Articles | Volume 13, issue 2
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Reconstructing climatic modes of variability from proxy records using ClimIndRec version 1.0
Environnements et Paléoenvironnements Océaniques et Continentaux (EPOC), UMR CNRS 5805 EPOC-OASU-Université de Bordeaux, Allee Geoffroy Saint-Hilaire, Pessac 33615, France
Environnements et Paléoenvironnements Océaniques et Continentaux (EPOC), UMR CNRS 5805 EPOC-OASU-Université de Bordeaux, Allee Geoffroy Saint-Hilaire, Pessac 33615, France
Institut National de la Recherche en Informatique et Automatique (INRIA), CQFD, 33400 Talence, France
BSC, Barcelona, Spain
Sorbonne Universités (UPMC, Univ. Paris 06)-CNRS-IRD-MNHN, LOCEAN Laboratory, 4 place Jussieu, 75005 Paris, France
Sorbonne Universités (UPMC, Univ. Paris 06)-CNRS-IRD-MNHN, LOCEAN Laboratory, 4 place Jussieu, 75005 Paris, France
No articles found.
Roberto Bilbao, Pablo Ortega, Didier Swingedouw, Leon Hermanson, Panos Athanasiadis, Rosie Eade, Marion Devilliers, Francisco Doblas-Reyes, Nick Dunstone, An-Chi Ho, William Merryfield, Juliette Mignot, Dario Nicolì, Margarida Samsó, Reinel Sospedra-Alfonso, Xian Wu, and Stephen Yeager
Earth Syst. Dynam. Discuss.,
Preprint under review for ESDShort summary
In recent decades three major volcanic eruptions have occurred: Mount Agung in 1963, El Chichón in 1982 and Mount Pinatubo in 1991. In this article we explore the climatic impacts of these volcanic eruptions with a purposefully designed set of simulations from six CMIP6 decadal prediction systems. We analyse the radiative and dynamical responses and show that including the volcanic forcing in these predictions is important to reproduce the observed surface temperature variations.
Nico Wunderling, Anna von der Heydt, Yevgeny Aksenov, Stephen Barker, Robbin Bastiaansen, Victor Brovkin, Maura Brunetti, Victor Couplet, Thomas Kleinen, Caroline H. Lear, Johannes Lohmann, Rosa Maria Roman-Cuesta, Sacha Sinet, Didier Swingedouw, Ricarda Winkelmann, Pallavi Anand, Jonathan Barichivich, Sebastian Bathiany, Mara Baudena, John T. Bruun, Christiano M. Chiessi, Helen K. Coxall, David Docquier, Jonathan F. Donges, Swinda K. J. Falkena, Ann Kristin Klose, David Obura, Juan Rocha, Stefanie Rynders, Norman Julius Steinert, and Matteo Willeit
This paper reviews the state-of-the-art literature on interactions between tipping elements and discusses the risk of potential tipping cascades under ongoing global warming. Specifically, we review the current knowledge on interactions between pairs of tipping elements from models to observations, review archetypal examples of tipping cascades in the past, and outline how future developments could improve our understanding of climate tipping element interactions.
Laura C. Jackson, Eduardo Alastrué de Asenjo, Katinka Bellomo, Gokhan Danabasoglu, Helmuth Haak, Aixue Hu, Johann Jungclaus, Warren Lee, Virna L. Meccia, Oleg Saenko, Andrew Shao, and Didier Swingedouw
Geosci. Model Dev., 16, 1975–1995,Short summary
The Atlantic meridional overturning circulation (AMOC) has an important impact on the climate. There are theories that freshening of the ocean might cause the AMOC to cross a tipping point (TP) beyond which recovery is difficult; however, it is unclear whether TPs exist in global climate models. Here, we outline a set of experiments designed to explore AMOC tipping points and sensitivity to additional freshwater input as part of the North Atlantic Hosing Model Intercomparison Project (NAHosMIP).
