Articles | Volume 12, issue 1
Earth Syst. Dynam., 12, 151–172, 2021
https://doi.org/10.5194/esd-12-151-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue: Understanding compound weather and climate events and related...
Earth Syst. Dynam., 12, 151–172, 2021
https://doi.org/10.5194/esd-12-151-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article 10 Feb 2021
Research article | 10 Feb 2021
Identifying meteorological drivers of extreme impacts: an application to simulated crop yields
Johannes Vogel et al.
Related authors
Johannes Vogel, Eva Paton, and Valentin Aich
Biogeosciences, 18, 5903–5927, https://doi.org/10.5194/bg-18-5903-2021, https://doi.org/10.5194/bg-18-5903-2021, 2021
Short summary
Short summary
This study investigates extreme ecosystem impacts evoked by temperature and soil moisture in the Mediterranean Basin for the time span 1999–2019 with a specific focus on seasonal variations. The analysis showed that ecosystem vulnerability is caused by several varying combinations of both drivers during the yearly cycle. The approach presented here helps to provide insights on the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs.
Johannes Vogel, Eva Paton, and Valentin Aich
Biogeosciences, 18, 5903–5927, https://doi.org/10.5194/bg-18-5903-2021, https://doi.org/10.5194/bg-18-5903-2021, 2021
Short summary
Short summary
This study investigates extreme ecosystem impacts evoked by temperature and soil moisture in the Mediterranean Basin for the time span 1999–2019 with a specific focus on seasonal variations. The analysis showed that ecosystem vulnerability is caused by several varying combinations of both drivers during the yearly cycle. The approach presented here helps to provide insights on the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs.
Jérôme Kopp, Pauline Rivoire, S. Mubashshir Ali, Yannick Barton, and Olivia Martius
Hydrol. Earth Syst. Sci., 25, 5153–5174, https://doi.org/10.5194/hess-25-5153-2021, https://doi.org/10.5194/hess-25-5153-2021, 2021
Short summary
Short summary
Episodes of extreme rainfall events happening in close temporal succession can lead to floods with dramatic impacts. We developed a novel method to individually identify those episodes and deduced the regions where they occur frequently and where their impact is substantial. Those regions are the east and northeast of the Asian continent, central Canada and the south of California, Afghanistan, Pakistan, the southwest of the Iberian Peninsula, and north of Argentina and south of Bolivia.
Elisabeth Tschumi, Sebastian Lienert, Karin van der Wiel, Fortunat Joos, and Jakob Zscheischler
Biogeosciences Discuss., https://doi.org/10.5194/bg-2021-191, https://doi.org/10.5194/bg-2021-191, 2021
Preprint under review for BG
Short summary
Short summary
Droughts and heatwaves are expected to occur more often in the future but their effects on land vegetation and the carbon cycle are poorly understood. We use six climate scenarios with differing extremes occurrence and a vegetation model to analyze these effects. We find that tree coverage and associated plant productivity increases under a climate with no extremes. Frequent co-occurring droughts and heatwaves decrease plant productivity more than the combined effects of single drought or heat.
Greta Cazzaniga, Carlo De Michele, Michele D'Amico, Cristina Deidda, Antonio Ghezzi, and Roberto Nebuloni
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-389, https://doi.org/10.5194/hess-2021-389, 2021
Preprint under review for HESS
Short summary
Short summary
Rainfall estimates are usually obtained from rain gauges, weather radars, or satellites. An alternative is the measurement of the signal loss induced by rainfall on commercial microwave links (CMLs). In this work we assess the hydrologic response of Lambro basin, when CML retrieved rainfall is used as input. CML estimates agree with rain gauges data. CML-driven discharge simulations show performances comparable with those from rain gauges, if a CML-based calibration of the model is undertaken.
Roberto Villalobos-Herrera, Emanuele Bevacqua, Andreia F. S. Ribeiro, Graeme Auld, Laura Crocetti, Bilyana Mircheva, Minh Ha, Jakob Zscheischler, and Carlo De Michele
Nat. Hazards Earth Syst. Sci., 21, 1867–1885, https://doi.org/10.5194/nhess-21-1867-2021, https://doi.org/10.5194/nhess-21-1867-2021, 2021
Short summary
Short summary
Climate hazards may be caused by events which have multiple drivers. Here we present a method to break down climate model biases in hazard indicators down to the bias caused by each driving variable. Using simplified fire and heat stress indicators driven by temperature and relative humidity as examples, we show how multivariate indicators may have complex biases and that the relationship between driving variables is a source of bias that must be considered in climate model bias corrections.
Henrique M. D. Goulart, Karin van der Wiel, Christian Folberth, Juraj Balkovic, and Bart van den Hurk
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2021-40, https://doi.org/10.5194/esd-2021-40, 2021
Revised manuscript accepted for ESD
Short summary
Short summary
Agriculture is sensitive to weather conditions and to climate change. We identify the weather conditions linked to soybean failures and explore changes related to climate change. Additionally, we build future versions of a historical extreme season under future climate scenarios. Results show that soybean failures are likely to increase with climate change. Future events with similar physical conditions to the extreme season are not expected to increase, but events with similar impacts are.
Jun Li, Zhaoli Wang, Xushu Wu, Jakob Zscheischler, Shenglian Guo, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 25, 1587–1601, https://doi.org/10.5194/hess-25-1587-2021, https://doi.org/10.5194/hess-25-1587-2021, 2021
Short summary
Short summary
We introduce a daily-scale index, termed the standardized compound drought and heat index (SCDHI), to measure the key features of compound dry-hot conditions. SCDHI can not only monitor the long-term compound dry-hot events, but can also capture such events at sub-monthly scale and reflect the related vegetation activity impacts. The index can provide a new tool to quantify sub-monthly characteristics of compound dry-hot events, which are vital for releasing early and timely warning.
Natacha Le Grix, Jakob Zscheischler, Charlotte Laufkötter, Cecile S. Rousseaux, and Thomas L. Frölicher
Biogeosciences, 18, 2119–2137, https://doi.org/10.5194/bg-18-2119-2021, https://doi.org/10.5194/bg-18-2119-2021, 2021
Short summary
Short summary
Marine ecosystems could suffer severe damage from the co-occurrence of a marine heat wave with extremely low chlorophyll concentration. Here, we provide a first assessment of compound marine heat wave and
low-chlorophyll events in the global ocean from 1998 to 2018. We reveal hotspots of these compound events in the equatorial Pacific and in the Arabian Sea and show that they mostly occur in summer at high latitudes and their frequency is modulated by large-scale modes of climate variability.
Gijs van Kempen, Karin van der Wiel, and Lieke Anna Melsen
Nat. Hazards Earth Syst. Sci., 21, 961–976, https://doi.org/10.5194/nhess-21-961-2021, https://doi.org/10.5194/nhess-21-961-2021, 2021
Short summary
Short summary
In this study, we combine climate model results with a hydrological model to investigate uncertainties in flood and drought risk. With the climate model, 2000 years of
current climatewas created. The hydrological model consisted of several building blocks that we could adapt. In this way, we could investigate the effect of these hydrological building blocks on high- and low-flow risk in four different climate zones with return periods of up to 500 years.
