Articles | Volume 16, issue 2
https://doi.org/10.5194/gmd-16-449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-449-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
23 Jan 2023
Model description paper |
| 23 Jan 2023
| 23 Jan 2023
URANOS v1.0 – the Ultra Rapid Adaptable Neutron-Only Simulation for Environmental Research
Markus Köhli
CORRESPONDING AUTHOR
Physikalisches Institut, Heidelberg University, Heidelberg, Germany
Physikalisches Institut, University of Bonn, Bonn, Germany
Martin Schrön
Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Steffen Zacharias
Department of Monitoring and Exploration Technologies, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany
Ulrich Schmidt
Physikalisches Institut, Heidelberg University, Heidelberg, Germany
Related authors
Daniel Rasche, Jannis Weimar, Martin Schrön, Markus Köhli, Markus Morgner, Andreas Güntner, and Theresa Blume
Hydrol. Earth Syst. Sci., 27, 3059–3082, https://doi.org/10.5194/hess-27-3059-2023, https://doi.org/10.5194/hess-27-3059-2023, 2023
Short summary
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We introduce passive downhole cosmic-ray neutron sensing (d-CRNS) as an approach for the non-invasive estimation of soil moisture in deeper layers of the unsaturated zone which exceed the observational window of above-ground CRNS applications. Neutron transport simulations are used to derive mathematical descriptions and transfer functions, while experimental measurements in an existing groundwater observation well illustrate the feasibility and applicability of the approach.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
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Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Martin Schrön, Markus Köhli, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 27, 723–738, https://doi.org/10.5194/hess-27-723-2023, https://doi.org/10.5194/hess-27-723-2023, 2023
Short summary
Short summary
This paper presents a new analytical concept to answer long-lasting questions of the cosmic-ray neutron sensing community, such as
what is the influence of a distant area or patches of different land use on the measurement signal?or
is the detector sensitive enough to detect a change of soil moisture (e.g. due to irrigation) in a remote field at a certain distance?The concept may support signal interpretation and sensor calibration, particularly in heterogeneous terrain.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Till Francke, Maik Heistermann, Markus Köhli, Christian Budach, Martin Schrön, and Sascha E. Oswald
Geosci. Instrum. Method. Data Syst., 11, 75–92, https://doi.org/10.5194/gi-11-75-2022, https://doi.org/10.5194/gi-11-75-2022, 2022
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools like soil moisture, snow, or vegetation. This study presents a directional shielding approach, aiming to measure in specific directions only. The results show that non-directional neutron transport blurs the signal of the targeted direction. For typical instruments, this does not allow acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates is feasible.
Daniel Rasche, Markus Köhli, Martin Schrön, Theresa Blume, and Andreas Güntner
Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, https://doi.org/10.5194/hess-25-6547-2021, 2021
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Cosmic-ray neutron sensing provides areal average soil moisture measurements. We investigated how distinct differences in spatial soil moisture patterns influence the soil moisture estimates and present two approaches to improve the estimate of soil moisture close to the instrument by reducing the influence of soil moisture further afield. Additionally, we show that the heterogeneity of soil moisture can be assessed based on the relationship of different neutron energies.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Martin Schrön, Steffen Zacharias, Gary Womack, Markus Köhli, Darin Desilets, Sascha E. Oswald, Jan Bumberger, Hannes Mollenhauer, Simon Kögler, Paul Remmler, Mandy Kasner, Astrid Denk, and Peter Dietrich
Geosci. Instrum. Method. Data Syst., 7, 83–99, https://doi.org/10.5194/gi-7-83-2018, https://doi.org/10.5194/gi-7-83-2018, 2018
Short summary
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Cosmic-ray neutron sensing (CRNS) is a unique technology to monitor water storages in complex environments, non-invasively, continuously, autonomuously, and representatively in large areas. However, neutron detector signals are not comparable per se: there is statistical noise, technical differences, and locational effects. We found out what it takes to make CRNS consistent in time and space to ensure reliable data quality. We further propose a method to correct for sealed areas in the footrint.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
Short summary
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A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Paolo Nasta, Günter Blöschl, Heye R. Bogena, Steffen Zacharias, Roland Baatz, Gabriëlle De Lannoy, Karsten H. Jensen, Salvatore Manfreda, Laurent Pfister, Ana M. Tarquis, Ilja van Meerveld, Marc Voltz, Yijian Zeng, William Kustas, Xin Li, Harry Vereecken, and Nunzio Romano
EGUsphere, https://doi.org/10.5194/egusphere-2024-1678, https://doi.org/10.5194/egusphere-2024-1678, 2024
Short summary
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The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to tackle catchment-scale challenges on a global scale. This opinion paper provocatively discusses two end members of possible future hydrological observatory (HO) networks for a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented super-sites.
Maik Heistermann, Till Francke, Martin Schrön, and Sascha E. Oswald
Hydrol. Earth Syst. Sci., 28, 989–1000, https://doi.org/10.5194/hess-28-989-2024, https://doi.org/10.5194/hess-28-989-2024, 2024
Short summary
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Cosmic-ray neutron sensing (CRNS) is a non-invasive technique used to obtain estimates of soil water content (SWC) at a horizontal footprint of around 150 m and a vertical penetration depth of up to 30 cm. However, typical CRNS applications require the local calibration of a function which converts neutron counts to SWC. As an alternative, we propose a generalized function as a way to avoid the use of local reference measurements of SWC and hence a major source of uncertainty.
Daniel Rasche, Jannis Weimar, Martin Schrön, Markus Köhli, Markus Morgner, Andreas Güntner, and Theresa Blume
Hydrol. Earth Syst. Sci., 27, 3059–3082, https://doi.org/10.5194/hess-27-3059-2023, https://doi.org/10.5194/hess-27-3059-2023, 2023
Short summary
Short summary
We introduce passive downhole cosmic-ray neutron sensing (d-CRNS) as an approach for the non-invasive estimation of soil moisture in deeper layers of the unsaturated zone which exceed the observational window of above-ground CRNS applications. Neutron transport simulations are used to derive mathematical descriptions and transfer functions, while experimental measurements in an existing groundwater observation well illustrate the feasibility and applicability of the approach.
Maik Heistermann, Till Francke, Lena Scheiffele, Katya Dimitrova Petrova, Christian Budach, Martin Schrön, Benjamin Trost, Daniel Rasche, Andreas Güntner, Veronika Döpper, Michael Förster, Markus Köhli, Lisa Angermann, Nikolaos Antonoglou, Manuela Zude-Sasse, and Sascha E. Oswald
Earth Syst. Sci. Data, 15, 3243–3262, https://doi.org/10.5194/essd-15-3243-2023, https://doi.org/10.5194/essd-15-3243-2023, 2023
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) allows for the non-invasive estimation of root-zone soil water content (SWC). The signal observed by a single CRNS sensor is influenced by the SWC in a radius of around 150 m (the footprint). Here, we have put together a cluster of eight CRNS sensors with overlapping footprints at an agricultural research site in north-east Germany. That way, we hope to represent spatial SWC heterogeneity instead of retrieving just one average SWC estimate from a single sensor.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
EGUsphere, https://doi.org/10.5194/egusphere-2023-1548, https://doi.org/10.5194/egusphere-2023-1548, 2023
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within mHM, using the Desilets equation with uniformly and with non-uniformly weighted average soil moisture, and the physically-based code COSMIC. The data not only improved soil moisture simulations, but also the parameterization of evapotranspiration in the model.