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,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,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,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,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,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,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,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,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,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,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,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,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,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,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,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,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,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,
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,
R. Séférian, L. Bopp, D. Swingedouw, and J. Servonnat
Earth Syst. Dynam., 4, 109–127,
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,
P. Ortega, M. Montoya, F. González-Rouco, H. Beltrami, and D. Swingedouw
Clim. Past, 9, 547–565,
Related subject area
Climate and Earth system modelingA sub-grid parameterization scheme for topographic vertical motion in CAM5-SETechnology to aid the analysis of large-volume multi-institute climate model output at a central analysis facility (PRIMAVERA Data Management Tool V2.10)A diffusion-based kernel density estimator (diffKDE, version 1) with optimal bandwidth approximation for the analysis of data in geoscience and ecological researchMonte Carlo drift correction – quantifying the drift uncertainty of global climate modelsImprovements in the Canadian Earth System Model (CanESM) through systematic model analysis: CanESM5.0 and CanESM5.1Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observationsCIOFC1.0: a common parallel input/output framework based on C-Coupler2.0Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet methodIntroducing a new floodplain scheme in ORCHIDEE (version 7885): validation and evaluation over the Pantanal wetlandsURock 2023a: an open-source GIS-based wind model for complex urban settingsDASH: a MATLAB toolbox for paleoclimate data assimilationComparing the Performance of Julia on CPUs versus GPUs and Julia-MPI versus Fortran-MPI: a case study with MPAS-Ocean (Version 7.1)All aboard! Earth system investigations with the CH2O-CHOO TRAIN v1.0The Canadian Atmospheric Model version 5 (CanAM5.0.3)The Teddy tool v1.1: temporal disaggregation of daily climate model data for climate impact analysisAssimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)Modernizing the open-source community Noah with multi-parameterization options (Noah-MP) land surface model (version 5.0) with enhanced modularity, interoperability, and applicabilitySimulated stable water isotopes during the mid-Holocene and pre-industrial periods using AWI-ESM-2.1-wisoTruly Conserving with Conservative Remapping MethodsRainbows and climate change: a tutorial on climate model diagnostics and parameterizationModE-Sim – a medium-sized atmospheric general circulation model (AGCM) ensemble to study climate variability during the modern era (1420 to 2009)MESMAR v1: a new regional coupled climate model for downscaling, predictability, and data assimilation studies in the Mediterranean regionClimate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applicationsIceTFT v1.0.0: interpretable long-term prediction of Arctic sea ice extent with deep learningEarth system modeling on Modular Supercomputing Architectures: coupled atmosphere-ocean simulations with ICON 2.6.6-rcThe KNMI Large Ensemble Time Slice (KNMI–LENTIS)ENSO statistics, teleconnections, and atmosphere–ocean coupling in the Taiwan Earth System Model version 1Using probabilistic machine learning to better model temporal patterns in parameterizations: a case study with the Lorenz 96 modelThe Regional Aerosol Model Intercomparison Project (RAMIP)DSCIM-Coastal v1.1: an open-source modeling platform for global impacts of sea level riseTIMBER v0.1: a conceptual framework for emulating temperature responses to tree cover changeRecalibration of a three-dimensional water quality model with a newly developed autocalibration toolkit (EFDC-ACT v1.0.0): how much improvement will be achieved with a wider hydrological variability?Description and evaluation of the JULES-ES set-up for ISIMIP2bSimplified Kalman smoother and ensemble Kalman smoother for improving reanalysesUnderstanding Changes in Cloud Simulations from E3SM Version 1 to Version 2Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCMModeling river water temperature with limiting forcing data: Air2stream v1.0.0, machine learning and multiple regressionWRF (v4.0)-SUEWS (v2018c) Coupled System: Development, Evaluation and ApplicationA machine learning approach targeting parameter estimation for plant functional type coexistence modeling using ELM-FATES (v2.0)Resolving the mesoscale at reduced computational cost with FESOM 2.5: efficient modeling approaches applied to the Southern OceanModeling and evaluating the effects of irrigation on land-atmosphere interaction in South-West Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterizationThe fully coupled regionally refined model of E3SM version 2: overview of the atmosphere, land, and river resultsThe mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddiesA new simplified parameterization of secondary organic aerosol in the Community Earth System Model Version 2 (CESM2; CAM6.3)Deep learning for stochastic precipitation generation – deep SPG v1.0Developing spring wheat in the Noah-MP land surface model (v4.4) for growing season dynamics and responses to temperature stressDeep Learning Model based on Multi-scale Feature Fusion for Precipitation NowcastingRobust 4D climate-optimal flight planning in structured airspace using parallelized simulation on GPUs: ROOST V1.0High resolution downscaling of CMIP6 Earth System and Global Climate Models using deep learning for IberiaThe Earth system model CLIMBER-X v1.0 – Part 2: The global carbon cycle
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873,Short summary
In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
Jon Seddon, Ag Stephens, Matthew S. Mizielinski, Pier Luigi Vidale, and Malcolm J. Roberts
Geosci. Model Dev., 16, 6689–6700,Short summary
The PRIMAVERA project aimed to develop a new generation of advanced global climate models. The large volume of data generated was uploaded to a central analysis facility (CAF) and was analysed by 100 PRIMAVERA scientists there. We describe how the PRIMAVERA project used the CAF's facilities to enable users to analyse this large dataset. We believe that similar, multi-institute, big-data projects could also use a CAF to efficiently share, organise and analyse large volumes of data.
