Articles | Volume 15, issue 20
Geosci. Model Dev., 15, 7913–7932, 2022
https://doi.org/10.5194/gmd-15-7913-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 15, 7913–7932, 2022
https://doi.org/10.5194/gmd-15-7913-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
28 Oct 2022
Development and technical paper
| 28 Oct 2022
A new bootstrap technique to quantify uncertainty in estimates of ground surface temperature and ground heat flux histories from geothermal data
Francisco José Cuesta-Valero et al.
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Francisco José Cuesta-Valero, Hugo Beltrami, Almudena García-García, Gerhard Krinner, Moritz Langer, Andrew H. MacDougall, Jan Nitzbon, Jian Peng, Karina von Schuckmann, Sonia I. Seneviratne, Noah Smith, Wim Thiery, Inne Vanderkelen, and Tonghua Wu
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2022-32, https://doi.org/10.5194/esd-2022-32, 2022
Revised manuscript under review for ESD
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Climate change is caused by the accumulated heat in the Earth system, with the land storing the second largest amount of this extra heat. Here, new estimates of continental heat storage are obtained, including changes in inland water heat storage and permafrost heat storage in addition to changes in ground heat storage. We also argue that heat gains in all three components should be monitored independently of their magnitude due to heat-dependent processes affecting society and ecosystems.
Karina von Schuckmann, Audrey Minère, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Richard Allan, Paul M. Barker, Hugo Beltrami, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nikolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Noah Smith, Andrea Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-239, https://doi.org/10.5194/essd-2022-239, 2022
Preprint under review for ESSD
Short summary
Short summary
Earth climate is out of energy balance and this study quantifies how much heat has consequently accumulated over the past decades (89 %: ocean, 6 %: land, 4 %: cryosphere, 1 %: atmosphere). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris agreement’s global stocktake.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, J. Fidel González-Rouco, and Elena García-Bustamante
Geosci. Model Dev., 15, 413–428, https://doi.org/10.5194/gmd-15-413-2022, https://doi.org/10.5194/gmd-15-413-2022, 2022
Short summary
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We study the sensitivity of a regional climate model to resolution and soil scheme changes. Our results show that the use of finer resolutions mainly affects precipitation outputs, particularly in summer due to changes in convective processes. Finer resolutions are associated with larger biases compared with observations. Changing the land surface model scheme affects the simulation of near-surface temperatures, yielding the lowest biases in mean temperature with the most complex soil scheme.
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.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, J. Fidel González-Rouco, and Elena García-Bustamante
Clim. Past, 17, 451–468, https://doi.org/10.5194/cp-17-451-2021, https://doi.org/10.5194/cp-17-451-2021, 2021
Short summary
Short summary
We provide new global estimates of changes in surface temperature, surface heat flux, and continental heat storage since preindustrial times from geothermal data. Our analysis includes new measurements and a more comprehensive description of uncertainties than previous studies. Results show higher continental heat storage than previously reported, with global land mean temperature changes of 1 K and subsurface heat gains of 12 ZJ during the last half of the 20th century.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, Fidel González-Rouco, Elena García-Bustamante, and Joel Finnis
Geosci. Model Dev., 13, 5345–5366, https://doi.org/10.5194/gmd-13-5345-2020, https://doi.org/10.5194/gmd-13-5345-2020, 2020
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, Eduardo Zorita, and Fernando Jaume-Santero
Clim. Past, 15, 1099–1111, https://doi.org/10.5194/cp-15-1099-2019, https://doi.org/10.5194/cp-15-1099-2019, 2019
Short summary
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A database of North American long-term ground surface temperatures, from approximately 1300 CE to 1700 CE, was assembled from geothermal data. These temperatures are useful for studying the future stability of permafrost, as well as for evaluating simulations of preindustrial climate that may help to improve estimates of climate models’ equilibrium climate sensitivity. The database will be made available to the climate science community.
Alessandro Cicoira, Samuel Weber, Andreas Biri, Ben Buchli, Reynald Delaloye, Reto Da Forno, Isabelle Gärtner-Roer, Stephan Gruber, Tonio Gsell, Andreas Hasler, Roman Lim, Philippe Limpach, Raphael Mayoraz, Matthias Meyer, Jeannette Noetzli, Marcia Phillips, Eric Pointner, Hugo Raetzo, Cristian Scapozza, Tazio Strozzi, Lothar Thiele, Andreas Vieli, Daniel Vonder Mühll, Vanessa Wirz, and Jan Beutel
Earth Syst. Sci. Data, 14, 5061–5091, https://doi.org/10.5194/essd-14-5061-2022, https://doi.org/10.5194/essd-14-5061-2022, 2022
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This paper documents a monitoring network of 54 positions, located on different periglacial landforms in the Swiss Alps: rock glaciers, landslides, and steep rock walls. The data serve basic research but also decision-making and mitigation of natural hazards. It is the largest dataset of its kind, comprising over 209 000 daily positions and additional weather data.
Philipp de Vrese, Goran Georgievski, Jesus Fidel Gonzalez Rouco, Dirk Notz, Tobias Stacke, Norman Julius Steinert, Stiig Wilkenskjeld, and Victor Brovkin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-150, https://doi.org/10.5194/tc-2022-150, 2022
Preprint under review for TC
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The current generation of Earth system models exhibits large inter-model differences in the simulated climate of the Arctic and subarctic zone. We used an adapted version of the MPI Earth System model to show that differences in the representation of the soil hydrology in permafrost-affected regions could help explain a large part of the inter-model spread in the Arctic and subarctic climate and also have pronounced impacts on important whether systems as far to the south as the tropics.
Francisco José Cuesta-Valero, Hugo Beltrami, Almudena García-García, Gerhard Krinner, Moritz Langer, Andrew H. MacDougall, Jan Nitzbon, Jian Peng, Karina von Schuckmann, Sonia I. Seneviratne, Noah Smith, Wim Thiery, Inne Vanderkelen, and Tonghua Wu
Earth Syst. Dynam. Discuss., https://doi.org/10.5194/esd-2022-32, https://doi.org/10.5194/esd-2022-32, 2022
Revised manuscript under review for ESD
Short summary
Short summary
Climate change is caused by the accumulated heat in the Earth system, with the land storing the second largest amount of this extra heat. Here, new estimates of continental heat storage are obtained, including changes in inland water heat storage and permafrost heat storage in addition to changes in ground heat storage. We also argue that heat gains in all three components should be monitored independently of their magnitude due to heat-dependent processes affecting society and ecosystems.
Karina von Schuckmann, Audrey Minère, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Richard Allan, Paul M. Barker, Hugo Beltrami, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nikolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Noah Smith, Andrea Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-239, https://doi.org/10.5194/essd-2022-239, 2022
Preprint under review for ESSD
Short summary
Short summary
Earth climate is out of energy balance and this study quantifies how much heat has consequently accumulated over the past decades (89 %: ocean, 6 %: land, 4 %: cryosphere, 1 %: atmosphere). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris agreement’s global stocktake.
Élise G. Devoie, Stephan Gruber, and Jeffrey M. McKenzie
Earth Syst. Sci. Data, 14, 3365–3377, https://doi.org/10.5194/essd-14-3365-2022, https://doi.org/10.5194/essd-14-3365-2022, 2022
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Soil freezing characteristic curves (SFCCs) relate the temperature of a soil to its ice content. SFCCs are needed in all physically based numerical models representing freezing and thawing soils, and they affect the movement of water in the subsurface, biogeochemical processes, soil mechanics, and ecology. Over a century of SFCC data exist, showing high variability in SFCCs based on soil texture, water content, and other factors. This repository summarizes all available SFCC data and metadata.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, J. Fidel González-Rouco, and Elena García-Bustamante
Geosci. Model Dev., 15, 413–428, https://doi.org/10.5194/gmd-15-413-2022, https://doi.org/10.5194/gmd-15-413-2022, 2022
Short summary
Short summary
We study the sensitivity of a regional climate model to resolution and soil scheme changes. Our results show that the use of finer resolutions mainly affects precipitation outputs, particularly in summer due to changes in convective processes. Finer resolutions are associated with larger biases compared with observations. Changing the land surface model scheme affects the simulation of near-surface temperatures, yielding the lowest biases in mean temperature with the most complex soil scheme.
Niccolò Tubini, Stephan Gruber, and Riccardo Rigon
The Cryosphere, 15, 2541–2568, https://doi.org/10.5194/tc-15-2541-2021, https://doi.org/10.5194/tc-15-2541-2021, 2021
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We present a new method to compute temperature changes with melting and freezing – a fundamental challenge in cryosphere research – extremely efficiently and with guaranteed correctness of the energy balance for any time step size. This is a key feature since the integration time step can then be chosen according to the timescale of the processes to be studied, from seconds to days.
