Articles | Volume 7, issue 4
Research article 02 Nov 2016
Research article | 02 Nov 2016
A user-friendly earth system model of low complexity: the ESCIMO system dynamics model of global warming towards 2100
Jorgen Randers et al.
No articles found.
Zebedee R. J. Nicholls, Malte Meinshausen, Jared Lewis, Robert Gieseke, Dietmar Dommenget, Kalyn Dorheim, Chen-Shuo Fan, Jan S. Fuglestvedt, Thomas Gasser, Ulrich Golüke, Philip Goodwin, Corinne Hartin, Austin P. Hope, Elmar Kriegler, Nicholas J. Leach, Davide Marchegiani, Laura A. McBride, Yann Quilcaille, Joeri Rogelj, Ross J. Salawitch, Bjørn H. Samset, Marit Sandstad, Alexey N. Shiklomanov, Ragnhild B. Skeie, Christopher J. Smith, Steve Smith, Katsumasa Tanaka, Junichi Tsutsui, and Zhiang Xie
Geosci. Model Dev., 13, 5175–5190,Short summary
Computational limits mean that we cannot run our most comprehensive climate models for all applications of interest. In such cases, reduced complexity models (RCMs) are used. Here, researchers working on 15 different models present the first systematic community effort to evaluate and compare RCMs: the Reduced Complexity Model Intercomparison Project (RCMIP). Our research ensures that users of RCMs can more easily evaluate the strengths, weaknesses and limitations of their tools.
Related subject area
Dynamics of the Earth system: modelsSpace–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generatorFirst assessment of the earth heat inventory within CMIP5 historical simulationsThe thermal response of small and shallow lakes to climate change: new insights from 3D hindcast modellingLabrador Sea subsurface density as a precursor of multidecadal variability in the North Atlantic: a multi-model studyHow modelling paradigms affect simulated future land use changeClimate controlled root zone parameters show potential to improve water flux simulations by land surface modelsIdentifying meteorological drivers of extreme impacts: an application to simulated crop yieldsSimulating compound weather extremes responsible for critical crop failure with stochastic weather generatorsCharacterisation of Atlantic meridional overturning hysteresis using Langevin dynamicsNet land-use change carbon flux estimates and sensitivities – An assessment with a bookkeeping model based on CMIP6 forcingEvaluating the dependence structure of compound precipitation and wind speed extremesFuture sea level contribution from Antarctica inferred from CMIP5 model forcing and its dependence on precipitation ansatzThe extremely warm summer of 2018 in Sweden – set in a historical contextClimate Change Projections of Terrestrial Primary Productivity over the Hindu Kush Himalayan ForestsEffect of changing ocean circulation on deep ocean temperature in the last millenniumHow large does a large ensemble need to be?Reconstructing coupled time series in climate systems using three kinds of machine-learning methodsAn investigation of weighting schemes suitable for incorporating large ensembles into multi-model ensemblesWhat could we learn about climate sensitivity from variability in the surface temperature record?Using a nested single-model large ensemble to assess the internal variability of the North Atlantic Oscillation and its climatic implications for central EuropeClimate change in a conceptual atmosphere–phytoplankton modelVariability of surface climate in simulations of past and futureStatistical estimation of global surface temperature response to forcing under the assumption of temporal scalingEmulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on landA global semi-empirical glacial isostatic adjustment (GIA) model based on Gravity Recovery and Climate Experiment (GRACE) dataImprovement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolutionSocietal breakdown as an emergent property of large-scale behavioural models of land use changeImproving weather and climate predictions by training of supermodelsEvaluating climate emulation: fundamental impulse testing of simple climate modelsMaximum power of saline and fresh water mixing in estuariesTipping the ENSO into a permanent El Niño can trigger state transitions in global terrestrial ecosystemsContributions of climate change and groundwater extraction to soil moisture trendsDownslope windstorms in the Isthmus of Tehuantepec during Tehuantepecer events: a numerical study with WRF high-resolution simulationsA radiative-convective model based on constrained maximum entropy productionESD Ideas: Propagation of high-frequency forcing to ice age dynamicsDevelopment and prospects of the regional MiKlip decadal prediction system over Europe: predictive skill, added value of regionalization, and ensemble size dependencyClimatological moisture sources for the Western North American Monsoon through a Lagrangian approach: their influence on precipitation intensityThe effect of univariate bias adjustment on multivariate hazard estimatesLight absorption by marine cyanobacteria affects tropical climate mean state and variabilitySensitivity study of the regional climate model RegCM4 to different convective schemes over West AfricaSimulation of observed climate changes in 1850–2014 with climate model INM-CM5A theoretical approach to assess soil moisture–climate coupling across CMIP5 and GLACE-CMIP5 experimentsImproving the representation of anthropogenic CO2 emissions in climate models: impact of a new parameterization for the Community Earth System Model (CESM)A theory of Pleistocene glacial rhythmicityUsing network theory and machine learning to predict El NiñoModelling feedbacks between human and natural processes in the land systemTagging moisture sources with Lagrangian and inertial tracers: application to intense atmospheric river eventsImpacts of climate change and climate extremes on major crops productivity in China at a global warming of 1.5 and 2.0 °CAnalytically tractable climate–carbon cycle feedbacks under 21st century anthropogenic forcingSensitivity of the tropical climate to an interhemispheric thermal gradient: the role of tropical ocean dynamics
Manuela I. Brunner, Eric Gilleland, and Andrew W. Wood
Earth Syst. Dynam., 12, 621–634,Short summary
Compound hot and dry events can lead to severe impacts whose severity may depend on their timescale and spatial extent. Here, we show that the spatial extent and timescale of compound hot–dry events are strongly related, spatial compound event extents are largest at sub-seasonal timescales, and short events are driven more by high temperatures, while longer events are more driven by low precipitation. Future climate impact studies should therefore be performed at different timescales.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, and Joel Finnis
Earth Syst. Dynam., 12, 581–600,Short summary
The current radiative imbalance at the top of the atmosphere is increasing the heat stored in the oceans, atmosphere, continental subsurface and cryosphere, with consequences for societies and ecosystems (e.g. sea level rise). We performed the first assessment of the ability of global climate models to represent such heat storage in the climate subsystems. Models are able to reproduce the observed atmosphere heat content, with biases in the simulation of heat content in the rest of components.
