Articles | Volume 9, issue 1
https://doi.org/10.5194/esd-9-227-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-9-227-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regional scaling of annual mean precipitation and water availability with global temperature change
Institute of Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
International Institute for Applied Systems Analysis, Laxenburg, Austria
Lukas Gudmundsson
Institute of Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Sonia I. Seneviratne
Institute of Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
Related authors
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
Short summary
Short summary
We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
Short summary
Short summary
Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Peter Burek, Yusuke Satoh, Taher Kahil, Ting Tang, Peter Greve, Mikhail Smilovic, Luca Guillaumot, Fang Zhao, and Yoshihide Wada
Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, https://doi.org/10.5194/gmd-13-3267-2020, 2020
Short summary
Short summary
We present the new global hydrological model "Community Water Model" (CWatM), which can be used globally and regionally. The model is open source and written with the Python programming language. It uses global, freely available data in a smart and state-of-the-art format. It includes the major hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demand from the agriculture, domestic, and industrial sectors.
Richard Wartenburger, Martin Hirschi, Markus G. Donat, Peter Greve, Andy J. Pitman, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, https://doi.org/10.5194/gmd-10-3609-2017, 2017
Short summary
Short summary
This article analyses regional changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. Readers are encouraged to use the online tool for visualization of specific indices of interest, e.g. to assess their response to 1.5 or 2 °C global warming.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
Short summary
Short summary
The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
Christoph Nathanael von Matt, Regula Muelchi, Lukas Gudmundsson, and Olivia Martius
Nat. Hazards Earth Syst. Sci., 24, 1975–2001, https://doi.org/10.5194/nhess-24-1975-2024, https://doi.org/10.5194/nhess-24-1975-2024, 2024
Short summary
Short summary
The simultaneous occurrence of meteorological (precipitation), agricultural (soil moisture), and hydrological (streamflow) drought can lead to augmented impacts. By analysing drought indices derived from the newest climate scenarios for Switzerland (CH2018, Hydro-CH2018), we show that with climate change the concurrence of all drought types will increase in all studied regions of Switzerland. Our results stress the benefits of and need for both mitigation and adaptation measures at early stages.
Sarah Schöngart, Lukas Gudmundsson, Mathias Hauser, Peter Pfleiderer, Quentin Lejeune, Shruti Nath, Sonia Isabelle Seneviratne, and Carl-Friedrich Schleußner
EGUsphere, https://doi.org/10.5194/egusphere-2024-278, https://doi.org/10.5194/egusphere-2024-278, 2024
Short summary
Short summary
Precipitation and temperature are two of the most impact-relevant climatic variables. Their joint distribution largely determines the division into climate regimes. Yet, projecting precipitation and temperature data under different emission scenarios relies on complex models that are computationally expensive. In this study, we propose a method that allows to generate monthly means of local precipitation and temperature at low computational costs.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-993, https://doi.org/10.5194/egusphere-2024-993, 2024
Short summary
Short summary
This study uses deep learning to predict spatially contiguous water runoff in Switzerland from 1962–2023. It outperforms traditional models, requiring less data and computational power. Key findings include increased dry years and summer water scarcity. This method offers significant advancements in water monitoring.
Dominik L. Schumacher, Mariam Zachariah, Friederike Otto, Clair Barnes, Sjoukje Philip, Sarah Kew, Maja Vahlberg, Roop Singh, Dorothy Heinrich, Julie Arrighi, Maarten van Aalst, Mathias Hauser, Martin Hirschi, Verena Bessenbacher, Lukas Gudmundsson, Hiroko K. Beaudoing, Matthew Rodell, Sihan Li, Wenchang Yang, Gabriel A. Vecchi, Luke J. Harrington, Flavio Lehner, Gianpaolo Balsamo, and Sonia I. Seneviratne
Earth Syst. Dynam., 15, 131–154, https://doi.org/10.5194/esd-15-131-2024, https://doi.org/10.5194/esd-15-131-2024, 2024
Short summary
Short summary
The 2022 summer was accompanied by widespread soil moisture deficits, including an unprecedented drought in Europe. Combining several observation-based estimates and models, we find that such an event has become at least 5 and 20 times more likely due to human-induced climate change in western Europe and the northern extratropics, respectively. Strong regional warming fuels soil desiccation; hence, projections indicate even more potent future droughts as we progress towards a 2 °C warmer world.
Yann Quilcaille, Lukas Gudmundsson, and Sonia I. Seneviratne
Earth Syst. Dynam., 14, 1333–1362, https://doi.org/10.5194/esd-14-1333-2023, https://doi.org/10.5194/esd-14-1333-2023, 2023
Short summary
Short summary
Climate models are powerful tools, but they have high computational costs, hindering their use in exploring future climate extremes. We demonstrate MESMER-X, the only existing emulator for spatial climate extremes (heatwaves, fires, droughts) that mimics all of their relevant properties. Thanks to its negligible computational cost, MESMER-X may greatly accelerate the exploration of future climate extremes or enable the integration of climate extremes in economic and financial models.
Shruti Nath, Lukas Gudmundsson, Jonas Schwaab, Gregory Duveiller, Steven J. De Hertog, Suqi Guo, Felix Havermann, Fei Luo, Iris Manola, Julia Pongratz, Sonia I. Seneviratne, Carl F. Schleussner, Wim Thiery, and Quentin Lejeune
Geosci. Model Dev., 16, 4283–4313, https://doi.org/10.5194/gmd-16-4283-2023, https://doi.org/10.5194/gmd-16-4283-2023, 2023
Short summary
Short summary
Tree cover changes play a significant role in climate mitigation and adaptation. Their regional impacts are key in informing national-level decisions and prioritising areas for conservation efforts. We present a first step towards exploring these regional impacts using a simple statistical device, i.e. emulator. The emulator only needs to train on climate model outputs representing the maximal impacts of aff-, re-, and deforestation, from which it explores plausible in-between outcomes itself.
Ryan S. Padrón, Lukas Gudmundsson, Laibao Liu, Vincent Humphrey, and Sonia I. Seneviratne
Biogeosciences, 19, 5435–5448, https://doi.org/10.5194/bg-19-5435-2022, https://doi.org/10.5194/bg-19-5435-2022, 2022
Short summary
Short summary
The answer to how much carbon land ecosystems are projected to remove from the atmosphere until 2100 is different for each Earth system model. We find that differences across models are primarily explained by the annual land carbon sink dependence on temperature and soil moisture, followed by the dependence on CO2 air concentration, and by average climate conditions. Our insights on why each model projects a relatively high or low land carbon sink can help to reduce the underlying uncertainty.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
Short summary
Short summary
We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Thomas Lees, Steven Reece, Frederik Kratzert, Daniel Klotz, Martin Gauch, Jens De Bruijn, Reetik Kumar Sahu, Peter Greve, Louise Slater, and Simon J. Dadson
Hydrol. Earth Syst. Sci., 26, 3079–3101, https://doi.org/10.5194/hess-26-3079-2022, https://doi.org/10.5194/hess-26-3079-2022, 2022
Short summary
Short summary
Despite the accuracy of deep learning rainfall-runoff models, we are currently uncertain of what these models have learned. In this study we explore the internals of one deep learning architecture and demonstrate that the model learns about intermediate hydrological stores of soil moisture and snow water, despite never having seen data about these processes during training. Therefore, we find evidence that the deep learning approach learns a physically realistic mapping from inputs to outputs.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
Short summary
Short summary
Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Lea Beusch, Zebedee Nicholls, Lukas Gudmundsson, Mathias Hauser, Malte Meinshausen, and Sonia I. Seneviratne
Geosci. Model Dev., 15, 2085–2103, https://doi.org/10.5194/gmd-15-2085-2022, https://doi.org/10.5194/gmd-15-2085-2022, 2022
Short summary
Short summary
We introduce the first chain of computationally efficient Earth system model (ESM) emulators to translate user-defined greenhouse gas emission pathways into regional temperature change time series accounting for all major sources of climate change projection uncertainty. By combining the global mean emulator MAGICC with the spatially resolved emulator MESMER, we can derive ESM-specific and constrained probabilistic emulations to rapidly provide targeted climate information at the local scale.
