Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-851-2023
© 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-16-851-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Methods for assessment of models
| 
03 Feb 2023
Methods for assessment of models |
| 03 Feb 2023
| 03 Feb 2023
Cell tracking of convective rainfall: sensitivity of climate-change signal to tracking algorithm and cell definition (Cell-TAO v1.0)
Edmund P. Meredith
CORRESPONDING AUTHOR
Institut für Meteorologie, Freie Universität Berlin, Berlin, Germany
Uwe Ulbrich
Institut für Meteorologie, Freie Universität Berlin, Berlin, Germany
Henning W. Rust
Institut für Meteorologie, Freie Universität Berlin, Berlin, Germany
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In a warming climate, extreme precipitation events are becoming more frequent. To advance our knowledge on such phenomena, we present a multidisciplinary analysis of a selected case study that took place on 29 June 2017 in the Berlin metropolitan area. Our analysis provides evidence of the extremeness of the case from the atmospheric and the impacts perspectives as well as new insights on the physical mechanisms of the event at the meteorological and climate scales.
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This paper investigates the formation of the Mediterranean hurricane that developed between Balearic Islands and Sardinia in October 1996, with a particular focus on the influence of sea surface temperature. We show that increased sea surface temperatures lead to greater probabilities of appearance and a greater strength of the resulting hurricane, suggesting that the processes for Mediterranean hurricanes at steady state are very similar to tropical cyclones.
Edmund P. Meredith, Henning W. Rust, and Uwe Ulbrich
Hydrol. Earth Syst. Sci., 22, 4183–4200, https://doi.org/10.5194/hess-22-4183-2018, https://doi.org/10.5194/hess-22-4183-2018, 2018
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Kilometre-scale climate-model data are of great benefit to both hydrologists and end users studying extreme precipitation, though often unavailable due to the computational expense associated with such high-resolution simulations. We develop a method which identifies days with enhanced risk of extreme rainfall over a catchment, so that high-resolution simulations can be performed only when such a risk exists, reducing computational expense by over 90 % while still well capturing the extremes.
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Nat. Hazards Earth Syst. Sci., 24, 1261–1285, https://doi.org/10.5194/nhess-24-1261-2024, https://doi.org/10.5194/nhess-24-1261-2024, 2024
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Andy Richling, Jens Grieger, and Henning W. Rust
EGUsphere, https://doi.org/10.5194/egusphere-2023-2582, https://doi.org/10.5194/egusphere-2023-2582, 2024
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score –a measure of forecast performance– as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
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Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024, https://doi.org/10.5194/hess-28-321-2024, 2024
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Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-376, https://doi.org/10.5194/essd-2023-376, 2023
Revised manuscript accepted for ESSD
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To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines are proposed as international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.
Katrin M. Nissen, Martina Wilde, Thomas M. Kreuzer, Annika Wohlers, Bodo Damm, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 23, 2737–2748, https://doi.org/10.5194/nhess-23-2737-2023, https://doi.org/10.5194/nhess-23-2737-2023, 2023
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The effect of climate change on rockfall probability in the German low mountain regions is investigated in observations and in 23 different climate scenario simulations. Under a pessimistic greenhouse gas scenario, the simulations suggest a decrease in rockfall probability. This reduction is mainly caused by a decrease in the number of freeze–thaw cycles due to higher atmospheric temperatures.
Johannes Riebold, Andy Richling, Uwe Ulbrich, Henning Rust, Tido Semmler, and Dörthe Handorf
Weather Clim. Dynam., 4, 663–682, https://doi.org/10.5194/wcd-4-663-2023, https://doi.org/10.5194/wcd-4-663-2023, 2023
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Arctic sea ice loss might impact the atmospheric circulation outside the Arctic and therefore extremes over mid-latitudes. Here, we analyze model experiments to initially assess the influence of sea ice loss on occurrence frequencies of large-scale circulation patterns. Some of these detected circulation changes can be linked to changes in occurrences of European temperature extremes. Compared to future global temperature increases, the sea-ice-related impacts are however of secondary relevance.