Maria-Theresia Pelz, Markus Schartau, Christopher J. Somes, Vanessa Lampe, and Thomas Slawig
Geosci. Model Dev., 16, 6609–6634,Short summary
Kernel density estimators (KDE) approximate the probability density of a data set without the assumption of an underlying distribution. We used the solution of the diffusion equation, and a new approximation of the optimal smoothing parameter build on two pilot estimation steps, to construct such a KDE best suited for typical characteristics of geoscientific data. The resulting KDE is insensitive to noise and well resolves multimodal data structures as well as boundary-close data.
Benjamin S. Grandey, Zhi Yang Koh, Dhrubajyoti Samanta, Benjamin P. Horton, Justin Dauwels, and Lock Yue Chew
Geosci. Model Dev., 16, 6593–6608,Short summary
Global climate models are susceptible to spurious trends known as drift. Fortunately, drift can be corrected when analysing data produced by models. To explore the uncertainty associated with drift correction, we develop a new method: Monte Carlo drift correction. For historical simulations of thermosteric sea level rise, drift uncertainty is relatively large. When analysing data susceptible to drift, researchers should consider drift uncertainty.
Michael Sigmond, James Anstey, Vivek Arora, Ruth Digby, Nathan Gillett, Viatcheslav Kharin, William Merryfield, Catherine Reader, John Scinocca, Neil Swart, John Virgin, Carsten Abraham, Jason Cole, Nicolas Lambert, Woo-Sung Lee, Yongxiao Liang, Elizaveta Malinina, Landon Rieger, Knut von Salzen, Christian Seiler, Clint Seinen, Andrew Shao, Reinel Sospedra-Alfonso, Libo Wang, and Duo Yang
Geosci. Model Dev., 16, 6553–6591,Short summary
We present a new activity which aims to organize the analysis of biases in the Canadian Earth System model (CanESM) in a systematic manner. Results of this “Analysis for Development” (A4D) activity includes a new CanESM version, CanESM5.1, which features substantial improvements regarding the simulation of dust and stratospheric temperatures, a second CanESM5.1 variant with reduced climate sensitivity, and insights into potential avenues to reduce various other model biases.
Shuaiqi Tang, Adam C. Varble, Jerome D. Fast, Kai Zhang, Peng Wu, Xiquan Dong, Fan Mei, Mikhail Pekour, Joseph C. Hardin, and Po-Lun Ma
Geosci. Model Dev., 16, 6355–6376,Short summary
To assess the ability of Earth system model (ESM) predictions, we developed a tool called ESMAC Diags to understand how aerosols, clouds, and aerosol–cloud interactions are represented in ESMs. This paper describes its version 2 functionality. We compared the model predictions with measurements taken by planes, ships, satellites, and ground instruments over four regions across the world. Results show that this new tool can help identify model problems and guide future development of ESMs.
Xinzhu Yu, Li Liu, Chao Sun, Qingu Jiang, Biao Zhao, Zhiyuan Zhang, Hao Yu, and Bin Wang
Geosci. Model Dev., 16, 6285–6308,Short summary
In this paper we propose a new common, flexible, and efficient parallel I/O framework for earth system modeling based on C-Coupler2.0. CIOFC1.0 can handle data I/O in parallel and provides a configuration file format that enables users to conveniently change the I/O configurations. It can automatically make grid and time interpolation, output data with an aperiodic time series, and accelerate data I/O when the field size is large.