Peter Burek, Yusuke Satoh, Taher Kahil, Ting Tang, Peter Greve, Mikhail Smilovic, Luca Guillaumot, Fang Zhao, and Yoshihide Wada
Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, https://doi.org/10.5194/gmd-13-3267-2020, 2020
Short summary
Short summary
We present the new global hydrological model "Community Water Model" (CWatM), which can be used globally and regionally. The model is open source and written with the Python programming language. It uses global, freely available data in a smart and state-of-the-art format. It includes the major hydrological processes but also takes into account human activities, such as water use and reservoir regulation, by calculating water demand from the agriculture, domestic, and industrial sectors.
Hong Xuan Do, Fang Zhao, Seth Westra, Michael Leonard, Lukas Gudmundsson, Julien Eric Stanislas Boulange, Jinfeng Chang, Philippe Ciais, Dieter Gerten, Simon N. Gosling, Hannes Müller Schmied, Tobias Stacke, Camelia-Eliza Telteu, and Yoshihide Wada
Hydrol. Earth Syst. Sci., 24, 1543–1564, https://doi.org/10.5194/hess-24-1543-2020, https://doi.org/10.5194/hess-24-1543-2020, 2020
Short summary
Short summary
We presented a global comparison between observed and simulated trends in a flood index over the 1971–2005 period using the Global Streamflow Indices and Metadata archive and six global hydrological models available through The Inter-Sectoral Impact Model Intercomparison Project. Streamflow simulations over 2006–2099 period robustly project high flood hazard in several regions. These high-flood-risk areas, however, are under-sampled by the current global streamflow databases.
Ryan S. Padrón, Lukas Gudmundsson, Dominik Michel, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 24, 793–807, https://doi.org/10.5194/hess-24-793-2020, https://doi.org/10.5194/hess-24-793-2020, 2020
Short summary
Short summary
We focus on the net exchange of water between land and air via evapotranspiration and dew during the night. We provide, for the first time, an overview of the magnitude and variability of this flux across the globe from observations and climate models. Nocturnal water loss from land is 7 % of total evapotranspiration on average and can be greater than 15 % locally. Our results highlight the relevance of this often overlooked flux, with implications for water resources and climate studies.
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.
Gionata Ghiggi, Vincent Humphrey, Sonia I. Seneviratne, and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, https://doi.org/10.5194/essd-11-1655-2019, 2019
Short summary
Short summary
Freshwater resources are of high societal relevance and understanding their past variability is vital to water management in the context of current and future climatic change. This study introduces GRUN: the first global gridded monthly reconstruction of runoff covering the period from 1902 to 2014. The dataset agrees on average much better with the streamflow observations than an ensemble of 13 state-of-the-art global hydrological models and will foster the understanding of freshwater dynamics.
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
Vincent Humphrey and Lukas Gudmundsson
Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, https://doi.org/10.5194/essd-11-1153-2019, 2019
Short summary
Short summary
Because changes in freshwater availability can impact many natural ecosystems and human activities, it is crucial to better understand long-term changes in the water cycle. This dataset is a reconstruction of past changes in land water storage over the last century, obtained by combining satellite observations with historical weather data. It can be used to investigate both regional changes in freshwater availability or drought frequency and long-term changes in the global water cycle.
Mathias Hauser, Wim Thiery, and Sonia Isabelle Seneviratne
Earth Syst. Dynam., 10, 157–169, https://doi.org/10.5194/esd-10-157-2019, https://doi.org/10.5194/esd-10-157-2019, 2019
Short summary
Short summary
We develop a method to keep the amount of water in the soil at the present-day level, using only local water sources in a global climate model. This leads to less drying over many land areas, but also decreases river runoff. We find that temperature extremes in the 21st century decrease substantially using our method. This provides a new perspective on how land water can influence regional climate and introduces land water management as potential tool for local mitigation of climate change.
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.
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.
Hong Xuan Do, Lukas Gudmundsson, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, https://doi.org/10.5194/essd-10-765-2018, 2018
Short summary
Short summary
The production of 30 959 daily streamflow time series in the Global Streamflow and Metadata Archive (GSIM) project is presented. The paper also describes the development of three metadata products that are freely available. Having collated an unprecedented number of stations and associated metadata, GSIM can be used to advance large-scale hydrological research and improve understanding of the global water cycle.
Lukas Gudmundsson, Hong Xuan Do, Michael Leonard, and Seth Westra
Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018, https://doi.org/10.5194/essd-10-787-2018, 2018
Short summary
Short summary
Time-series indices characterizing streamflow at annual, seasonal and monthly resolution at more than 30 000 stations around the world are presented. The data belong to the Global Streamflow and Metadata Archive (GSIM) and allow for an assessment of water balance components, hydrological extremes and the seasonality of water availability. The quality of the data is tested using automated methods to aid potential users to gauge the suitability of the data for specific applications.
Richard Wartenburger, Martin Hirschi, Markus G. Donat, Peter Greve, Andy J. Pitman, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, https://doi.org/10.5194/gmd-10-3609-2017, 2017
Short summary
Short summary
This article analyses regional changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. Readers are encouraged to use the online tool for visualization of specific indices of interest, e.g. to assess their response to 1.5 or 2 °C global warming.
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.
Mathias Hauser, René Orth, and Sonia I. Seneviratne
Geosci. Model Dev., 10, 1665–1677, https://doi.org/10.5194/gmd-10-1665-2017, https://doi.org/10.5194/gmd-10-1665-2017, 2017
Short summary
Short summary
Water in the soil can influence temperature and precipitation of the atmosphere. However, the atmosphere also alters the soil moisture content. Climate model simulations prescribing soil moisture are a means to decouple these relationships. We find that the atmospheric response depends strongly on the method used to fix the soil moisture, as well as on the employed soil moisture data set.
Martin Hirschi and Sonia I. Seneviratne
Earth Syst. Sci. Data, 9, 251–258, https://doi.org/10.5194/essd-9-251-2017, https://doi.org/10.5194/essd-9-251-2017, 2017
Short summary
Short summary
Terrestrial water storage comprises all forms of water storage on land surfaces, and its seasonal and inter-annual variations are mostly determined by soil moisture, groundwater, snow cover, and surface water. Soil moisture, especially, contributes to land--atmosphere coupling in an essential way. This paper presents an update of a basin-scale diagnostic dataset of monthly variations in terrestrial water storage for large river basins worldwide.
Lukas Gudmundsson and Sonia I. Seneviratne
Earth Syst. Sci. Data, 8, 279–295, https://doi.org/10.5194/essd-8-279-2016, https://doi.org/10.5194/essd-8-279-2016, 2016
Short summary
Short summary
Despite the scientific and societal relevance of freshwater, there are to date no observation-based pan-European runoff estimates available. Here we employ state-of-the-art techniques to estimate monthly runoff rates in Europe. The new data product is based on an unprecedented collection of river flow observations which are combined with atmospheric variables using machine learning. Potential applications of the presented product include climatological assessments and drought monitoring.