Sarah F. Kew, Sjoukje Y. Philip, Mathias Hauser, Mike Hobbins, Niko Wanders, Geert Jan van Oldenborgh, Karin van der Wiel, Ted I. E. Veldkamp, Joyce Kimutai, Chris Funk, and Friederike E. L. Otto
Earth Syst. Dynam., 12, 17–35, https://doi.org/10.5194/esd-12-17-2021, https://doi.org/10.5194/esd-12-17-2021, 2021
Short summary
Short summary
Motivated by the possible influence of rising temperatures, this study synthesises results from observations and climate models to explore trends (1900–2018) in eastern African (EA) drought measures. However, no discernible trends are found in annual soil moisture or precipitation. Positive trends in potential evaporation indicate that for irrigated regions more water is now required to counteract increased evaporation. Precipitation deficit is, however, the most useful indicator of EA drought.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021, https://doi.org/10.5194/esd-12-1-2021, 2021
Short summary
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.
Sjoukje Philip, Sarah Kew, Geert Jan van Oldenborgh, Friederike Otto, Robert Vautard, Karin van der Wiel, Andrew King, Fraser Lott, Julie Arrighi, Roop Singh, and Maarten van Aalst
Adv. Stat. Clim. Meteorol. Oceanogr., 6, 177–203, https://doi.org/10.5194/ascmo-6-177-2020, https://doi.org/10.5194/ascmo-6-177-2020, 2020
Short summary
Short summary
Event attribution studies can now be performed at short notice. We document a protocol developed by the World Weather Attribution group. It includes choices of which events to analyse, the event definition, observational analysis, model evaluation, multi-model multi-method attribution, hazard synthesis, vulnerability and exposure analysis, and communication procedures. The protocol will be useful for future event attribution studies and as a basis for an operational attribution service.
Andreia Filipa Silva Ribeiro, Ana Russo, Célia Marina Gouveia, Patrícia Páscoa, and Jakob Zscheischler
Biogeosciences, 17, 4815–4830, https://doi.org/10.5194/bg-17-4815-2020, https://doi.org/10.5194/bg-17-4815-2020, 2020
Short summary
Short summary
This study investigates the impacts of compound dry and hot extremes on crop yields, namely wheat and barley, over two regions in Spain dominated by rainfed agriculture. We provide estimates of the conditional probability of crop loss under compound dry and hot conditions, which could be an important tool for responsible authorities to mitigate the impacts magnified by the interactions between the different hazards.
Inne Vanderkelen, Jakob Zschleischler, Lukas Gudmundsson, Klaus Keuler, Francois Rineau, Natalie Beenaerts, Jaco Vangronsveld, and Wim Thiery
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-267, https://doi.org/10.5194/bg-2019-267, 2019
Manuscript not accepted for further review
Pauline Rivoire, Yves Tramblay, Luc Neppel, Elke Hertig, and Sergio M. Vicente-Serrano
Nat. Hazards Earth Syst. Sci., 19, 1629–1638, https://doi.org/10.5194/nhess-19-1629-2019, https://doi.org/10.5194/nhess-19-1629-2019, 2019
Short summary
Short summary
In order to define a dry period, a threshold for wet days is usually considered to account for measurement errors and evaporation. In the present study, we compare the threshold of 1 mm d−1, the most commonly used threshold, to a time-varying threshold describing evapotranspiration to compare how the risk of extreme dry spells is estimated with both thresholds. Results indicate that considering a fixed threshold can underestimate extreme dry spells during the extended summer.
Sjoukje Philip, Sarah Sparrow, Sarah F. Kew, Karin van der Wiel, Niko Wanders, Roop Singh, Ahmadul Hassan, Khaled Mohammed, Hammad Javid, Karsten Haustein, Friederike E. L. Otto, Feyera Hirpa, Ruksana H. Rimi, A. K. M. Saiful Islam, David C. H. Wallom, and Geert Jan van Oldenborgh
Hydrol. Earth Syst. Sci., 23, 1409–1429, https://doi.org/10.5194/hess-23-1409-2019, https://doi.org/10.5194/hess-23-1409-2019, 2019
Short summary
Short summary
In August 2017 Bangladesh faced one of its worst river flooding events in recent history. For the large Brahmaputra basin, using precipitation alone as a proxy for flooding might not be appropriate. In this paper we explicitly test this assumption by performing an attribution of both precipitation and discharge as a flooding-related measure to climate change. We find the change in risk to be of similar order of magnitude (between 1 and 2) for both the meteorological and hydrological approach.
Jakob Zscheischler, Erich M. Fischer, and Stefan Lange
Earth Syst. Dynam., 10, 31–43, https://doi.org/10.5194/esd-10-31-2019, https://doi.org/10.5194/esd-10-31-2019, 2019
Short summary
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.
Martha M. Vogel, Jakob Zscheischler, and Sonia I. Seneviratne
Earth Syst. Dynam., 9, 1107–1125, https://doi.org/10.5194/esd-9-1107-2018, https://doi.org/10.5194/esd-9-1107-2018, 2018
Short summary
Short summary
Climate change projections of temperature extremes are particularly uncertain in central Europe. We demonstrate that varying soil moisture–atmosphere feedbacks in current climate models leads to an enhancement of model differences; thus, they can explain the large uncertainties in extreme temperature projections. Using an observation-based constraint, we show that the strong drying and large increase in temperatures exhibited by models on the hottest day in central Europe are highly unlikely.
Donghai Wu, Philippe Ciais, Nicolas Viovy, Alan K. Knapp, Kevin Wilcox, Michael Bahn, Melinda D. Smith, Sara Vicca, Simone Fatichi, Jakob Zscheischler, Yue He, Xiangyi Li, Akihiko Ito, Almut Arneth, Anna Harper, Anna Ukkola, Athanasios Paschalis, Benjamin Poulter, Changhui Peng, Daniel Ricciuto, David Reinthaler, Guangsheng Chen, Hanqin Tian, Hélène Genet, Jiafu Mao, Johannes Ingrisch, Julia E. S. M. Nabel, Julia Pongratz, Lena R. Boysen, Markus Kautz, Michael Schmitt, Patrick Meir, Qiuan Zhu, Roland Hasibeder, Sebastian Sippel, Shree R. S. Dangal, Stephen Sitch, Xiaoying Shi, Yingping Wang, Yiqi Luo, Yongwen Liu, and Shilong Piao
Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
Short summary
Short summary
Our results indicate that most ecosystem models do not capture the observed asymmetric responses under normal precipitation conditions, suggesting an overestimate of the drought effects and/or underestimate of the watering impacts on primary productivity, which may be the result of inadequate representation of key eco-hydrological processes. Collaboration between modelers and site investigators needs to be strengthened to improve the specific processes in ecosystem models in following studies.