Martin Schrön, Markus Köhli, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 27, 723–738, https://doi.org/10.5194/hess-27-723-2023, https://doi.org/10.5194/hess-27-723-2023, 2023
Short summary
Short summary
This paper presents a new analytical concept to answer long-lasting questions of the cosmic-ray neutron sensing community, such as
what is the influence of a distant area or patches of different land use on the measurement signal?or
is the detector sensitive enough to detect a change of soil moisture (e.g. due to irrigation) in a remote field at a certain distance?The concept may support signal interpretation and sensor calibration, particularly in heterogeneous terrain.
Cosimo Brogi, Heye Reemt Bogena, Markus Köhli, Johan Alexander Huisman, Harrie-Jan Hendricks Franssen, and Olga Dombrowski
Geosci. Instrum. Method. Data Syst., 11, 451–469, https://doi.org/10.5194/gi-11-451-2022, https://doi.org/10.5194/gi-11-451-2022, 2022
Short summary
Short summary
Accurate monitoring of water in soil can improve irrigation efficiency, which is important considering climate change and the growing world population. Cosmic-ray neutrons sensors (CRNSs) are a promising tool in irrigation monitoring due to a larger sensed area and to lower maintenance than other ground-based sensors. Here, we analyse the feasibility of irrigation monitoring with CRNSs and the impact of the irrigated field dimensions, of the variations of water in soil, and of instrument design.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Maik Heistermann, Heye Bogena, Till Francke, Andreas Güntner, Jannis Jakobi, Daniel Rasche, Martin Schrön, Veronika Döpper, Benjamin Fersch, Jannis Groh, Amol Patil, Thomas Pütz, Marvin Reich, Steffen Zacharias, Carmen Zengerle, and Sascha Oswald
Earth Syst. Sci. Data, 14, 2501–2519, https://doi.org/10.5194/essd-14-2501-2022, https://doi.org/10.5194/essd-14-2501-2022, 2022
Short summary
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This paper presents a dense network of cosmic-ray neutron sensing (CRNS) to measure spatio-temporal soil moisture patterns during a 2-month campaign in the Wüstebach headwater catchment in Germany. Stationary, mobile, and airborne CRNS technology monitored the root-zone water dynamics as well as spatial heterogeneity in the 0.4 km2 area. The 15 CRNS stations were supported by a hydrogravimeter, biomass sampling, and a wireless soil sensor network to facilitate holistic hydrological analysis.
Andreas Wieser, Andreas Güntner, Peter Dietrich, Jan Handwerker, Dina Khordakova, Uta Ködel, Martin Kohler, Hannes Mollenhauer, Bernhard Mühr, Erik Nixdorf, Marvin Reich, Christian Rolf, Martin Schrön, Claudia Schütze, and Ute Weber
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-131, https://doi.org/10.5194/hess-2022-131, 2022
Preprint withdrawn
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We present an event-triggered observation concept which covers the entire process chain from heavy precipitation to flooding at the catchment scale. It combines flexible and mobile observing systems out of the fields of meteorology, hydrology and geophysics with stationary networks to capture atmospheric transport processes, heterogeneous precipitation patterns, land surface and subsurface storage processes, and runoff dynamics.
Mandy Kasner, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-123, https://doi.org/10.5194/hess-2022-123, 2022
Publication in HESS not foreseen
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Cosmic-ray neutron sensing (CRNS) is a non-invasive technique that is used to quantify field-scale root-zone soil moisture. We hypothesize that unaccounted spatiotemporal changes of soil density may have impact on the quality of CRNS soil moisture products. Our results indicate a significant dependency of neutrons on soil density, which also depends on the soil moisture state. A correction approach is provided that can be recommended for practical use.
Heye Reemt Bogena, Martin Schrön, Jannis Jakobi, Patrizia Ney, Steffen Zacharias, Mie Andreasen, Roland Baatz, David Boorman, Mustafa Berk Duygu, Miguel Angel Eguibar-Galán, Benjamin Fersch, Till Franke, Josie Geris, María González Sanchis, Yann Kerr, Tobias Korf, Zalalem Mengistu, Arnaud Mialon, Paolo Nasta, Jerzy Nitychoruk, Vassilios Pisinaras, Daniel Rasche, Rafael Rosolem, Hami Said, Paul Schattan, Marek Zreda, Stefan Achleitner, Eduardo Albentosa-Hernández, Zuhal Akyürek, Theresa Blume, Antonio del Campo, Davide Canone, Katya Dimitrova-Petrova, John G. Evans, Stefano Ferraris, Félix Frances, Davide Gisolo, Andreas Güntner, Frank Herrmann, Joost Iwema, Karsten H. Jensen, Harald Kunstmann, Antonio Lidón, Majken Caroline Looms, Sascha Oswald, Andreas Panagopoulos, Amol Patil, Daniel Power, Corinna Rebmann, Nunzio Romano, Lena Scheiffele, Sonia Seneviratne, Georg Weltin, and Harry Vereecken
Earth Syst. Sci. Data, 14, 1125–1151, https://doi.org/10.5194/essd-14-1125-2022, https://doi.org/10.5194/essd-14-1125-2022, 2022
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Monitoring of increasingly frequent droughts is a prerequisite for climate adaptation strategies. This data paper presents long-term soil moisture measurements recorded by 66 cosmic-ray neutron sensors (CRNS) operated by 24 institutions and distributed across major climate zones in Europe. Data processing followed harmonized protocols and state-of-the-art methods to generate consistent and comparable soil moisture products and to facilitate continental-scale analysis of hydrological extremes.
Till Francke, Maik Heistermann, Markus Köhli, Christian Budach, Martin Schrön, and Sascha E. Oswald
Geosci. Instrum. Method. Data Syst., 11, 75–92, https://doi.org/10.5194/gi-11-75-2022, https://doi.org/10.5194/gi-11-75-2022, 2022
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a non-invasive tool for measuring hydrogen pools like soil moisture, snow, or vegetation. This study presents a directional shielding approach, aiming to measure in specific directions only. The results show that non-directional neutron transport blurs the signal of the targeted direction. For typical instruments, this does not allow acceptable precision at a daily time resolution. However, the mere statistical distinction of two rates is feasible.
Daniel Rasche, Markus Köhli, Martin Schrön, Theresa Blume, and Andreas Güntner
Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, https://doi.org/10.5194/hess-25-6547-2021, 2021
Short summary
Short summary
Cosmic-ray neutron sensing provides areal average soil moisture measurements. We investigated how distinct differences in spatial soil moisture patterns influence the soil moisture estimates and present two approaches to improve the estimate of soil moisture close to the instrument by reducing the influence of soil moisture further afield. Additionally, we show that the heterogeneity of soil moisture can be assessed based on the relationship of different neutron energies.