John Mohd Wani, Renoj J. Thayyen, Chandra Shekhar Prasad Ojha, and Stephan Gruber
The Cryosphere, 15, 2273–2293, https://doi.org/10.5194/tc-15-2273-2021, https://doi.org/10.5194/tc-15-2273-2021, 2021
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We study the surface energy balance from a cold-arid permafrost environment in the Indian Himalayan region. The GEOtop model was used for the modelling of surface energy balance. Our results show that the variability in the turbulent heat fluxes is similar to that reported from the seasonally frozen ground and permafrost regions of the Tibetan Plateau. Further, the low relative humidity could be playing a critical role in the surface energy balance and the permafrost processes.
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.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, J. Fidel González-Rouco, and Elena García-Bustamante
Clim. Past, 17, 451–468, https://doi.org/10.5194/cp-17-451-2021, https://doi.org/10.5194/cp-17-451-2021, 2021
Short summary
Short summary
We provide new global estimates of changes in surface temperature, surface heat flux, and continental heat storage since preindustrial times from geothermal data. Our analysis includes new measurements and a more comprehensive description of uncertainties than previous studies. Results show higher continental heat storage than previously reported, with global land mean temperature changes of 1 K and subsurface heat gains of 12 ZJ during the last half of the 20th century.
Rupesh Subedi, Steven V. Kokelj, and Stephan Gruber
The Cryosphere, 14, 4341–4364, https://doi.org/10.5194/tc-14-4341-2020, https://doi.org/10.5194/tc-14-4341-2020, 2020
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Permafrost beneath tundra near Lac de Gras (Northwest Territories, Canada) contains more ice and less organic carbon than shown in global compilations. Excess-ice content of 20–60 %, likely remnant Laurentide basal ice, is found in upland till. This study is based on 24 boreholes up to 10 m deep. Findings highlight geology and glacial legacy as determinants of a mosaic of permafrost characteristics with potential for thaw subsidence up to several metres in some locations.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, Fidel González-Rouco, Elena García-Bustamante, and Joel Finnis
Geosci. Model Dev., 13, 5345–5366, https://doi.org/10.5194/gmd-13-5345-2020, https://doi.org/10.5194/gmd-13-5345-2020, 2020
Andrea N. Hahmann, Tija Sīle, Björn Witha, Neil N. Davis, Martin Dörenkämper, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Bjarke T. Olsen, and Stefan Söderberg
Geosci. Model Dev., 13, 5053–5078, https://doi.org/10.5194/gmd-13-5053-2020, https://doi.org/10.5194/gmd-13-5053-2020, 2020
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Wind energy resource assessment routinely uses numerical weather prediction model output. We describe the evaluation procedures used for picking the suitable blend of model setup and parameterizations for simulating European wind climatology with the WRF model. We assess the simulated winds against tall mast measurements using a suite of metrics, including the Earth Mover's Distance, which diagnoses the performance of each ensemble member using the full wind speed and direction distribution.
Martin Dörenkämper, Bjarke T. Olsen, Björn Witha, Andrea N. Hahmann, Neil N. Davis, Jordi Barcons, Yasemin Ezber, Elena García-Bustamante, J. Fidel González-Rouco, Jorge Navarro, Mariano Sastre-Marugán, Tija Sīle, Wilke Trei, Mark Žagar, Jake Badger, Julia Gottschall, Javier Sanz Rodrigo, and Jakob Mann
Geosci. Model Dev., 13, 5079–5102, https://doi.org/10.5194/gmd-13-5079-2020, https://doi.org/10.5194/gmd-13-5079-2020, 2020
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This is the second of two papers that document the creation of the New European Wind Atlas (NEWA). The paper includes a detailed description of the technical and practical aspects that went into running the mesoscale simulations and the microscale downscaling for generating the climatology. A comprehensive evaluation of each component of the NEWA model chain is presented using observations from a large set of tall masts located all over Europe.
Karina von Schuckmann, Lijing Cheng, Matthew D. Palmer, James Hansen, Caterina Tassone, Valentin Aich, Susheel Adusumilli, Hugo Beltrami, Tim Boyer, Francisco José Cuesta-Valero, Damien Desbruyères, Catia Domingues, Almudena García-García, Pierre Gentine, John Gilson, Maximilian Gorfer, Leopold Haimberger, Masayoshi Ishii, Gregory C. Johnson, Rachel Killick, Brian A. King, Gottfried Kirchengast, Nicolas Kolodziejczyk, John Lyman, Ben Marzeion, Michael Mayer, Maeva Monier, Didier Paolo Monselesan, Sarah Purkey, Dean Roemmich, Axel Schweiger, Sonia I. Seneviratne, Andrew Shepherd, Donald A. Slater, Andrea K. Steiner, Fiammetta Straneo, Mary-Louise Timmermans, and Susan E. Wijffels
Earth Syst. Sci. Data, 12, 2013–2041, https://doi.org/10.5194/essd-12-2013-2020, https://doi.org/10.5194/essd-12-2013-2020, 2020
Short summary
Short summary
Understanding how much and where the heat is distributed in the Earth system is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to obtain the Earth heat inventory over the period 1960–2018.
Bin Cao, Stephan Gruber, Donghai Zheng, and Xin Li
The Cryosphere, 14, 2581–2595, https://doi.org/10.5194/tc-14-2581-2020, https://doi.org/10.5194/tc-14-2581-2020, 2020
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This study reports that ERA5-Land (ERA5L) soil temperature bias in permafrost regions correlates with the bias in air temperature and with maximum snow height. While global reanalyses are important drivers for permafrost study, ERA5L soil data are not well suited for directly informing permafrost research decision making due to their warm bias in winter. To address this, future soil temperature products in reanalyses will require permafrost-specific alterations to their land surface models.
Pedro José Roldán-Gómez, Jesús Fidel González-Rouco, Camilo Melo-Aguilar, and Jason E. Smerdon
Clim. Past, 16, 1285–1307, https://doi.org/10.5194/cp-16-1285-2020, https://doi.org/10.5194/cp-16-1285-2020, 2020
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This work analyses the behavior of atmospheric dynamics and hydroclimate in climate simulations of the last millennium. In particular, how external forcing factors, like solar and volcanic activity and greenhouse gas emissions, impact variables like temperature, pressure, wind, precipitation, and soil moisture is assessed. The results of these analyses show that changes in the forcing could alter the zonal circulation and the intensity and distribution of monsoons and convergence zones.
Stephan Gruber
The Cryosphere, 14, 1437–1447, https://doi.org/10.5194/tc-14-1437-2020, https://doi.org/10.5194/tc-14-1437-2020, 2020
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A simple method to record heave and subsidence of the land surface at specific field locations is described. Hourly observations from three sites, over two winters and one summer, are analyzed and discussed. The data are rich in features that point to the influence of freezing and thawing and of wetting and drying of the soil. This type of observation may offer new insight into the processes of heat and mass transfer in soil and help to monitor climate change impacts.
Ignacio Hermoso de Mendoza, Hugo Beltrami, Andrew H. MacDougall, and Jean-Claude Mareschal
Geosci. Model Dev., 13, 1663–1683, https://doi.org/10.5194/gmd-13-1663-2020, https://doi.org/10.5194/gmd-13-1663-2020, 2020
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We study the impact that the thickness of the subsurface and the geothermal gradient have in land models for climate simulations. To do this, we modify the Community Land Model version 4.5. In a scenario of rising atmospheric temperatures, the temperature of an insufficiently deep subsurface rises faster than it would in the real land. For the model, this produces faster permafrost thawing and increased emissions of land carbon to the atmosphere.
Camilo Melo-Aguilar, J. Fidel González-Rouco, Elena García-Bustamante, Norman Steinert, Johann H. Jungclaus, Jorge Navarro, and Pedro J. Roldán-Gómez
Clim. Past, 16, 453–474, https://doi.org/10.5194/cp-16-453-2020, https://doi.org/10.5194/cp-16-453-2020, 2020
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This study explores potential sources of bias on borehole-based temperature reconstruction from both methodological and physical factors using pseudo-proxy experiments that consider ensembles of simulations from the Community Earth System Model. The results indicate that both methodological and physical factors may have an impact on the estimation of the recent temperature trends at different spatial scales. Internal variability arises also as an important issue influencing pseudo-proxy results.
Bin Cao, Xiaojing Quan, Nicholas Brown, Emilie Stewart-Jones, and Stephan Gruber
Geosci. Model Dev., 12, 4661–4679, https://doi.org/10.5194/gmd-12-4661-2019, https://doi.org/10.5194/gmd-12-4661-2019, 2019
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GlobSim is a tool for simulating land-surface processes and phenomena at point locations globally, even where no site-specific meteorological observations exist. This is important because simulation can add insight to the analysis of observations or help in anticipating climate-change impacts and because site-specific simulation can help in model evaluation.