Toshiki Matsushima, Seiya Nishizawa, and Shin-ichiro Shima
Geosci. Model Dev., 16, 6211–6245,Short summary
A particle-based cloud model was developed for meter- to submeter-scale resolution in cloud simulations. Our new cloud model's computational performance is superior to a bin method and comparable to a two-moment bulk method. A highlight of this study is the 2 m resolution shallow cloud simulations over an area covering ∼10 km2. This model allows for studying turbulence and cloud physics at spatial scales that overlap with those covered by direct numerical simulations and field studies.
Anthony Schrapffer, Jan Polcher, Anna Sörensson, and Lluís Fita
Geosci. Model Dev., 16, 5755–5782,Short summary
The present paper introduces a floodplain scheme for a high-resolution land surface model river routing. It was developed and evaluated over one of the world’s largest floodplains: the Pantanal in South America. This shows the impact of tropical floodplains on land surface conditions (soil moisture, temperature) and on land–atmosphere fluxes and highlights the potential impact of floodplains on land–atmosphere interactions and the importance of integrating this module in coupled simulations.
Jérémy Bernard, Fredrik Lindberg, and Sandro Oswald
Geosci. Model Dev., 16, 5703–5727,Short summary
The UMEP plug-in integrated in the free QGIS software can now calculate the spatial variation of the wind speed within urban settings. This paper shows that the new wind model, URock, generally fits observations well and highlights the main needed improvements. According to this work, pedestrian wind fields and outdoor thermal comfort can now simply be estimated by any QGIS user (researchers, students, and practitioners).
Jonathan King, Jessica Tierney, Matthew Osman, Emily J. Judd, and Kevin J. Anchukaitis
Geosci. Model Dev., 16, 5653–5683,Short summary
Paleoclimate data assimilation is a useful method that allows researchers to combine climate models with natural archives of past climates. However, it can be difficult to implement in practice. To facilitate this method, we present DASH, a MATLAB toolbox. The toolbox provides routines that implement common steps of paleoclimate data assimilation, and it can be used to implement assimilations for a wide variety of time periods, spatial regions, data networks, and analytical algorithms.
Siddhartha Bishnu, Robert R. Strauss, and Mark R. Petersen
Geosci. Model Dev., 16, 5539–5559,Short summary
Here we test Julia, a relatively new programming language, which is designed to be simple to write, but also fast on advanced computer architectures. We found that Julia is both convenient and fast, but there is no free lunch. Our first attempt to develop an ocean model in Julia was relatively easy, but the code was slow. After several months of further development, we created a Julia code that is as fast on supercomputers as a Fortran ocean model.
Tyler Kukla, Daniel E. Ibarra, Kimberly V. Lau, and Jeremy K. C. Rugenstein
Geosci. Model Dev., 16, 5515–5538,Short summary
The CH2O-CHOO TRAIN model can simulate how climate and the long-term carbon cycle interact across millions of years on a standard PC. While efficient, the model accounts for many factors including the location of land masses, the spatial pattern of the water cycle, and fundamental climate feedbacks. The model is a powerful tool for investigating how short-term climate processes can affect long-term changes in the Earth system.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448,Short summary
The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Florian Zabel and Benjamin Poschlod
Geosci. Model Dev., 16, 5383–5399,Short summary
Today, most climate model data are provided at daily time steps. However, more and more models from different sectors, such as energy, water, agriculture, and health, require climate information at a sub-daily temporal resolution for a more robust and reliable climate impact assessment. Here we describe and validate the Teddy tool, a new model for the temporal disaggregation of daily climate model data for climate impact analysis.
Young-Chan Noh, Yonghan Choi, Hyo-Jong Song, Kevin Raeder, Joo-Hong Kim, and Youngchae Kwon
Geosci. Model Dev., 16, 5365–5382,Short summary
This is the first attempt to assimilate the observations of microwave temperature sounders into the global climate forecast model in which the satellite observations have not been assimilated in the past. To do this, preprocessing schemes are developed to make the satellite observations suitable to be assimilated. In the assimilation experiments, the model analysis is significantly improved by assimilating the observations of microwave temperature sounders.