Peter Greve, Lukas Gudmundsson, Boris Orlowsky, and Sonia I. Seneviratne
Hydrol. Earth Syst. Sci., 20, 2195–2205, https://doi.org/10.5194/hess-20-2195-2016, https://doi.org/10.5194/hess-20-2195-2016, 2016
Short summary
Short summary
The widely used Budyko framework is by definition limited to steady-state conditions. In this study we analytically derive a new, two-parameter formulation of the Budyko framework that represents conditions under which evapotranspiration exceeds precipitation. This is technically achieved by rotating the water supply limit within the Budyko space. The new formulation is shown to be capable to represent first-order seasonal dynamics within the hydroclimatological system.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci., 19, 2859–2879, https://doi.org/10.5194/hess-19-2859-2015, https://doi.org/10.5194/hess-19-2859-2015, 2015
Short summary
Short summary
Water storages and fluxes on land are key variables in the Earth system. To provide context for local investigations and to understand phenomena that emerge at large spatial scales, information on continental freshwater dynamics is needed. This paper presents a methodology to estimate continental-scale runoff on a 0.5° spatial grid, which combines the advantages of in situ observations with the power of machine learning regression. The resulting runoff estimates compare well with observations.
L. Gudmundsson and S. I. Seneviratne
Proc. IAHS, 369, 75–79, https://doi.org/10.5194/piahs-369-75-2015, https://doi.org/10.5194/piahs-369-75-2015, 2015
Short summary
Short summary
Recent climate projections suggest changes in European drought frequency, indicating increased drought risk in the south and less droughts in the north. Here we show that a similar change pattern can be identified in the observed record. The results raise the question whether observed changes in European drought frequency are a consequence of anthropogenic climate change.
L. Gudmundsson and S. I. Seneviratne
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-10-13191-2013, https://doi.org/10.5194/hessd-10-13191-2013, 2013
Manuscript not accepted for further review
Related subject area
Earth system change: climate prediction
Past and future response of the North Atlantic warming hole to anthropogenic forcing
Performance-based sub-selection of CMIP6 models for impact assessments in Europe
Emergent constraints for the climate system as effective parameters of bulk differential equations
Ensemble forecast of an index of the Madden–Julian Oscillation using a stochastic weather generator based on circulation analogs
Reconstructions and predictions of the global carbon budget with an emission-driven Earth system model
PInc-PanTher estimates of Arctic permafrost soil carbon under the GeoMIP G6solar and G6sulfur experiments
El Niño–Southern Oscillation (ENSO) predictability in equilibrated warmer climates
Investigation of the extreme wet–cold compound events changes between 2025–2049 and 1980–2004 using regional simulations in Greece
Constraining low-frequency variability in climate projections to predict climate on decadal to multi-decadal timescales – a poor man's initialized prediction system
Resilience of UK crop yields to compound climate change
Evaluating uncertainty in aerosol forcing of tropical precipitation shifts
A non-stationary extreme-value approach for climate projection ensembles: application to snow loads in the French Alps
Atmospheric regional climate projections for the Baltic Sea region until 2100
Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble
Extreme metrics from large ensembles: investigating the effects of ensemble size on their estimates
Reduced-complexity model for the impact of anthropogenic CO2 emissions on future glacial cycles
Is time a variable like the others in multivariate statistical downscaling and bias correction?
Trivial improvements in predictive skill due to direct reconstruction of the global carbon cycle
Abrupt climate change as a rate-dependent cascading tipping point
Bayesian estimation of Earth's climate sensitivity and transient climate response from observational warming and heat content datasets
Comparison of CMIP6 historical climate simulations and future projected warming to an empirical model of global climate
Assessment of a full-field initialized decadal climate prediction system with the CMIP6 version of EC-Earth
A new view of heat wave dynamics and predictability over the eastern Mediterranean
Emergent constraints on equilibrium climate sensitivity in CMIP5: do they hold for CMIP6?
Dating hiatuses: a statistical model of the recent slowdown in global warming and the next one
Calibrating large-ensemble European climate projections using observational data
Reduced global warming from CMIP6 projections when weighting models by performance and independence
Emergent constraints on transient climate response (TCR) and equilibrium climate sensitivity (ECS) from historical warming in CMIP5 and CMIP6 models
Multivariate bias corrections of climate simulations: which benefits for which losses?
Historical and future anthropogenic warming effects on droughts, fires and fire emissions of CO2 and PM2.5 in equatorial Asia when 2015-like El Niño events occur
The impact of regional climate model formulation and resolution on simulated precipitation in Africa
Bayesian deconstruction of climate sensitivity estimates using simple models: implicit priors and the confusion of the inverse
Intensification of the hydrological cycle expected in West Africa over the 21st century
Winter hydrometeorological extreme events modulated by large-scale atmospheric circulation in southern Ontario
Investigating ENSO and its teleconnections under climate change in an ensemble view – a new perspective
Human influence on European winter wind storms such as those of January 2018
September Arctic sea ice minimum prediction – a skillful new statistical approach
ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing
Predicting near-term variability in ocean carbon uptake
A mathematical approach to understanding emergent constraints
Seasonal prediction skill of East Asian summer monsoon in CMIP5 models
Assessing the impact of a future volcanic eruption on decadal predictions
Projections of East Asian summer monsoon change at global warming of 1.5 and 2 °C
Changes in extremely hot days under stabilized 1.5 and 2.0 °C global warming scenarios as simulated by the HAPPI multi-model ensemble
Irreversible ocean thermal expansion under carbon dioxide removal
Changes in tropical cyclones under stabilized 1.5 and 2.0 °C global warming scenarios as simulated by the Community Atmospheric Model under the HAPPI protocols
Selecting a climate model subset to optimise key ensemble properties
Return levels of temperature extremes in southern Pakistan
On the meaning of independence in climate science
Minimal change of thermal continentality in Slovakia within the period 1961–2013
Saïd Qasmi
Earth Syst. Dynam., 14, 685–695, https://doi.org/10.5194/esd-14-685-2023, https://doi.org/10.5194/esd-14-685-2023, 2023
Short summary
Short summary
A new statistical method combining climate models and observations confirms the anthropogenic role in the cooling of the North Atlantic warming hole. Aerosols increase sea surface temperature (SST), while greenhouse gases contribute to the cooling over the 1870–2020 period. The method is able to reduce model uncertainty in the SST projections by 65% in the short term and up to 50% in the long term, excluding previous unlikely temperature increase scenarios.
Tamzin E. Palmer, Carol F. McSweeney, Ben B. B. Booth, Matthew D. K. Priestley, Paolo Davini, Lukas Brunner, Leonard Borchert, and Matthew B. Menary
Earth Syst. Dynam., 14, 457–483, https://doi.org/10.5194/esd-14-457-2023, https://doi.org/10.5194/esd-14-457-2023, 2023
Short summary
Short summary
We carry out an assessment of an ensemble of general climate models (CMIP6) based on the ability of the models to represent the key physical processes that are important for representing European climate. Filtering the models with the assessment leads to more models with less global warming being removed, and this shifts the lower part of the projected temperature range towards greater warming. This is in contrast to the affect of weighting the ensemble using global temperature trends.
Chris Huntingford, Peter M. Cox, Mark S. Williamson, Joseph J. Clarke, and Paul D. L. Ritchie
Earth Syst. Dynam., 14, 433–442, https://doi.org/10.5194/esd-14-433-2023, https://doi.org/10.5194/esd-14-433-2023, 2023
Short summary
Short summary
Emergent constraints (ECs) reduce the spread of projections between climate models. ECs estimate changes to climate features impacting adaptation policy, and with this high profile, the method is under scrutiny. Asking
What is an EC?, we suggest they are often the discovery of parameters that characterise hidden large-scale equations that climate models solve implicitly. We present this conceptually via two examples. Our analysis implies possible new paths to link ECs and physical processes.
Meriem Krouma, Riccardo Silini, and Pascal Yiou
Earth Syst. Dynam., 14, 273–290, https://doi.org/10.5194/esd-14-273-2023, https://doi.org/10.5194/esd-14-273-2023, 2023
Short summary
Short summary
We present a simple system to forecast the Madden–Julian Oscillation (MJO). We use atmospheric circulation as input to our system. We found a good-skill forecast of the MJO amplitude within 40 d using this methodology. Comparing our results with ECMWF and machine learning forecasts confirmed the good skill of our system.