Joe R. Melton, Diana L. Verseghy, Reinel Sospedra-Alfonso, and Stephan Gruber
Geosci. Model Dev., 12, 4443–4467, https://doi.org/10.5194/gmd-12-4443-2019, https://doi.org/10.5194/gmd-12-4443-2019, 2019
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Soils in cold regions store large amounts of carbon that could be released to the atmosphere if the soils thaw. To best simulate these soils, we explored different configurations and parameterizations of the CLASS-CTEM model and compared to observations. The revised model with a deeper soil column, new soil depth dataset, and inclusion of moss simulated greatly improved annual thaw depths and ground temperatures. We estimate subgrid-scale features limit further improvements against observations.
Samuel Weber, Jan Beutel, Reto Da Forno, Alain Geiger, Stephan Gruber, Tonio Gsell, Andreas Hasler, Matthias Keller, Roman Lim, Philippe Limpach, Matthias Meyer, Igor Talzi, Lothar Thiele, Christian Tschudin, Andreas Vieli, Daniel Vonder Mühll, and Mustafa Yücel
Earth Syst. Sci. Data, 11, 1203–1237, https://doi.org/10.5194/essd-11-1203-2019, https://doi.org/10.5194/essd-11-1203-2019, 2019
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In this paper, we describe a unique 10-year or more data record obtained from in situ measurements in steep bedrock permafrost in an Alpine environment on the Matterhorn Hörnligrat, Zermatt, Switzerland, at 3500 m a.s.l. By documenting and sharing these data in this form, we contribute to facilitating future research based on them, e.g., in the area of analysis methodology, comparative studies, assessment of change in the environment, natural hazard warning and the development of process models.
Francisco José Cuesta-Valero, Almudena García-García, Hugo Beltrami, Eduardo Zorita, and Fernando Jaume-Santero
Clim. Past, 15, 1099–1111, https://doi.org/10.5194/cp-15-1099-2019, https://doi.org/10.5194/cp-15-1099-2019, 2019
Short summary
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A database of North American long-term ground surface temperatures, from approximately 1300 CE to 1700 CE, was assembled from geothermal data. These temperatures are useful for studying the future stability of permafrost, as well as for evaluating simulations of preindustrial climate that may help to improve estimates of climate models’ equilibrium climate sensitivity. The database will be made available to the climate science community.
Camilo Melo-Aguilar, J. Fidel González-Rouco, Elena García-Bustamante, Jorge Navarro-Montesinos, and Norman Steinert
Clim. Past, 14, 1583–1606, https://doi.org/10.5194/cp-14-1583-2018, https://doi.org/10.5194/cp-14-1583-2018, 2018
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Air–ground temperature coupling is the central assumption of borehole temperature reconstructions. Here, this premise is assessed from a pseudo-reality perspective by considering last millennium ensembles of simulations from the Community Earth System Model. The results show that long-term variations in the energy fluxes at the surface during industrial times, due to the influence of external forcings, impact the long-term air–ground temperature coupling.
Carolyne Pickler, Edmundo Gurza Fausto, Hugo Beltrami, Jean-Claude Mareschal, Francisco Suárez, Arlette Chacon-Oecklers, Nicole Blin, Maria Teresa Cortés Calderón, Alvaro Montenegro, Rob Harris, and Andres Tassara
Clim. Past, 14, 559–575, https://doi.org/10.5194/cp-14-559-2018, https://doi.org/10.5194/cp-14-559-2018, 2018
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We compiled 31 temperature–depth profiles to reconstruct the ground surface temperature of the last 500 years in northern Chile. They suggest that the region experienced a cooling from 1850 to 1980 followed by a warming of 1.9 K. The cooling could coincide with a cooling interval in 1960. The warming is greater than that of proxy reconstructions for nearby regions and model simulations. These differences could be due to differences in spatial and temporal resolution between data and models.
Johann H. Jungclaus, Edouard Bard, Mélanie Baroni, Pascale Braconnot, Jian Cao, Louise P. Chini, Tania Egorova, Michael Evans, J. Fidel González-Rouco, Hugues Goosse, George C. Hurtt, Fortunat Joos, Jed O. Kaplan, Myriam Khodri, Kees Klein Goldewijk, Natalie Krivova, Allegra N. LeGrande, Stephan J. Lorenz, Jürg Luterbacher, Wenmin Man, Amanda C. Maycock, Malte Meinshausen, Anders Moberg, Raimund Muscheler, Christoph Nehrbass-Ahles, Bette I. Otto-Bliesner, Steven J. Phipps, Julia Pongratz, Eugene Rozanov, Gavin A. Schmidt, Hauke Schmidt, Werner Schmutz, Andrew Schurer, Alexander I. Shapiro, Michael Sigl, Jason E. Smerdon, Sami K. Solanki, Claudia Timmreck, Matthew Toohey, Ilya G. Usoskin, Sebastian Wagner, Chi-Ju Wu, Kok Leng Yeo, Davide Zanchettin, Qiong Zhang, and Eduardo Zorita
Geosci. Model Dev., 10, 4005–4033, https://doi.org/10.5194/gmd-10-4005-2017, https://doi.org/10.5194/gmd-10-4005-2017, 2017
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Climate model simulations covering the last millennium provide context for the evolution of the modern climate and for the expected changes during the coming centuries. They can help identify plausible mechanisms underlying palaeoclimatic reconstructions. Here, we describe the forcing boundary conditions and the experimental protocol for simulations covering the pre-industrial millennium. We describe the PMIP4 past1000 simulations as contributions to CMIP6 and additional sensitivity experiments.
Bin Cao, Stephan Gruber, and Tingjun Zhang
Geosci. Model Dev., 10, 2905–2923, https://doi.org/10.5194/gmd-10-2905-2017, https://doi.org/10.5194/gmd-10-2905-2017, 2017
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To derive the air temperature in mountain enviroments, we propose a new downscaling method with a spatially variable magnitude of surface effects. Our findings suggest that the difference between near-surface air temperature and upper-air temerpature is a good proxy of surface effects. It can be used to improve downscaling results, especially in valleys with strong surface effects and cold air pooling during winter.
Stephan Gruber, Renate Fleiner, Emilie Guegan, Prajjwal Panday, Marc-Olivier Schmid, Dorothea Stumm, Philippus Wester, Yinsheng Zhang, and Lin Zhao
The Cryosphere, 11, 81–99, https://doi.org/10.5194/tc-11-81-2017, https://doi.org/10.5194/tc-11-81-2017, 2017
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We review what can be inferred about permafrost in the mountains of the Hindu Kush Himalaya region. This is important because the area of permafrost exceeds that of glaciers in this region. Climate change will produce diverse permafrost-related impacts on vegetation, water quality, geohazards, and livelihoods. To mitigate this, a better understanding of high-elevation permafrost in subtropical latitudes as well as the pathways connecting environmental change and human livelihoods, is needed.
Carolyne Pickler, Hugo Beltrami, and Jean-Claude Mareschal
Clim. Past, 12, 2215–2227, https://doi.org/10.5194/cp-12-2215-2016, https://doi.org/10.5194/cp-12-2215-2016, 2016
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The ground surface temperature histories of the past 500 years were reconstructed at 10 sites in northern Ontario and Quebec. The regions experienced a warming of ~1–2 K for the past 150 years, agreeing with borehole reconstructions for southern Ontario and Quebec and proxy data. Permafrost maps locate the sites in a region of discontinuous permafrost but our reconstructions suggest that the potential for permafrost was minimal to absent over the past 500 years.
Fernando Jaume-Santero, Carolyne Pickler, Hugo Beltrami, and Jean-Claude Mareschal
Clim. Past, 12, 2181–2194, https://doi.org/10.5194/cp-12-2181-2016, https://doi.org/10.5194/cp-12-2181-2016, 2016
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Within the framework of the PAGES NAm2k project, we estimated regional trends in the ground surface temperature change for the past 500 years in North America. The mean North American ground surface temperature history suggests a warming of 1.8 °C between preindustrial times and 2000. A regional analysis of mean temperature changes over the last 5 centuries shows that all regions experienced warming, but this warming displays large spatial variability and is more marked in high-latitude regions.
Ignacio Hermoso de Mendoza, Jean-Claude Mareschal, and Hugo Beltrami
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-116, https://doi.org/10.5194/cp-2016-116, 2016
Preprint retracted
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We simulated ice flow and heat conduction at the Dome C site in Antarctica with a 1D numerical model, using as inputs past conditions at the site over the past 800Ky. Several model parameters (basal heat flux, flux function parameter, ice surface velocity and air-ice temperature offset) are set as free parameters whose values yield different temperature profiles that we can compare to that at Dome C. Using this criteria, we estimate these free parameters through Montecarlo methods.