Francesco Piccioni, Céline Casenave, Bruno Jacques Lemaire, Patrick Le Moigne, Philippe Dubois, and Brigitte Vinçon-Leite
Earth Syst. Dynam., 12, 439–456,Short summary
Small lakes are ecosystems highly impacted by climate change. Here, the thermal regime of a small, shallow lake over the past six decades was reconstructed via 3D modelling. Significant changes were found: strong water warming in spring and summer (0.7 °C/decade) as well as increased stratification and thermal energy for cyanobacteria growth, especially in spring. The strong spatial patterns detected for stratification might create local conditions particularly favourable to cyanobacteria bloom.
Pablo Ortega, Jon I. Robson, Matthew Menary, Rowan T. Sutton, Adam Blaker, Agathe Germe, Jöel J.-M. Hirschi, Bablu Sinha, Leon Hermanson, and Stephen Yeager
Earth Syst. Dynam., 12, 419–438,Short summary
Deep Labrador Sea densities are receiving increasing attention because of their link to many of the processes that govern decadal climate oscillations in the North Atlantic and their potential use as a precursor of those changes. This article explores those links and how they are represented in global climate models, documenting the main differences across models. Models are finally compared with observational products to identify the ones that reproduce the links more realistically.
Calum Brown, Ian Holman, and Mark Rounsevell
Earth Syst. Dynam., 12, 211–231,Short summary
The variety of human and natural processes in the land system can be modelled in many different ways. However, little is known about how and why basic model assumptions affect model results. We compared two models that represent land use in completely distinct ways and found several results that differed greatly. We identify the main assumptions that caused these differences and therefore key issues that need to be addressed for more robust model development.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam. Discuss.,
Revised manuscript accepted for ESDShort summary
The roots of vegetation largely control the Earth's water cycle by transporting water from the subsurface to the atmosphere, but are not adequately represented in land surface models, causing uncertainties in modeled water fluxes. We replaced the root parameters in an existing model with more realistic ones that account for a climate control on root development, and found an improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Johannes Vogel, Pauline Rivoire, Cristina Deidda, Leila Rahimi, Christoph A. Sauter, Elisabeth Tschumi, Karin van der Wiel, Tianyi Zhang, and Jakob Zscheischler
Earth Syst. Dynam., 12, 151–172,Short summary
We present a statistical approach for automatically identifying multiple drivers of extreme impacts based on LASSO regression. We apply the approach to simulated crop failure in the Northern Hemisphere and identify which meteorological variables including climate extreme indices and which seasons are relevant to predict crop failure. The presented approach can help unravel compounding drivers in high-impact events and could be applied to other impacts such as wildfires or flooding.
Peter Pfleiderer, Aglaé Jézéquel, Juliette Legrand, Natacha Legrix, Iason Markantonis, Edoardo Vignotto, and Pascal Yiou
Earth Syst. Dynam., 12, 103–120,Short summary
In 2016, northern France experienced an unprecedented wheat crop loss. This crop loss was likely due to an extremely warm December 2015 and abnormally high precipitation during the following spring season. Using stochastic weather generators we investigate how severe the metrological conditions leading to the crop loss could be in current climate conditions. We find that December temperatures were close to the plausible maximum but that considerably wetter springs would be possible.
Jelle van den Berk, Sybren Drijfhout, and Wilco Hazeleger
Earth Syst. Dynam., 12, 69–81,Short summary
A collapse of the Atlantic Meridional Overturning Circulation can be described by six parameters and Langevin dynamics. These parameters can be determined from collapses seen in climate models of intermediate complexity. With this parameterisation, it might be possible to estimate how much fresh water is needed to observe a collapse in more complicated models and reality.