Hongmei Li, Tatiana Ilyina, Tammas Loughran, Aaron Spring, and Julia Pongratz
Earth Syst. Dynam., 14, 101–119, https://doi.org/10.5194/esd-14-101-2023, https://doi.org/10.5194/esd-14-101-2023, 2023
Short summary
Short summary
For the first time, our decadal prediction system based on Max Planck Institute Earth System Model enables prognostic atmospheric CO2 with an interactive carbon cycle. The evolution of CO2 fluxes and atmospheric CO2 growth is reconstructed well by assimilating data products; retrospective predictions show high confidence in predicting changes in the next year. The Earth system predictions provide valuable inputs for understanding the global carbon cycle and informing climate-relevant policy.
Aobo Liu, John C. Moore, and Yating Chen
Earth Syst. Dynam., 14, 39–53, https://doi.org/10.5194/esd-14-39-2023, https://doi.org/10.5194/esd-14-39-2023, 2023
Short summary
Short summary
Permafrost thaws and releases carbon (C) as the Arctic warms. Most earth system models (ESMs) have poor estimates of C stored now, so their future C losses are much lower than using the permafrost C model with climate inputs from six ESMs. Bias-corrected soil temperatures and plant productivity plus geoengineering lowering global temperatures from a no-mitigation baseline scenario to a moderate emissions level keep C in the soil worth about USD 0–70 (mean 20) trillion in climate damages by 2100.
Yiyu Zheng, Maria Rugenstein, Patrick Pieper, Goratz Beobide-Arsuaga, and Johanna Baehr
Earth Syst. Dynam., 13, 1611–1623, https://doi.org/10.5194/esd-13-1611-2022, https://doi.org/10.5194/esd-13-1611-2022, 2022
Short summary
Short summary
El Niño–Southern Oscillation (ENSO) is one of the dominant climatic phenomena in the equatorial Pacific. Understanding and predicting how ENSO might change in a warmer climate is both societally and scientifically important. We use 1000-year-long simulations from seven climate models to analyze ENSO in an idealized stable climate. We show that ENSO will be weaker and last shorter under the warming, while the skill of ENSO prediction will unlikely change.
Iason Markantonis, Diamando Vlachogiannis, Athanasios Sfetsos, and Ioannis Kioutsioukis
Earth Syst. Dynam., 13, 1491–1504, https://doi.org/10.5194/esd-13-1491-2022, https://doi.org/10.5194/esd-13-1491-2022, 2022
Short summary
Short summary
This work focuses on the study of daily wet–cold compound events in Greece in the period November–April. We firstly study the historic period 1980–2004 in which we validate projection models with observations. Then we compare the model results with future period 2025–2049 RCP4.5 and RCP8.5 scenarios. The aim of the study is to calculate the probability of the events and to locate the areas where those are higher and how the probabilities will change at the future.
Rashed Mahmood, Markus G. Donat, Pablo Ortega, Francisco J. Doblas-Reyes, Carlos Delgado-Torres, Margarida Samsó, and Pierre-Antoine Bretonnière
Earth Syst. Dynam., 13, 1437–1450, https://doi.org/10.5194/esd-13-1437-2022, https://doi.org/10.5194/esd-13-1437-2022, 2022
Short summary
Short summary
Near-term climate change projections are strongly affected by the uncertainty from internal climate variability. Here we present a novel approach to reduce such uncertainty by constraining decadal-scale variability in the projections using observations. The constrained ensembles show significant added value over the unconstrained ensemble in predicting global climate 2 decades ahead. We also show the applicability of regional constraints for attributing predictability to certain ocean regions.
Louise J. Slater, Chris Huntingford, Richard F. Pywell, John W. Redhead, and Elizabeth J. Kendon
Earth Syst. Dynam., 13, 1377–1396, https://doi.org/10.5194/esd-13-1377-2022, https://doi.org/10.5194/esd-13-1377-2022, 2022
Short summary
Short summary
This work considers how wheat yields are affected by weather conditions during the three main wheat growth stages in the UK. Impacts are strongest in years with compound weather extremes across multiple growth stages. Future climate projections are beneficial for wheat yields, on average, but indicate a high risk of unseen weather conditions which farmers may struggle to adapt to and mitigate against.
Amy H. Peace, Ben B. B. Booth, Leighton A. Regayre, Ken S. Carslaw, David M. H. Sexton, Céline J. W. Bonfils, and John W. Rostron
Earth Syst. Dynam., 13, 1215–1232, https://doi.org/10.5194/esd-13-1215-2022, https://doi.org/10.5194/esd-13-1215-2022, 2022
Short summary
Short summary
Anthropogenic aerosol emissions have been linked to driving climate responses such as shifts in the location of tropical rainfall. However, the interaction of aerosols with climate remains one of the most uncertain aspects of climate modelling and limits our ability to predict future climate change. We use an ensemble of climate model simulations to investigate what impact the large uncertainty in how aerosols interact with climate has on predicting future tropical rainfall shifts.
Erwan Le Roux, Guillaume Evin, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
Earth Syst. Dynam., 13, 1059–1075, https://doi.org/10.5194/esd-13-1059-2022, https://doi.org/10.5194/esd-13-1059-2022, 2022
Short summary
Short summary
Anticipating risks related to climate extremes is critical for societal adaptation to climate change. In this study, we propose a statistical method in order to estimate future climate extremes from past observations and an ensemble of climate change simulations. We apply this approach to snow load data available in the French Alps at 1500 m elevation and find that extreme snow load is projected to decrease by −2.9 kN m−2 (−50 %) between 1986–2005 and 2080–2099 for a high-emission scenario.
Ole Bøssing Christensen, Erik Kjellström, Christian Dieterich, Matthias Gröger, and Hans Eberhard Markus Meier
Earth Syst. Dynam., 13, 133–157, https://doi.org/10.5194/esd-13-133-2022, https://doi.org/10.5194/esd-13-133-2022, 2022
Short summary
Short summary
The Baltic Sea Region is very sensitive to climate change, whose impacts could easily exacerbate biodiversity stress from society and eutrophication of the Baltic Sea. Therefore, there has been a focus on estimations of future climate change and its impacts in recent research. Models show a strong warming, in particular in the north in winter. Precipitation is projected to increase in the whole region apart from the south during summer. New results improve estimates of future climate change.
Guillaume Evin, Samuel Somot, and Benoit Hingray
Earth Syst. Dynam., 12, 1543–1569, https://doi.org/10.5194/esd-12-1543-2021, https://doi.org/10.5194/esd-12-1543-2021, 2021
Short summary
Short summary
This research paper proposes an assessment of mean climate change responses and related uncertainties over Europe for mean seasonal temperature and total seasonal precipitation. An advanced statistical approach is applied to a large ensemble of 87 high-resolution EURO-CORDEX projections. For the first time, we provide a comprehensive estimation of the relative contribution of GCMs and RCMs, RCP scenarios, and internal variability to the total variance of a very large ensemble.
Claudia Tebaldi, Kalyn Dorheim, Michael Wehner, and Ruby Leung
Earth Syst. Dynam., 12, 1427–1501, https://doi.org/10.5194/esd-12-1427-2021, https://doi.org/10.5194/esd-12-1427-2021, 2021
Short summary
Short summary
We address the question of how large an initial condition ensemble of climate model simulations should be if we are concerned with accurately projecting future changes in temperature and precipitation extremes. We find that for most cases (and both models considered), an ensemble of 20–25 members is sufficient for many extreme metrics, spatial scales and time horizons. This may leave computational resources to tackle other uncertainties in climate model simulations with our ensembles.