Maik Heistermann, Till Francke, Martin Schrön, and Sascha E. Oswald
Hydrol. Earth Syst. Sci., 25, 4807–4824, https://doi.org/10.5194/hess-25-4807-2021, https://doi.org/10.5194/hess-25-4807-2021, 2021
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Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil moisture in footprints extending over hectometres in the horizontal and decimetres in the vertical. This study, however, demonstrates the potential of CRNS to obtain spatio-temporal patterns of soil moisture beyond isolated footprints. To that end, we analyse data from a unique observational campaign that featured a dense network of more than 20 neutron detectors in an area of just 1 km2.
Edoardo Martini, Matteo Bauckholt, Simon Kögler, Manuel Kreck, Kurt Roth, Ulrike Werban, Ute Wollschläger, and Steffen Zacharias
Earth Syst. Sci. Data, 13, 2529–2539, https://doi.org/10.5194/essd-13-2529-2021, https://doi.org/10.5194/essd-13-2529-2021, 2021
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We present the in situ data available from the soil monitoring network
STH-net, recently implemented at the Schäfertal Hillslope site (Germany). The STH-net provides data (soil water content, soil temperature, water level, and meteorological variables – measured at a 10 min interval since 1 January 2019) for developing and testing modelling approaches in the context of vadose zone hydrology at spatial scales ranging from the pedon to the hillslope.
Benjamin Fersch, Till Francke, Maik Heistermann, Martin Schrön, Veronika Döpper, Jannis Jakobi, Gabriele Baroni, Theresa Blume, Heye Bogena, Christian Budach, Tobias Gränzig, Michael Förster, Andreas Güntner, Harrie-Jan Hendricks Franssen, Mandy Kasner, Markus Köhli, Birgit Kleinschmit, Harald Kunstmann, Amol Patil, Daniel Rasche, Lena Scheiffele, Ulrich Schmidt, Sandra Szulc-Seyfried, Jannis Weimar, Steffen Zacharias, Marek Zreda, Bernd Heber, Ralf Kiese, Vladimir Mares, Hannes Mollenhauer, Ingo Völksch, and Sascha Oswald
Earth Syst. Sci. Data, 12, 2289–2309, https://doi.org/10.5194/essd-12-2289-2020, https://doi.org/10.5194/essd-12-2289-2020, 2020
Mehdi Rahmati, Lutz Weihermüller, Jan Vanderborght, Yakov A. Pachepsky, Lili Mao, Seyed Hamidreza Sadeghi, Niloofar Moosavi, Hossein Kheirfam, Carsten Montzka, Kris Van Looy, Brigitta Toth, Zeinab Hazbavi, Wafa Al Yamani, Ammar A. Albalasmeh, Ma'in Z. Alghzawi, Rafael Angulo-Jaramillo, Antônio Celso Dantas Antonino, George Arampatzis, Robson André Armindo, Hossein Asadi, Yazidhi Bamutaze, Jordi Batlle-Aguilar, Béatrice Béchet, Fabian Becker, Günter Blöschl, Klaus Bohne, Isabelle Braud, Clara Castellano, Artemi Cerdà, Maha Chalhoub, Rogerio Cichota, Milena Císlerová, Brent Clothier, Yves Coquet, Wim Cornelis, Corrado Corradini, Artur Paiva Coutinho, Muriel Bastista de Oliveira, José Ronaldo de Macedo, Matheus Fonseca Durães, Hojat Emami, Iraj Eskandari, Asghar Farajnia, Alessia Flammini, Nándor Fodor, Mamoun Gharaibeh, Mohamad Hossein Ghavimipanah, Teamrat A. Ghezzehei, Simone Giertz, Evangelos G. Hatzigiannakis, Rainer Horn, Juan José Jiménez, Diederik Jacques, Saskia Deborah Keesstra, Hamid Kelishadi, Mahboobeh Kiani-Harchegani, Mehdi Kouselou, Madan Kumar Jha, Laurent Lassabatere, Xiaoyan Li, Mark A. Liebig, Lubomír Lichner, María Victoria López, Deepesh Machiwal, Dirk Mallants, Micael Stolben Mallmann, Jean Dalmo de Oliveira Marques, Miles R. Marshall, Jan Mertens, Félicien Meunier, Mohammad Hossein Mohammadi, Binayak P. Mohanty, Mansonia Pulido-Moncada, Suzana Montenegro, Renato Morbidelli, David Moret-Fernández, Ali Akbar Moosavi, Mohammad Reza Mosaddeghi, Seyed Bahman Mousavi, Hasan Mozaffari, Kamal Nabiollahi, Mohammad Reza Neyshabouri, Marta Vasconcelos Ottoni, Theophilo Benedicto Ottoni Filho, Mohammad Reza Pahlavan-Rad, Andreas Panagopoulos, Stephan Peth, Pierre-Emmanuel Peyneau, Tommaso Picciafuoco, Jean Poesen, Manuel Pulido, Dalvan José Reinert, Sabine Reinsch, Meisam Rezaei, Francis Parry Roberts, David Robinson, Jesús Rodrigo-Comino, Otto Corrêa Rotunno Filho, Tadaomi Saito, Hideki Suganuma, Carla Saltalippi, Renáta Sándor, Brigitta Schütt, Manuel Seeger, Nasrollah Sepehrnia, Ehsan Sharifi Moghaddam, Manoj Shukla, Shiraki Shutaro, Ricardo Sorando, Ajayi Asishana Stanley, Peter Strauss, Zhongbo Su, Ruhollah Taghizadeh-Mehrjardi, Encarnación Taguas, Wenceslau Geraldes Teixeira, Ali Reza Vaezi, Mehdi Vafakhah, Tomas Vogel, Iris Vogeler, Jana Votrubova, Steffen Werner, Thierry Winarski, Deniz Yilmaz, Michael H. Young, Steffen Zacharias, Yijian Zeng, Ying Zhao, Hong Zhao, and Harry Vereecken
Earth Syst. Sci. Data, 10, 1237–1263, https://doi.org/10.5194/essd-10-1237-2018, https://doi.org/10.5194/essd-10-1237-2018, 2018
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This paper presents and analyzes a global database of soil infiltration data, the SWIG database, for the first time. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists or they were digitized from published articles. We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models.
Roland Baatz, Pamela L. Sullivan, Li Li, Samantha R. Weintraub, Henry W. Loescher, Michael Mirtl, Peter M. Groffman, Diana H. Wall, Michael Young, Tim White, Hang Wen, Steffen Zacharias, Ingolf Kühn, Jianwu Tang, Jérôme Gaillardet, Isabelle Braud, Alejandro N. Flores, Praveen Kumar, Henry Lin, Teamrat Ghezzehei, Julia Jones, Henry L. Gholz, Harry Vereecken, and Kris Van Looy
Earth Syst. Dynam., 9, 593–609, https://doi.org/10.5194/esd-9-593-2018, https://doi.org/10.5194/esd-9-593-2018, 2018
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Focusing on the usage of integrated models and in situ Earth observatory networks, three challenges are identified to advance understanding of ESD, in particular to strengthen links between biotic and abiotic, and above- and below-ground processes. We propose developing a model platform for interdisciplinary usage, to formalize current network infrastructure based on complementarities and operational synergies, and to extend the reanalysis concept to the ecosystem and critical zone.