Kerstin Hartung, Ana Bastos, Louise Chini, Raphael Ganzenmüller, Felix Havermann, George C. Hurtt, Tammas Loughran, Julia E. M. S. Nabel, Tobias Nützel, Wolfgang A. Obermeier, and Julia Pongratz
Earth Syst. Dynam. Discuss.,
Revised manuscript accepted for ESDShort summary
In this study, we model the relative importance of several contributors to the land-use and land-cover change (LULCC) flux based on a LULCC dataset including uncertainty estimates. The uncertainty of LULCC is as relevant as applying wood harvest and gross transitions for the cumulative LULCC flux over the industrial period. However, LULCC uncertainty matters less than the other two factors for the LULCC flux in 2014; historical LULCC uncertainty is negligible for estimates of future scenarios.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16,Short summary
Compound extremes such as heavy precipitation and extreme winds can lead to large damage. To date it is unclear how well climate models represent such compound extremes. Here we present a new measure to assess differences in the dependence structure of bivariate extremes. This measure is applied to assess differences in the dependence of compound precipitation and wind extremes between three model simulations and one reanalysis dataset in a domain in central Europe.
Christian B. Rodehacke, Madlene Pfeiffer, Tido Semmler, Özgür Gurses, and Thomas Kleiner
Earth Syst. Dynam., 11, 1153–1194,Short summary
In the warmer future, Antarctica's ice sheet will lose more ice due to enhanced iceberg calving and a warming ocean that melts more floating ice from below. However, the hydrological cycle is also stronger in a warmer world. Hence, more snowfall will precipitate on Antarctica and may balance the amplified ice loss. We have used future climate scenarios from various global climate models to perform numerous ice sheet simulations to show that precipitation may counteract mass loss.
Renate Anna Irma Wilcke, Erik Kjellström, Changgui Lin, Daniela Matei, Anders Moberg, and Evangelos Tyrlis
Earth Syst. Dynam., 11, 1107–1121,Short summary
Two long-lasting high-pressure systems in summer 2018 led to heat waves over Scandinavia and an extended summer period with devastating impacts on both agriculture and human life. Using five climate model ensembles, the unique 263-year Stockholm temperature time series and a composite 150-year time series for the whole of Sweden, we found that anthropogenic climate change has strongly increased the probability of a warm summer, such as the one observed in 2018, occurring in Sweden.
Halima Usman, Thomas A. M. Pugh, Anders Ahlström, and Sofia Baig
Earth Syst. Dynam. Discuss.,
Revised manuscript accepted for ESDShort summary
The study assesses the impacts of climate change on forest productivity in the Hindu Kush Himalayan region. LPJ-GUESS was simulated from 1850–2100. In first approach, the model was compared with observational estimates. The comparison showed a moderate to weak agreement. In the second approach, the model was assessed for the temporal and spatial trends of net biome productivity and carbon pool. A reduction was found from 1951–2005 however, increase in both variables were predicted in 2100.
Jeemijn Scheen and Thomas F. Stocker
Earth Syst. Dynam., 11, 925–951,Short summary
Variability of sea surface temperatures (SST) in 1200–2000 CE is quite well-known, but the history of deep ocean temperatures is not. Forcing an ocean model with these SSTs, we simulate temperatures in the ocean interior. The circulation changes alter the amplitude and timing of deep ocean temperature fluctuations below 2 km depth, e.g. delaying the atmospheric signal by ~ 200 years in the deep Atlantic. Thus ocean circulation changes are shown to be as important as SST changes at these depths.
Sebastian Milinski, Nicola Maher, and Dirk Olonscheck
Earth Syst. Dynam., 11, 885–901,Short summary
Initial-condition large ensembles with ensemble sizes ranging from 30 to 100 members have become a commonly used tool to quantify the forced response and internal variability in various components of the climate system, but there is no established method to determine the required ensemble size for a given problem. We propose a new framework that can be used to estimate the required ensemble size from a model's control run or an existing large ensemble.
Yu Huang, Lichao Yang, and Zuntao Fu
Earth Syst. Dynam., 11, 835–853,Short summary
We investigate the applicability of machine learning (ML) on time series reconstruction and find that the dynamical coupling relation and nonlinear causality are crucial for the application of ML. Our results could provide insights into causality and ML approaches for paleoclimate reconstruction, parameterization schemes, and prediction in climate studies.
Anna Louise Merrifield, Lukas Brunner, Ruth Lorenz, Iselin Medhaug, and Reto Knutti
Earth Syst. Dynam., 11, 807–834,Short summary
Justifiable uncertainty estimates of future change in northern European winter and Mediterranean summer temperature can be obtained by weighting a multi-model ensemble comprised of projections from different climate models and multiple projections from the same climate model. Weights reduce the influence of model biases and handle dependence by identifying a projection's model of origin from historical characteristics; contributions from the same model are scaled by the number of members.
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, and Bjorn Stevens
Earth Syst. Dynam., 11, 709–719,Short summary
In this paper we explore the potential of variability for constraining the equilibrium response of the climate system to external forcing. We show that the constraint is inherently skewed, with a long tail to high sensitivity, and that while the variability may contain some useful information, it is unlikely to generate a tight constraint.
