean over the last millennium, Clim. Past, 7, 1439–1455, https://doi.org/10.5194/cp-7-1439-2011, 2011. a
Mitchell, J. M. J., Dzerdzeevskii, B., Flohn, H., Hofmeyr, W. L., Lamb, H. H., Rao, K. N., and Wallén, C. C.: Climatic change: Technical note No. 79, report of a working group for the commission of climatology, World Meteorologicl Organization, Geneva, Switzerland, 1966. a
Mysterud, A., Stenseth, N. C., Yoccoz, N. G., Langvatn, R., and Steinheim, G.: Nonlinear effects of large-scale climatic variability on wild and domestic herbivores, Nature, 410, 1096–1099, https://doi.org/10.1038/35074099, 2001. a
Naurzbaev, M. M., Vaganov, E. A., Sidorova, O. V., and Schweingruber, F. H.: Summer temperatures in eastern Taimyr inferred from a 2427-year late-Holocene tree-ring chronology and earlier floating series,
The Holocene, 12, 727–736, https://doi.org/10.1191/0959683602hl586rp, 2002.
Neelin, J. D., Anthony, S. B., Hirst, A. C., Jin, F.-F., Wakata, Y., Yamagata, T., and Zebiak, S. E.: ENSO theory, J. Geophys. Res., 103, 14261–14290, https://doi.org/10.1029/97JC03424, 1998. a
Ortega, P., Lehner, F., Swingedouw, D., Masson-Delmotte, V., Raible, C. C., Casado, M., and Yiou, P.: A model-tested North Atlantic Oscillation reconstruction for the past millennium, Nature, 523, 71–74, https://doi.org/10.1038/nature14518, 2015. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z, aa, ab, ac, ad
PAGES 2K Consortium: Continental-scale temperature variability during the past two millennia, Nat. Geosci., 6, 339–346, https://doi.org/10.1038/NGEO1797, 2013. a
PAGES 2K Consortium: A global multiproxy database for temperature reconstructions of the Common Era, Scientific Data, 4, 170088, https://doi.org/10.1038/sdata.2017.88, 2017. a, b
Pierce, D.: ncdf4: Interface to Unidata netCDF (Version 4 or Earlier) Format Data Files, r package version 1.16, available at: https://CRAN.R-project.org/package=ncdf4 (last access: 1 July 2017), 2017.
Reynolds, D. J., Scourse, J. D., Halloran, P. R., Nederbragt, A. J., Wanamaker, A. D., Butler, P. G., Richardson, C. A., Heinemeier, J., Eiriksson, J., Knudsen, K. L., and Hall, I. R.: Annually resolved North Atlantic marine climate over the last millennium, Nat. Commun., 7, 13502, https://doi.org/10.1038/ncomms13502, 2016.
Salzer, M. W. and Kipfmueller, K. F.: Reconstructed Temperature and Precipitation on a Millennial Timescale from Tree-Rings in the Southern Colorado Plateau, U.S.A., Climatic Change, 70, 465–487, 2005.