Stefanie Talento and Andrey Ganopolski
Earth Syst. Dynam., 12, 1275–1293, https://doi.org/10.5194/esd-12-1275-2021, https://doi.org/10.5194/esd-12-1275-2021, 2021
Short summary
Short summary
We propose a model for glacial cycles and produce an assessment of possible trajectories for the next 1 million years. Under natural conditions, the next glacial inception would most likely occur ∼50 kyr after present. We show that fossil-fuel CO2 releases can have an extremely long-term effect. Potentially achievable CO2 anthropogenic emissions during the next centuries will most likely provoke ice-free conditions in the Northern Hemisphere landmasses throughout the next half a million years.
Yoann Robin and Mathieu Vrac
Earth Syst. Dynam., 12, 1253–1273, https://doi.org/10.5194/esd-12-1253-2021, https://doi.org/10.5194/esd-12-1253-2021, 2021
Short summary
Short summary
We propose a new multivariate downscaling and bias correction approach called
time-shifted multivariate bias correction, which aims to correct temporal dependencies in addition to inter-variable and spatial ones. Our method is evaluated in a
perfect model experimentcontext where simulations are used as pseudo-observations. The results show a large reduction of the biases in the temporal properties, while inter-variable and spatial dependence structures are still correctly adjusted.
Aaron Spring, István Dunkl, Hongmei Li, Victor Brovkin, and Tatiana Ilyina
Earth Syst. Dynam., 12, 1139–1167, https://doi.org/10.5194/esd-12-1139-2021, https://doi.org/10.5194/esd-12-1139-2021, 2021
Short summary
Short summary
Numerical carbon cycle prediction models usually do not start from observed carbon states due to sparse observations. Instead, only physical climate is reconstructed, assuming that the carbon cycle follows indirectly. Here, we test in an idealized framework how well this indirect and direct reconstruction with perfect observations works. We find that indirect reconstruction works quite well and that improvements from the direct method are limited, strengthening the current indirect use.
Johannes Lohmann, Daniele Castellana, Peter D. Ditlevsen, and Henk A. Dijkstra
Earth Syst. Dynam., 12, 819–835, https://doi.org/10.5194/esd-12-819-2021, https://doi.org/10.5194/esd-12-819-2021, 2021
Short summary
Short summary
Tipping of one climate subsystem could trigger a cascade of subsequent tipping points and even global-scale climate tipping. Sequential shifts of atmosphere, sea ice and ocean have been recorded in proxy archives of past climate change. Based on this we propose a conceptual model for abrupt climate changes of the last glacial. Here, rate-induced tipping enables tipping cascades in systems with relatively weak coupling. An early warning signal is proposed that may detect such a tipping.
Philip Goodwin and B. B. Cael
Earth Syst. Dynam., 12, 709–723, https://doi.org/10.5194/esd-12-709-2021, https://doi.org/10.5194/esd-12-709-2021, 2021
Short summary
Short summary
Climate sensitivityis a key measure of how sensitive Earth's climate is to human release of greenhouse gasses, such as from fossil fuels. However, there is still uncertainty as to the value of climate sensitivity, in part because different climate feedbacks operate over multiple timescales. This study assesses hundreds of millions of climate simulations against historical observations to reduce uncertainty in climate sensitivity and future climate warming.
Laura A. McBride, Austin P. Hope, Timothy P. Canty, Brian F. Bennett, Walter R. Tribett, and Ross J. Salawitch
Earth Syst. Dynam., 12, 545–579, https://doi.org/10.5194/esd-12-545-2021, https://doi.org/10.5194/esd-12-545-2021, 2021
Short summary
Short summary
We use a reduced-complexity climate model trained by observations to show that at the current rate of human release of CO2, total cumulative emissions will pass the 66 % likelihood of limiting warming to 1.5° or 2°C in about 10 and 35 years, respectively. We also show that complex climate models often used to guide policy tend to warm faster than observed over the past few decades. To achieve the Paris Climate Agreement, CO2 and CH4 emissions must be severely curtailed in the next decade.
Roberto Bilbao, Simon Wild, Pablo Ortega, Juan Acosta-Navarro, Thomas Arsouze, Pierre-Antoine Bretonnière, Louis-Philippe Caron, Miguel Castrillo, Rubén Cruz-García, Ivana Cvijanovic, Francisco Javier Doblas-Reyes, Markus Donat, Emanuel Dutra, Pablo Echevarría, An-Chi Ho, Saskia Loosveldt-Tomas, Eduardo Moreno-Chamarro, Núria Pérez-Zanon, Arthur Ramos, Yohan Ruprich-Robert, Valentina Sicardi, Etienne Tourigny, and Javier Vegas-Regidor
Earth Syst. Dynam., 12, 173–196, https://doi.org/10.5194/esd-12-173-2021, https://doi.org/10.5194/esd-12-173-2021, 2021
Short summary
Short summary
This paper presents and evaluates a set of retrospective decadal predictions with the EC-Earth3 climate model. These experiments successfully predict past changes in surface air temperature but show poor predictive capacity in the subpolar North Atlantic, a well-known source region of decadal climate variability. The poor predictive capacity is linked to an initial shock affecting the Atlantic Ocean circulation, ultimately due to a suboptimal representation of the Labrador Sea density.
Assaf Hochman, Sebastian Scher, Julian Quinting, Joaquim G. Pinto, and Gabriele Messori
Earth Syst. Dynam., 12, 133–149, https://doi.org/10.5194/esd-12-133-2021, https://doi.org/10.5194/esd-12-133-2021, 2021
Short summary
Short summary
Skillful forecasts of extreme weather events have a major socioeconomic relevance. Here, we compare two approaches to diagnose the predictability of eastern Mediterranean heat waves: one based on recent developments in dynamical systems theory and one leveraging numerical ensemble weather forecasts. We conclude that the former can be a useful and cost-efficient complement to conventional numerical forecasts for understanding the dynamics of eastern Mediterranean heat waves.
Manuel Schlund, Axel Lauer, Pierre Gentine, Steven C. Sherwood, and Veronika Eyring
Earth Syst. Dynam., 11, 1233–1258, https://doi.org/10.5194/esd-11-1233-2020, https://doi.org/10.5194/esd-11-1233-2020, 2020
Short summary
Short summary
As an important measure of climate change, the Equilibrium Climate Sensitivity (ECS) describes the change in surface temperature after a doubling of the atmospheric CO2 concentration. Climate models from the Coupled Model Intercomparison Project (CMIP) show a wide range in ECS. Emergent constraints are a technique to reduce uncertainties in ECS with observational data. Emergent constraints developed with data from CMIP phase 5 show reduced skill and higher ECS ranges when applied to CMIP6 data.
J. Isaac Miller and Kyungsik Nam
Earth Syst. Dynam., 11, 1123–1132, https://doi.org/10.5194/esd-11-1123-2020, https://doi.org/10.5194/esd-11-1123-2020, 2020
Short summary
Short summary
We augment an energy balance model with a novel measure of the oceans' multidecadal temperatures cycles to assess the contributions of model forcings and natural variability to the so-called hiatus in global warming. The model partially explains the recent slowdown and explains nearly all of the subsequent warming. The natural cycle suggests the possibility of a much longer hiatus over roughly 2023–2061.
Christopher H. O'Reilly, Daniel J. Befort, and Antje Weisheimer
Earth Syst. Dynam., 11, 1033–1049, https://doi.org/10.5194/esd-11-1033-2020, https://doi.org/10.5194/esd-11-1033-2020, 2020
Short summary
Short summary
This study examines how the output of large single-model ensembles can be calibrated using observational data to provide improved future projections over Europe. Using an out-of-sample
imperfect modeltest, in which calibration techniques are applied to individual climate model realisations, these techniques are shown to generally improve the reliability of European climate projections for the next 40 years, particularly for regional surface temperature.