V. Wirz, S. Gruber, R. S. Purves, J. Beutel, I. Gärtner-Roer, S. Gubler, and A. Vieli
Earth Surf. Dynam., 4, 103–123, https://doi.org/10.5194/esurf-4-103-2016, https://doi.org/10.5194/esurf-4-103-2016, 2016
C. Pickler, H. Beltrami, and J.-C. Mareschal
Clim. Past, 12, 115–127, https://doi.org/10.5194/cp-12-115-2016, https://doi.org/10.5194/cp-12-115-2016, 2016
M.-O. Schmid, P. Baral, S. Gruber, S. Shahi, T. Shrestha, D. Stumm, and P. Wester
The Cryosphere, 9, 2089–2099, https://doi.org/10.5194/tc-9-2089-2015, https://doi.org/10.5194/tc-9-2089-2015, 2015
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The extent and distribution of permafrost in the mountainous parts of the Hindu Kush Himalayan (HKH) region are largely unknown. This article provides a first-order assessment of the two available permafrost maps in the HKH region based on the mapping of rock glaciers in Google Earth. The Circum-Arctic Map of Permafrost and Ground Ice Conditions does not reproduce mapped conditions in the HKH region adequately, whereas the Global Permafrost Zonation Index does so with more success.
A. Hasler, M. Geertsema, V. Foord, S. Gruber, and J. Noetzli
The Cryosphere, 9, 1025–1038, https://doi.org/10.5194/tc-9-1025-2015, https://doi.org/10.5194/tc-9-1025-2015, 2015
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In this paper we describe surface and thermal offsets derived from distributed measurements at seven field sites in British Columbia. Key findings are i) a small variation of the surface offsets between surface types; ii) small thermal offsets at all sites; iii) a clear influence of the micro-topography due to snow cover effects; iv) a north--south difference of the surface offset of 4°C in vertical bedrock and of 1.5–-3°C on open gentle slopes; v) only small macroclimatic differences.
J. Fiddes, S. Endrizzi, and S. Gruber
The Cryosphere, 9, 411–426, https://doi.org/10.5194/tc-9-411-2015, https://doi.org/10.5194/tc-9-411-2015, 2015
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This paper demonstrates a new land surface modelling approach that uses globally available data sets to generate high-resolution simulation results of land surface processes. We successfully simulate a highly resolution-dependent variable, ground surface temperatures, over the entire Swiss Alps at high resolution. We use a large evaluation data set to test the model. We suggest that this scheme represents a useful step in application of numerical models over large areas in heterogeneous terrain.
S. Endrizzi, S. Gruber, M. Dall'Amico, and R. Rigon
Geosci. Model Dev., 7, 2831–2857, https://doi.org/10.5194/gmd-7-2831-2014, https://doi.org/10.5194/gmd-7-2831-2014, 2014
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GEOtop is a fine scale grid-based simulator that represents the heat and water budgets at and below the soil surface, reproduces the highly non-linear interactions between the water and energy balance during soil freezing and thawing and simulates snow cover. The core components of GEOtop 2.0. are described. Based on a synthetic simulation, it is shown that the interaction of processes represented in GEOtop 2.0. can result in phenomena that are relevant for applications involving frozen soils.
V. Wirz, J. Beutel, S. Gruber, S. Gubler, and R. S. Purves
Nat. Hazards Earth Syst. Sci., 14, 2503–2520, https://doi.org/10.5194/nhess-14-2503-2014, https://doi.org/10.5194/nhess-14-2503-2014, 2014
H. Beltrami, G. S. Matharoo, L. Tarasov, V. Rath, and J. E. Smerdon
Clim. Past, 10, 1693–1706, https://doi.org/10.5194/cp-10-1693-2014, https://doi.org/10.5194/cp-10-1693-2014, 2014
J. Fiddes and S. Gruber
Geosci. Model Dev., 7, 387–405, https://doi.org/10.5194/gmd-7-387-2014, https://doi.org/10.5194/gmd-7-387-2014, 2014
S. Gubler, S. Endrizzi, S. Gruber, and R. S. Purves
Geosci. Model Dev., 6, 1319–1336, https://doi.org/10.5194/gmd-6-1319-2013, https://doi.org/10.5194/gmd-6-1319-2013, 2013
P. Ortega, M. Montoya, F. González-Rouco, H. Beltrami, and D. Swingedouw
Clim. Past, 9, 547–565, https://doi.org/10.5194/cp-9-547-2013, https://doi.org/10.5194/cp-9-547-2013, 2013
L. Fernández-Donado, J. F. González-Rouco, C. C. Raible, C. M. Ammann, D. Barriopedro, E. García-Bustamante, J. H. Jungclaus, S. J. Lorenz, J. Luterbacher, S. J. Phipps, J. Servonnat, D. Swingedouw, S. F. B. Tett, S. Wagner, P. Yiou, and E. Zorita
Clim. Past, 9, 393–421, https://doi.org/10.5194/cp-9-393-2013, https://doi.org/10.5194/cp-9-393-2013, 2013
Related subject area
Climate and Earth system modeling
WRF–ML v1.0: a bridge between WRF v4.3 and machine learning parameterizations and its application to atmospheric radiative transfer
The Euro-Mediterranean Center on Climate Change (CMCC) decadal prediction system
Climate impacts of parameterizing subgrid variation and partitioning of land surface heat fluxes to the atmosphere with the NCAR CESM1.2
Accelerated photosynthesis routine in LPJmL4
Improving scalability of Earth system models through coarse-grained component concurrency – a case study with the ICON v2.6.5 modelling system
Temperature forecasting by deep learning methods
Pathfinder v1.0.1: a Bayesian-inferred simple carbon–climate model to explore climate change scenarios
Inclusion of a cold hardening scheme to represent frost tolerance is essential to model realistic plant hydraulics in the Arctic–boreal zone in CLM5.0-FATES-Hydro
Implementation and evaluation of the GEOS-Chem chemistry module version 13.1.2 within the Community Earth System Model v2.1
Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2
Global biomass burning fuel consumption and emissions at 500 m spatial resolution based on the Global Fire Emissions Database (GFED)
Impact of increased resolution on the representation of the Canary upwelling system in climate models
Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI): protocol and initial results from the first simulations
Introducing the VIIRS-based Fire Emission Inventory version 0 (VFEIv0)
Impact of physical parameterizations on wind simulation with WRF V3.9.1.1 under stable conditions at planetary boundary layer gray-zone resolution: a case study over the coastal regions of North China
Advancing precipitation prediction using a new-generation storm-resolving model framework – SIMA-MPAS (V1.0): a case study over the western United States
SURFER v2.0: a flexible and simple model linking anthropogenic CO2 emissions and solar radiation modification to ocean acidification and sea level rise
Modeling the topographic influence on aboveground biomass using a coupled model of hillslope hydrology and ecosystem dynamics
Impacts of the ice-particle size distribution shape parameter on climate simulations with the Community Atmosphere Model Version 6 (CAM6)
A modeling framework to understand historical and projected ocean climate change in large coupled ensembles
TriCCo v1.1.0 – a cubulation-based method for computing connected components on triangular grids
Estimation of missing building height in OpenStreetMap data: a French case study using GeoClimate 0.0.1
The Moist Quasi-Geostrophic Coupled Model: MQ-GCM 2.0
Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)
Transport parameterization of the Polar SWIFT model (version 2)
Analog data assimilation for the selection of suitable general circulation models
Uncertainty and sensitivity analysis for probabilistic weather and climate-risk modelling: an implementation in CLIMADA v.3.1.0
Grid refinement in ICON v2.6.4
Classification of tropical cyclone containing images using a convolutional neural network: performance and sensitivity to the learning dataset
The ICON-A model for direct QBO simulations on GPUs (version icon-cscs:baf28a514)
Evaluation of Native Earth System Model Output with ESMValTool v2.6.0
Further improvement and evaluation of nudging in the E3SM Atmosphere Model version 1 (EAMv1): simulations of the mean climate, weather events, and anthropogenic aerosol effects
HORAYZON v1.2: an efficient and flexible ray-tracing algorithm to compute horizon and sky view factor
LPJ-GUESS/LSMv1.0: a next-generation land surface model with high ecological realism
Downscaling multi-model climate projection ensembles with deep learning (DeepESD): contribution to CORDEX EUR-44
Intercomparison of four algorithms for detecting tropical cyclones using ERA5
Inland lake temperature initialization via coupled cycling with atmospheric data assimilation
wavetrisk-2.1: an adaptive dynamical core for ocean modelling
Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime
AWI-CM3 coupled climate model: description and evaluation experiments for a prototype post-CMIP6 model
The Seasonal-to-Multiyear Large Ensemble (SMYLE) prediction system using the Community Earth System Model version 2
Combining Regional Mesh Refinement With Vertically Enhanced Physics to Target Marine Stratocumulus Biases
Comparison and evaluation of updates to WRF-Chem (v3.9) biogenic emissions using MEGAN
Checkerboard patterns in E3SMv2 and E3SM-MMFv2
AttentionFire_v1.0: interpretable machine learning fire model for burned area predictions over tropics
MIdASv0.2.1 – MultI-scale bias AdjuStment
Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1
Monthly-Scale Extended Predictions Using the Atmospheric Model Coupled with a Slab-Ocean
FOCI-MOPS v1 – integration of marine biogeochemistry within the Flexible Ocean and Climate Infrastructure version 1 (FOCI 1) Earth system model
Assessment of the Paris urban heat island in ERA5 and offline SURFEX-TEB (v8.1) simulations using the METEOSAT land surface temperature product
Xiaohui Zhong, Zhijian Ma, Yichen Yao, Lifei Xu, Yuan Wu, and Zhibin Wang
Geosci. Model Dev., 16, 199–209, https://doi.org/10.5194/gmd-16-199-2023, https://doi.org/10.5194/gmd-16-199-2023, 2023
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More and more researchers use deep learning models to replace physics-based parameterizations to accelerate weather simulations. However, embedding the ML models within the weather models is difficult as they are implemented in different languages. This work proposes a coupling framework to allow ML-based parameterizations to be coupled with the Weather Research and Forecasting (WRF) model. We also demonstrate using the coupler to couple the ML-based radiation schemes with the WRF model.