Martin Schrön, Steffen Zacharias, Gary Womack, Markus Köhli, Darin Desilets, Sascha E. Oswald, Jan Bumberger, Hannes Mollenhauer, Simon Kögler, Paul Remmler, Mandy Kasner, Astrid Denk, and Peter Dietrich
Geosci. Instrum. Method. Data Syst., 7, 83–99, https://doi.org/10.5194/gi-7-83-2018, https://doi.org/10.5194/gi-7-83-2018, 2018
Short summary
Short summary
Cosmic-ray neutron sensing (CRNS) is a unique technology to monitor water storages in complex environments, non-invasively, continuously, autonomuously, and representatively in large areas. However, neutron detector signals are not comparable per se: there is statistical noise, technical differences, and locational effects. We found out what it takes to make CRNS consistent in time and space to ensure reliable data quality. We further propose a method to correct for sealed areas in the footrint.
Martin Schrön, Markus Köhli, Lena Scheiffele, Joost Iwema, Heye R. Bogena, Ling Lv, Edoardo Martini, Gabriele Baroni, Rafael Rosolem, Jannis Weimar, Juliane Mai, Matthias Cuntz, Corinna Rebmann, Sascha E. Oswald, Peter Dietrich, Ulrich Schmidt, and Steffen Zacharias
Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, https://doi.org/10.5194/hess-21-5009-2017, 2017
Short summary
Short summary
A field-scale average of near-surface water content can be sensed by cosmic-ray neutron detectors. To interpret, calibrate, and validate the integral signal, it is important to account for its sensitivity to heterogeneous patterns like dry or wet spots. We show how point samples contribute to the neutron signal based on their depth and distance from the detector. This approach robustly improves the sensor performance and data consistency, and even reveals otherwise hidden hydrological features.
Edoardo Martini, Ulrike Werban, Steffen Zacharias, Marco Pohle, Peter Dietrich, and Ute Wollschläger
Hydrol. Earth Syst. Sci., 21, 495–513, https://doi.org/10.5194/hess-21-495-2017, https://doi.org/10.5194/hess-21-495-2017, 2017
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With a process-based interpretation of electromagnetic induction measurements, we discussed the potential and limitations of such a method for soil moisture mapping. Results will help clarify the complex and time-varying effect of stable soil properties and dynamic state variables on the physical parameters measured, with implications for future studies. We highlighted the importance of time-series data and the need for a multidisciplinary approach for proper interpretation.
Related subject area
Climate and Earth system modeling
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
Applying double-cropping and interactive irrigation in the North China Plain using WRF4.5
CD-type discretization for sea ice dynamics in FESOM version 2
Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
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Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
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Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
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Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
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The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
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Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
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We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
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The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
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This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
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We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
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Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
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To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
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This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
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We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
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Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
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All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
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We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
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In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
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Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
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Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
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Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
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In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
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Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
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We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
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Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
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Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
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Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
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We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
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This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
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The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
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This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
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Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
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Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-38, https://doi.org/10.5194/gmd-2024-38, 2024
Revised manuscript accepted for GMD
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Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
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Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
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This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
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This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
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Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
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Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
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Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Peters, Bjørn Hallvard Samset, Benjamin M. Sanderson, and Ragnhild Bieltvedt Skeie
EGUsphere, https://doi.org/10.5194/egusphere-2024-196, https://doi.org/10.5194/egusphere-2024-196, 2024
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The CICERO-SCM has existed as a FORTRAN model since 1999 and consists of a part that calculates radiative forcing and concentrations from emissions, and an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper we describe an updated version ported to python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
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We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
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Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