Andrea Böhnisch, Ralf Ludwig, and Martin Leduc
Earth Syst. Dynam., 11, 617–640,Short summary
North Atlantic air pressure variations influencing European climate variables are simulated in coarse-resolution global climate models (GCMs). As single-model runs do not sufficiently describe variations of their patterns, several model runs with slightly diverging initial conditions are analyzed. The study shows that GCM and regional climate model (RCM) patterns vary in a similar range over the same domain, while RCMs add consistent fine-scale information due to their higher spatial resolution.
György Károlyi, Rudolf Dániel Prokaj, István Scheuring, and Tamás Tél
Earth Syst. Dynam., 11, 603–615,Short summary
We construct a conceptual model to understand the interplay between the atmosphere and the ocean biosphere in a climate change framework, including couplings between extraction of carbon dioxide by phytoplankton and climate change, temperature and carrying capacity of phytoplankton, and wind energy and phytoplankton production. We find that sufficiently strong mixing can result in decaying global phytoplankton content.
Kira Rehfeld, Raphaël Hébert, Juan M. Lora, Marcus Lofverstrom, and Chris M. Brierley
Earth Syst. Dynam., 11, 447–468,Short summary
Under continued anthropogenic greenhouse gas emissions, it is likely that global mean surface temperature will continue to increase. Little is known about changes in climate variability. We analyze surface climate variability and compare it to mean change in colder- and warmer-than-present climate model simulations. In most locations, but not on subtropical land, simulated temperature variability up to decadal timescales decreases with mean temperature, and precipitation variability increases.
Eirik Myrvoll-Nilsen, Sigrunn Holbek Sørbye, Hege-Beate Fredriksen, Håvard Rue, and Martin Rypdal
Earth Syst. Dynam., 11, 329–345,Short summary
This paper presents efficient Bayesian methods for linear response models of global mean surface temperature that take into account long-range dependence. We apply the methods to the instrumental temperature record and historical model runs in the CMIP5 ensemble to provide estimates of the transient climate response and temperature projections under the Representative Concentration Pathways.
Lea Beusch, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 11, 139–159,Short summary
Earth system models (ESMs) are invaluable to study the climate system but expensive to run. Here, we present a statistical tool which emulates ESMs at a negligible computational cost by creating stochastic realizations of yearly land temperature field time series. Thereby, 40 ESMs are considered, and for each ESM, a single simulation is required to train the tool. The resulting ESM-specific realizations closely resemble ESM simulations not employed during training at point to regional scales.
Yu Sun and Riccardo E. M. Riva
Earth Syst. Dynam., 11, 129–137,Short summary
The solid Earth is still deforming because of the effect of past ice sheets through glacial isostatic adjustment (GIA). Satellite gravity observations by the Gravity Recovery and Climate Experiment (GRACE) mission are sensitive to those signals but are superimposed on the redistribution effect of water masses by the hydrological cycle. We propose a method separating the two signals, providing new constraints for forward GIA models and estimating the global water cycle's patterns and magnitude.
Mareike Schuster, Jens Grieger, Andy Richling, Thomas Schartner, Sebastian Illing, Christopher Kadow, Wolfgang A. Müller, Holger Pohlmann, Stephan Pfahl, and Uwe Ulbrich
Earth Syst. Dynam., 10, 901–917,Short summary
Decadal climate predictions are valuable to society as they allow us to estimate climate conditions several years in advance. We analyze the latest version of the German MiKlip prediction system (https://www.fona-miklip.de) and assess the effect of the model resolution on the skill of the system. The increase in the resolution of the system reduces the bias and significantly improves the forecast skill for North Atlantic extratropical winter dynamics for lead times of two to five winters.
Calum Brown, Bumsuk Seo, and Mark Rounsevell
Earth Syst. Dynam., 10, 809–845,Short summary
Concerns are growing that human activity will lead to social and environmental breakdown, but it is hard to anticipate when and where such breakdowns might occur. We developed a new model of land management decisions in Europe to explore possible future changes and found that decision-making that takes into account social and environmental conditions can produce unexpected outcomes that include societal breakdown in challenging conditions.
Francine Schevenhoven, Frank Selten, Alberto Carrassi, and Noel Keenlyside
Earth Syst. Dynam., 10, 789–807,Short summary
Weather and climate predictions potentially improve by dynamically combining different models into a
supermodel. A crucial step is to train the supermodel on the basis of observations. Here, we apply two different training methods to the global atmosphere–ocean–land model SPEEDO. We demonstrate that both training methods yield climate and weather predictions of superior quality compared to the individual models. Supermodel predictions can also outperform the commonly used multi-model mean.