Jannis von Buttlar, Jakob Zscheischler, Anja Rammig, Sebastian Sippel, Markus Reichstein, Alexander Knohl, Martin Jung, Olaf Menzer, M. Altaf Arain, Nina Buchmann, Alessandro Cescatti, Damiano Gianelle, Gerard Kiely, Beverly E. Law, Vincenzo Magliulo, Hank Margolis, Harry McCaughey, Lutz Merbold, Mirco Migliavacca, Leonardo Montagnani, Walter Oechel, Marian Pavelka, Matthias Peichl, Serge Rambal, Antonio Raschi, Russell L. Scott, Francesco P. Vaccari, Eva van Gorsel, Andrej Varlagin, Georg Wohlfahrt, and Miguel D. Mahecha
Biogeosciences, 15, 1293–1318, https://doi.org/10.5194/bg-15-1293-2018, https://doi.org/10.5194/bg-15-1293-2018, 2018
Short summary
Short summary
Our work systematically quantifies extreme heat and drought event impacts on gross primary productivity (GPP) and ecosystem respiration globally across a wide range of ecosystems. We show that heat extremes typically increased mainly respiration whereas drought decreased both fluxes. Combined heat and drought extremes had opposing effects offsetting each other for respiration, but there were also strong reductions in GPP and hence the strongest reductions in the ecosystems carbon sink capacity.
Miguel D. Mahecha, Fabian Gans, Sebastian Sippel, Jonathan F. Donges, Thomas Kaminski, Stefan Metzger, Mirco Migliavacca, Dario Papale, Anja Rammig, and Jakob Zscheischler
Biogeosciences, 14, 4255–4277, https://doi.org/10.5194/bg-14-4255-2017, https://doi.org/10.5194/bg-14-4255-2017, 2017
Short summary
Short summary
We investigate the likelihood of ecological in situ networks to detect and monitor the impact of extreme events in the terrestrial biosphere.
Jakob Zscheischler, Miguel D. Mahecha, Valerio Avitabile, Leonardo Calle, Nuno Carvalhais, Philippe Ciais, Fabian Gans, Nicolas Gruber, Jens Hartmann, Martin Herold, Kazuhito Ichii, Martin Jung, Peter Landschützer, Goulven G. Laruelle, Ronny Lauerwald, Dario Papale, Philippe Peylin, Benjamin Poulter, Deepak Ray, Pierre Regnier, Christian Rödenbeck, Rosa M. Roman-Cuesta, Christopher Schwalm, Gianluca Tramontana, Alexandra Tyukavina, Riccardo Valentini, Guido van der Werf, Tristram O. West, Julie E. Wolf, and Markus Reichstein
Biogeosciences, 14, 3685–3703, https://doi.org/10.5194/bg-14-3685-2017, https://doi.org/10.5194/bg-14-3685-2017, 2017
Short summary
Short summary
Here we synthesize a wide range of global spatiotemporal observational data on carbon exchanges between the Earth surface and the atmosphere. A key challenge was to consistently combining observational products of terrestrial and aquatic surfaces. Our primary goal is to identify today’s key uncertainties and observational shortcomings that would need to be addressed in future measurement campaigns or expansions of in situ observatories.
Jakob Zscheischler, Rene Orth, and Sonia I. Seneviratne
Biogeosciences, 14, 3309–3320, https://doi.org/10.5194/bg-14-3309-2017, https://doi.org/10.5194/bg-14-3309-2017, 2017
Short summary
Short summary
We use newly established methods to compute bivariate return periods of temperature and precipitation and relate those to crop yield variability in Europe. Most often, crop yields are lower when it is hot and dry and higher when it is cold and wet. The variability in crop yields along a specific climate gradient can be captured well by return periods aligned with these gradients. This study provides new possibilities for investigating the relationship between crop yield variability and climate.
Sebastian Sippel, Jakob Zscheischler, Miguel D. Mahecha, Rene Orth, Markus Reichstein, Martha Vogel, and Sonia I. Seneviratne
Earth Syst. Dynam., 8, 387–403, https://doi.org/10.5194/esd-8-387-2017, https://doi.org/10.5194/esd-8-387-2017, 2017
Short summary
Short summary
The present study (1) evaluates land–atmosphere coupling in the CMIP5 multi-model ensemble against an ensemble of benchmarking datasets and (2) refines the model ensemble using a land–atmosphere coupling diagnostic as constraint. Our study demonstrates that a considerable fraction of coupled climate models overemphasize warm-season
moisture-limitedclimate regimes in midlatitude regions. This leads to biases in daily-scale temperature extremes, which are alleviated in a constrained ensemble.
Karin van der Wiel, Sarah B. Kapnick, Geert Jan van Oldenborgh, Kirien Whan, Sjoukje Philip, Gabriel A. Vecchi, Roop K. Singh, Julie Arrighi, and Heidi Cullen
Hydrol. Earth Syst. Sci., 21, 897–921, https://doi.org/10.5194/hess-21-897-2017, https://doi.org/10.5194/hess-21-897-2017, 2017
Short summary
Short summary
During August 2016, heavy precipitation led to devastating floods in south Louisiana, USA. Here, we analyze the climatological statistics of the precipitation event, as defined by its 3-day total over 12–14 August. Using observational data and high-resolution global coupled model experiments, we find for a comparable event on the central US Gulf Coast an average return period of about 30 years and the odds being increased by at least 1.4 since 1900 due to anthropogenic climate change.
Sebastian Sippel, Jakob Zscheischler, Martin Heimann, Holger Lange, Miguel D. Mahecha, Geert Jan van Oldenborgh, Friederike E. L. Otto, and Markus Reichstein
Hydrol. Earth Syst. Sci., 21, 441–458, https://doi.org/10.5194/hess-21-441-2017, https://doi.org/10.5194/hess-21-441-2017, 2017
Short summary
Short summary
The paper re-investigates the question whether observed precipitation extremes and annual totals have been increasing in the world's dry regions over the last 60 years. Despite recently postulated increasing trends, we demonstrate that large uncertainties prevail due to (1) the choice of dryness definition and (2) statistical data processing. In fact, we find only minor (and only some significant) increases if (1) dryness is based on aridity and (2) statistical artefacts are accounted for.
Bjorn-Gustaf J. Brooks, Ankur R. Desai, Britton B. Stephens, Anna M. Michalak, and Jakob Zscheischler
Biogeosciences Discuss., https://doi.org/10.5194/bg-2016-223, https://doi.org/10.5194/bg-2016-223, 2016
Manuscript not accepted for further review
Short summary
Short summary
CO2 is the primary greenhouse gas, and its abundance in the atmosphere tends to increase during disturbances like drought. This paper demonstrates how CO2 measurements are combined with models to determine not only how strongly different locations influence CO2 measurement stations, but also the capacity of those measurement stations to detect drought effects. Understanding detection sensitivity will help assess what kinds of changes and turnings points can be monitored using atmospheric CO2.