Dario Nicolì, Alessio Bellucci, Paolo Ruggieri, Panos J. Athanasiadis, Stefano Materia, Daniele Peano, Giusy Fedele, Riccardo Hénin, and Silvio Gualdi
Geosci. Model Dev., 16, 179–197, https://doi.org/10.5194/gmd-16-179-2023, https://doi.org/10.5194/gmd-16-179-2023, 2023
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Decadal climate predictions, obtained by constraining the initial condition of a dynamical model through a truthful estimate of the observed climate state, provide an accurate assessment of the near-term climate and are useful for informing decision-makers on future climate-related risks. The predictive skill for key variables is assessed from the operational decadal prediction system compared with non-initialized historical simulations so as to quantify the added value of initialization.
Ming Yin, Yilun Han, Yong Wang, Wenqi Sun, Jianbo Deng, Daoming Wei, Ying Kong, and Bin Wang
Geosci. Model Dev., 16, 135–156, https://doi.org/10.5194/gmd-16-135-2023, https://doi.org/10.5194/gmd-16-135-2023, 2023
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All global climate models (GCMs) use the grid-averaged surface heat fluxes to drive the atmosphere, and thus their horizontal variations within the grid cell are averaged out. In this regard, a novel scheme considering the variation and partitioning of the surface heat fluxes within the grid cell is developed. The scheme reduces the long-standing rainfall biases on the southern and eastern margins of the Tibetan Plateau. The performance of key variables at the global scale is also evaluated.
Jenny Niebsch, Werner von Bloh, Kirsten Thonicke, and Ronny Ramlau
Geosci. Model Dev., 16, 17–33, https://doi.org/10.5194/gmd-16-17-2023, https://doi.org/10.5194/gmd-16-17-2023, 2023
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The impacts of climate change require strategies for climate adaptation. Dynamic global vegetation models (DGVMs) are used to study the effects of multiple processes in the biosphere under climate change. There is a demand for a better computational performance of the models. In this paper, the photosynthesis model in the Lund–Potsdam–Jena managed Land DGVM (4.0.002) was examined. We found a better numerical solution of a nonlinear equation. A significant run time reduction was possible.
Leonidas Linardakis, Irene Stemmler, Moritz Hanke, Lennart Ramme, Fatemeh Chegini, Tatiana Ilyina, and Peter Korn
Geosci. Model Dev., 15, 9157–9176, https://doi.org/10.5194/gmd-15-9157-2022, https://doi.org/10.5194/gmd-15-9157-2022, 2022
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In Earth system modelling, we are facing the challenge of making efficient use of very large machines, with millions of cores. To meet this challenge we will need to employ multi-level and multi-dimensional parallelism. Component concurrency, being a function parallel technique, offers an additional dimension to the traditional data-parallel approaches. In this paper we examine the behaviour of component concurrency and identify the conditions for its optimal application.
Bing Gong, Michael Langguth, Yan Ji, Amirpasha Mozaffari, Scarlet Stadtler, Karim Mache, and Martin G. Schultz
Geosci. Model Dev., 15, 8931–8956, https://doi.org/10.5194/gmd-15-8931-2022, https://doi.org/10.5194/gmd-15-8931-2022, 2022
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Inspired by the success of deep learning in various domains, we test the applicability of video prediction methods by generative adversarial network (GAN)-based deep learning to predict the 2 m temperature over Europe. Our video prediction models have skill in predicting the diurnal cycle of 2 m temperature up to 12 h ahead. Complemented by probing the relevance of several model parameters, this study confirms the potential of deep learning in meteorological forecasting applications.
Thomas Bossy, Thomas Gasser, and Philippe Ciais
Geosci. Model Dev., 15, 8831–8868, https://doi.org/10.5194/gmd-15-8831-2022, https://doi.org/10.5194/gmd-15-8831-2022, 2022
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We developed a new simple climate model designed to fill a perceived gap within the existing simple climate models by fulfilling three key requirements: calibration using Bayesian inference, the possibility of coupling with integrated assessment models, and the capacity to explore climate scenarios compatible with limiting climate impacts. Here, we describe the model and its calibration using the latest data from complex CMIP6 models and the IPCC AR6, and we assess its performance.
Marius S. A. Lambert, Hui Tang, Kjetil S. Aas, Frode Stordal, Rosie A. Fisher, Yilin Fang, Junyan Ding, and Frans-Jan W. Parmentier
Geosci. Model Dev., 15, 8809–8829, https://doi.org/10.5194/gmd-15-8809-2022, https://doi.org/10.5194/gmd-15-8809-2022, 2022
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In this study, we implement a hardening mortality scheme into CTSM5.0-FATES-Hydro and evaluate how it impacts plant hydraulics and vegetation growth. Our work shows that the hydraulic modifications prescribed by the hardening scheme are necessary to model realistic vegetation growth in cold climates, in contrast to the default model that simulates almost nonexistent and declining vegetation due to abnormally large water loss through the roots.
Thibaud M. Fritz, Sebastian D. Eastham, Louisa K. Emmons, Haipeng Lin, Elizabeth W. Lundgren, Steve Goldhaber, Steven R. H. Barrett, and Daniel J. Jacob
Geosci. Model Dev., 15, 8669–8704, https://doi.org/10.5194/gmd-15-8669-2022, https://doi.org/10.5194/gmd-15-8669-2022, 2022
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We bring the state-of-the-science chemistry module GEOS-Chem into the Community Earth System Model (CESM). We show that some known differences between results from GEOS-Chem and CESM's CAM-chem chemistry module may be due to the configuration of model meteorology rather than inherent differences in the model chemistry. This is a significant step towards a truly modular Earth system model and allows two strong but currently separate research communities to benefit from each other's advances.
Rainer Schneck, Veronika Gayler, Julia E. M. S. Nabel, Thomas Raddatz, Christian H. Reick, and Reiner Schnur
Geosci. Model Dev., 15, 8581–8611, https://doi.org/10.5194/gmd-15-8581-2022, https://doi.org/10.5194/gmd-15-8581-2022, 2022
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The versions of ICON-A and ICON-Land/JSBACHv4 used for this study constitute the first milestone in the development of the new ICON Earth System Model ICON-ESM. JSBACHv4 is the successor of JSBACHv3, and most of the parameterizations of JSBACHv4 are re-implementations from JSBACHv3. We assess and compare the performance of JSBACHv4 and JSBACHv3. Overall, the JSBACHv4 results are as good as JSBACHv3, but both models reveal the same main shortcomings, e.g. the depiction of the leaf area index.
Dave van Wees, Guido R. van der Werf, James T. Randerson, Brendan M. Rogers, Yang Chen, Sander Veraverbeke, Louis Giglio, and Douglas C. Morton
Geosci. Model Dev., 15, 8411–8437, https://doi.org/10.5194/gmd-15-8411-2022, https://doi.org/10.5194/gmd-15-8411-2022, 2022
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We present a global fire emission model based on the GFED model framework with a spatial resolution of 500 m. The higher resolution allowed for a more detailed representation of spatial heterogeneity in fuels and emissions. Specific modules were developed to model, for example, emissions from fire-related forest loss and belowground burning. Results from the 500 m model were compared to GFED4s, showing that global emissions were relatively similar but that spatial differences were substantial.