Adria K. Schwarber, Steven J. Smith, Corinne A. Hartin, Benjamin Aaron Vega-Westhoff, and Ryan Sriver
Earth Syst. Dynam., 10, 729–739,Short summary
Simple climate models (SCMs) underlie many important scientific and decision-making endeavors. This illustrates the need for their use to be rooted in a clear understanding of their fundamental responses. In this study, we provide a comprehensive assessment of model performance by evaluating the fundamental responses of several SCMs. We find biases in some responses, which have implications for decision science. We conclude by recommending a standard set of validation tests for any SCM.
Zhilin Zhang and Hubert Savenije
Earth Syst. Dynam., 10, 667–684,Short summary
Natural systems evolve towards a state of maximum power, including estuarine circulation. The energy of lighter fresh water drives circulation, while it dissipates by friction. This rotational flow causes the spread of salinity, which is represented by the dispersion coefficient. In this paper, the maximum power concept provides a new equation for this coefficient. Together with the steady-state equation, this results in a new analytical model for density-driven salinity intrusion.
Mateo Duque-Villegas, Juan Fernando Salazar, and Angela Maria Rendón
Earth Syst. Dynam., 10, 631–650,Short summary
Earth's climate can be studied as a system with different components that can be strongly altered by human influence. One possibility is that the El Niño phenomenon becomes more frequent. We investigated the potential impacts of the most frequent El Niño: a permanent one. The most noticeable impacts include variations in global water availability and vegetation productivity, potential dieback of the Amazon rainforest, greening of western North America, and further aridification of Australia.
Longhuan Wang, Zhenghui Xie, Binghao Jia, Jinbo Xie, Yan Wang, Bin Liu, Ruichao Li, and Si Chen
Earth Syst. Dynam., 10, 599–615,Short summary
We quantify the contributions of climate change and groundwater extraction to the trends in soil moisture through two groups of simulations. In summary, climate change dominates the soil moisture trends, while GW extraction accelerates or decelerates soil moisture trends under climate change. This work will improve our understanding of how human activities affect soil water content and will help to determine the mechanisms underlying the global water cycle.
Miguel A. Prósper, Ian Sosa Tinoco, Carlos Otero-Casal, and Gonzalo Miguez-Macho
Earth Syst. Dynam., 10, 485–499,Short summary
We study the fine-scale structure of Tehuano winds in the Isthmus of Tehuantepec, focusing on the flow beyond the well-known strong gap wind jet. We use high-resolution WRF model simulations to show that different downslope windstorm conditions and hydraulic jumps with rotor circulations develop in the mountains east of Chivela Pass depending on crest height and thermodynamic conditions of the air mass. The intense turbulent flows can have a large impact on the existent wind farms in the region.
Vincent Labarre, Didier Paillard, and Bérengère Dubrulle
Earth Syst. Dynam., 10, 365–378,Short summary
We tried to represent atmospheric convection induced by radiative forcing with a simple climate model based on maximum entropy production. Contrary to previous models, we give a minimal description of energy transport in the atmosphere. It allows us to give better results in terms of temperature and vertical energy flux profiles.
Mikhail Y. Verbitsky, Michel Crucifix, and Dmitry M. Volobuev
Earth Syst. Dynam., 10, 257–260,Short summary
We demonstrate here that nonlinear character of ice sheet dynamics, which was derived naturally from the conservation laws, is an effective means for propagating high-frequency forcing upscale.
Mark Reyers, Hendrik Feldmann, Sebastian Mieruch, Joaquim G. Pinto, Marianne Uhlig, Bodo Ahrens, Barbara Früh, Kameswarrao Modali, Natalie Laube, Julia Moemken, Wolfgang Müller, Gerd Schädler, and Christoph Kottmeier
Earth Syst. Dynam., 10, 171–187,Short summary
In this study, the regional MiKlip decadal prediction system is evaluated. This system has been established to deliver highly resolved forecasts for the timescale of 1 to 10 years for Europe. Evidence of the general potential for regional decadal predictability for the variables temperature, precipitation, and wind speed is provided, but the performance of the prediction system depends on region, variable, and system generation.
Paulina Ordoñez, Raquel Nieto, Luis Gimeno, Pedro Ribera, David Gallego, Carlos Abraham Ochoa-Moya, and Arturo Ignacio Quintanar
Earth Syst. Dynam., 10, 59–72,Short summary
The identification of moisture sources for a region is of prominent importance regarding the characterization of precipitation. In this work, the moisture sources for the western North American monsoon (WNAM) region are identified; these sources are the Gulf of California, the WNAM itself, eastern Mexico and the Caribbean Sea. We find that rainfall intensity over the WNAM region is related to the amount of moisture transported from the Caribbean Sea and eastern Mexico during the preceding days.
Jakob Zscheischler, Erich M. Fischer, and Stefan Lange
Earth Syst. Dynam., 10, 31–43,Short summary
Many climate models have biases in different variables throughout the world. Adjusting these biases is necessary for estimating climate impacts. Here we demonstrate that widely used univariate bias adjustment methods do not work well for multivariate impacts. We illustrate this problem using fire risk and heat stress as impact indicators. Using an approach that adjusts not only biases in the individual climate variables but also biases in the correlation between them can resolve these problems.