Alberto Caldas-Alvarez, Markus Augenstein, Georgy Ayzel, Klemens Barfus, Ribu Cherian, Lisa Dillenardt, Felix Fauer, Hendrik Feldmann, Maik Heistermann, Alexia Karwat, Frank Kaspar, Heidi Kreibich, Etor Emanuel Lucio-Eceiza, Edmund P. Meredith, Susanna Mohr, Deborah Niermann, Stephan Pfahl, Florian Ruff, Henning W. Rust, Lukas Schoppa, Thomas Schwitalla, Stella Steidl, Annegret H. Thieken, Jordis S. Tradowsky, Volker Wulfmeyer, and Johannes Quaas
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Katrin M. Nissen, Stefan Rupp, Thomas M. Kreuzer, Björn Guse, Bodo Damm, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 22, 2117–2130, https://doi.org/10.5194/nhess-22-2117-2022, https://doi.org/10.5194/nhess-22-2117-2022, 2022
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A statistical model is introduced which quantifies the influence of individual potential triggering factors and their interactions on rockfall probability in central Europe. The most important factor is daily precipitation, which is most effective if sub-surface moisture levels are high. Freeze–thaw cycles in the preceding days can further increase the rockfall hazard. The model can be applied to climate simulations in order to investigate the effect of climate change on rockfall probability.
Robert Polzin, Annette Müller, Henning Rust, Peter Névir, and Péter Koltai
Nonlin. Processes Geophys., 29, 37–52, https://doi.org/10.5194/npg-29-37-2022, https://doi.org/10.5194/npg-29-37-2022, 2022
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In this study, a recent algorithmic framework called Direct Bayesian Model Reduction (DBMR) is applied which provides a scalable probability-preserving identification of reduced models directly from data. The stochastic method is tested in a meteorological application towards a model reduction to latent states of smaller scale convective activity conditioned on large-scale atmospheric flow.
Noelia Otero, Oscar E. Jurado, Tim Butler, and Henning W. Rust
Atmos. Chem. Phys., 22, 1905–1919, https://doi.org/10.5194/acp-22-1905-2022, https://doi.org/10.5194/acp-22-1905-2022, 2022
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Surface ozone and temperature are strongly dependent and their extremes might be exacerbated by underlying climatological drivers, such as atmospheric blocking. Using an observational data set, we measure the dependence structure between ozone and temperature under the influence of atmospheric blocking. Blocks enhanced the probability of occurrence of compound ozone and temperature extremes over northwestern and central Europe, leading to greater health risks.
Felix S. Fauer, Jana Ulrich, Oscar E. Jurado, and Henning W. Rust
Hydrol. Earth Syst. Sci., 25, 6479–6494, https://doi.org/10.5194/hess-25-6479-2021, https://doi.org/10.5194/hess-25-6479-2021, 2021
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Extreme rainfall events are modeled in this study for different timescales. A new parameterization of the dependence between extreme values and their timescale enables our model to estimate extremes on very short (1 min) and long (5 d) timescales simultaneously. We compare different approaches of modeling this dependence and find that our new model improves performance for timescales between 2 h and 2 d without affecting model performance on other timescales.
Jana Ulrich, Felix S. Fauer, and Henning W. Rust
Hydrol. Earth Syst. Sci., 25, 6133–6149, https://doi.org/10.5194/hess-25-6133-2021, https://doi.org/10.5194/hess-25-6133-2021, 2021
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The characteristics of extreme precipitation on different timescales as well as in different seasons are relevant information, e.g., for designing hydrological structures or managing water supplies. Therefore, our aim is to describe these characteristics simultaneously within one model. We find similar characteristics for short extreme precipitation at all considered stations in Germany but pronounced regional differences with respect to the seasonality of long-lasting extreme events.
Carola Detring, Annette Müller, Lisa Schielicke, Peter Névir, and Henning W. Rust
Weather Clim. Dynam., 2, 927–952, https://doi.org/10.5194/wcd-2-927-2021, https://doi.org/10.5194/wcd-2-927-2021, 2021
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Stationary, long-lasting blocked weather patterns can lead to extreme conditions. Within this study the temporal evolution of the occurrence probability is analyzed, and the onset, decay and transition probabilities of blocking within the past 30 years are modeled. Using Markov models combined with logistic regression, we found large changes in summer, where the probability of transitions to so-called Omega blocks increases strongly, while the unblocked state becomes less probable.