J. Zscheischler, M. Reichstein, S. Harmeling, A. Rammig, E. Tomelleri, and M. D. Mahecha
Biogeosciences, 11, 2909–2924, https://doi.org/10.5194/bg-11-2909-2014, https://doi.org/10.5194/bg-11-2909-2014, 2014
J. v. Buttlar, J. Zscheischler, and M. D. Mahecha
Nonlin. Processes Geophys., 21, 203–215, https://doi.org/10.5194/npg-21-203-2014, https://doi.org/10.5194/npg-21-203-2014, 2014
Related subject area
Dynamics of the Earth system: models
Climate change in the High Mountain Asia in CMIP6
The sensitivity of the El Niño–Southern Oscillation to volcanic aerosol spatial distribution in the MPI Grand Ensemble
Coupled regional Earth system modeling in the Baltic Sea region
Climate change projections of terrestrial primary productivity over the Hindu Kush Himalayan forests
Bookkeeping estimates of the net land-use change flux – a sensitivity study with the CMIP6 land-use dataset
Climate-controlled root zone parameters show potential to improve water flux simulations by land surface models
Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator
First assessment of the earth heat inventory within CMIP5 historical simulations
The thermal response of small and shallow lakes to climate change: new insights from 3D hindcast modelling
Labrador Sea subsurface density as a precursor of multidecadal variability in the North Atlantic: a multi-model study
How modelling paradigms affect simulated future land use change
Simulating compound weather extremes responsible for critical crop failure with stochastic weather generators
Characterisation of Atlantic meridional overturning hysteresis using Langevin dynamics
Evaluating the dependence structure of compound precipitation and wind speed extremes
Future sea level contribution from Antarctica inferred from CMIP5 model forcing and its dependence on precipitation ansatz
The extremely warm summer of 2018 in Sweden – set in a historical context
Effect of changing ocean circulation on deep ocean temperature in the last millennium
How large does a large ensemble need to be?
Reconstructing coupled time series in climate systems using three kinds of machine-learning methods
An investigation of weighting schemes suitable for incorporating large ensembles into multi-model ensembles
The Fractional Energy Balance Equation for Climate projections through 2100
What 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 Europe
Agricultural management effects on mean and extreme temperature trends
Climate change in a conceptual atmosphere–phytoplankton model
Variability of surface climate in simulations of past and future
Statistical estimation of global surface temperature response to forcing under the assumption of temporal scaling
Emulating Earth system model temperatures with MESMER: from global mean temperature trajectories to grid-point-level realizations on land
A global semi-empirical glacial isostatic adjustment (GIA) model based on Gravity Recovery and Climate Experiment (GRACE) data
Improvement in the decadal prediction skill of the North Atlantic extratropical winter circulation through increased model resolution
Societal breakdown as an emergent property of large-scale behavioural models of land use change
Improving weather and climate predictions by training of supermodels
Evaluating climate emulation: fundamental impulse testing of simple climate models
Maximum power of saline and fresh water mixing in estuaries
Tipping the ENSO into a permanent El Niño can trigger state transitions in global terrestrial ecosystems
Contributions of climate change and groundwater extraction to soil moisture trends
Downslope windstorms in the Isthmus of Tehuantepec during Tehuantepecer events: a numerical study with WRF high-resolution simulations
A radiative-convective model based on constrained maximum entropy production
ESD Ideas: Propagation of high-frequency forcing to ice age dynamics
Development and prospects of the regional MiKlip decadal prediction system over Europe: predictive skill, added value of regionalization, and ensemble size dependency
Climatological moisture sources for the Western North American Monsoon through a Lagrangian approach: their influence on precipitation intensity
The effect of univariate bias adjustment on multivariate hazard estimates
Light absorption by marine cyanobacteria affects tropical climate mean state and variability
Sensitivity study of the regional climate model RegCM4 to different convective schemes over West Africa
Simulation of observed climate changes in 1850–2014 with climate model INM-CM5
A theoretical approach to assess soil moisture–climate coupling across CMIP5 and GLACE-CMIP5 experiments
Improving 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 rhythmicity
Using network theory and machine learning to predict El Niño
Modelling feedbacks between human and natural processes in the land system
Mickaël Lalande, Martin Ménégoz, Gerhard Krinner, Kathrin Naegeli, and Stefan Wunderle
Earth Syst. Dynam., 12, 1061–1098, https://doi.org/10.5194/esd-12-1061-2021, https://doi.org/10.5194/esd-12-1061-2021, 2021
Short summary
Short summary
Climate change over High Mountain Asia is investigated with CMIP6 climate models. A general cold bias is found in this area, often related to a snow cover overestimation in the models. Ensemble experiments generally encompass the past observed trends, suggesting that even biased models can reproduce the trends. Depending on the future scenario, a warming from 1.9 to 6.5 °C, associated with a snow cover decrease and precipitation increase, is expected at the end of the 21st century.
Benjamin Ward, Francesco S. R. Pausata, and Nicola Maher
Earth Syst. Dynam., 12, 975–996, https://doi.org/10.5194/esd-12-975-2021, https://doi.org/10.5194/esd-12-975-2021, 2021
Short summary
Short summary
Using the largest ensemble of a climate model currently available, the Max Planck Institute Grand Ensemble (MPI-GE), we investigated the impact of the spatial distribution of volcanic aerosols on the El Niño–Southern Oscillation (ENSO) response. By selecting three eruptions with different aerosol distributions, we found that the shift of the Intertropical Convergence Zone (ITCZ) is the main driver of the ENSO response, while other mechanisms commonly invoked seem less important in our model.
Matthias Gröger, Christian Dieterich, Jari Haapala, Ha Thi Minh Ho-Hagemann, Stefan Hagemann, Jaromir Jakacki, Wilhelm May, H. E. Markus Meier, Paul A. Miller, Anna Rutgersson, and Lichuan Wu
Earth Syst. Dynam., 12, 939–973, https://doi.org/10.5194/esd-12-939-2021, https://doi.org/10.5194/esd-12-939-2021, 2021
Short summary
Short summary
Regional climate studies are typically pursued by single Earth system component models (e.g., ocean models and atmosphere models). These models are driven by prescribed data which hamper the simulation of feedbacks between Earth system components. To overcome this, models were developed that interactively couple model components and allow an adequate simulation of Earth system interactions important for climate. This article reviews recent developments of such models for the Baltic Sea region.
Halima Usman, Thomas A. M. Pugh, Anders Ahlström, and Sofia Baig
Earth Syst. Dynam., 12, 857–870, https://doi.org/10.5194/esd-12-857-2021, https://doi.org/10.5194/esd-12-857-2021, 2021
Short summary
Short summary
The study assesses the impacts of climate change on forest productivity in the Hindu Kush Himalayan region. LPJ-GUESS was simulated from 1851 to 2100. In first approach, the model was compared with observational estimates. The comparison showed a moderate agreement. In the second approach, the model was assessed for the temporal and spatial trends of net biome productivity and its components along with carbon pool. Increases in both variables were predicted in 2100.