Cenlin He, Prasanth Valayamkunnath, Michael Barlage, Fei Chen, David Gochis, Ryan Cabell, Tim Schneider, Roy Rasmussen, Guo-Yue Niu, Zong-Liang Yang, Dev Niyogi, and Michael Ek
Geosci. Model Dev., 16, 5131–5151,Short summary
Noah-MP is one of the most widely used open-source community land surface models in the world, designed for applications ranging from uncoupled land surface and ecohydrological process studies to coupled numerical weather prediction and decadal climate simulations. To facilitate model developments and applications, we modernize Noah-MP by adopting modern Fortran code and data structures and standards, which substantially enhance model modularity, interoperability, and applicability.
Xiaoxu Shi, Alexandre Cauquoin, Gerrit Lohmann, Lukas Jonkers, Qiang Wang, Hu Yang, Yuchen Sun, and Martin Werner
Geosci. Model Dev., 16, 5153–5178,Short summary
We developed a new climate model with isotopic capabilities and simulated the pre-industrial and mid-Holocene periods. Despite certain regional model biases, the modeled isotope composition is in good agreement with observations and reconstructions. Based on our analyses, the observed isotope–temperature relationship in polar regions may have a summertime bias. Using daily model outputs, we developed a novel isotope-based approach to determine the onset date of the West African summer monsoon.
Karl E. Taylor
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Geosci. Model Dev., 16, 4937–4956,Short summary
A representation of rainbows is developed for a climate model. The diagnostic raises many common issues. Simulated rainbows are evaluated against limited observations. The pattern of rainbows in the model matches observations and theory about when and where rainbows are most common. The diagnostic is used to assess the past and future state of rainbows. Changes to clouds from climate change are expected to increase rainbows as cloud cover decreases in a warmer world.
Ralf Hand, Eric Samakinwa, Laura Lipfert, and Stefan Brönnimann
Geosci. Model Dev., 16, 4853–4866,Short summary
ModE-Sim is an ensemble of simulations with an atmosphere model. It uses observed sea surface temperatures, sea ice conditions, and volcanic aerosols for 1420 to 2009 as model input while accounting for uncertainties in these conditions. This generates several representations of the possible climate given these preconditions. Such a setup can be useful to understand the mechanisms that contribute to climate variability. This paper describes the setup of ModE-Sim and evaluates its performance.
Andrea Storto, Yassmin Hesham Essa, Vincenzo de Toma, Alessandro Anav, Gianmaria Sannino, Rosalia Santoleri, and Chunxue Yang
Geosci. Model Dev., 16, 4811–4833,Short summary
Regional climate models are a fundamental tool for a very large number of applications and are being increasingly used within climate services, together with other complementary approaches. Here, we introduce a new regional coupled model, intended to be later extended to a full Earth system model, for climate investigations within the Mediterranean region, coupled data assimilation experiments, and several downscaling exercises (reanalyses and long-range predictions).
Anna L. Merrifield, Lukas Brunner, Ruth Lorenz, Vincent Humphrey, and Reto Knutti
Geosci. Model Dev., 16, 4715–4747,Short summary
Using all Coupled Model Intercomparison Project (CMIP) models is unfeasible for many applications. We provide a subselection protocol that balances user needs for model independence, performance, and spread capturing CMIP’s projection uncertainty simultaneously. We show how sets of three to five models selected for European applications map to user priorities. An audit of model independence and its influence on equilibrium climate sensitivity uncertainty in CMIP is also presented.