Alexander Pasternack, Jens Grieger, Henning W. Rust, and Uwe Ulbrich
Geosci. Model Dev., 14, 4335–4355, https://doi.org/10.5194/gmd-14-4335-2021, https://doi.org/10.5194/gmd-14-4335-2021, 2021
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Decadal climate ensemble forecasts are increasingly being used to guide adaptation measures. To ensure the applicability of these probabilistic predictions, inherent systematic errors of the prediction system must be adjusted. Since it is not clear which statistical model is optimal for this purpose, we propose a recalibration strategy with a systematic model selection based on non-homogeneous boosting for identifying the most relevant features for both ensemble mean and ensemble spread.
Nico Becker, Henning W. Rust, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 20, 2857–2871, https://doi.org/10.5194/nhess-20-2857-2020, https://doi.org/10.5194/nhess-20-2857-2020, 2020
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A set of models is developed to forecast hourly probabilities of weather-related road accidents in Germany at the spatial scale of administrative districts. Model verification shows that using precipitation and temperature data leads to the best accident forecasts. Based on weather forecast data we show that skilful predictions of accident probabilities of up to 21 h ahead are possible. The models can be used to issue impact-based warnings, which are relevant for road users and authorities.
Noelia Otero, Henning W. Rust, and Tim Butler
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-691, https://doi.org/10.5194/acp-2020-691, 2020
Revised manuscript not accepted
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Surface ozone concentrations are strongly correlated with temperature in summertime. Using long-term measurements, we investigate changes in the observed relationship between ozone and temperature over Germany. We propose a new statistical approach based on Generalized Additive Models (GAMs) to describe ozone production rates as a function of nitrogen oxides (NOx) and temperature. Our results suggest that NOx reductions alone can not explain the changes in the temperature dependence of ozone.
Mareike Schuster, Jens Grieger, Andy Richling, Thomas Schartner, Sebastian Illing, Christopher Kadow, Wolfgang A. Müller, Holger Pohlmann, Stephan Pfahl, and Uwe Ulbrich
Earth Syst. Dynam., 10, 901–917, https://doi.org/10.5194/esd-10-901-2019, https://doi.org/10.5194/esd-10-901-2019, 2019
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Decadal climate predictions are valuable to society as they allow us to estimate climate conditions several years in advance. We analyze the latest version of the German MiKlip prediction system (https://www.fona-miklip.de) and assess the effect of the model resolution on the skill of the system. The increase in the resolution of the system reduces the bias and significantly improves the forecast skill for North Atlantic extratropical winter dynamics for lead times of two to five winters.
Robin Noyelle, Uwe Ulbrich, Nico Becker, and Edmund P. Meredith
Nat. Hazards Earth Syst. Sci., 19, 941–955, https://doi.org/10.5194/nhess-19-941-2019, https://doi.org/10.5194/nhess-19-941-2019, 2019
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This paper investigates the formation of the Mediterranean hurricane that developed between Balearic Islands and Sardinia in October 1996, with a particular focus on the influence of sea surface temperature. We show that increased sea surface temperatures lead to greater probabilities of appearance and a greater strength of the resulting hurricane, suggesting that the processes for Mediterranean hurricanes at steady state are very similar to tropical cyclones.
Noelia Otero, Jana Sillmann, Kathleen A. Mar, Henning W. Rust, Sverre Solberg, Camilla Andersson, Magnuz Engardt, Robert Bergström, Bertrand Bessagnet, Augustin Colette, Florian Couvidat, Cournelius Cuvelier, Svetlana Tsyro, Hilde Fagerli, Martijn Schaap, Astrid Manders, Mihaela Mircea, Gino Briganti, Andrea Cappelletti, Mario Adani, Massimo D'Isidoro, María-Teresa Pay, Mark Theobald, Marta G. Vivanco, Peter Wind, Narendra Ojha, Valentin Raffort, and Tim Butler
Atmos. Chem. Phys., 18, 12269–12288, https://doi.org/10.5194/acp-18-12269-2018, https://doi.org/10.5194/acp-18-12269-2018, 2018
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This paper evaluates the capability of air-quality models to capture the observed relationship between surface ozone concentrations and meteorology over Europe. The air-quality models tended to overestimate the influence of maximum temperature and surface solar radiation. None of the air-quality models captured the strength of the observed relationship between ozone and relative humidity appropriately, underestimating the effect of relative humidity, a key factor in the ozone removal processes.