Adama Sylla, Emilia Sanchez Gomez, Juliette Mignot, and Jorge López-Parages
Geosci. Model Dev., 15, 8245–8267, https://doi.org/10.5194/gmd-15-8245-2022, https://doi.org/10.5194/gmd-15-8245-2022, 2022
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Increasing model resolution depends on the subdomain of the Canary upwelling considered. In the Iberian Peninsula, the high-resolution (HR) models do not seem to better simulate the upwelling indices, while in Morocco to the Senegalese coast, the HR models show a clear improvement. Thus increasing the resolution of a global climate model does not necessarily have to be the only way to better represent the climate system. There is still much work to be done in terms of physical parameterizations.
Jadwiga H. Richter, Daniele Visioni, Douglas G. MacMartin, David A. Bailey, Nan Rosenbloom, Brian Dobbins, Walker R. Lee, Mari Tye, and Jean-Francois Lamarque
Geosci. Model Dev., 15, 8221–8243, https://doi.org/10.5194/gmd-15-8221-2022, https://doi.org/10.5194/gmd-15-8221-2022, 2022
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Solar climate intervention using stratospheric aerosol injection is a proposed method of reducing global mean temperatures to reduce the worst consequences of climate change. We present a new modeling protocol aimed at simulating a plausible deployment of stratospheric aerosol injection and reproducibility of simulations using other Earth system models: Assessing Responses and Impacts of Solar climate intervention on the Earth system with stratospheric aerosol injection (ARISE-SAI).
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Entao Yu, Rui Bai, Xia Chen, and Lifang Shao
Geosci. Model Dev., 15, 8111–8134, https://doi.org/10.5194/gmd-15-8111-2022, https://doi.org/10.5194/gmd-15-8111-2022, 2022
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A large number of simulations are conducted to investigate how different physical parameterization schemes impact surface wind simulations under stable weather conditions over the coastal regions of North China using the Weather Research and Forecasting model with a horizontal grid spacing of 0.5 km. Results indicate that the simulated wind speed is most sensitive to the planetary boundary layer schemes, followed by short-wave/long-wave radiation schemes and microphysics schemes.
Xingying Huang, Andrew Gettelman, William C. Skamarock, Peter Hjort Lauritzen, Miles Curry, Adam Herrington, John T. Truesdale, and Michael Duda
Geosci. Model Dev., 15, 8135–8151, https://doi.org/10.5194/gmd-15-8135-2022, https://doi.org/10.5194/gmd-15-8135-2022, 2022
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We focus on the recent development of a state-of-the-art storm-resolving global climate model and investigate how this next-generation model performs for precipitation prediction over the western USA. Results show realistic representations of precipitation with significantly enhanced snowpack over complex terrains. The model evaluation advances the unified modeling of large-scale forcing constraints and realistic fine-scale features to advance multi-scale climate predictions and changes.
Marina Martínez Montero, Michel Crucifix, Victor Couplet, Nuria Brede, and Nicola Botta
Geosci. Model Dev., 15, 8059–8084, https://doi.org/10.5194/gmd-15-8059-2022, https://doi.org/10.5194/gmd-15-8059-2022, 2022
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We present SURFER, a lightweight model that links CO2 emissions and geoengineering to ocean acidification and sea level rise from glaciers, ocean thermal expansion and Greenland and Antarctic ice sheets. The ice sheet module adequately describes the tipping points of both Greenland and Antarctica. SURFER is understandable, fast, accurate up to several thousands of years, capable of emulating results obtained by state of the art models and well suited for policy analyses.
Yilin Fang, L. Ruby Leung, Charles D. Koven, Gautam Bisht, Matteo Detto, Yanyan Cheng, Nate McDowell, Helene Muller-Landau, S. Joseph Wright, and Jeffrey Q. Chambers
Geosci. Model Dev., 15, 7879–7901, https://doi.org/10.5194/gmd-15-7879-2022, https://doi.org/10.5194/gmd-15-7879-2022, 2022
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We develop a model that integrates an Earth system model with a three-dimensional hydrology model to explicitly resolve hillslope topography and water flow underneath the land surface to understand how local-scale hydrologic processes modulate vegetation along water availability gradients. Our coupled model can be used to improve the understanding of the diverse impact of local heterogeneity and water flux on nutrient availability and plant communities.
Wentao Zhang, Xiangjun Shi, and Chunsong Lu
Geosci. Model Dev., 15, 7751–7766, https://doi.org/10.5194/gmd-15-7751-2022, https://doi.org/10.5194/gmd-15-7751-2022, 2022
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The two-moment bulk cloud microphysics scheme used in CAM6 was modified to consider the impacts of the ice-crystal size distribution shape parameter (μi). After that, how the μi impacts cloud microphysical processes and then climate simulations is clearly illustrated by offline tests and CAM6 model experiments. Our results and findings are useful for the further development of μi-related parameterizations.
Yona Silvy, Clément Rousset, Eric Guilyardi, Jean-Baptiste Sallée, Juliette Mignot, Christian Ethé, and Gurvan Madec
Geosci. Model Dev., 15, 7683–7713, https://doi.org/10.5194/gmd-15-7683-2022, https://doi.org/10.5194/gmd-15-7683-2022, 2022
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A modeling framework is introduced to understand and decompose the mechanisms causing the ocean temperature, salinity and circulation to change since the pre-industrial period and into 21st century scenarios of global warming. This framework aims to look at the response to changes in the winds and in heat and freshwater exchanges at the ocean interface in global climate models, throughout the 1850–2100 period, to unravel their individual effects on the changing physical structure of the ocean.
Aiko Voigt, Petra Schwer, Noam von Rotberg, and Nicole Knopf
Geosci. Model Dev., 15, 7489–7504, https://doi.org/10.5194/gmd-15-7489-2022, https://doi.org/10.5194/gmd-15-7489-2022, 2022
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In climate science, it is helpful to identify coherent objects, for example, those formed by clouds. However, many models now use unstructured grids, which makes it harder to identify coherent objects. We present a new method that solves this problem by moving model data from an unstructured triangular grid to a structured cubical grid. We implement the method in an open-source Python package and show that the method is ready to be applied to climate model data.
Jérémy Bernard, Erwan Bocher, Elisabeth Le Saux Wiederhold, François Leconte, and Valéry Masson
Geosci. Model Dev., 15, 7505–7532, https://doi.org/10.5194/gmd-15-7505-2022, https://doi.org/10.5194/gmd-15-7505-2022, 2022
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OpenStreetMap is a collaborative project aimed at creaing a free dataset containing topographical information. Since these data are available worldwide, they can be used as standard data for geoscience studies. However, most buildings miss the height information that constitutes key data for numerous fields (urban climate, noise propagation, air pollution). In this work, the building height is estimated using statistical modeling using indicators that characterize the building's environment.
Sergey Kravtsov, Ilijana Mastilovic, Andrew McC. Hogg, William K. Dewar, and Jeffrey R. Blundell
Geosci. Model Dev., 15, 7449–7469, https://doi.org/10.5194/gmd-15-7449-2022, https://doi.org/10.5194/gmd-15-7449-2022, 2022
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Climate is a complex system whose behavior is shaped by multitudes of processes operating on widely different spatial scales and timescales. In hierarchical modeling, one goes back and forth between highly idealized process models and state-of-the-art models coupling the entire range of climate subsystems to identify specific phenomena and understand their dynamics. The present contribution highlights an intermediate climate model focussing on midlatitude ocean–atmosphere interactions.
Edmund P. Meredith, Uwe Ulbrich, and Henning W. Rust
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-202, https://doi.org/10.5194/gmd-2022-202, 2022
Revised manuscript accepted for GMD
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Cell tracking algorithms allow the properties of a convective cell to be studied across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm’s criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Ingo Wohltmann, Daniel Kreyling, and Ralph Lehmann
Geosci. Model Dev., 15, 7243–7255, https://doi.org/10.5194/gmd-15-7243-2022, https://doi.org/10.5194/gmd-15-7243-2022, 2022
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The study evaluates the performance of the Data Assimilation Research Testbed (DART), equipped with the recently added forward operator Radiative Transfer for TOVS (RTTOV), in assimilating FY-4A visible images into the Weather Research and Forecasting (WRF) model. The ability of the WRF-DART/RTTOV system to improve the forecasting skills for a tropical storm over East Asia and the Western Pacific is demonstrated in an Observing System Simulation Experiment framework.