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As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
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In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
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This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
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A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
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Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Cited articles
Agostinelli, S., Allison, J., Amako, K., et al.: GEANT4 – a simulation toolkit, Nucl. Instrum.
Meth. A, 506, 250–303,
https://doi.org/10.1016/S0168-9002(03)01368-8, 2003. a
Andreasen, M., Jensen, H. K., Zreda, M., Desilets, D., Bogena, H., and Looms,
C.: Modeling cosmic ray neutron field measurements, Water Resour. Res.,
52, 6451–6471, https://doi.org/10.1002/2015wr018236, 2016. a
Badiee, A., Wallbank, J., Pulido Fentanes, J., Trill, E., Scarlet, P., Zhu,
Y., Cielniak, G., Cooper, H., Blake, J., Evans, J., Zreda, M., Köhli, M.,
and Pearson, S.: Using Additional Moderator to Control the Footprint of a
COSMOS Rover for Soil Moisture Measurement, Water Resour. Res., 57, e2020WR028478,
https://doi.org/10.1029/2020wr028478, 2021. a, b
Baroni, G., Scheiffele, L., Schrön, M., Ingwersen, J., and Oswald, S.:
Uncertainty, sensitivity and improvements in soil moisture estimation with
cosmic-ray neutron sensing, J. Hydrol., 564, 873–887,
https://doi.org/10.1016/j.jhydrol.2018.07.053, 2018. a
Battistoni, G., Boehlen, T., Cerutti, F., Chin, P., Esposito, L., Fasso, A.,
Ferrari, A., Lechner, A., Empl, A., Mairani, A., Mereghetti, A., Ortega, P.,
Ranft, J., Roesler, S., Sala, P., Vlachoudis, V., and Smirnov, G.: Overview
of the FLUKA code, Ann. Nucl. Energ., 82, 10–18,
https://doi.org/10.1016/j.anucene.2014.11.007, 2015. a
Boudard, A., Cugnon, J., David, J.-C., Leray, S., and Mancusi, D.: New
potentialities of the Liège intranuclear cascade model for reactions
induced by nucleons and light charged particles, Phys. Rev. C, 87,
014606, https://doi.org/10.1103/PhysRevC.87.014606, 2013. a
Bramblett, R. and Bonner, T.: Neutron evaporation spectra from (p, n)
reactions, Nucl. Phys., 20, 395–407, https://doi.org/10.1016/0029-5582(60)90182-6,
1960. a
Bramblett, R., Ewing, R., and Bonner, T.: A new type of neutron spectrometer,
Nucl. Instrum. Methods, 9, 1–12,
https://doi.org/10.1016/0029-554X(60)90043-4, 1960. a
Briesmeister, J.: MCNP-A general Monte Carlo N-particle
transport code, Version 4C, LA-13709-M,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-13709-M,
2000. a
Brown, D., Chadwick, M., Capote, R., Kahler, A., Trkov, A., Herman, M.,
Sonzogni, A., Danon, Y., Carlson, A., Dunn, M., Smith, D., Hale, G., Arbanas,
G., Arcilla, R., Bates, C., Beck, B., Becker, B., Brown, F., Casperson, R.,
Conlin, J., Cullen, D., Descalle, M.-A., Firestone, R., Gaines, T., Guber,
K., Hawari, A., Holmes, J., Johnson, T., Kawano, T., Kiedrowski, B., Koning,
A., Kopecky, S., Leal, L., Lestone, J., Lubitz, C., Damiá¡n, J. M.,
Mattoon, C., McCutchan, E., Mughabghab, S., Navratil, P., Neudecker, D.,
Nobre, G., Noguere, G., Paris, M., Pigni, M., Plompen, A., Pritychenko, B.,
Pronyaev, V., Roubtsov, D., Rochman, D., Romano, P., Schillebeeckx, P.,
Simakov, S., Sin, M., Sirakov, I., Sleaford, B., Sobes, V., Soukhovitskii,
E., Stetcu, I., Talou, P., Thompson, I., van der Marck, S.,
Welser-Sherrill, L., Wiarda, D., White, M., Wormald, J., Wright, R., Zerkle,
M., Žerovnik, G., and Zhu, Y.: ENDF/B-VIII.0: The 8th Major
Release of the Nuclear Reaction Data Library with CIELO-project Cross
Sections, New Standards and Thermal Scattering Data, Nucl. Data Sheets,
148, 1–142, https://doi.org/10.1016/j.nds.2018.02.001, 2018. a
Brun, R. and Rademakers, F.: ROOT – An Object Oriented Data Analysis
Framework, in: Proceedings of AIHENP’96 Workshop, Lausanne, vol. 389,
81–86, https://doi.org/10.1016/S0168-9002(97)00048-X, 1997. a, b
Caswell, R., Gabbard, R., Padgett, D., and Doering, W.: Attenuation of
14.1-Mev Neutrons in Water, Nucl. Sci. Eng., 2, 143–159,
https://doi.org/10.13182/NSE57-A25383, 1957. a, b, c, d
Chadwick, M., Herman, M., Obložinský, P., Dunn, M., Danon, Y.,
Kahler, A., Smith, D., Pritychenko, B., Arbanas, G., Arcilla, R., Brewer, R.,
Brown, D., Capote, R., Carlson, A., Cho, Y., Derrien, H., Guber, K., Hale,
G., Hoblit, S., Holloway, S., Johnson, T., Kawano, T., Kiedrowski, B., Kim,
H., Kunieda, S., Larson, N., Leal, L., Lestone, J., Little, R., McCutchan,
E., MacFarlane, R., MacInnes, M., Mattoon, C., McKnight, R., Mughabghab,
S., Nobre, G., Palmiotti, G., Palumbo, A., Pigni, M., Pronyaev, V., Sayer,
R., Sonzogni, A., Summers, N., Talou, P., Thompson, I., Trkov, A., Vogt, R.,
van der Marck, S., Wallner, A., White, M., Wiarda, D., and Young, P.:
ENDF/B-VII.1 Nuclear Data for Science and Technology: Cross Sections,
Covariances, Fission Product Yields and Decay Data, Nucl. Data Sheets, 112,
2887–2996, https://doi.org/10.1016/j.nds.2011.11.002, 2011. a
Cnudde, V. and Boone, M.: High-resolution X-ray computed tomography in
geosciences: A review of the current technology and applications,
Earth-Sci. Rev., 123, 1–17, https://doi.org/10.1016/j.earscirev.2013.04.003,
2013. a
Cugnon, J., Volant, C., and Vuillier, S.: Nucleon and deuteron induced
spallation reactions, Nucl. Phys. A, 625, 729–757,
https://doi.org/10.1016/S0375-9474(97)00602-7, 1997. a
Decker, A., McHale, S., Shannon, M., Clinton, J., and McClory, J.: Novel
Bonner Sphere Spectrometer Response Functions Using MCNP6, IEEE
T. Nucl. Sci., 62, 1689–1694,
https://doi.org/10.1109/TNS.2015.2416652, 2015. a
Desilets, D. and Zreda, M.: Footprint diameter for a cosmic-ray soil moisture
probe: Theory and Monte Carlo simulations, Water Resour. Res., 49,
3566–3575, https://doi.org/10.1002/wrcr.20187, 2013. a
Desilets, D., Zreda, M., and Prabu, T.: Extended scaling factors for in situ
cosmogenic nuclides: new measurements at low latitude, Earth Planet.
Sc. Lett., 246, 265–276, https://doi.org/10.1016/j.epsl.2006.03.051, 2006. a
Emmett, M.: The MORSE Monte Carlo Transport Code System, ORNL-4972/R2,
https://inis.iaea.org/collection/NCLCollectionStore/_Public/16/029/16029296.pdf,
1975. a
Federico, C., Gonçalez, O., Fonseca, E., Martin, I., and Caldas, L.:
Neutron spectra measurements in the south Atlantic anomaly region,
Radiat. Meas., 45, 1526–1528, https://doi.org/10.1016/j.radmeas.2010.06.038,
2010. a
Francke, T., Heistermann, M., Köhli, M., Budach, C., Schrön, M., and Oswald, S. E.: Assessing the feasibility of a directional cosmic-ray neutron sensing sensor for estimating soil moisture, Geosci. Instrum. Method. Data Syst., 11, 75–92, https://doi.org/10.5194/gi-11-75-2022, 2022. a, b
Franz, T. E., Zreda, M., Rosolem, R., and Ferre, T. P. A.: A universal calibration function for determination of soil moisture with cosmic-ray neutrons, Hydrol. Earth Syst. Sci., 17, 453–460, https://doi.org/10.5194/hess-17-453-2013, 2013. a
Galassi, M., Davies, J., Theiler, J., Gough, B., Jungman, G., Alken, P., Booth,
M., Rossi, F., and Ulerich, R.: GNU Scientific Library: reference manual for GSL
version 2.7, Free Software Foundation,
https://www.gnu.org/software/gsl/manual/gsl-ref.pdf (last access: 18 January 2023), 2016. a
Garny, S., Mares, V., and Rühm, W.: Response functions of a Bonner
Sphere Spectrometer calculated with GEANT4, Nucl. Instrum.
Meth. A, 604, 612–617, https://doi.org/10.1016/j.nima.2009.02.044,
2009. a
Gelbard, E.: Epithermal scattering in VIM, Tech. Rep. FRA-TM-123, Argonne
National Laboratory, IL, USA, technical Memorandum, 1979. a
Goldhagen, P., Reginatto, M., Kniss, T., Wilson, J., Singleterry, R., Jones,
I., and Van Steveninck, W.: Measurement of the energy spectrum of
cosmic-ray induced neutrons aboard an ER-2 high-altitude airplane, Nucl. Instrum.
Meth. A, 476, 42–51,
https://doi.org/10.1016/S0168-9002(01)01386-9, 2002. a
Goldman, L.: Principles of CT and CT Technology, J. Nucl.