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., 12, 763–782, https://doi.org/10.5194/esd-12-763-2021, https://doi.org/10.5194/esd-12-763-2021, 2021
Short summary
Short 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.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, and Andrea Alessandri
Earth Syst. Dynam., 12, 725–743, https://doi.org/10.5194/esd-12-725-2021, https://doi.org/10.5194/esd-12-725-2021, 2021
Short summary
Short 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 improved timing of modeled river discharge. Further extension of our approach could improve modeled water fluxes globally.
Manuela I. Brunner, Eric Gilleland, and Andrew W. Wood
Earth Syst. Dynam., 12, 621–634, https://doi.org/10.5194/esd-12-621-2021, https://doi.org/10.5194/esd-12-621-2021, 2021
Short summary
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, https://doi.org/10.5194/esd-12-581-2021, https://doi.org/10.5194/esd-12-581-2021, 2021
Short summary
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, https://doi.org/10.5194/esd-12-439-2021, https://doi.org/10.5194/esd-12-439-2021, 2021
Short summary
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, https://doi.org/10.5194/esd-12-419-2021, https://doi.org/10.5194/esd-12-419-2021, 2021
Short summary
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, https://doi.org/10.5194/esd-12-211-2021, https://doi.org/10.5194/esd-12-211-2021, 2021
Short summary
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.
Peter Pfleiderer, Aglaé Jézéquel, Juliette Legrand, Natacha Legrix, Iason Markantonis, Edoardo Vignotto, and Pascal Yiou
Earth Syst. Dynam., 12, 103–120, https://doi.org/10.5194/esd-12-103-2021, https://doi.org/10.5194/esd-12-103-2021, 2021
Short summary
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, https://doi.org/10.5194/esd-12-69-2021, https://doi.org/10.5194/esd-12-69-2021, 2021
Short summary
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.
Jakob Zscheischler, Philippe Naveau, Olivia Martius, Sebastian Engelke, and Christoph C. Raible
Earth Syst. Dynam., 12, 1–16, https://doi.org/10.5194/esd-12-1-2021, https://doi.org/10.5194/esd-12-1-2021, 2021
Short summary
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, https://doi.org/10.5194/esd-11-1153-2020, https://doi.org/10.5194/esd-11-1153-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-1107-2020, https://doi.org/10.5194/esd-11-1107-2020, 2020
Short summary
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.
Jeemijn Scheen and Thomas F. Stocker
Earth Syst. Dynam., 11, 925–951, https://doi.org/10.5194/esd-11-925-2020, https://doi.org/10.5194/esd-11-925-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-885-2020, https://doi.org/10.5194/esd-11-885-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-835-2020, https://doi.org/10.5194/esd-11-835-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-807-2020, https://doi.org/10.5194/esd-11-807-2020, 2020
Short summary
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.
Roman Procyk, Shaun Lovejoy, and Raphael Hébert
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-48, https://doi.org/10.5194/esd-2020-48, 2020
Revised manuscript accepted for ESD
Short summary
Short summary
This paper presents a new class of energy balance model that accounts for the long memory within the Earth's energy storage. The model is calibrated on instrumental temperature records and the historical energy budget of the Earth using an error model predicted by the model itself. Our equilibrium climate sensitivity and future temperature projection estimates are consistent with those estimated by complex climate models.
James D. Annan, Julia C. Hargreaves, Thorsten Mauritsen, and Bjorn Stevens
Earth Syst. Dynam., 11, 709–719, https://doi.org/10.5194/esd-11-709-2020, https://doi.org/10.5194/esd-11-709-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-617-2020, https://doi.org/10.5194/esd-11-617-2020, 2020
Short summary
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.
Aine M. Gormley-Gallagher, Sebastian Sterl, Annette L. Hirsch, Sonia I. Seneviratne, Edouard L. Davin, and Wim Thiery
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2020-35, https://doi.org/10.5194/esd-2020-35, 2020
Revised manuscript accepted for ESD
György Károlyi, Rudolf Dániel Prokaj, István Scheuring, and Tamás Tél
Earth Syst. Dynam., 11, 603–615, https://doi.org/10.5194/esd-11-603-2020, https://doi.org/10.5194/esd-11-603-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-447-2020, https://doi.org/10.5194/esd-11-447-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-329-2020, https://doi.org/10.5194/esd-11-329-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-139-2020, https://doi.org/10.5194/esd-11-139-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-11-129-2020, https://doi.org/10.5194/esd-11-129-2020, 2020
Short summary
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, https://doi.org/10.5194/esd-10-901-2019, https://doi.org/10.5194/esd-10-901-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-809-2019, https://doi.org/10.5194/esd-10-809-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-789-2019, https://doi.org/10.5194/esd-10-789-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-729-2019, https://doi.org/10.5194/esd-10-729-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-667-2019, https://doi.org/10.5194/esd-10-667-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-631-2019, https://doi.org/10.5194/esd-10-631-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-599-2019, https://doi.org/10.5194/esd-10-599-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-485-2019, https://doi.org/10.5194/esd-10-485-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-365-2019, https://doi.org/10.5194/esd-10-365-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-257-2019, https://doi.org/10.5194/esd-10-257-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-171-2019, https://doi.org/10.5194/esd-10-171-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-59-2019, https://doi.org/10.5194/esd-10-59-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-10-31-2019, https://doi.org/10.5194/esd-10-31-2019, 2019
Short summary
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, https://doi.org/10.5194/esd-9-1283-2018, https://doi.org/10.5194/esd-9-1283-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-1261-2018, https://doi.org/10.5194/esd-9-1261-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-1235-2018, https://doi.org/10.5194/esd-9-1235-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-1217-2018, https://doi.org/10.5194/esd-9-1217-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-1045-2018, https://doi.org/10.5194/esd-9-1045-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-1025-2018, https://doi.org/10.5194/esd-9-1025-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-969-2018, https://doi.org/10.5194/esd-9-969-2018, 2018
Short summary
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, https://doi.org/10.5194/esd-9-895-2018, https://doi.org/10.5194/esd-9-895-2018, 2018
Short summary
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.