Edmund P. Meredith, Henning W. Rust, and Uwe Ulbrich
Hydrol. Earth Syst. Sci., 22, 4183–4200, https://doi.org/10.5194/hess-22-4183-2018, https://doi.org/10.5194/hess-22-4183-2018, 2018
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Kilometre-scale climate-model data are of great benefit to both hydrologists and end users studying extreme precipitation, though often unavailable due to the computational expense associated with such high-resolution simulations. We develop a method which identifies days with enhanced risk of extreme rainfall over a catchment, so that high-resolution simulations can be performed only when such a risk exists, reducing computational expense by over 90 % while still well capturing the extremes.
Stefanie Kremser, Jordis S. Tradowsky, Henning W. Rust, and Greg E. Bodeker
Atmos. Meas. Tech., 11, 3021–3029, https://doi.org/10.5194/amt-11-3021-2018, https://doi.org/10.5194/amt-11-3021-2018, 2018
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We investigate the feasibility of quantifying the difference in biases of two instrument types (i.e. radiosondes) by flying the old and new instruments on alternating days, so-called interlacing, to statistically derive the systematic biases between the instruments. While it is in principle possible to estimate the difference between two instrument biases from interlaced measurements, the number of required interlaced flights is very large for reasonable autocorrelation coefficient values.
Stefan Liersch, Julia Tecklenburg, Henning Rust, Andreas Dobler, Madlen Fischer, Tim Kruschke, Hagen Koch, and Fred Fokko Hattermann
Hydrol. Earth Syst. Sci., 22, 2163–2185, https://doi.org/10.5194/hess-22-2163-2018, https://doi.org/10.5194/hess-22-2163-2018, 2018
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Application-oriented regional impact studies require accurate simulations of future climate variables and water availability. We analyse the quality of global and regional climate projections and discuss potentials of correction methods that partly overcome this quality issue. The model ensemble used in this study projects increasing average annual discharges and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.
Alexander Pasternack, Jonas Bhend, Mark A. Liniger, Henning W. Rust, Wolfgang A. Müller, and Uwe Ulbrich
Geosci. Model Dev., 11, 351–368, https://doi.org/10.5194/gmd-11-351-2018, https://doi.org/10.5194/gmd-11-351-2018, 2018
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We propose a decadal forecast recalibration strategy (DeFoReSt) which simultaneously adjusts unconditional and conditional bias, as well as the ensemble spread while considering the typical setting of decadal predictions, i.e., model drift and a climate trend. We apply DeFoReSt to decadal toy model data and surface temperature forecasts from the MiKlip system and find consistent improvements in forecast quality compared with a simple calibration of the lead-time-dependent systematic errors.
Christoph Ritschel, Uwe Ulbrich, Peter Névir, and Henning W. Rust
Hydrol. Earth Syst. Sci., 21, 6501–6517, https://doi.org/10.5194/hess-21-6501-2017, https://doi.org/10.5194/hess-21-6501-2017, 2017
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A stochastic model for precipitation is used to simulate an observed precipitation series; it is compared to the original series in terms of intensity–duration frequency curves. Basis for the latter curves is a parametric model for the duration dependence of the underlying extreme value model allowing a consistent estimation of one single duration-dependent distribution using all duration series simultaneously. The stochastic model reproduces the curves except for very rare extreme events.
Katrin M. Nissen and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 17, 1177–1190, https://doi.org/10.5194/nhess-17-1177-2017, https://doi.org/10.5194/nhess-17-1177-2017, 2017
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The effect of climate change on potentially infrastructure damaging heavy precipitation events in Europe is investigated. A novel technique records not only event frequency but also event size, duration and severity as these parameters determine the potential consequences of the event. Over most of Europe the frequency and size of heavy precipitation events is predicted to increase. Moreover, the most severe events are predicted for future periods.