Med. Tech., 35, 115–128, https://doi.org/10.2967/jnmt.107.042978, 2007. a
Goorley, T., James, M., Booth, T., Brown, F., Bull, J., Cox, L., Durkee, J.,
Elson, J., Fensin, M., Forster, R., Hendricks, J., Hughes, H., Johns, R.,
Kiedrowski, B., Martz, R., Mashnik, S., McKinney, G., Pelowitz, D., Prael,
R., Sweezy, J., Waters, L., Wilcox, T., and Zukaitis, T.: Initial MCNP6
Release Overview, Nucl. Tech., 180, 298–315, https://doi.org/10.13182/NT11-135,
2012. a, b
Gudima, K., Mashnik, S., and Toneev, V.: Cascade-exciton model of nuclear
reactions, Nucl. Phys. A, 401, 329–361,
https://doi.org/10.1016/0375-9474(83)90532-8, 1983. a
Gudima, K., Mashnik, S., and Sierk, A.: User Manual for the Code LAQGSM,
LA-UR-01-6804,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-01-6804,
2001. a
Hébert, A.: Multigroup Neutron Transport and Diffusion Computations,
Springer US, Boston, 751–911, https://doi.org/10.1007/978-0-387-98149-9_8, 2010. a
Heidbüchel, I., Güntner, A., and Blume, T.: Use of cosmic-ray neutron sensors for soil moisture monitoring in forests, Hydrol. Earth Syst. Sci., 20, 1269–1288, https://doi.org/10.5194/hess-20-1269-2016, 2016. a
Hertel, N. and Davidson, J.: The response of Bonner Spheres to neutrons
from thermal energies to 17.3 MeV, Nucl. Instrum. Meth. A, 238, 509–516, https://doi.org/10.1016/0168-9002(85)90494-2,
1985. a
ISO group 85/SC 2 Radiological protection: Reference neutron radiations –
Part 1, Standard, International Organization for Standardization, Geneva, CH,
https://www.iso.org/standard/25666.html (last access: 18 January 2023), 2001. a
Iwamoto, O., Iwamoto, N., Kunieda, S., Minato, F., and Shibata, K.: The CCONE
Code System and its Application to Nuclear Data Evaluation for Fission and
Other Reactions, Nucl. Data Sheets, 131, 259–288,
https://doi.org/10.1016/j.nds.2015.12.004,
2016. a
Iwase, H., Niita, K., and Nakamura, T.: Development of General-Purpose Particle
and Heavy Ion Transport Monte Carlo Code, J. Nucl. Sci.
Technol., 39, 1142–1151, https://doi.org/10.1080/18811248.2002.9715305, 2002. a, b
Iwema, J., Schrön, M., Da Silva, J. K., Schweiser De Paiva Lopes, R.,
and Rosolem, R.: Accuracy and precision of the cosmic-ray neutron sensor for
soil moisture estimation at humid environments, Hydrol. Process., 35, e14419,
https://doi.org/10.1002/hyp.14419, 2021. a
Iyer, M. and Ganguly, A.: Neutron Evaporation and Energy Distribution in
Individual Fission Fragments, Phys. Rev. C, 5, 1410–1421,
https://doi.org/10.1103/PhysRevC.5.1410, 1972. a
Jakobi, J., Huisman, J., Köhli, M., Rasche, D., Vereecken, H., and Bogena,
H.: The Footprint Characteristics of Cosmic Ray Thermal Neutrons, Geophys.
Res. Lett., 48, e2021GL094281, https://doi.org/10.1029/2021gl094281, 2021. a, b
Kawano, T., Talou, P., Stetcu, I., and Chadwick, M.: Statistical and
evaporation models for the neutron emission energy spectrum in the
center-of-mass system from fission fragments, Nucl. Phys. A, 913, 51–70,
https://doi.org/10.1016/j.nuclphysa.2013.05.020, 2013. a
Kittelmann, T. and Boin, M.: Polycrystalline neutron scattering for Geant4:
NXSG4, Comput. Phys. Commun., 189, 114–118,
https://doi.org/10.1016/j.cpc.2014.11.009, 2015. a
Knuth, D.: The Art of Computer Programming, Volume 2, 3rd Edn.,
Seminumerical Algorithms, Addison-Wesley Longman Publishing Co., Inc.,
Boston, MA, USA, ISBN 9780321635778, 1997. a
Köhli, M.: URANOS v1.0, Harvard Dataverse V1 [code], https://doi.org/10.7910/DVN/THPNZW, 2022a. a, b
Köhli, M.: mkoehli/uranos: URANOS v1.0 (URANOS), Zenodo [data set], https://doi.org/10.5281/zenodo.6578668, 2022b. a
Köhli, M. and Schmoldt, J.-P.: Feasibility of UXO detection via pulsed
neutron-neutron logging, Appl. Radiat. Isotopes, 188, 110403,
https://doi.org/10.1016/j.apradiso.2022.110403, 2022. a, b
Köhli, M., Schrön, M., Zreda, M., Schmidt, U., Dietrich, P., and
Zacharias, S.: Footprint characteristics revised for field-scale soil
moisture monitoring with cosmic-ray neutrons, Water Resour. Res., 51,
5772–5790, https://doi.org/10.1002/2015WR017169, 2015. a, b, c
Köhli, M., Allmendinger, F., Häußler, W., Schröder, T., Klein,
M., Meven, M., and Schmidt, U.: Efficiency and spatial resolution of the
CASCADE thermal neutron detector, Nucl. Instrum. Meth. A, 828, 242–249, https://doi.org/10.1016/j.nima.2016.05.014, 2016. a, b
Köhli, M., Desch, K., Gruber, M., Kaminski, J., Schmidt, F., and Wagner,
T.: Novel neutron detectors based on the time projection method, Physica B, 551, 517–522, https://doi.org/10.1016/j.physb.2018.03.026, 2018a. a, b
Köhli, M., Schrön, M., and Schmidt, U.: Response functions for
detectors in cosmic ray neutron sensing, Nucl. Instrum. Meth. A, 902, 184–189, https://doi.org/10.1016/j.nima.2018.06.052,
2018b. a, b, c
Köhli, M., Weimar, J., Schrön, M., Baatz, R., and Schmidt, U.: Soil
Moisture and Air Humidity Dependence of the Above-Ground Cosmic-Ray Neutron
Intensity, Front. Water, 2, 15, https://doi.org/10.3389/frwa.2020.544847, 2021. a, b, c
Koning, A., Bauge, E., Dean, C., Dupont, E., Nordborg, C., Rugama, Y., Fischer,
U., Forrest, R., Kellett, M., Jacqmin, R., Leeb, H., Mills, R., Pescarini,
M., and Rullhusen, P.: Status of the JEFF Nuclear Data Library, J.
Korean Phys. Soc., 59, 1057–1062, https://doi.org/10.3938/jkps.59.1057,
2011. a
Lefmann, K. and Nielsen, K.: McStas, a general software package for neutron
ray-tracing simulations, Neutron News, 10, 20–23,
https://doi.org/10.1080/10448639908233684, 1999. a
Li, D., Schrön, M., Köhli, M., Bogena, H., Weimar, J., Jiménez
Bello, M., Han, X., Martínez Gimeno, M., Zacharias, S., Vereecken,
H., and Hendricks Franssen, H.: Can Drip Irrigation be Scheduled with
Cosmic-Ray Neutron Sensing?, Vadose Zone J., 18, 190053,
https://doi.org/10.2136/vzj2019.05.0053, 2019. a, b
Liu, H., Hou, Y., Li, H., Song, Y., Hu, L., and Liang, M.: Cosmic-ray neutron
fluxes and spectra at different altitudes based on Monte Carlo
simulations, Appl. Radiat. Isotopes, 175, 109800,
https://doi.org/10.1016/j.apradiso.2021.109800, 2021. a
Maire, E. and Withers, P.: Quantitative X-ray tomography, Int.