Lukas Brunner, Angeline G. Pendergrass, Flavio Lehner, Anna L. Merrifield, Ruth Lorenz, and Reto Knutti
Earth Syst. Dynam., 11, 995–1012, https://doi.org/10.5194/esd-11-995-2020, https://doi.org/10.5194/esd-11-995-2020, 2020
Short summary
Short summary
In this study, we weight climate models by their performance with respect to simulating aspects of historical climate and their degree of interdependence. Our method is found to increase projection skill and to correct for structurally similar models. The weighted end-of-century mean warming (2081–2100 relative to 1995–2014) is 3.7 °C with a likely (66 %) range of 3.1 to 4.6 °C for the strong climate change scenario SSP5-8.5; this is a reduction of 0.4 °C compared with the unweighted mean.
Femke J. M. M. Nijsse, Peter M. Cox, and Mark S. Williamson
Earth Syst. Dynam., 11, 737–750, https://doi.org/10.5194/esd-11-737-2020, https://doi.org/10.5194/esd-11-737-2020, 2020
Short summary
Short summary
One of the key questions in climate science is how much more heating we will get for a given rise in carbon dioxide in the atmosphere. A new generation of models showed that this might be more than previously expected. Comparing the new models to observed temperature rise since 1970, we show that there is no need to revise the estimate upwards. Air pollution, whose effect on climate warming is poorly understood, stopped rising, allowing us to better constrain the greenhouse gas signal.
Bastien François, Mathieu Vrac, Alex J. Cannon, Yoann Robin, and Denis Allard
Earth Syst. Dynam., 11, 537–562, https://doi.org/10.5194/esd-11-537-2020, https://doi.org/10.5194/esd-11-537-2020, 2020
Short summary
Short summary
Recently, multivariate bias correction (MBC) methods designed to adjust climate simulations have been proposed. However, they use different approaches, leading potentially to different results. Therefore, this study intends to intercompare four existing MBC methods to provide end users with aid in choosing such methods for their applications. To do so, a wide range of evaluation criteria have been used to assess the ability of MBC methods to correct statistical properties of climate models.
Hideo Shiogama, Ryuichi Hirata, Tomoko Hasegawa, Shinichiro Fujimori, Noriko N. Ishizaki, Satoru Chatani, Masahiro Watanabe, Daniel Mitchell, and Y. T. Eunice Lo
Earth Syst. Dynam., 11, 435–445, https://doi.org/10.5194/esd-11-435-2020, https://doi.org/10.5194/esd-11-435-2020, 2020
Short summary
Short summary
Based on climate simulations, we suggested that historical warming increased chances of drought exceeding the severe 2015 event in equatorial Asia due to El Niño. The fire and fire emissions of CO2/PM2.5 will largely increase at 1.5 and 2 °C warming. If global warming reaches 3 °C, as is expected from the current mitigation policies, chances of fire and CO2/PM2.5 emissions exceeding the 2015 event become approximately 100 %. Future climate policy has to consider these climate change effects.
Minchao Wu, Grigory Nikulin, Erik Kjellström, Danijel Belušić, Colin Jones, and David Lindstedt
Earth Syst. Dynam., 11, 377–394, https://doi.org/10.5194/esd-11-377-2020, https://doi.org/10.5194/esd-11-377-2020, 2020
Short summary
Short summary
Regional Climate Models constitute a downscaling tool to provide high-resolution data for impact and adaptation studies. However, there is no unique definition of the added value of downscaling as it depends on many factors. We investigate the impact of spatial resolution and model formulation on downscaled rainfall in Africa. Our results show that improvements in downscaled rainfall compared to the driving reanalysis are often related to model formulation and not always to higher resolution.
James D. Annan and Julia C. Hargreaves
Earth Syst. Dynam., 11, 347–356, https://doi.org/10.5194/esd-11-347-2020, https://doi.org/10.5194/esd-11-347-2020, 2020
Short summary
Short summary
We explore the implicit assumptions that underlie many published probabilistic estimates of the equilibrium climate sensitivity – that is, the amount the climate will warm under a doubling of the atmospheric CO2 concentration. We demonstrate that many such estimates have made assumptions that would be difficult to justify and show how the calculations can be repeated in a more defensible manner. Our results show some significant differences from previous calculations.
Stella Todzo, Adeline Bichet, and Arona Diedhiou
Earth Syst. Dynam., 11, 319–328, https://doi.org/10.5194/esd-11-319-2020, https://doi.org/10.5194/esd-11-319-2020, 2020
Short summary
Short summary
This study uses climate projections over West Africa to investigate the future changes in different aspects of its hydrological cycle. Over the 21st century, temperatures are expected to increase at a faster rate (+0.5 °C per decade) than the global average (+0.3 °C per decade), leading to an intensification of the hydrological cycle on average of +11 % per °C over the Sahel (more intense precipitation and longer dry spells) and +3 % per °C over the Guinea Coast (more intense precipitation).
Olivier Champagne, Martin Leduc, Paulin Coulibaly, and M. Altaf Arain
Earth Syst. Dynam., 11, 301–318, https://doi.org/10.5194/esd-11-301-2020, https://doi.org/10.5194/esd-11-301-2020, 2020
Short summary
Short summary
Southern Ontario has seen more high flows in winter recently due to earlier snowmelt. We show that 10 mm of daily rain and temperature higher than 5 °C are necessary conditions to generate winter high flows in the historical period. These conditions are associated with high pressure on the east coast bringing warm and wet conditions from the south. In the future, as snowfall decreases, warm events will generate less high flows, while rainfall will become a greater high-flow contributor.
Tímea Haszpra, Mátyás Herein, and Tamás Bódai
Earth Syst. Dynam., 11, 267–280, https://doi.org/10.5194/esd-11-267-2020, https://doi.org/10.5194/esd-11-267-2020, 2020
Short summary
Short summary
We investigate the changes in the ENSO phenomenon and the alterations of its precipitation-related teleconnections in the CESM-LE. To avoid the disadvantages of the subjective choices of traditional temporal methods, we use an ensemble-based snapshot framework providing instantaneous quantities computed over the ensemble dimension of the simulation. We find that ENSO teleconnections undergo considerable changes, and the ENSO amplitude remarkably increases by 2100.
Robert Vautard, Geert Jan van Oldenborgh, Friederike E. L. Otto, Pascal Yiou, Hylke de Vries, Erik van Meijgaard, Andrew Stepek, Jean-Michel Soubeyroux, Sjoukje Philip, Sarah F. Kew, Cecilia Costella, Roop Singh, and Claudia Tebaldi
Earth Syst. Dynam., 10, 271–286, https://doi.org/10.5194/esd-10-271-2019, https://doi.org/10.5194/esd-10-271-2019, 2019
Short summary
Short summary
The effect of human activities on the probability of winter wind storms like the ones that occurred in Western Europe in January 2018 is analysed using multiple model ensembles. Despite a significant probability decline in observations, we find no significant change in probabilities due to human influence on climate so far. However, such extreme events are likely to be slightly more frequent in the future. The observed decrease in storminess is likely to be due to increasing roughness.
Monica Ionita, Klaus Grosfeld, Patrick Scholz, Renate Treffeisen, and Gerrit Lohmann
Earth Syst. Dynam., 10, 189–203, https://doi.org/10.5194/esd-10-189-2019, https://doi.org/10.5194/esd-10-189-2019, 2019
Short summary
Short summary
Based on a simple statistical model we show that the September sea ice extent has a high predictive skill, up to 4 months ahead, based on previous months' oceanic and atmospheric conditions. Our statistical model skillfully captures the interannual variability of the September sea ice extent and could provide a valuable tool for identifying relevant regions and oceanic and atmospheric parameters that are important for the sea ice development in the Arctic.