Tobias Pardowitz, Robert Osinski, Tim Kruschke, and Uwe Ulbrich
Nat. Hazards Earth Syst. Sci., 16, 2391–2402, https://doi.org/10.5194/nhess-16-2391-2016, https://doi.org/10.5194/nhess-16-2391-2016, 2016
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This paper describes an approach to derive probabilistic predictions of local winter storm damage occurrences. Such predictions are subject to large uncertainty due to meteorological forecast uncertainty and uncertainties in modelling weather impacts. The paper aims to quantify these uncertainties and demonstrate that valuable predictions can be made on the district level several days ahead.
R. Osinski, P. Lorenz, T. Kruschke, M. Voigt, U. Ulbrich, G. C. Leckebusch, E. Faust, T. Hofherr, and D. Majewski
Nat. Hazards Earth Syst. Sci., 16, 255–268, https://doi.org/10.5194/nhess-16-255-2016, https://doi.org/10.5194/nhess-16-255-2016, 2016
U. Dayan, K. Nissen, and U. Ulbrich
Nat. Hazards Earth Syst. Sci., 15, 2525–2544, https://doi.org/10.5194/nhess-15-2525-2015, https://doi.org/10.5194/nhess-15-2525-2015, 2015
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This review discusses published studies analyzing the atmospheric conditions that induce extreme precipitation over the eastern and western Mediterranean regions. It presents a systematic description of the interlacing role of several atmospheric processes of different scales - local, meso, and synoptic - that enable the development of torrential rains.
D. J. Befort, M. Fischer, G. C. Leckebusch, U. Ulbrich, A. Ganske, G. Rosenhagen, and H. Heinrich
Nat. Hazards Earth Syst. Sci., 15, 1437–1447, https://doi.org/10.5194/nhess-15-1437-2015, https://doi.org/10.5194/nhess-15-1437-2015, 2015
B. Merz, J. Aerts, K. Arnbjerg-Nielsen, M. Baldi, A. Becker, A. Bichet, G. Blöschl, L. M. Bouwer, A. Brauer, F. Cioffi, J. M. Delgado, M. Gocht, F. Guzzetti, S. Harrigan, K. Hirschboeck, C. Kilsby, W. Kron, H.-H. Kwon, U. Lall, R. Merz, K. Nissen, P. Salvatti, T. Swierczynski, U. Ulbrich, A. Viglione, P. J. Ward, M. Weiler, B. Wilhelm, and M. Nied
Nat. Hazards Earth Syst. Sci., 14, 1921–1942, https://doi.org/10.5194/nhess-14-1921-2014, https://doi.org/10.5194/nhess-14-1921-2014, 2014
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ibicus: a new open-source Python package and comprehensive interface for statistical bias adjustment and evaluation in climate modelling (v1.0.1)
Disentangling the hydrological and hydraulic controls on streamflow variability in Energy Exascale Earth System Model (E3SM) V2 – a case study in the Pantanal region
Constraining the carbon cycle in JULES-ES-1.0
The utility of simulated ocean chlorophyll observations: a case study with the Chlorophyll Observation Simulator Package (version 1) in CESMv2.2
GeoPDNN 1.0: a semi-supervised deep learning neural network using pseudo-labels for three-dimensional shallow strata modelling and uncertainty analysis in urban areas from borehole data
The prototype NOAA Aerosol Reanalysis version 1.0: description of the modeling system and its evaluation
Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1
Monsoon Mission Coupled Forecast System version 2.0: model description and Indian monsoon simulations
Exploring the ocean mesoscale at reduced computational cost with FESOM 2.5: efficient modeling strategies applied to the Southern Ocean
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid-ammonia nucleation
Truly conserving with conservative remapping methods
High-resolution downscaling of CMIP6 Earth system and global climate models using deep learning for Iberia
Earth system modeling on modular supercomputing architecture: coupled atmosphere–ocean simulations with ICON 2.6.6-rc
Global Downscaled Projections for Climate Impacts Research (GDPCIR): preserving quantile trends for modeling future climate impacts
Understanding changes in cloud simulations from E3SM version 1 to version 2
WRF (v4.0)–SUEWS (v2018c) coupled system: development, evaluation and application
Scenario setup and forcing data for impact model evaluation and impact attribution within the third round of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a)
Deep learning model based on multi-scale feature fusion for precipitation nowcasting
The Framework for Assessing Changes To Sea-level (FACTS) v1.0: a platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change
Getting the leaves right matters for estimating temperature extremes
The Southern Ocean Freshwater Input from Antarctica (SOFIA) Initiative: scientific objectives and experimental design
Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization
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.