Hanna Paulsen, Tatiana Ilyina, Johann H. Jungclaus, Katharina D. Six, and Irene Stemmler
Earth Syst. Dynam., 9, 1283–1300,Short summary
We use an Earth system model to study the effects of light absorption by marine cyanobacteria on climate. We find that cyanobacteria have a considerable cooling effect on tropical SST with implications for ocean and atmosphere circulation patterns as well as for climate variability. The results indicate the importance of considering phytoplankton light absorption in climate models, and specifically highlight the role of cyanobacteria due to their regulative effect on tropical SST and climate.
Brahima Koné, Arona Diedhiou, N'datchoh Evelyne Touré, Mouhamadou Bamba Sylla, Filippo Giorgi, Sandrine Anquetin, Adama Bamba, Adama Diawara, and Arsene Toka Kobea
Earth Syst. Dynam., 9, 1261–1278,Short summary
Simulations of regional climate are very sensitive to physical parameterization schemes, particularly over the tropics where convection plays a major role in monsoon dynamics. The latest version of RegCM4 was used to assess the performance and sensitivity of the simulated West African climate system to different convection schemes. The configuration of RegCM4 with CLM4.5 as a land surface model and the Emanuel convective scheme is recommended for the study of the West African climate.
Evgeny Volodin and Andrey Gritsun
Earth Syst. Dynam., 9, 1235–1242,Short summary
Climate changes of 1850–2014 are modeled with the climate model INM-CM5. Periods of fast warming in 1920–1940 and 1980–2000 as well as its slowdown in 1950–1975 and 2000–2014 are correctly reproduced by the model. The notable improvement with respect to the previous model version is the correct reproduction of slowdowns in global warming that we attribute to a new aerosol block in the model and a more accurate description of the solar constant in the new (CMIP6) IPCC protocol.
Clemens Schwingshackl, Martin Hirschi, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 1217–1234,Short summary
Changing amounts of water in the soil can have a strong impact on atmospheric temperatures. We present a theoretical approach that can be used to quantify the effect that soil moisture has on temperature and validate it using climate model simulations in which soil moisture is prescribed. This theoretical approach also allows us to study the soil moisture effect on temperature in standard climate models, even if they do not provide dedicated soil moisture simulations.
Andrés Navarro, Raúl Moreno, and Francisco J. Tapiador
Earth Syst. Dynam., 9, 1045–1062,Short summary
Earth system models provide simplified accounts of human–Earth interactions. Most current models treat CO2 emissions as a homogeneously distributed forcing. However, this paper presents a new parameterization, POPEM (POpulation Parameterization for Earth Models), that computes anthropogenic CO2 emissions at a grid point scale. A major advantage of this approach is the increased capacity to understand the potential effects of localized pollutant emissions on long-term global climate statistics.
Mikhail Y. Verbitsky, Michel Crucifix, and Dmitry M. Volobuev
Earth Syst. Dynam., 9, 1025–1043,Short summary
Using a dynamical climate model purely reduced from the conservation laws of ice-moving media, we show that ice-sheet physics coupled with a linear climate temperature feedback conceal enough dynamics to satisfactorily explain the system response over the full Pleistocene. There is no need, a priori, to call for a nonlinear response of, for example, the carbon cycle.
Peter D. Nooteboom, Qing Yi Feng, Cristóbal López, Emilio Hernández-García, and Henk A. Dijkstra
Earth Syst. Dynam., 9, 969–983,Short summary
The prediction of the El Niño phenomenon, an increased sea surface temperature in the eastern Pacific, fascinates people for a long time. El Niño is associated with natural disasters, such as droughts and floods. Current methods can make a reliable prediction of this phenomenon up to 6 months ahead. However, this article presents a method which combines network theory and machine learning which predicts El Niño up to 1 year ahead.
Derek T. Robinson, Alan Di Vittorio, Peter Alexander, Almut Arneth, C. Michael Barton, Daniel G. Brown, Albert Kettner, Carsten Lemmen, Brian C. O'Neill, Marco Janssen, Thomas A. M. Pugh, Sam S. Rabin, Mark Rounsevell, James P. Syvitski, Isaac Ullah, and Peter H. Verburg
Earth Syst. Dynam., 9, 895–914,Short summary
Understanding the complexity behind the rapid use of Earth’s resources requires modelling approaches that couple human and natural systems. We propose a framework that comprises the configuration, frequency of interaction, and coordination of communication between models along with eight lessons as guidelines to increase the success of coupled human–natural systems modelling initiatives. We also suggest a way to expedite model coupling and increase the longevity and interoperability of models.
Vicente Pérez-Muñuzuri, Jorge Eiras-Barca, and Daniel Garaboa-Paz
Earth Syst. Dynam., 9, 785–795,Short summary
Two Lagrangian tracer tools are evaluated for studies on atmospheric moisture sources and pathways. Usual Lagrangian methods consider the initial moisture volume to remain constant and the particle to follow flow path lines exactly. In a different approach, the initial volume can be considered to depend on time as it is advected by the flow due to thermodynamic processes. Drag and buoyancy forces must then be considered.