Cited articles
Allstadt, A. J., Vavrus, S. J., Heglund, P. J., Pidgeon, A. M., Thogmartin, W. E., and Radeloff, V. C.: Spring plant phenology and false springs in the
conterminous US during the 21st century, Environ. Res. Lett., 10, 104008, https://doi.org/10.1088/1748-9326/10/10/104008, 2015. a
Asseng, S., Ewert, F., Rosenzweig, C., Jones, J. W., Hatfield, J. L., Ruane, A. C., Boote, K. J., Thorburn, P. J., Rötter, R. P., Cammarano, D., Brisson, N., Basso, B., Martre, P., Aggarwal, P. K., Angulo, C., Bertuzzi, P., Biernath, C., Challinor, A. J., Doltra, J., Gayler, S., Goldberg, R., Grant, R., Heng, L., Hooker, J., Hunt, L. A., Ingwersen, J., Izaurralde, R. C., Kersebaum, K. C., Müller, C., Naresh Kumar, S., Nendel, C., O'Leary, G., Olesen, J. E., Osborne, T. M., Palosuo, T., Priesack, E., Ripoche, D., Semenov, M. A., Shcherbak, I., Steduto, P., Stöckle, C., Stratonovitch, P., Streck, T., Supit, I., Tao, F., Travasso, M., Waha, K., Wallach, D., White, J. W., Williams, J. R., and Wolf, J.: Uncertainty in simulating wheat yields under climate change, Nat. Clim. Change, 3, 827–832, https://doi.org/10.1038/nclimate1916, 2013. a
Batjes, N. H.: ISRIC-WISE derived soil properties on a 5 by 5 arc-minutes global grid (ver. 1.2), Report 2012/01, ISRIC-World Soil Information, Wageningen, 2012. a
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. a
Buizza, R., Milleer, M., and Palmer, T. N.: Stochastic representation of model uncertainties in the ECMWF ensemble prediction system, Q. J. Roy. Meteorol. Soc., 125, 2887–2908, https://doi.org/10.1002/qj.49712556006, 1999. a
Daryanto, S., Wang, L., and Jacinthe, P.-A.: Global Synthesis of Drought
Effects on Maize and Wheat Production, PloS One, 11, e0156362,
https://doi.org/10.1371/journal.pone.0156362, 2016. a, b
Deser, C., Lehner, F., Rodgers, K. B., Ault, T., Delworth, T. L., DiNezio, P. N., Fiore, A., Frankignoul, C., Fyfe, J. C., Horton, D. E., Kay, J. E., Knutti, R., Lovenduski, N. S., Marotzke, J., McKinnon, K. A., Minobe, S.,
Randerson, J., Screen, J. A., Simpson, I. R., and Ting, M.: Insights from
Earth system model initial-condition large ensembles and future prospects, Nat. Clim. Change, 10, 277–286, https://doi.org/10.1038/s41558-020-0731-2, 2020. a
Forkel, M., Thonicke, K., Beer, C., Cramer, W., Bartalev, S., and Schmullius,
C.: Extreme fire events are related to previous-year surface moisture
conditions in permafrost-underlain larch forests of Siberia, Environ. Res. Lett., 7, 044021, https://doi.org/10.1088/1748-9326/7/4/044021, 2012. a
Frank, D., Reichstein, M., Bahn, M., Thonicke, K., Frank, D., Mahecha, M. D.,
Smith, P., van der Velde, M., Vicca, S., Babst, F., Beer, C., Buchmann, N.,
Canadell, J. G., Ciais, P., Cramer, W., Ibrom, A., Miglietta, F., Poulter, B., Rammig, A., Seneviratne, S. I., Walz, A., Wattenbach, M., Zavala, M. A.,
and Zscheischler, J.: Effects of climate extremes on the terrestrial carbon
cycle: concepts, processes and potential future impacts, Global Change Biol., 21, 2861–2880, https://doi.org/10.1111/gcb.12916, 2015. a
Friedman, J., Hastie, T., and Tibshirani, R.: Regularization Paths for
Generalized Linear Models via Coordinate Descent, J. Stat. Softw., 33, 1–22, https://doi.org/10.18637/jss.v033.i01, 2010. a, b
Furnival, G. M. and Wilson, R. W.: Regressions by Leaps and Bounds, Technometrics, 16, 499–511, https://doi.org/10.1080/00401706.1974.10489231, 1974. a
Grossiord, C., Buckley, T. N., Cernusak, L. A., Novick, K. A., Poulter, B.,
Siegwolf, R. T. W., Sperry, J. S., and McDowell, N. G.: Plant responses to
rising vapor pressure deficit, New Phytol., 226, 1550–1566, https://doi.org/10.1111/nph.16485, 2020. a, b, c
Hand, D. J.: Measuring classifier performance: a coherent alternative to the
area under the ROC curve, Mach. Learn., 77, 103–123, https://doi.org/10.1007/s10994-009-5119-5, 2009. a
Hazeleger, W., Wang, X., Severijns, C., Ştefănescu, S., Bintanja, R., Sterl, A., Wyser, K., Semmler, T., Yang, S., Van den Hurk, B., van Noije, T., van der Linden, E., and van der Wiel, K.: EC-Earth V2.2: description and validation of a new seamless earth system prediction model, Clim. Dynam., 39, 2611–2629, https://doi.org/10.1007/s00382-011-1228-5, 2012. a
Iizumi, T. and Ramankutty, N.: How do weather and climate influence cropping
area and intensity?, Global Food Secur., 4, 46–50, https://doi.org/10.1016/j.gfs.2014.11.003, 2015. a, b
Jagadish, K. S. V., Kadam, N. N., Xiao, G., Melgar, R. J., Bahuguna, R. N.,
Quinones, C., Tamilselvan, A., Prasad, P. V. V., and Jagadish, K. S.:
Agronomic and Physiological Responses to High Temperature, Drought, and
Elevated CO2 Interactions in Cereals, in: Advances in Agronomy, vol. 127 of Advances in Agronomy, edited by: Sparks, D. L., Elsevier Science, Burlington, 111–156, https://doi.org/10.1016/B978-0-12-800131-8.00003-0, 2014. a
Jentsch, A., Kreyling, J., and Beierkuhnlein, C.: A new generation of
climate-change experiments: events, not trends, Front. Ecol. Environ., 5, 365–374, https://doi.org/10.1890/1540-9295(2007)5[365:ANGOCE]2.0.CO;2, 2007. a
Kern, A., Barcza, Z., Marjanović, H., Árendás, T., Fodor, N.,
Bónis, P., Bognár, P., and Lichtenberger, J.: Statistical modelling of crop yield in Central Europe using climate data and remote sensing vegetation indices, Agr. Forest Meteorol., 260-261, 300–320, https://doi.org/10.1016/j.agrformet.2018.06.009, 2018. a, b, c
Kogan, F., Kussul, N., Adamenko, T., Skakun, S., Kravchenko, O., Kryvobok, O., Shelestov, A., Kolotii, A., Kussul, O., and Lavrenyuk, A.: Winter wheat
yield forecasting in Ukraine based on Earth observation, meteorologicaldata
and biophysical models, Int. J. Appl. Earth Obs. Geoinform., 23, 192–203, https://doi.org/10.1016/j.jag.2013.01.002, 2013. a
Krstajic, D., Buturovic, L. J., Leahy, D. E., and Thomas, S.: Cross-validation pitfalls when selecting and assessing regression and classification models, J. Cheminform., 6, 1–15, https://doi.org/10.1186/1758-2946-6-10, 2014. a