Bin Mu, Xiaodan Luo, Shijin Yuan, and Xi Liang
Geosci. Model Dev., 16, 4677–4697,Short summary
To improve the long-term forecast skill for sea ice extent (SIE), we introduce IceTFT, which directly predicts 12 months of averaged Arctic SIE. The results show that IceTFT has higher forecasting skill. We conducted a sensitivity analysis of the variables in the IceTFT model. These sensitivities can help researchers study the mechanisms of sea ice development, and they also provide useful references for the selection of variables in data assimilation or the input of deep learning models.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere-ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 59 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Laura Muntjewerf, Richard Bintanja, Thomas Reerink, and Karin van der Wiel
Geosci. Model Dev., 16, 4581–4597,Short summary
The KNMI Large Ensemble Time Slice (KNMI–LENTIS) is a large ensemble of global climate model simulations with EC-Earth3. It covers two climate scenarios by focusing on two time slices: the present day (2000–2009) and a future +2 K climate (2075–2084 in the SSP2-4.5 scenario). We have 1600 simulated years for the two climates with (sub-)daily output frequency. The sampled climate variability allows for robust and in-depth research into (compound) extreme events such as heat waves and droughts.
Yi-Chi Wang, Wan-Ling Tseng, Yu-Luen Chen, Shih-Yu Lee, Huang-Hsiung Hsu, and Hsin-Chien Liang
Geosci. Model Dev., 16, 4599–4616,Short summary
This study focuses on evaluating the performance of the Taiwan Earth System Model version 1 (TaiESM1) in simulating the El Niño–Southern Oscillation (ENSO), a significant tropical climate pattern with global impacts. Our findings reveal that TaiESM1 effectively captures several characteristics of ENSO, such as its seasonal variation and remote teleconnections. Its pronounced ENSO strength bias is also thoroughly investigated, aiming to gain insights to improve climate model performance.
Raghul Parthipan, Hannah M. Christensen, J. Scott Hosking, and Damon J. Wischik
Geosci. Model Dev., 16, 4501–4519,Short summary
How can we create better climate models? We tackle this by proposing a data-driven successor to the existing approach for capturing key temporal trends in climate models. We combine probability, allowing us to represent uncertainty, with machine learning, a technique to learn relationships from data which are undiscoverable to humans. Our model is often superior to existing baselines when tested in a simple atmospheric simulation.
Laura J. Wilcox, Robert J. Allen, Bjørn H. Samset, Massimo A. Bollasina, Paul T. Griffiths, James Keeble, Marianne T. Lund, Risto Makkonen, Joonas Merikanto, Declan O'Donnell, David J. Paynter, Geeta G. Persad, Steven T. Rumbold, Toshihiko Takemura, Kostas Tsigaridis, Sabine Undorf, and Daniel M. Westervelt
Geosci. Model Dev., 16, 4451–4479,Short summary
Changes in anthropogenic aerosol emissions have strongly contributed to global and regional climate change. However, the size of these regional impacts and the way they arise are still uncertain. With large changes in aerosol emissions a possibility over the next few decades, it is important to better quantify the potential role of aerosol in future regional climate change. The Regional Aerosol Model Intercomparison Project will deliver experiments designed to facilitate this.
Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang
Geosci. Model Dev., 16, 4331–4366,Short summary
This work presents a novel open-source modeling platform for evaluating future sea level rise (SLR) impacts. Using nearly 10 000 discrete coastline segments around the world, we estimate 21st-century costs for 230 SLR and socioeconomic scenarios. We find that annual end-of-century costs range from USD 100 billion under a 2 °C warming scenario with proactive adaptation to 7 trillion under a 4 °C warming scenario with minimal adaptation, illustrating the cost-effectiveness of coastal adaptation.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313,Short summary
Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Chen Zhang and Tianyu Fu
Geosci. Model Dev., 16, 4315–4329,Short summary
A new automatic calibration toolkit was developed and implemented into the recalibration of a 3-D water quality model, with observations in a wider range of hydrological variability. Compared to the model calibrated with the original strategy, the recalibrated model performed significantly better in modeled total phosphorus, chlorophyll a, and dissolved oxygen. Our work indicates that hydrological variability in the calibration periods has a non-negligible impact on the water quality models.
Camilla Mathison, Eleanor Burke, Andrew J. Hartley, Douglas I. Kelley, Chantelle Burton, Eddy Robertson, Nicola Gedney, Karina Williams, Andy Wiltshire, Richard J. Ellis, Alistair A. Sellar, and Chris D. Jones
Geosci. Model Dev., 16, 4249–4264,Short summary
This paper describes and evaluates a new modelling methodology to quantify the impacts of climate change on water, biomes and the carbon cycle. We have created a new configuration and set-up for the JULES-ES land surface model, driven by bias-corrected historical and future climate model output provided by the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). This allows us to compare projections of the impacts of climate change across multiple impact models and multiple sectors.