Gab Abramowitz, Nadja Herger, Ethan Gutmann, Dorit Hammerling, Reto Knutti, Martin Leduc, Ruth Lorenz, Robert Pincus, and Gavin A. Schmidt
Earth Syst. Dynam., 10, 91–105, https://doi.org/10.5194/esd-10-91-2019, https://doi.org/10.5194/esd-10-91-2019, 2019
Short summary
Short summary
Best estimates of future climate projections typically rely on a range of climate models from different international research institutions. However, it is unclear how independent these different estimates are, and, for example, the degree to which their agreement implies robustness. This work presents a review of the varied and disparate attempts to quantify and address model dependence within multi-model climate projection ensembles.
Nicole S. Lovenduski, Stephen G. Yeager, Keith Lindsay, and Matthew C. Long
Earth Syst. Dynam., 10, 45–57, https://doi.org/10.5194/esd-10-45-2019, https://doi.org/10.5194/esd-10-45-2019, 2019
Short summary
Short summary
This paper shows that the absorption of carbon dioxide by the ocean is predictable several years in advance. This is important because fossil-fuel-derived carbon dioxide is largely responsible for anthropogenic global warming and because carbon dioxide emission management and global carbon cycle budgeting exercises can benefit from foreknowledge of ocean carbon absorption. The promising results from this new forecast system justify the need for additional oceanic observations.
Femke J. M. M. Nijsse and Henk A. Dijkstra
Earth Syst. Dynam., 9, 999–1012, https://doi.org/10.5194/esd-9-999-2018, https://doi.org/10.5194/esd-9-999-2018, 2018
Short summary
Short summary
State-of-the-art climate models sometimes differ in their prediction of key aspects of climate change. The technique of
emergent constraintsuses observations of current climate to improve those predictions, using relationships between different climate models. Our paper first classifies the different uses of the technique, and continues with proposing a mathematical justification for their use. We also highlight when the application of emergent constraints might give biased predictions.
Bo Huang, Ulrich Cubasch, and Christopher Kadow
Earth Syst. Dynam., 9, 985–997, https://doi.org/10.5194/esd-9-985-2018, https://doi.org/10.5194/esd-9-985-2018, 2018
Short summary
Short summary
We find that CMIP5 models show more significant improvement in predicting zonal winds with initialisation than without initialisation based on the knowledge that zonal wind indices can be used as potential predictors for the EASM. Given the initial conditions, two models improve the seasonal prediction skill of the EASM, while one model decreases it. The models have different responses to initialisation due to their ability to depict the EASM–ESNO coupled mode.
Sebastian Illing, Christopher Kadow, Holger Pohlmann, and Claudia Timmreck
Earth Syst. Dynam., 9, 701–715, https://doi.org/10.5194/esd-9-701-2018, https://doi.org/10.5194/esd-9-701-2018, 2018
Jiawei Liu, Haiming Xu, and Jiechun Deng
Earth Syst. Dynam., 9, 427–439, https://doi.org/10.5194/esd-9-427-2018, https://doi.org/10.5194/esd-9-427-2018, 2018
Short summary
Short summary
A novel method based on
present–futurerelationship in observed climate and model-simulated future climate is applied to give more reliable projections of East Asian summer monsoon intensity and associated precipitation changes at 1.5 and 2 °C warming levels. Projected future changes suggest decreased precipitation over the Meiyu belt and increased precipitation over the high latitudes of East Asia and central China, together with a considerable weakening of EASM intensity.
Michael Wehner, Dáithí Stone, Dann Mitchell, Hideo Shiogama, Erich Fischer, Lise S. Graff, Viatcheslav V. Kharin, Ludwig Lierhammer, Benjamin Sanderson, and Harinarayan Krishnan
Earth Syst. Dynam., 9, 299–311, https://doi.org/10.5194/esd-9-299-2018, https://doi.org/10.5194/esd-9-299-2018, 2018
Short summary
Short summary
The United Nations Framework Convention on Climate Change challenged the scientific community to describe the impacts of stabilizing the global temperature at its 21st Conference of Parties. A specific target of 1.5 °C above preindustrial levels had not been seriously considered by the climate modeling community prior to the Paris Agreement. This paper analyzes heat waves in simulations designed for this target. We find there are reductions in extreme temperature compared to a 2 °C target.
Dana Ehlert and Kirsten Zickfeld
Earth Syst. Dynam., 9, 197–210, https://doi.org/10.5194/esd-9-197-2018, https://doi.org/10.5194/esd-9-197-2018, 2018
Short summary
Short summary
This study uses a global climate model to explore the extent to which sea level rise due to thermal expansion of the ocean is reversible if the atmospheric concentration of carbon dioxide (CO2) declines. It is found that sea level continues to rise for several decades after atmospheric CO2 starts to decline and does not return to the pre-industrial level for over thousand years after atmospheric CO2 is restored to the pre-industrial concentration.
Michael F. Wehner, Kevin A. Reed, Burlen Loring, Dáithí Stone, and Harinarayan Krishnan
Earth Syst. Dynam., 9, 187–195, https://doi.org/10.5194/esd-9-187-2018, https://doi.org/10.5194/esd-9-187-2018, 2018
Short summary
Short summary
The United Nations Framework Convention on Climate Change invited the scientific community to explore the impacts of a world in which anthropogenic global warming is stabilized at only 1.5 °C above preindustrial average temperatures. We present a projection of future tropical cyclone statistics for both 1.5 and 2.0 °C stabilized warming scenarios using a high-resolution global climate model. We find more frequent and intense tropical cyclones, but a reduction in weaker storms.
Nadja Herger, Gab Abramowitz, Reto Knutti, Oliver Angélil, Karsten Lehmann, and Benjamin M. Sanderson
Earth Syst. Dynam., 9, 135–151, https://doi.org/10.5194/esd-9-135-2018, https://doi.org/10.5194/esd-9-135-2018, 2018
Short summary
Short summary
Users presented with large multi-model ensembles commonly use the equally weighted model mean as a best estimate, ignoring the issue of near replication of some climate models. We present an efficient and flexible tool that finds a subset of models with improved mean performance compared to the multi-model mean while at the same time maintaining the spread and addressing the problem of model interdependence. Out-of-sample skill and reliability are demonstrated using model-as-truth experiments.
Maida Zahid, Richard Blender, Valerio Lucarini, and Maria Caterina Bramati
Earth Syst. Dynam., 8, 1263–1278, https://doi.org/10.5194/esd-8-1263-2017, https://doi.org/10.5194/esd-8-1263-2017, 2017
Short summary
Short summary
The southern part of Pakistan (Sindh province) has been exposed to frequent and intense temperature extremes recently and is highly vulnerable to their impacts due to lack of information on recurrence of extremes. In this paper for the first time we estimated the return levels of daily maximum temperatures and daily maximum wet-bulb temperatures over the different return periods in Sindh, which would help the local administrations to prioritize the regions in terms of adaptations.
James D. Annan and Julia C. Hargreaves
Earth Syst. Dynam., 8, 211–224, https://doi.org/10.5194/esd-8-211-2017, https://doi.org/10.5194/esd-8-211-2017, 2017
Short summary
Short summary
The concept of independence has been frequently raised in climate science, but has rarely been defined and discussed in a theoretically robust and quantifiable manner. Improved understanding of this topic is critical to better understanding of climate change. In this paper, we introduce a unifying approach based on the statistical definition of independence, and illustrate with simple examples how it can be applied to practical questions.
Jozef Vilček, Jaroslav Škvarenina, Jaroslav Vido, Paulína Nalevanková, Radoslav Kandrík, and Jana Škvareninová
Earth Syst. Dynam., 7, 735–744, https://doi.org/10.5194/esd-7-735-2016, https://doi.org/10.5194/esd-7-735-2016, 2016
Short summary
Short summary
Thermal continentality plays an important role not only in the basic characterisation of the climate in particular regions but also in the phytogeographic distribution of plants and ecosystem formation. Due to ongoing climate change, questions surrounding the changes of thermal continentality are very relevant. Our results show that the continentality of Slovakia increased in the period 1961 to 2013; however, this trend is not significant.