Leng, G., Zhang, X., Huang, M., Asrar, G. R., and Leung, L. R.: The Role of
Climate Covariability on Crop Yields in the Conterminous United States, Sci. Rep., 6, 33160, https://doi.org/10.1038/srep33160, 2016. a
Leonard, M., Westra, S., Phatak, A., Lambert, M., van den Hurk, B., Mcinnes,
K., Risbey, J., Schuster, S., Jakob, D., and Stafford-Smith, M.: A compound
event framework for understanding extreme impacts, Wiley Interdisciplin. Rev.: Clim. Change, 5, 113–128, https://doi.org/10.1002/wcc.252, 2014. a
Lesk, C., Rowhani, P., and Ramankutty, N.: Influence of extreme weather
disasters on global crop production, Nature, 529, 84–87, https://doi.org/10.1038/nature16467, 2016. a, b
Li, K., Yang, X., Liu, Z., Zhang, T., Lu, S., and Liu, Y.: Low yield gap of
winter wheat in the North China Plain, Eur. J. Agron., 59, 1–12, https://doi.org/10.1016/j.eja.2014.04.007, 2014. a
Liaw, A. and Wiener, M.: Classification and Regression by randomForest, R News, 2, 18–22, available at: https://CRAN.R-project.org/doc/Rnews/
(last access: 18 November 2020), 2002. a
Lobell, D. B.: Changes in diurnal temperature range and national cereal yields, Agr. Forest Meteorol., 145, 229–238, https://doi.org/10.1016/j.agrformet.2007.05.002, 2007. a
Lobell, D. B. and Asner, G. P.: Climate and Management Contributions to Recent Trends in U.S. Agricultural Yields, Science, 299, 1032,
https://doi.org/10.1126/science.1078475, 2003. a
Lobell, D. B. and Burke, M. B.: Why are agricultural impacts of climate change so uncertain? The importance of temperature relative to precipitation,
Environ. Res. Lett., 3, 034007, https://doi.org/10.1088/1748-9326/3/3/034007, 2008. a
Lobell, D. B. and Burke, M. B.: On the use of statistical models to predict
crop yield responses to climate change, Agr. Forest Meteorol., 150, 1443–1452, https://doi.org/10.1016/j.agrformet.2010.07.008, 2010. a
Lobell, D. B., Schlenker, W., and Costa-Roberts, J.: Climate Trends and Global Crop Production Since 1980, Science, 333, 616–620,
https://doi.org/10.1126/science.1204531, 2011. a
Luo, Q.: Temperature thresholds and crop production: a review, Climatic Change, 109, 583–598, https://doi.org/10.1007/s10584-011-0028-6, 2011. a
Mason, I.: Dependence of the Critical Success Index on sample climate and
threshold probability, Aust. Meteorol. Mag., 37, 75–81, 1989. a
McDowell, N. G., Beerling, D. J., Breshears, D. D., Fisher, R. A., Raffa, K. F., and Stitt, M.: The interdependence of mechanisms underlying climate-driven vegetation mortality, Trends Ecol. Evol., 26, 523–532, https://doi.org/10.1016/j.tree.2011.06.003, 2011. a
McLeod, A., Xu, C., and Lai, Y.: bestglm: Best Subset GLM and Regression
Utilities, r package version 0.37.3, available at: https://CRAN.R-project.org/package=bestglm, last access: 18 November 2020. a
Morice, C. P., Kennedy, J. J., Rayner, N. A., and Jones, P. D.: Quantifying
uncertainties in global and regional temperature change using an ensemble of
observational estimates: The HadCRUT4 data set, J. Geophys. Res.-Atmos., 117, D08101, https://doi.org/10.1029/2011JD017187, 2012. a
Mueller, N. D., Gerber, J. S., Johnston, M., Ray, D. K., Ramankutty, N., and
Foley, J. A.: Closing yield gaps through nutrient and water management, Nature, 490, 254–257, https://doi.org/10.1038/nature11420, 2012. a
Novick, K. A., Ficklin, D. L., Stoy, P. C., Williams, C. A., Bohrer, G., Oishi, A. C., Papuga, S. A., Blanken, P. D., Noormets, A., Sulman, B. N., Scott, R. L., Wang, L., and Phillips, R. P.: The increasing importance of
atmospheric demand for ecosystem water and carbon fluxes, Nat. Clim. Change, 6, 1023–1027, https://doi.org/10.1038/nclimate3114, 2016. a
Oppenheimer, M., Campos, M., Warren, R., Birkmann, J., Luber, G., O'Neill, B., and Takahashi, K.: Emergent risks and key vulnerabilities, in: Climate Change 2014 Impacts, Adaptation and Vulnerability: Part A: Global and Sectoral Aspects, Cambridge University Press, Cambridge, 1039–1100, https://doi.org/10.1017/CBO9781107415379.024, 2015. a
Pan, S., Yang, J., Tian, H., Shi, H., Chang, J., Ciais, P., Francois, L.,
Frieler, K., Fu, B., Hickler, T., Ito, A., Nishina, K., Ostberg, S., Reyer,
C. P., Schaphoff, S., Steinkamp, J., and Zhao, F.: Climate Extreme Versus Carbon Extreme: Responses of Terrestrial Carbon Fluxes to Temperature and Precipitation, J. Geophys. Res.-Biogeo., 125, e2019JG005252, https://doi.org/10.1029/2019JG005252, 2020. a
Porter, J. R. and Gawith, M.: Temperatures and the growth and development of
wheat: a review, Eur. J. Agron., 10, 23–36, https://doi.org/10.1016/S1161-0301(98)00047-1, 1999. a, b, c
Rawson, H. M., Begg, J. E., and Woodward, R. G.: The Effect of Atmospheric
Humidity on Photosynthesis, Transpiration and Water Use Efficiency of Leaves
of Several Plant Species, Planta, 134, 5–10, https://doi.org/10.1007/BF00390086, 1977. a, b
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, available at:
https://www.R-project.org/ (last access: 18 November 2020), 2019. a
Ribeiro, A. F. S., Russo, A., Gouveia, C. M., Páscoa, P., and Zscheischler, J.: Risk of crop failure due to compound dry and hot extremes estimated with nested copulas, Biogeosciences, 17, 4815–4830,
https://doi.org/10.5194/bg-17-4815-2020, 2020. a
Rosenzweig, C., Elliott, J., Deryng, D., Ruane, A. C., Müller, C., Arneth, A., Boote, K. J., Folberth, C., Glotter, M., Khabarov, N., Neumann, K., Piontek, F., Pugh, T. A. M., Schmid, E., Stehfest, E., Yang, H., and Jones, J. W.: Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison, P. Natl. Acad. Sci. USA, 111, 3268–3273, https://doi.org/10.1073/pnas.1222463110, 2014. a
Ruane, A. C., Goldberg, R., and Chryssanthacopoulos, J.: Climate forcing
datasets for agricultural modeling: Merged products for gap-filling and
historical climate series estimation, Agr. Forest Meteorol., 200, 233–248, https://doi.org/10.1016/j.agrformet.2014.09.016, 2015. a
Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E.,
Glymour, C., Kretschmer, M., Mahecha, M. D., Muñoz-Marí, J., van Nes, E. H., Peters, J., Quax, R., Reichstein, M., Scheffer, M., Schölkopf, B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., and Zscheischler, J.: Inferring causation from time series in Earth system sciences, Nat. Commun., 10, 2553, https://doi.org/10.1038/s41467-019-10105-3, 2019. a
Sacks, W. J., Deryng, D., Foley, J. A., and Ramankutty, N.: Crop planting
dates: an analysis of global patterns, Global Ecol. Biogeogr., 19, 607–620, https://doi.org/10.1111/j.1466-8238.2010.00551.x, 2010. a, b
Schauberger, B., Archontoulis, S., Arneth, A., Balkovic, J., Ciais, P., Deryng, D., Elliott, J., Folberth, C., Khabarov, N., Müller, C., Pugh, T. A. M., Rolinski, S., Schaphoff, S., Schmid, E., Wang, X., Schlenker, W., and
Frieler, K.: Consistent negative response of US crops to high temperatures in
observations and crop models, Nat. Commun., 8, 13931,
https://doi.org/10.1038/ncomms13931, 2017. a
Seyfert, F.: Phänologie, in: vol. 255 of Die neue Brehm-Bücherei,
nachdr., 2. unveränd. Edn., VerlagsKG Wolf, Magdeburg, 1960. a
Shah, N. and Paulsen, G.: Interaction of drought and high temperature on
photosynthesis and grain-filling of wheat, Plant Soil, 257, 219–226,
https://doi.org/10.1023/a:1026237816578, 2003. a
Shi, W., Tao, F., and Zhang, Z.: A review on statistical models for
identifying climate contributions to crop yields, J. Geogr. Sci., 23, 567–576, https://doi.org/10.1007/s11442-013-1029-3, 2013. a, b
Singh, A., Phadke, V. S., and Patwardhan, A.: Impact of Drought and Flood on
Indian Food Grain Production, in: Challenges and Opportunities in
Agrometeorology, Springer, Berlin, Heidelberg, 421–433,
https://doi.org/10.1007/978-3-642-19360-6_32, 2011. a
Sippel, S., Zscheischler, J., and Reichstein, M.: Ecosystem impacts of climate extremes crucially depend on the timing, P. Natl. Acad. Sci. USA, 113, 5768–5770, https://doi.org/10.1073/pnas.1605667113, 2016. a
Stocker, B. D., Zscheischler, J., Keenan, T. F., Prentice, I. C., Seneviratne, S. I., and Peñuelas, J.: Drought impacts on terrestrial primary production underestimated by satellite monitoring, Nat. Geosci., 12,
264–270, https://doi.org/10.1038/s41561-019-0318-6, 2019. a
Tschumi, E. and Zscheischler, J.: Countrywide climate features during recorded climate-related disasters, Climatic Change, 158, 593–609,
https://doi.org/10.1007/s10584-019-02556-w, 2020. a
Van der Wiel, K., Stoop, L., van Zuijlen, B., Blackport, R., van den Broek, M., and Selten, F.: Meteorological conditions leading to extreme low variable
renewable energy production and extreme high energy shortfall, Renew. Sustain. Energy Rev., 111, 261–275, https://doi.org/10.1016/j.rser.2019.04.065, 2019a. a
Van der Wiel, K., Wanders, N., Selten, F., and Bierkens, M.: Added value of
large ensemble simulations for assessing extreme river discharge in a 2 ∘C warmer world, Geophys. Res. Lett., 46, 2093–2102, https://doi.org/10.1029/2019GL081967, 2019b. a
Van der Wiel, K., Selten, F. M., Bintanja, R., Blackport, R., and Screen, J. A.: Ensemble climate-impact modelling: extreme impacts from moderate
meteorological conditions, Environ. Res. Lett., 15, 034050,
https://doi.org/10.1088/1748-9326/ab7668, 2020. a, b, c
Vogel, J., Rivoire, P., Deidda, C., Sauter, C. A., Tschumi, E.: Identify_crop_yield_drivers, available at: https://github.com/jo-vogel/Identify_crop_yield_drivers, last access: February 2021. a
Yuan, W., Zheng, Y., Piao, S., Ciais, P., Lombardozzi, D., Wang, Y., Ryu, Y.,
Chen, G., Dong, W., Hu, Z., Jain, A. K., Jiang, C., Kato, E., Li, S.,
Lienert, S., Liu, S., Nabel, J. E., Qin, Z., Quine, T., Sitch, S., Smith, W. K., Wang, F., Wu, C., Xiao, Z., and Yang, S.: Increased atmospheric vapor
pressure deficit reduces global vegetation growth, Sci. Adv., 5, eaax1396, https://doi.org/10.1126/sciadv.aax1396, 2019. a, b
Zhang, S., Tao, F., and Zhang, Z.: Spatial and temporal changes in vapor
pressure deficit and their impacts on crop yields in China during 1980–2008, J. Meteorol. Res., 31, 800–808, https://doi.org/10.1007/s13351-017-6137-z, 2017. a, b, c
Zheng, B., Chenu, K., Doherty, A., and Chapman, S.: The APSIM-wheat module (7.5 R3008), Agricultural Production Systems Simulator (APSIM) Initiative, Toowoomba, Australia, available at: https://www.apsim.info/documentation/model-documentation/crop-module-documentation/wheat/
(last access: 18 November 2020), 2014. a, b, c
Zscheischler, J., Mahecha, M. D., Harmeling, S., and Reichstein, M.: Detection and attribution of large spatiotemporal extreme events in Earth observation data, Ecol. Inform., 15, 66–73, https://doi.org/10.1016/j.ecoinf.2013.03.004, 2013.
a
Zscheischler, J., Fatichi, S., Wolf, S., Blanken, P. D., Bohrer, G., Clark, K., Desai, A. R., Hollinger, D., Keenan, T., Novick, K. A., and Seneviratne,
S. I.: Short-term favorable weather conditions are an important control of
interannual variability in carbon and water fluxes, J. Geophys. Res.-Biogeo., 121, 2186–2198, https://doi.org/10.1002/2016JG003503, 2016. a
Zscheischler, J., Westra, S., van den Hurk, B., Seneviratne, S. I., Ward, P. J., Pitman, A., AghaKouchak, A., Bresch, D. N., Leonard, M., Wahl, T., and
Zhang, X.: Future climate risk from compound events, Nat. Clim. Change, 8, 469–477, https://doi.org/10.1038/s41558-018-0156-3, 2018. a
Zscheischler, J., Martius, O., Westra, S., Bevacqua, E. R. C., Horton, R. M.,
van den Hurk, B., AghaKouchak, A., Jézéquel, A., Mahecha, M. D.,
Maraun, D., Ramos, A. M., Ridder, N., Thiery, W., and Vignotto, E.: A typology of compound weather and climate events, Nat. Rev. Earth Environ., 1, 333–347, https://doi.org/10.1038/s43017-020-0060-z, 2020. a, b
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.
We present a statistical approach for automatically identifying multiple drivers of extreme...
Altmetrics
Final-revised paper
Preprint