Bo Dong, Ross Bannister, Yumeng Chen, Alison Fowler, and Keith Haines
Geosci. Model Dev., 16, 4233–4247,Short summary
Traditional Kalman smoothers are expensive to apply in large global ocean operational forecast and reanalysis systems. We develop a cost-efficient method to overcome the technical constraints and to improve the performance of existing reanalysis products.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
We performed systematic evaluation of clouds simulated in the E3SMv2 to document model performance on clouds and understand what updates in E3SMv2 have caused the changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved primarily due to the re-tuning of cloud macrophysics parameters. This study offers additional insights about clouds simulated in E3SMv2 and will benefit the future E3SM developments.
Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello
Geosci. Model Dev., 16, 4113–4136,Short summary
In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Manuel C. Almeida and Pedro S. Coelho
Geosci. Model Dev., 16, 4083–4112,Short summary
Water temperature (WT) datasets of low-order rivers are scarce. In this study, five different models are used to predict the WT of 83 rivers. Generally, the results show that the models' hyperparameter optimization is essential and that to minimize the prediction error it is relevant to apply all the models considered in this study. Results also show that there is a logarithmic correlation among the error of the predicted river WT and the watershed time of concentration.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Lingcheng Li, Yilin Fang, Zhonghua Zheng, Mingjie Shi, Marcos Longo, Charles D. Koven, Jennifer A. Holm, Rosie A. Fisher, Nate G. McDowell, Jeffrey Chambers, and L. Ruby Leung
Geosci. Model Dev., 16, 4017–4040,Short summary
Accurately modeling plant coexistence in vegetation demographic models like ELM-FATES is challenging. This study proposes a repeatable method that uses machine-learning-based surrogate models to optimize plant trait parameters in ELM-FATES. Our approach significantly improves plant coexistence modeling, thus reducing errors. It has important implications for modeling ecosystem dynamics in response to climate change.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Ocean models struggle to simulate small-scale ocean flows due to the computational cost of high-resolution simulations. Several cost-reducing strategies are applied to simulations of the Southern Ocean and evaluated with respect to observations and traditional, lower-resolution modelling methods. The high-resolution simulations effectively reproduce small-scale flows seen in satellite data and are largely consistent with traditional model simulations regarding their response to climate change.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Irrigation modifies the land surface and soil conditions. The caused effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which is simulating the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Qi Tang, Jean-Christophe Golaz, Luke P. Van Roekel, Mark A. Taylor, Wuyin Lin, Benjamin R. Hillman, Paul A. Ullrich, Andrew M. Bradley, Oksana Guba, Jonathan D. Wolfe, Tian Zhou, Kai Zhang, Xue Zheng, Yunyan Zhang, Meng Zhang, Mingxuan Wu, Hailong Wang, Cheng Tao, Balwinder Singh, Alan M. Rhoades, Yi Qin, Hong-Yi Li, Yan Feng, Yuying Zhang, Chengzhu Zhang, Charles S. Zender, Shaocheng Xie, Erika L. Roesler, Andrew F. Roberts, Azamat Mametjanov, Mathew E. Maltrud, Noel D. Keen, Robert L. Jacob, Christiane Jablonowski, Owen K. Hughes, Ryan M. Forsyth, Alan V. Di Vittorio, Peter M. Caldwell, Gautam Bisht, Renata B. McCoy, L. Ruby Leung, and David C. Bader
Geosci. Model Dev., 16, 3953–3995,Short summary
High-resolution simulations are superior to low-resolution ones in capturing regional climate changes and climate extremes. However, uniformly reducing the grid size of a global Earth system model is too computationally expensive. We provide an overview of the fully coupled regionally refined model (RRM) of E3SMv2 and document a first-of-its-kind set of climate production simulations using RRM at an economic cost. The key to this success is our innovative hybrid time step method.