Yi Chen, Zhao Zhang, and Fulu Tao
Earth Syst. Dynam., 9, 543–562,Short summary
We evaluated the effects of warming scenarios (1.5 and 2.0˚C) on the production of maize, wheat and rice in China using MCWLA models and four global climate models. Results showed that the warming scenarios would bring more opportunities than risks for food security in China. A 2.0˚C warming would lead to larger variability of crop yield but less probability of crop yield decrease than 1.5˚C warming. More attention should be paid to adaptations to the expected increase in extreme event impacts.
Steven J. Lade, Jonathan F. Donges, Ingo Fetzer, John M. Anderies, Christian Beer, Sarah E. Cornell, Thomas Gasser, Jon Norberg, Katherine Richardson, Johan Rockström, and Will Steffen
Earth Syst. Dynam., 9, 507–523,Short summary
Around half of the carbon that humans emit into the atmosphere each year is taken up on land (by trees) and in the ocean (by absorption). We construct a simple model of carbon uptake that, unlike the complex models that are usually used, can be analysed mathematically. Our results include that changes in atmospheric carbon may affect future carbon uptake more than changes in climate. Our simple model could also study mechanisms that are currently too uncertain for complex models.
Stefanie Talento and Marcelo Barreiro
Earth Syst. Dynam., 9, 285–297,Short summary
In a series of simulations, with models of different complexity, we analyse the role of the tropical ocean dynamics in the transmission of information when an extratropical thermal forcing is imposed. In terms of annual means we find that the tropical ocean dynamics oppose the remote extratropical signal. However, changes in the sea surface temperature seasonal cycle in the equatorial Pacific Ocean become significant only once the tropical ocean dynamics are incorporated.
Akbari, H., Matthews, H. D., and Seto, D.: The long-term effect of increasing the albedo of urban areas, Environ. Res. Lett., 7, 024004, https://doi.org/10.1088/1748-9326/7/2/024004, 2012.
Bates, N. R., Best, M. H. P., Neely, K., Garley, R., Dickson, A. G., and Johnson, R. J.: Detecting anthropogenic carbon dioxide uptake and ocean acidification in the North Atlantic Ocean, Biogeosciences, 9, 2509–2522, https://doi.org/10.5194/bg-9-2509-2012, 2012.
Church, J. A. and White, N. J.: Sea-Level Rise from the Late 19th to the Early 21st Century, Surv. Geophys., 32, 585–602, https://doi.org/10.1007/s10712-011-9119-1, 2011.
CMIP5 scenario runs: http://climexp.knmi.nl/selectfield_cmip5.cgi?id=someone@somewhere (last access: 27 October 2016), 2015.
C-ROADS: https://www.climateinteractive.org/tools/c-roads/, last access: 11 November 2015.
Dore, J. E., Lukas, R., Sadler, D. W., Church, M. J., and Karl, D. M.: Physical and biogeochemical modulation of ocean acidification in the central North Pacific, P. Natl. Acad. Sci. USA, 106, 12235–12240, 2009.
Eschenbach, W.: CMIP5 Model Temperature Results in Excel: WUWT 2014, updated 22 December, available from: http://wattsupwiththat.com/2014/12/22/cmip5-model-temperature-results-in-excel/ (last access: 27 October 2016), 2014.
FAO: Global Forest Resources Assessment 2015, Desk reference, Food and Agriculture Organization of The United Nations, Rome, 2015.
Gaffin, S., Imhoff, M., Rosenzweig, C., Khanbilvardi, R., Pasqualini, A., Kong, A. Y., Grillo, D., Freed, A., Hillel, D., and Hartung, E.: Bright is the new black – multi-year performance of high-albedo roofs in an urban climate, Environ. Res. Lett., 7, 014029, https://doi.org/10.1088/1748-9326/7/1/014029, 2012.
Hansen, J., Ruedy, R., Sato, M., and Lo, K.: Global surface temperature change, Rev. Geophys., 48, RG4004, https://doi.org/10.1029/2010RG000345, 2010.
Haszeldine, R. S.: Carbon capture and storage: how green can black be?, Science, 325, 1647–1652, 2009.
Holtsmark, B.: Harvesting in boreal forests and the biofuel carbon debt, Climatic Change, 112, 415–428, 2012.
IPCC: Climate Change 2013: The Physical Science Basis, in: Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge, UK and New York, NY, USA, 1535 pp., https://doi.org/10.1017/CBO9781107415324, 2013.
Irvine, P. and Ridgwell, A.: 'Geoengineering' – taking control of our planet's climate, Sci. Progr., 92, 139–162, 2009.
Jamieson, D.: Some whats, whys and worries of geoengineering, Climatic Change, 121, 527–537, 2013.