Mater. Rev., 59, 1–43, https://doi.org/10.1179/1743280413Y.0000000023, 2013. a
Mares, V. and Schraube, H.: Evaluation of the response matrix of a Bonner
Sphere Spectrometer with LiI detector from thermal energy to 100 MeV,
Nucl. Instrum. Meth. A, 337, 461–473,
https://doi.org/10.1016/0168-9002(94)91116-9, 1994. a
Mares, V., Schraube, G., and Schraube, H.: Calculated neutron response of a
Bonner Sphere Spectrometer with 3He counter, Nucl. Instrum. Meth. A, 307, 398–412,
https://doi.org/10.1016/0168-9002(91)90210-H, 1991. a, b
Matsumoto, M. and Nishimura, T.: Mersenne Twister: A 623-dimensionally
Equidistributed Uniform Pseudo-random Number Generator, ACM T.
Model. Comput. Sim., 8, 3–30, https://doi.org/10.1145/272991.272995,
1998. a
McConn Jr., R., Gesh, C., Pagh, R., Rucker, R., and Williams III, R.:
Compendium of Material Composition Data for Radiation Transport Modeling,
Tech. Rep. PNNL-15870 Rev. 1, Pacific Northwest National Laboratory,
Richland, Washington 99352,
https://www.pnnl.gov/main/publications/external/technical_reports/pnnl-15870rev1.pdf,
2011. a
McKinney, G.: MCNP6 Cosmic and Terrestrial Background Particle Fluxes,
LA-UR-13-24293, release
3,
https://mcnp.lanl.gov/pdf_files/la-ur-13-24293.pdf, 2013. a
McKinney, G., Armstrong, H., James, M., Clem, J., and Goldhagen, P.: MCNP6
Cosmic-Source Option, LA-UR-12-22318,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-12-22318,
2012. a
Metropolis, N. and Ulam, S.: The Monte Carlo Method, J. Am.
Stat. Assoc., 44, 335–341, https://doi.org/10.2307/2280232, 1949. a
Nelms, A.: Energy loss and range of electrons and positrons, United States
Department of Commerce, national
Bureau of Standards Circular 577 and Suppl.,
https://catalog.hathitrust.org/Record/007291096 (last access: 18 January 2023), 1956. a
Niita, K.: QMD and JAM Calculations for High Energy Nucleon-Nucleus
Collisions, J. Nucl. Sci. Technol., 39, 714–719,
https://doi.org/10.1080/00223131.2002.10875198, 2002. a
Niita, K., Takada, H., Meigo, S., and Ikeda, Y.: High-energy particle transport
code NMTC/JAM, Nucl. Instrum. Meth. B, 184, 406–420,
https://doi.org/10.1016/S0168-583X(01)00784-4, 2001. a
Otuka, N., Dupont, E., Semkova, V., Pritychenko, B., Blokhin, A., Aikawa, M.,
Babykina, S., Bossant, M., Chen, G., Dunaeva, S., Forrest, R., Fukahori, T.,
Furutachi, N., Ganesan, S., Ge, Z., Gritzay, O., Herman, M., Hlavač,
S., Kato, K., Lalremruata, B., Lee, Y., Makinaga, A., Matsumoto, K.,
Mikhaylyukova, M., Pikulina, G., Pronyaev, V., Saxena, A., Schwerer, O.,
Simakov, S., Soppera, N., Suzuki, R., Takács, S., Tao, X., Taova, S.,
Tárkányi, F., Varlamov, V., Wang, J., Yang, S., Zerkin, V., and
Zhuang, Y.: Towards a More Complete and Accurate Experimental Nuclear
Reaction Data Library (EXFOR): International Collaboration Between Nuclear
Reaction Data Centres (NRDC), Nucl. Data Sheets, 120, 272–276,
https://doi.org/10.1016/j.nds.2014.07.065, 2014. a
Pazianotto, M., Cortés-Giraldo, M., Federico, C., Gonçalez, O.,
Quesada, J., and Carlson, B.: Determination of the cosmic-ray-induced neutron
flux and ambient dose equivalent at flight altitude, J. Phys.
Conf. Ser., 630, 012022, https://doi.org/10.1088/1742-6596/630/1/012022, 2015. a
Peggs, S., et al.: European Spallation Source Technical Design Report,
Technical Design Report ESS, ESS, Lundt, ESS-2013-001,
http://docdb01.esss.lu.se/DocDB/0002/000274/006/TDR_final_130423_print_ch1.pdf,
2013. a
Prael, R. and Lichtenstein, H.: User Guide to LCS: The LAHET Code System,
LA-UR-89-3014,
https://permalink.lanl.gov/object/tr?what=info:lanl-repo/lareport/LA-UR-89-3014,
1989. a
Rasche, D., Köhli, M., Schrön, M., Blume, T., and Güntner, A.: Towards disentangling heterogeneous soil moisture patterns in cosmic-ray neutron sensor footprints, Hydrol. Earth Syst. Sci., 25, 6547–6566, https://doi.org/10.5194/hess-25-6547-2021, 2021. a
Romano, P. and Forget, B.: The OpenMC Monte Carlo particle transport code,
Ann. Nucl. Energ., 51, 274–281, https://doi.org/10.1016/j.anucene.2012.06.040,
2013. a, b
Roth, S.: Ray casting for modeling solids, Comput. Vision Graph., 18, 109–144, https://doi.org/10.1016/0146-664X(82)90169-1, 1982. a
Šaroun, J. and Kulda, J.: RESTRAX – a program for TAS
resolution calculation and scan profile simulation, Physica B, 234-236, 1102–1104, https://doi.org/10.1016/s0921-4526(97)00037-9, 1997. a
Sato, T.: Analytical Model for Estimating Terrestrial Cosmic Ray Fluxes Nearly
Anytime and Anywhere in the World: Extension of PARMA/EXPACS, PLOS ONE, 10,
1–33, https://doi.org/10.1371/journal.pone.0144679, 2015. a
Sato, T. and Niita, K.: Analytical Functions to Predict Cosmic-Ray Neutron
Spectra in the Atmosphere, Radiation Research, 166, 544–555,
https://doi.org/10.1667/RR0610.1, 2006. a
Sato, T., Yasuda, H., Niita, K., Endo, A., and Sihver, L.: Development of
PARMA: PHITS-based Analytical Radiation Model in the Atmosphere,
Radiat. Res., 170, 244–259, https://doi.org/10.1667/RR1094.1, 2008. a, b, c
Schattan, P., Köhli, M., Schrön, M., Baroni, G., and Oswald, S.:
Sensing Area-Average Snow Water Equivalent with Cosmic-Ray Neutrons: The
Influence of Fractional Snow Cover, Water Resour. Res., 55,
10796–10812, https://doi.org/10.1029/2019WR025647, 2019. a, b
Schrön, M., Köhli, M., Scheiffele, L., Iwema, J., Bogena, H. R., Lv, L., Martini, E., Baroni, G., Rosolem, R., Weimar, J., Mai, J., Cuntz, M., Rebmann, C., Oswald, S. E., Dietrich, P., Schmidt, U., and Zacharias, S.: Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity, Hydrol. Earth Syst. Sci., 21, 5009–5030, https://doi.org/10.5194/hess-21-5009-2017, 2017. a, b
Schrön, M., Rosolem, R., Köhli, M., Piussi, L., Schröter, I.,