Santer, B. D., Bonfils, C., Painter, J. F., Zelinka, M. D., Mears, C., Solomon, S., Schmidt, G. A., Fyfe, J. C., Cole, J. N. S., Nazarenko, L., Taylor, K. E., and Wentz, F. J.: Volcanic contribution to decadal changes in
tropospheric temperatures, Nat. Geosci., 7, 185–189, https://doi.org/10.1038/ngeo2098, 2014. a
Schneider, T.: Analysis of Incomplete Climate Data: Estimation of Mean Values and Covariance Matrices and Imputation of Missing Values, J. Climate, 14, 853–871, 2001. a
Seidenglanz, A., Prange, M., Varma, V., and Schulz, M.: Ocean temperature response to idealized Gleissberg and de Vries solar cycles in a comprehensive climate model, Geophys. Res. Lett., 39, L22602, https://doi.org/10.1029/2012GL053624, 2012. a
Shindell, D. T., Schmidt, G. A., Mann, M. E., and Faluvegi, G.: Dynamic winter climate response to large tropical volcanic eruptions since 1600, J. Geophys. Res., 109, D05104, https://doi.org/10.1029/2003JD004151, 2004. a
Sigl, M., Winstrup, M., McConnell, J. R., Welten, K. C., Plunkett, G., Ludlow, F., Büntgen, U., Caffee, M., Chellman, N., Dahl-Jensen, D., Fischer, H., Kipfstuhl, S., Kostick, C., Maselli, O. J., Mekhaldi, F., Mulvaney, R., Muscheler, R., Pasteris, D. R., Pilcher, J. R., Salzer, M., Schüpbach, S., Steffensen, J. P., Vinther, B. M., and Woodruff, T. E.: Timing and climate forcing of volcanic eruptions for the past 2,500 years, Nature, 523, 543–549, 2015. a, b
Singh, H. K. A., Hakim, G. J., Tardif, R., Emile-Geay, J., and Noone, D. C.: Insights into Atlantic multidecadal variability using the Last Millennium Reanalysis framework, Clim. Past, 14, 157–174, https://doi.org/10.5194/cp-14-157-2018, 2018. a
Stahle, D. K., Burnette, D. J., and Stahle, D. W.: A Moisture Balance Reconstruction for the Drainage Basin of Albemarle Sound, North Carolina, Estuar. Coast., 36, 1340–1353, https://doi.org/10.1007/s12237-013-9643-y,
2013.
Stahle, D. W.: International Tree-ring Data Bank AR050, available at: (last access: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1996a.
Stahle, D. W.: International Tree-ring Data Bank LA001, available at: (last access: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1996b.
Stahle, D. W. and Cleaveland, M. K.: International Tree-ring Data Bank AR052, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 2005a.
Stahle, D. W. and Cleaveland, M. K.: International Tree-ring Data Bank FL001, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 2005b.
Stahle, D. W., Villanueva Diaz, J., Brunette, D. J., Cerano Paredes, J., Heim Jr., R. R., Fye, F. K., Acuna Soto, R., Therell, M. D., Cleaveland, M. K., and Stahle, D. K.: Major Mesoamerican droughts of the past millennium,
Geophys. Res. Lett., 38, L05703, https://doi.org/10.1029/2010GL046472, 2011.
Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M. M. B., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M.: Climate Change 2013, The Physical Science Basis. Working Group I Contribution to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, 2013. a, b
Swingedouw, D., Terray, L., Cassou, C., Voldoire, A., Salas-Mélia, D., and Servonnat, J.: Natural forcing of climate during the last millennium: fingerprint of solar variability, Clim. Dynam., 36, 1349–1364, https://doi.org/10.1007/s00382-010-0803-5, 2011. a
Swingedouw, D., Ortega, P., Mignot, J., Guilyardi, E., Masson-delmotte, V., Butler, P. G., Khodri, M., and Séférian, R.: Bidecadal North Atlantic ocean circulation variability controlled by timing of volcanic eruptions, Nat. Commun., 6, 6545, https://doi.org/10.1038/ncomms7545, 2015. a
Swingedouw, D., Mignot, J., Ortega, P., Khodri, M., Menegoz, M., Cassou, C., and Hanquiez, V.: Impact of explosive volcanic eruptions on the main climate variability modes, Global Planet. Change, 150, 24–45, https://doi.org/10.1016/j.gloplacha.2017.01.006, 2017. a, b
Tingley, M. P.: A Bayesian ANOVA Scheme for Calculating Climate Anomalies, with Applications to the Instrumental Temperature Record, J. Climate, 25, 777–791, 2012. a
Tingley, M. P. and Huybers, P.: A Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time. Part I: Development and Applications to Paleoclimate Reconstruction Problems, J. Climate, 23, 2759–2781, 2010a. a
Tingley, M. P. and Huybers, P.: A Bayesian Algorithm for Reconstructing Climate Anomalies in Space and Time. Part II: Comparison with the Regularized Expectation-Maximization Algorithm, J. Climate, 23, 2782–2800, 2010b. a
Tingley, M. P. and Huybers, P.: Recent temperature extremes at high northern latitudes unprecedented in the past 600 years, Nature, 496, 201–205, 2013. a
Tingley, M. P., Craigmile, P. F., Haran, M., Li, B., Mannshardt, E., and Rajaratnam, B.: Piecing together the past: statistical insights into paleoclimatic reconstructions, Quaternary Sci. Rev., 35, 1–22, 2012. a
Tosh, R.: International Tree-ring Data Bank CA051, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 1994.