Le Quéré, C., Moriarty, R., Andrew, R. M., Canadell, J. G., Sitch, S., Korsbakken, J. I., Friedlingstein, P., Peters, G. P., Andres, R. J., Boden, T. A., Houghton, R. A., House, J. I., Keeling, R. F., Tans, P., Arneth, A., Bakker, D. C. E., Barbero, L., Bopp, L., Chang, J., Chevallier, F., Chini, L. P., Ciais, P., Fader, M., Feely, R. A., Gkritzalis, T., Harris, I., Hauck, J., Ilyina, T., Jain, A. K., Kato, E., Kitidis, V., Klein Goldewijk, K., Koven, C., Landschützer, P., Lauvset, S. K., Lefèvre, N., Lenton, A., Lima, I. D., Metzl, N., Millero, F., Munro, D. R., Murata, A., Nabel, J. E. M. S., Nakaoka, S., Nojiri, Y., O'Brien, K., Olsen, A., Ono, T., Pérez, F. F., Pfeil, B., Pierrot, D., Poulter, B., Rehder, G., Rödenbeck, C., Saito, S., Schuster, U., Schwinger, J., Séférian, R., Steinhoff, T., Stocker, B. D., Sutton, A. J., Takahashi, T., Tilbrook, B., van der Laan-Luijkx, I. T., van der Werf, G. R., van Heuven, S., Vandemark, D., Viovy, N., Wiltshire, A., Zaehle, S., and Zeng, N.: Global Carbon Budget 2015, Earth Syst. Sci. Data, 7, 349–396, https://doi.org/10.5194/essd-7-349-2015, 2015.
Levitus, S., Antonov, J. I., Boyer, T. P., Baranova, O. K., Garcia, H. E., Locarnini, R. A., Mishonov, A. V., Reagan, J. R., Seidov, D., Yarosh, E. S., and Zweng, M. M.: World ocean heat content and thermosteric sea level change (0–2000 m), 1955–2010, Geophys. Res. Lett., 39, L10603, https://doi.org/10.1029/2012GL051106, 2012.
Martin, C.: On the Edge: The State and Fate of the World's Tropical Rainforests, Greystone, Canada, 2015.
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J.-F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K., Thomson, A., Velders, G. J. M., and Vuuren, D. P. P.: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300, Climatic Change, 109, 213–241, https://doi.org/10.1007/s10584-011-0156-z, 2011.
Mouginot, J., Rignot, E., Scheuchl, B., Fenty, I., Khazendar, A., Morlighem, M., Buzzi, A., and Paden, J.: Fast retreat of Zachariæ Isstrøm, northeast Greenland, Science, 11, 1357–1361, https://doi.org/10.1126/science.aac7111, 2015.
NOAA: GHCN-Monthly Version 3: http://www.ncdc.noaa.gov/ghcnm/v3.php (last access: 27 October 2016), 2015a.
NOAA: Climate at a Glance: http://www.ncdc.noaa.gov/cag/time-series/global (last access: 27 October 2016), 2015b.
Randers, J.: 2052: A Global Forecast for the Next Forty Years, Club of Rome, Chelsea Green Publishing, Chelsea, http://www.2052.info/ (last access: 2 March 2016), 2012.
Royal Society: Geoengineering the climate: science, governance and uncertainty 2009 2 March 2016, available at: http://royalsociety.org/policy/publications/2009/geoengineering-climate/ (last access: 27 October 2016), 2009.
Sterman, J., Fiddaman, T., Franck, T., Jones, A., McCauley, S., Rice, P., Sawin, E., and Siegel, L.: Climate interactive: the C-ROADS climate policy model, Syst. Dynam. Rev., 28, 295–305, 2012.
Stocker, B. D., Roth, R., Joos, F., Spahni, R., Steinacher, M., Zaehle, S., Bouwman, L., and Prentice, I. C.: Multiple greenhouse-gas feedbacks from the land biosphere under future climate change scenarios, Nat. Clim. Change, 3, 666–672, 2013.
Tokimatsu, K., Konishi, S., Ishihara, K., Tezuka, T., Yasuoka, R., and Nishio, M.: Role of innovative technologies under the global zero emissions scenarios, Appl. Energy, 162, 1483–1493, 2016.
UNEP: Towards a Green Economy: Pathways to Sustainable Development and Poverty Eradication, http://www.unep.org/greeneconomy (last access: 27 October 2016), 2011.
University of Illinois Sea Ice Dataset: http://arctic.atmos.uiuc.edu/SEAICE/ (last access: 27 October 2016), 2015.
Vensim: http://vensim.com/download/, last access: 12 November 2015.
Ward, J. D., Mohr, S. H., Myers, B. R., and Nel, W. P.: High estimates of supply constrained emissions scenarios for long-term climate risk assessment, Energy Policy, 51, 598–604, 2012.
We describe ESCIMO, a system dynamics simulation model which is designed to make it simple to estimate the effects of possible human interventions to influence the global surface temperature. ESCIMO consists of sectors that track global carbon flows, global energy flows and global albedo change. One conclusion is that human interventions that cost less than 1 % of world GDP are at most able to lower the temperature rise in 2050 by up to 0.5 °C and in 2100 by up to 1.0 °C.
We describe ESCIMO, a system dynamics simulation model which is designed to make it simple to...