Juan Ruiz, Pierre Ailliot, Thi Tuyet Trang Chau, Pierre Le Bras, Valérie Monbet, Florian Sévellec, and Pierre Tandeo
Geosci. Model Dev., 15, 7203–7220, https://doi.org/10.5194/gmd-15-7203-2022, https://doi.org/10.5194/gmd-15-7203-2022, 2022
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We present a new approach to validate numerical simulations of the current climate. The method can take advantage of existing climate simulations produced by different centers combining an analog forecasting approach with data assimilation to quantify how well a particular model reproduces a sequence of observed values. The method can be applied with different observations types and is implemented locally in space and time significantly reducing the associated computational cost.
Chahan M. Kropf, Alessio Ciullo, Laura Otth, Simona Meiler, Arun Rana, Emanuel Schmid, Jamie W. McCaughey, and David N. Bresch
Geosci. Model Dev., 15, 7177–7201, https://doi.org/10.5194/gmd-15-7177-2022, https://doi.org/10.5194/gmd-15-7177-2022, 2022
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Mathematical models are approximations, and modellers need to understand and ideally quantify the arising uncertainties. Here, we describe and showcase the first, simple-to-use, uncertainty and sensitivity analysis module of the open-source and open-access climate-risk modelling platform CLIMADA. This may help to enhance transparency and intercomparison of studies among climate-risk modellers, help focus future research, and lead to better-informed decisions on climate adaptation.
Günther Zängl, Daniel Reinert, and Florian Prill
Geosci. Model Dev., 15, 7153–7176, https://doi.org/10.5194/gmd-15-7153-2022, https://doi.org/10.5194/gmd-15-7153-2022, 2022
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This article describes the implementation of grid refinement in the ICOsahedral Nonhydrostatic (ICON) model, which has been jointly developed at several German institutions and constitutes a unified modeling system for global and regional numerical weather prediction and climate applications. The grid refinement allows using a higher resolution in regional domains and transferring the information back to the global domain by means of a feedback mechanism.
Sébastien Gardoll and Olivier Boucher
Geosci. Model Dev., 15, 7051–7073, https://doi.org/10.5194/gmd-15-7051-2022, https://doi.org/10.5194/gmd-15-7051-2022, 2022
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Tropical cyclones (TCs) are one of the most devastating natural disasters, which justifies monitoring and prediction in the context of a changing climate. In this study, we have adapted and tested a convolutional neural network (CNN) for the classification of reanalysis outputs (ERA5 and MERRA-2 labeled by HURDAT2) according to the presence or absence of TCs. We tested the impact of interpolation and of "mixing and matching" the training and test sets on the performance of the CNN.
Marco A. Giorgetta, William Sawyer, Xavier Lapillonne, Panagiotis Adamidis, Dmitry Alexeev, Valentin Clément, Remo Dietlicher, Jan Frederik Engels, Monika Esch, Henning Franke, Claudia Frauen, Walter M. Hannah, Benjamin R. Hillman, Luis Kornblueh, Philippe Marti, Matthew R. Norman, Robert Pincus, Sebastian Rast, Daniel Reinert, Reiner Schnur, Uwe Schulzweida, and Bjorn Stevens
Geosci. Model Dev., 15, 6985–7016, https://doi.org/10.5194/gmd-15-6985-2022, https://doi.org/10.5194/gmd-15-6985-2022, 2022
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This work presents a first version of the ICON atmosphere model that works not only on CPUs, but also on GPUs. This GPU-enabled ICON version is benchmarked on two GPU machines and a CPU machine. While the weak scaling is very good on CPUs and GPUs, the strong scaling is poor on GPUs. But the high performance of GPU machines allowed for first simulations of a short period of the quasi-biennial oscillation at very high resolution with explicit convection and gravity wave forcing.
Manuel Schlund, Birgit Hassler, Axel Lauer, Bouwe Andela, Patrick Jöckel, Rémi Kazeroni, Saskia Loosveldt Tomas, Brian Medeiros, Valeriu Predoi, Stéphane Sénési, Jérôme Servonnat, Tobias Stacke, Javier Vegas-Regidor, Klaus Zimmermann, and Veronika Eyring
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-205, https://doi.org/10.5194/gmd-2022-205, 2022
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for routine evaluation of Earth system models. Originally, ESMValTool has been designed to process reformatted output provided by large model intercomparison projects like the Coupled Model Intercomparison Project (CMIP). Here, we describe a new extension of ESMValTool that allows reading and processing native climate model output, i.e., data that has not been reformatted before.
Shixuan Zhang, Kai Zhang, Hui Wan, and Jian Sun
Geosci. Model Dev., 15, 6787–6816, https://doi.org/10.5194/gmd-15-6787-2022, https://doi.org/10.5194/gmd-15-6787-2022, 2022
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This study investigates the nudging implementation in the EAMv1 model. We find that (1) revising the sequence of calculations and using higher-frequency constraining data to improve the performance of a simulation nudged to EAMv1’s own meteorology, (2) using the relocated nudging tendency and 3-hourly ERA5 reanalysis to obtain a better agreement between nudged simulations and observations, and (3) using wind-only nudging are recommended for the estimates of global mean aerosol effects.
Christian R. Steger, Benjamin Steger, and Christoph Schär
Geosci. Model Dev., 15, 6817–6840, https://doi.org/10.5194/gmd-15-6817-2022, https://doi.org/10.5194/gmd-15-6817-2022, 2022
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Terrain horizon and sky view factor are crucial quantities for many geoscientific applications; e.g. they are used to account for effects of terrain on surface radiation in climate and land surface models. Because typical terrain horizon algorithms are inefficient for high-resolution (< 30 m) elevation data, we developed a new algorithm based on a ray-tracing library. A comparison with two conventional methods revealed both its high performance and its accuracy for complex terrain.
David Martín Belda, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth
Geosci. Model Dev., 15, 6709–6745, https://doi.org/10.5194/gmd-15-6709-2022, https://doi.org/10.5194/gmd-15-6709-2022, 2022
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We present a number of augmentations to the ecosystem model LPJ-GUESS, which will allow us to use it in studies of the interactions between the land biosphere and the climate. The new module enables calculation of fluxes of energy and water into the atmosphere that are consistent with the modelled vegetation processes. The modelled fluxes are in fair agreement with observations across 21 sites from the FLUXNET network.
Jorge Baño-Medina, Rodrigo Manzanas, Ezequiel Cimadevilla, Jesús Fernández, Jose González-Abad, Antonio S. Cofiño, and José Manuel Gutiérrez
Geosci. Model Dev., 15, 6747–6758, https://doi.org/10.5194/gmd-15-6747-2022, https://doi.org/10.5194/gmd-15-6747-2022, 2022
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Deep neural networks are used to produce downscaled regional climate change projections over Europe for temperature and precipitation for the first time. The resulting dataset, DeepESD, is analyzed against state-of-the-art downscaling methodologies, reproducing more accurately the observed climate in the historical period and showing plausible future climate change signals with low computational requirements.
Stella Bourdin, Sébastien Fromang, William Dulac, Julien Cattiaux, and Fabrice Chauvin
Geosci. Model Dev., 15, 6759–6786, https://doi.org/10.5194/gmd-15-6759-2022, https://doi.org/10.5194/gmd-15-6759-2022, 2022
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When studying tropical cyclones in a large dataset, one needs objective and automatic procedures to detect their specific pattern. Applying four different such algorithms to a reconstruction of the climate, we show that the choice of the algorithm is crucial to the climatology obtained. Mainly, the algorithms differ in their sensitivity to weak storms so that they provide different frequencies and durations. We review the different options to consider for the choice of the tracking methodology.
Stanley G. Benjamin, Tatiana G. Smirnova, Eric P. James, Eric J. Anderson, Ayumi Fujisaki-Manome, John G. W. Kelley, Greg E. Mann, Andrew D. Gronewold, Philip Chu, and Sean G. T. Kelley
Geosci. Model Dev., 15, 6659–6676, https://doi.org/10.5194/gmd-15-6659-2022, https://doi.org/10.5194/gmd-15-6659-2022, 2022
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Application of 1-D lake models coupled within earth-system prediction models will improve accuracy but requires accurate initialization of lake temperatures. Here, we describe a lake initialization method by cycling within a weather prediction model to constrain lake temperature evolution. We compared these lake temperature values with other estimates and found much reduced errors (down to 1-2 K). The lake cycling initialization is now applied to two operational US NOAA weather models.