Cited articles
Andrews, T., Forster, P. M., and Gregory, J. M.: A Surface Energy Perspective
on Climate Change, J. Climate, 22, 2557–2570, https://doi.org/10.1175/2008JCLI2759.1, 2009. a, b, c
Fischer, E. M., Sedláček, J., Hawkins, E., and Knutti, R.: Models agree
on forced response pattern of precipitation and temperature extremes, Geophys.
Res. Lett., 41, 8554–8562, https://doi.org/10.1002/2014GL062018, 2014. a, b
Frieler, K., Meinshausen, M., Schneider von Deimling, T., Andrews, T., and
Forster, P.: Changes in global-mean precipitation in response to warming,
greenhouse gas forcing and black carbon, Geophys. Res. Lett., 38, L04702,
https://doi.org/10.1029/2010GL045953, 2011. a, b, c
Good, P., Booth, B. B. B., Chadwick, R., Hawkins, E., Jonko, A., and Lowe, J.
A.: Large differences in regional precipitation change between a first and
second 2 K of global warming, Nat. Commun., 7, 13667, https://doi.org/10.1038/ncomms13667, 2016. a
Greve, P. and Seneviratne, S. I.: Assessment of future changes in water
availability and aridity, Geophys. Res. Lett., 42, 5493–5499, https://doi.org/10.1002/2015GL064127, 2015. a
Guiot, J. and Cramer, W.: Climate change: The 2015 Paris Agreement thresholds
and Mediterranean basin ecosystems, Science, 354, 465–468, https://doi.org/10.1126/science.aah5015, 2016. a
Hawkins, E. and Sutton, R.: The Potential to Narrow Uncertainty in Regional
Climate Predictions, B. Am. Meteorol. Soc., 90, 1095–1107, https://doi.org/10.1175/2009BAMS2607.1, 2009. a
Herger, N., Sanderson, B. M., and Knutti, R.: Improved pattern scaling approaches
for the use in climate impact studies, Geophys. Res. Lett., 42, 3486–3494, https://doi.org/10.1002/2015GL063569, 2015. a, b
James, R., Washington, R., Schleussner, C.-F., Rogelj, J., and Conway, D.:
Characterizing half-a-degree difference: a review of methods for identifying
regional climate responses to global warming targets, WIREs Clim. Change, 8,
e457, https://doi.org/10.1002/wcc.457, 2017. a
Knutti, R., Rogelj, J., Sedláček, J., and Fischer, E. M.: A scientific
critique of the two-degree climate change target, Nat. Geosci., 9, 13–18,
https://doi.org/10.1038/ngeo2595, 2016. a
Kravitz, B., Lynch, C., Hartin, C., and Bond-Lamberty, B.: Exploring precipitation
pattern scaling methodologies and robustness among CMIP5 models, Geosci. Model
Dev., 10, 1889–1902, https://doi.org/10.5194/gmd-10-1889-2017, 2017. a
Liepert, B. G. and Lo, F.: CMIP5 update of `Inter-model variability and biases
of the global water cycle in CMIP3 coupled climate models', Environ. Res. Lett.,
8, 029401, https://doi.org/10.1088/1748-9326/8/2/029401, 2013. a
Liepert, B. G. and Previdi, M.: Inter-model variability and biases of the
global water cycle in CMIP3 coupled climate models, Environ. Res. Lett., 7,
014006, https://doi.org/10.1088/1748-9326/7/1/014006, 2012. a
Mitchell, T. D.: Pattern Scaling: An Examination of the Accuracy of the
Technique for Describing Future Climates, Climatic Change, 60, 217–242,
https://doi.org/10.1023/A:1026035305597, 2003. a
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K.,
van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G.
A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R.
J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation of
scenarios for climate change research and assessment, Nature, 463, 747–756,
https://doi.org/10.1038/nature08823, 2010. a
Orlowsky, B. and Seneviratne, S. I.: Elusive drought: uncertainty in observed
trends and short- and long-term CMIP5 projections, Hydrol. Earth Syst. Sci.,
17, 1765–1781, https://doi.org/10.5194/hess-17-1765-2013, 2013. a
Pendergrass, A. G. and Hartmann, D. L.: Global-mean precipitation and black
carbon in AR4 simulations, Geophys. Res. Lett., 39, L01703, https://doi.org/10.1029/2011GL050067, 2012. a, b, c, d
Santer, B., Wigley, M., Schlesinger, M., and Mitchell, J.: Developing climate
scenarios from equilibrium GCM results, Tech. Rep., Hamburg, Germany, 1990. a
Schleussner, C.-F., Lissner, T. K., Fischer, E. M., Wohland, J., Perrette, M.,
Golly, A., Rogelj, J., Childers, K., Schewe, J., Frieler, K., Mengel, M., Hare,
W., and Schaeffer, M.: Differential climate impacts for policy-relevant limits
to global warming: the case of 1.5 ∘C and 2 ∘C, Earth Syst.
Dynam., 7, 327–351, https://doi.org/10.5194/esd-7-327-2016, 2016. a
Seneviratne, S. I., Nicholls, N., Easterling, D., Goodess, C., Kanae, S., Kossin,
J., Luo, Y., Marengo, J., McInnes, K., Rahimi, M., Reichstein, M., Sorteberg,
A., Vera, C., and Zhang, X.: Changes in climate extremes and their impacts on
the natural physical environment, in: Managing the Risks of Extreme Events and
Disasters to Advance Climate Change Adaptation, A Special Report of Working
Groups I and II of the Intergovernmental Panel on Climate Change, edited by:
Field, C. B., Barros, V., Stocker, T. F., Qin, D., Dokken, D. J., Ebi, K. J.,
Mastrandrea, M. D., Mach, K. J., Plattner, G.-K., Allen, S. K., Tignor, M., and
Midgley, P. M., IPCC, Cambridge University Press, Cambridge, UK, and New York, NY, USA, 2012. a, b
Solomon, S., Plattner, G.-K., Knutti, R., and Friedlingstein, P.: Irreversible
climate change due to carbon dioxide emissions, P. Natl. Acad. Sci. USA, 106,
1704–1709, https://doi.org/10.1073/pnas.0812721106, 2009. a
Taylor, K., Stouffer, R., and Meehl, G.: An Overview of CMIP5 and the Experiment
Design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
Tebaldi, C. and Arblaster, J. M.: Pattern scaling: Its strengths and limitations,
and an update on the latest model simulations, Climatic Change, 122, 459–471,
https://doi.org/10.1007/s10584-013-1032-9, 2014.
a, b, c
Victor, D. G. and Kennel, C. F.: Climate policy: Ditch the 2 ∘C warming
goal, Nature News, 514, 30–31, https://doi.org/10.1038/514030a, 2014. a
Wartenburger, R., Hirschi, M., Donat, M. G., Greve, P., Pitman, A. J., and
Seneviratne, S. I.: Changes in regional climate extremes as a function of global
mean temperature: an interactive plotting framework, Geosci. Model Dev., 10,
3609–3634, https://doi.org/10.5194/gmd-10-3609-2017, 2017. a, b, c
Short summary
Assessing projected hydroclimatological changes is crucial, but associated with large uncertainties. We statistically assess here the response of precipitation and water availability to global temperature change, enabling us to estimate the significance of drying/wetting tendencies under anthropogenic climate change. We further show that opting for a 1.5 K warming target just slightly influences the mean response but could substantially reduce the risk of experiencing extreme changes.
Assessing projected hydroclimatological changes is crucial, but associated with large...
Altmetrics
Final-revised paper
Preprint