Iwema, J., Kögler, S., Oswald, S., Wollschläger, U., Samaniego, L.,
Dietrich, P., and Zacharias, S.: Cosmic-ray Neutron Rover Surveys of Field
Soil Moisture and the Influence of Roads, Water Resour. Res., 54,
6441–6459, https://doi.org/10.1029/2017WR021719, 2018. a
Schrön, M., Zacharias, S., Womack, G., Köhli, M., Desilets, D., Oswald, S. E., Bumberger, J., Mollenhauer, H., Kögler, S., Remmler, P., Kasner, M., Denk, A., and Dietrich, P.: Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment, Geosci. Instrum. Method. Data Syst., 7, 83–99, https://doi.org/10.5194/gi-7-83-2018, 2018. a, b, c
Schrön, M., Oswald, S., Zacharias, S., Kasner, M., Dietrich, P., and
Attinger, S.: Neutrons on Rails: Transregional Monitoring of Soil Moisture
and Snow Water Equivalent, Geophys. Res. Lett., 48, e2021GL093924,
https://doi.org/10.1029/2021gl093924, 2021. a
Shibata, K., Iwamoto, O., Nakagawa, T., Iwamoto, N., Ichihara, A., Kunieda, S.,
Chiba, S., Furutaka, K., Otuka, N., Ohsawa, T., Murata, T., Matsunobu, H.,
Zukeran, A., Kamada, S., and Katakura, J.: JENDL-4.0: A New Library for
Nuclear Science and Engineering, J. Nucl. Sci. Technol.,
48, 1–30, https://doi.org/10.1080/18811248.2011.9711675, 2011. a
Smith, A., Fields, P., and Roberts, J.: Spontaneous Fission Neutron Spectrum of
252Cf, Phys. Rev., 108, 411–413,
https://doi.org/10.1103/PhysRev.108.411, 1957. a
Solovyev, A., Fedorov, V., Kharlov, V., and Stepanova, U.: Comparative analysis
of MCNPX and GEANT4 codes for fast-neutron radiation treatment planning,
Nucl. Energ. Technol., 1, 14–19, https://doi.org/10.1016/j.nucet.2015.11.004,
2015. a
Sun Programmers Group: Fortran 77 Reference Manual, Tech. rep., SunSoft,
http://wwwcdf.pd.infn.it/localdoc/f77_sun.pdf,
1995a. a
Sun Programmers Group: Fortran 90 User's Guide, Tech. rep., SunSoft,
http://smdc.sinp.msu.ru/doc/Fortran90UsersGuide.pdf,
1995b. a
Sweezy, J., Hertel, N., and Veinot, K.: BUMS – Bonner Sphere Unfolding
Made Simple: an HTML based multisphere neutron spectrometer unfolding
package, Nucl. Instrum. Meth. A, 476,
263–269, https://doi.org/10.1016/S0168-9002(01)01466-8,
2002. a
Terrell, J.: Fission Neutron Spectra and Nuclear Temperatures, Phys. Rev.,
113, 527–541, https://doi.org/10.1103/PhysRev.113.527, 1959. a
Thomas, D. and Alevra, A.: Bonner Sphere Spectrometers – a critical
review, Nucl. Instrum. Meth. A, 476, 12–20,
https://doi.org/10.1016/S0168-9002(01)01379-1, 2002. a
van der Ende, B., Atanackovic, J., Erlandson, A., and Bentoumi, G.: Use of
GEANT4 vs. MCNPX for the characterization of a boron-lined neutron
detector, Nucl. Instrum. Meth. A, 820, 40–47,
https://doi.org/10.1016/j.nima.2016.02.082, 2016. a
Walsh, J., Forget, B., and Smith, K.: Accelerated sampling of the free gas
resonance elastic scattering kernel, Ann. Nucl. Energ., 69, 116–124,
https://doi.org/10.1016/j.anucene.2014.01.017, 2014. a
Waters, L., McKinney, G., Durkee, J., Fensin, M., Hendricks, J., James, M.,
Johns, R., and Pelowitz, D.: The MCNPX Monte Carlo Radiation Transport
Code, AIP Conf. Proc., 896, 81–90, https://doi.org/10.1063/1.2720459,
2007. a, b
Watt, B.: Energy Spectrum of Neutrons from Thermal Fission of
235U, Phys. Rev., 87, 1037–1041,
https://doi.org/10.1103/PhysRev.87.1037, 1952. a
Wechsler, D., Zsigmond, G., Streffer, F., and Mezei, F.: VITESS: Virtual
instrumentation tool for pulsed and continuous sources, Neutron News, 11,
25–28, https://doi.org/10.1080/10448630008233764, 2000. a
Weimar, J., Köhli, M., Budach, C., and Schmidt, U.: Large-Scale Boron-Lined
Neutron Detection Systems as a 3He Alternative for Cosmic Ray Neutron
Sensing, Front. Water, 2, 16, https://doi.org/10.3389/frwa.2020.00016, 2020. a, b
Weisskopf, V.: Statistics and Nuclear Reactions, Phys. Rev., 52, 295–303,
https://doi.org/10.1103/PhysRev.52.295, 1937. a
X-5 Monte Carlo Team: MCNP-A general Monte Carlo N-particle transport
code, Version 5, LA-UR-03-1987, volume I: Overview and Theory,
https://laws.lanl.gov/vhosts/mcnp.lanl.gov/pdf_files/la-ur-03-1987.pdf,
2003.
a
Yamashita, M., Stephens, L., and Patterson, H.: Cosmic-ray-produced neutrons at
ground level: Neutron production rate and flux distribution, J.
Geophys. Res., 71, 3817–3834, https://doi.org/10.1029/JZ071i016p03817, 1966. a
Ziegler, J.: Terrestrial cosmic ray intensities, IBM J. Res.
Dev., 42, 117–140, https://doi.org/10.1147/rd.421.0117, 1998. a
Zreda, M., Desilets, D., Ferré, T., and Scott, R.: Measuring soil moisture
content non-invasively at intermediate spatial scale using cosmic-ray
neutrons, Geophys. Res. Lett., 35, L21402,
https://doi.org/10.1029/2008GL035655, 2008. a
Zreda, M., Shuttleworth, W. J., Zeng, X., Zweck, C., Desilets, D., Franz, T., and Rosolem, R.: COSMOS: the COsmic-ray Soil Moisture Observing System, Hydrol. Earth Syst. Sci., 16, 4079–4099, https://doi.org/10.5194/hess-16-4079-2012, 2012. a
Zweck, C., Zreda, M., and Desilets, D.: Snow shielding factors for cosmogenic
nuclide dating inferred from Monte Carlo neutron transport simulations,
Earth Planet. Sc. Lett., 379, 64–71,
https://doi.org/10.1016/j.epsl.2013.07.023, 2013. a
Short summary
In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface. As an alternative for the growing community of CRNS, we developed URANOS. The main model features are tracking of particle histories from creation to detection, detector representations as layers or geometric shapes, a voxel-based geometry model, and material setup based on color codes in ASCII matrices or bitmap images. The entire software is developed in C++ and features a graphical user interface.
In the last decades, Monte Carlo codes were often consulted to study neutrons near the surface....