Nicholas K.-R. Kevlahan and Florian Lemarié
Geosci. Model Dev., 15, 6521–6539, https://doi.org/10.5194/gmd-15-6521-2022, https://doi.org/10.5194/gmd-15-6521-2022, 2022
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WAVETRISK-2.1 is an innovative climate model for the world's oceans. It uses state-of-the-art techniques to change the model's resolution locally, from O(100 km) to O(5 km), as the ocean changes. This dynamic adaptivity makes optimal use of available supercomputer resources, and allows two-dimensional global scales and three-dimensional submesoscales to be captured in the same simulation. WAVETRISK-2.1 is designed to be coupled its companion global atmosphere model, WAVETRISK-1.x.
Meng Huang, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung
Geosci. Model Dev., 15, 6371–6384, https://doi.org/10.5194/gmd-15-6371-2022, https://doi.org/10.5194/gmd-15-6371-2022, 2022
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The land surface in one grid cell may be diverse in character. This study uses an explicit way to account for that subgrid diversity in a state-of-the-art Earth system model (ESM) and explores its implications for the overlying atmosphere. We find that the shallow clouds are increased significantly with the land surface diversity. Our work highlights the importance of accurately representing the land surface and its interaction with the atmosphere in next-generation ESMs.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Stephen G. Yeager, Nan Rosenbloom, Anne A. Glanville, Xian Wu, Isla Simpson, Hui Li, Maria J. Molina, Kristen Krumhardt, Samuel Mogen, Keith Lindsay, Danica Lombardozzi, Will Wieder, Who M. Kim, Jadwiga H. Richter, Matthew Long, Gokhan Danabasoglu, David Bailey, Marika Holland, Nicole Lovenduski, Warren G. Strand, and Teagan King
Geosci. Model Dev., 15, 6451–6493, https://doi.org/10.5194/gmd-15-6451-2022, https://doi.org/10.5194/gmd-15-6451-2022, 2022
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The Earth system changes over a range of time and space scales, and some of these changes are predictable in advance. Short-term weather forecasts are most familiar, but recent work has shown that it is possible to generate useful predictions several seasons or even a decade in advance. This study focuses on predictions over intermediate timescales (up to 24 months in advance) and shows that there is promising potential to forecast a variety of changes in the natural environment.
Peter A. Bogenschutz, Hsiang-He Lee, Qi Tang, and Takanobu Yamaguchi
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-175, https://doi.org/10.5194/gmd-2022-175, 2022
Revised manuscript accepted for GMD
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Models that are used to simulated and predict climate often have trouble representing specific cloud types, such as stratocumulus, that are particularly thin in the vertical direction. It has been found that increasing the model resolution can help improve this problem. In this paper we develop a novel framework that increases the horizontal and vertical resolution only for areas of the globe that contain stratocumulus, hence reducing model run-time while providing better results.
Mauro Morichetti, Sasha Madronich, Giorgio Passerini, Umberto Rizza, Enrico Mancinelli, Simone Virgili, and Mary Barth
Geosci. Model Dev., 15, 6311–6339, https://doi.org/10.5194/gmd-15-6311-2022, https://doi.org/10.5194/gmd-15-6311-2022, 2022
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In the present study, we explore the effect of making simple changes to the existing WRF-Chem MEGAN v2.04 emissions to provide MEGAN updates that can be used independently of the land surface model chosen. The changes made to the MEGAN algorithm implemented in WRF-Chem were the following: (i) update of the emission activity factors, (ii) update of emission factor values for each plant functional type (PFT), and (iii) the assignment of the emission factor by PFT to isoprene.
Walter Hannah, Kyle Pressel, Mikhail Ovchinnikov, and Gregory Elsaesser
Geosci. Model Dev., 15, 6243–6257, https://doi.org/10.5194/gmd-15-6243-2022, https://doi.org/10.5194/gmd-15-6243-2022, 2022
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An unphysical checkerboard signal is identified in two configurations of the atmospheric component of E3SM. The signal is very persistent and visible after averaging years of data. The signal is very difficult to study because it is often mixed with realistic weather. A method is presented to detect checkerboard patterns and compare the model with satellite observations. The causes of the signal are identified, and a solution for one configuration is discussed.
Fa Li, Qing Zhu, William Riley, Lei Zhao, Li Xu, Kunxiaojia Yuan, Min Chen, Huayi Wu, Zhipeng Gui, Jianya Gong, and James Randerson
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-195, https://doi.org/10.5194/gmd-2022-195, 2022
Preprint under review for GMD
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In this work, we developed an interpretable machine learning model to predict sub-seasonal and near future wildfire burned area over African and South American regions. We found strong time-lagged controls (up to 6–8 month) from local climate wetness on burned areas. A skillful use of such time-lagged controls in machine learning model result in high accurate predictions of wildfire burned area, also will help develop relevant early warming and management system for tropical wildfire.
Peter Berg, Thomas Bosshard, Wei Yang, and Klaus Zimmermann
Geosci. Model Dev., 15, 6165–6180, https://doi.org/10.5194/gmd-15-6165-2022, https://doi.org/10.5194/gmd-15-6165-2022, 2022
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When performing impact analyses with climate models, one is often confronted with the issue that the models have significant bias. Commonly, the modelled climatological temperature deviates from the observed climate by a few degrees or it rains excessively in the model. MIdAS employs a novel statistical model to translate the model climatology toward that observed using novel methodologies and modern tools. The coding platform allows opportunities to develop methods for high-resolution models.
Heather Suzanne Rumbold, Richard J. J. Gilham, and Martin John Best
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-139, https://doi.org/10.5194/gmd-2022-139, 2022
Preprint under review for GMD
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The Joint UK Land Environment Simulator (JULES) uses a tiled representation of land cover but can only model a single dominant soil type within a grid box, hence there is no representation of sub-grid soil heterogeneity. This paper evaluates a new surface-soil tiling scheme in JULES and demonstrates the impacts of the scheme using several soil tiling approaches. Results show that soil tiling has an impact on the water and energy exchanges due to the way vegetation accesses the soil moisture.
Zhenming Wang, Shaoqing Zhang, Yishuai Jin, Yinglai Jia, Yangyang Yu, Yang Gao, Xiaolin Yu, Mingkui Li, Xiaopei Lin, and Lixin Wu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2022-159, https://doi.org/10.5194/gmd-2022-159, 2022
Revised manuscript accepted for GMD
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To improve the numerical model predictability of monthly extended-range scales, we use the simplified SOM to restrict the complicated SST bias from 3-D dynamical ocean model. As for SST prediction, whether in space or time, the WRF-SOM is verified to have the performance than that of the WRF-ROMS, which has a significant impact on the atmosphere. For the extreme weather event such as typhoons, the predictions of WRF-SOM are in good agreement with WRF-ROMS.
Chia-Te Chien, Jonathan V. Durgadoo, Dana Ehlert, Ivy Frenger, David P. Keller, Wolfgang Koeve, Iris Kriest, Angela Landolfi, Lavinia Patara, Sebastian Wahl, and Andreas Oschlies
Geosci. Model Dev., 15, 5987–6024, https://doi.org/10.5194/gmd-15-5987-2022, https://doi.org/10.5194/gmd-15-5987-2022, 2022
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We present the implementation and evaluation of a marine biogeochemical model, Model of Oceanic Pelagic Stoichiometry (MOPS) in the Flexible Ocean and Climate Infrastructure (FOCI) climate model. FOCI-MOPS enables the simulation of marine biological processes, the marine carbon, nitrogen and oxygen cycles, and air–sea gas exchange of CO2 and O2. As shown by our evaluation, FOCI-MOPS shows an overall adequate performance that makes it an appropriate tool for Earth climate system simulations.
Miguel Nogueira, Alexandra Hurduc, Sofia Ermida, Daniela C. A. Lima, Pedro M. M. Soares, Frederico Johannsen, and Emanuel Dutra
Geosci. Model Dev., 15, 5949–5965, https://doi.org/10.5194/gmd-15-5949-2022, https://doi.org/10.5194/gmd-15-5949-2022, 2022
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We evaluated the quality of the ERA5 reanalysis representation of the urban heat island (UHI) over the city of Paris and performed a set of offline runs using the SURFEX land surface model. They were compared with observations (satellite and in situ). The SURFEX-TEB runs showed the best performance in representing the UHI, reducing its bias significantly. We demonstrate the ability of the SURFEX-TEB framework to simulate urban climate, which is crucial for studying climate change in cities.
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Short summary
Inversions of subsurface temperature profiles provide past long-term estimates of ground surface temperature histories and ground heat flux histories at timescales of decades to millennia. Theses estimates complement high-frequency proxy temperature reconstructions and are the basis for studying continental heat storage. We develop and release a new bootstrap method to derive meaningful confidence intervals for the average surface temperature and heat flux histories from any number of profiles.
Inversions of subsurface temperature profiles provide past long-term estimates of ground surface...