Anne Marie Treguier, Clement de Boyer Montégut, Alexandra Bozec, Eric P. Chassignet, Baylor Fox-Kemper, Andy McC. Hogg, Doroteaciro Iovino, Andrew E. Kiss, Julien Le Sommer, Yiwen Li, Pengfei Lin, Camille Lique, Hailong Liu, Guillaume Serazin, Dmitry Sidorenko, Qiang Wang, Xiaobio Xu, and Steve Yeager
Geosci. Model Dev., 16, 3849–3872,Short summary
The ocean mixed layer is the interface between the ocean interior and the atmosphere and plays a key role in climate variability. We evaluate the performance of the new generation of ocean models for climate studies, designed to resolve
ocean eddies, which are the largest source of ocean variability and modulate the mixed-layer properties. We find that the mixed-layer depth is better represented in eddy-rich models but, unfortunately, not uniformly across the globe and not in all models.
Duseong S. Jo, Simone Tilmes, Louisa K. Emmons, Siyuan Wang, and Francis Vitt
Geosci. Model Dev., 16, 3893–3906,Short summary
A new simple secondary organic aerosol (SOA) scheme has been developed for the Community Atmosphere Model (CAM) based on the complex SOA scheme in CAM with detailed chemistry (CAM-chem). The CAM with the new SOA scheme shows better agreements with CAM-chem in terms of aerosol concentrations and radiative fluxes, which ensures more consistent results between different compsets in the Community Earth System Model. The new SOA scheme also has technical advantages for future developments.
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808,Short summary
Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Zhe Zhang, Yanping Li, Fei Chen, Phillip Harder, Warren Helgason, James Famiglietti, Prasanth Valayamkunnath, Cenlin He, and Zhenhua Li
Geosci. Model Dev., 16, 3809–3825,Short summary
Crop models incorporated in Earth system models are essential to accurately simulate crop growth processes on Earth's surface and agricultural production. In this study, we aim to model the spring wheat in the Northern Great Plains, focusing on three aspects: (1) develop the wheat model at a point scale, (2) apply dynamic planting and harvest schedules, and (3) adopt a revised heat stress function. The results show substantial improvements and have great importance for agricultural production.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
1. This study present a deep learning architecture MFF to improve the forecast skills of precipitations especially for heavy precipitations. 2. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. 3. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors, so that heavy precipitations are produced.
Abolfazl Simorgh, Manuel Soler, Daniel González-Arribas, Florian Linke, Benjamin Lührs, Maximilian M. Meuser, Simone Dietmüller, Sigrun Matthes, Hiroshi Yamashita, Feijia Yin, Federica Castino, Volker Grewe, and Sabine Baumann
Geosci. Model Dev., 16, 3723–3748,Short summary
This paper addresses the robust climate optimal trajectory planning problem under uncertain meteorological conditions within the structured airspace. Based on the optimization methodology, a Python library has been developed, which can be accessed using the following DOI: https://doi.org/10.5281/zenodo.7121862. The developed tool is capable of providing robust trajectories taking into account all probable realizations of meteorological conditions provided by an EPS computationally very fast.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio Bento, and Angelina Bushenkova
Geosci. Model Dev. Discuss.,
Revised manuscript accepted for GMDShort summary
This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data, and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Matteo Willeit, Tatiana Ilyina, Bo Liu, Christoph Heinze, Mahé Perrette, Malte Heinemann, Daniela Dalmonech, Victor Brovkin, Guy Munhoven, Janine Börker, Jens Hartmann, Gibran Romero-Mujalli, and Andrey Ganopolski
Geosci. Model Dev., 16, 3501–3534,Short summary
In this paper we present the carbon cycle component of the newly developed fast Earth system model CLIMBER-X. The model can be run with interactive atmospheric CO2 to investigate the feedbacks between climate and the carbon cycle on temporal scales ranging from decades to > 100 000 years. CLIMBER-X is expected to be a useful tool for studying past climate–carbon cycle changes and for the investigation of the long-term future evolution of the Earth system.
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.
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.
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
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
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.
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.
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
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.
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
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.
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
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.
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
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
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
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
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.
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
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
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.
Zou, H.: The Adaptive Lasso and its Oracle Properties, J. Am. Stat. Assoc., 101, 1418–1429, 2006. a
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...