Touchan, R., Garfin, G. M., Meko, D. M., Funkhouser, G., Erkan, N., Hughes, M. K., and Wallin, B. S.: Preliminary reconstructions of spring precipitation in southwestern Turkey from tree-ring width, Int. J. Climatol., 23, 157–171, https://doi.org/10.1002/joc.850, 2003.
Touchan, R., Woodhouse, C. A., Meko, D. M., and Allen, C.: Millennial precipitation reconstruction for the Jemez Mountains, New Mexico, reveals changing drought signal, Int. J. Climatol., 31, 896–906, 2011.
Trenberth, K. E. and Fasullo, J. T.: Atlantic meridional heat transports computed from balancing Earth’s energy locally, Geophys. Res. Lett., 44, 1919–1927, https://doi.org/10.1002/2016GL072475, 2017. a
Trenberth, K. E. and Shea, D. J.: Atlantic hurricanes and natural variability in 2005, Geophys. Res. Lett., 33, L12704, https://doi.org/10.1029/2006GL026894, 2006. a
Trouet, V., Esper, J., Graham, N., Baker, A., Scourse, J., and Frank, D.: Persistent positive North Atlantic oscillation mode dominated the Medieval Climate Anomaly, Science, 324, 78–80, 2009. a
Vieira, L. E. A., Solanki, S. K., Krivova, N. A., and Usoskin, I.: Evolution of the solar irradiance during the Holocene, Astron. Astrophys., 531, A6, https://doi.org/10.1051/0004-6361/201015843, 2011. a
Visbeck, M., Chassignet, E. P., Curry, R. G., Delworth, T. L., Dickson, R. R., and Krahmann, G.: The North Atlantic Oscillation Climate significance and environmental impacts: The Ocean's response to North Atlantic Oscillation variability, edited by: Hurrell, J. W., Kushnir, Y., Ottersen, G., and Visbeck, M., Geoph. Monog. Series, 134, 113–145, 2003. a
Wang, J., Emile-Geay, J., Guillot, D., Smerdon, J. E., and Rajaratnam, B.: Evaluating climate field reconstruction techniques using improved emulations of real-world conditions, Clim. Past, 10, 1–19, https://doi.org/10.5194/cp-10-1-2014, 2014.
a
Wickham, H.: stringr: Simple, Consistent Wrappers for Common String Operations, r package version 1.2.0, available at: https://CRAN.R-project.org/package=stringr, last access: 1 July 2017.
Wilson, R., Miles, D., Loader, N. J., Cooper, R., and Briffa, K.: A millennial long March-July precipitation reconstruction for southern-central England, Clim. Dynam., 40, 997–1017, https://doi.org/10.1007/s00382-012-1318-z, 2013.
Woodhouse, C. A. and Brown, P. M.: Internation Tree-ring Data Bank CO572, available at: https://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets/tree-ring (last access: 6 June 2017), 2006.
Young, G. H. F., McCarroll, D., Loader, N. J., Gagen, M., Kirchhefer, A. J., and Demmler, J. C.: Changes in atmospheric circulation and the Arctic Oscillation preserved within a millennial length reconstruction
of summer cloud cover from northern Fennoscandia, Clim. Dynam., 39, 495–507, https://doi.org/10.1177/0959683609351902, 2012.
Zhang, P., Linderholm, H. W., Gunnarson, B. E., Björklund, J., and Chen, D.: 1200 years of warm-season temperature variability in central Scandinavia inferred from tree-ring density, Clim. Past, 12, 1297–1312, https://doi.org/10.5194/cp-12-1297-2016, 2016.
Zhang, Y. and Yang, Y.: Cross-validation for selecting a model selection procedure, J. Econometrics, 187, 95–112, https://doi.org/10.1016/j.jeconom.2015.02.006, 2015. a
Zou, H.: The Adaptive Lasso and its Oracle Properties, J. Am. Stat. Assoc., 101, 1418–1429, 2006. a
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.
Natural archives such as sediments, ice, tree rings or speleothems provide indirect observations...