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.
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.
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.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
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The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Carl Svenhag, Moa Kristina Sporre, Tinja Olenius, Daniel Yazgi, Sara Marie Blichner, Lars Peter Nieradzik, and Pontus Roldin
EGUsphere, https://doi.org/10.5194/egusphere-2023-2665, https://doi.org/10.5194/egusphere-2023-2665, 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 showed that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacted the number of particles in the air and clouds. It also changed the radiation balance in the same magnitude as man-made greenhouse emissions.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
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The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
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This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
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Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
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Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
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Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Cited articles
Amengual, A., Borga, M., Ravazzani, G., and Crema, S.: The role of storm
movement in controlling flash flood response: An analysis of the 28 September
2012 extreme event in Murcia, southeastern Spain, J.
Hydrometeorol., 22, 2379–2392, 2021. a
Armon, M., Marra, F., Enzel, Y., Rostkier-Edelstein, D., Garfinkel, C. I.,
Adam, O., Dayan, U., and Morin, E.: Reduced Rainfall in Future Heavy
Precipitation Events Related to Contracted Rain Area Despite Increased Rain
Rate, Earth's Future, 10, e2021EF002397, https://doi.org/10.1029/2021EF002397, 2022. a
Baur, F., Keil, C., and Craig, G. C.: Soil moisture–precipitation coupling
over Central Europe: Interactions between surface anomalies at different
scales and the dynamical implication, Q. J. Roy.
Meteor. Soc., 144, 2863–2875, https://doi.org/10.1002/qj.3415, 2018. a
Bennett, L., Melchers, B., and Proppe, B.: Curta: A General-purpose High-Performance Computer at ZEDAT, Freie Universität Berlin, https://doi.org/10.17169/refubium-26754, 2020. a
Brisson, E., Demuzere, M., and van Lipzig, N. P.: Modelling strategies for
performing convection-permitting climate simulations, Meteorol. Z., 25,
149–163, https://doi.org/10.1127/metz/2015/0598, 2016a. a
Brisson, E., Van Weverberg, K., Demuzere, M., Devis, A., Saeed, S., Stengel,
M., and van Lipzig, N. P.: How well can a convection-permitting climate model
reproduce decadal statistics of precipitation, temperature and cloud
characteristics?, Clim. Dynam., 47, 3043–3061,
https://doi.org/10.1007/s00382-016-3012-z, 2016b. a
Brisson, E., Brendel, C., Herzog, S., and Ahrens, B.: Lagrangian evaluation of
convective shower characteristics in a convection-permitting model,
Meteorol. Z., 27, 59–66, https://doi.org/10.1127/metz/2017/0817, 2018. a, b, c, d
Bronstert, A., Agarwal, A., Boessenkool, B., Crisologo, I., Fischer, M.,
Heistermann, M., Köhn-Reich, L., López-Tarazón, J. A., Moran, T., Ozturk,
U., Reinhardt-Imjela, C., and Wendi, D.: Forensic hydro-meteorological
analysis of an extreme flash flood: The 2016-05-29 event in Braunsbach, SW
Germany, Sci. Total Environ., 630, 977–991,
https://doi.org/10.1016/j.scitotenv.2018.02.241, 2018. a
Burghardt, B. J., Evans, C., and Roebber, P. J.: Assessing the Predictability
of Convection Initiation in the High Plains Using an Object-Based Approach,
Weather Forecast., 29, 403–418, https://doi.org/10.1175/WAF-D-13-00089.1, 2014. a
Caillaud, C., Somot, S., Alias, A., Bernard-Bouissières, I., Fumière,
Q., Laurantin, O., Seity, Y., and Ducrocq, V.: Modelling Mediterranean
heavy precipitation events at climate scale: an object-oriented evaluation of
the CNRM-AROME convection-permitting regional climate model, Clim.
Dynam., 56, 1717–1752, https://doi.org/10.1007/s00382-020-05558-y, 2021. a, b
Caine, S., Lane, T. P., May, P. T., Jakob, C., Siems, S. T., Manton, M. J., and
Pinto, J.: Statistical Assessment of Tropical Convection-Permitting Model
Simulations Using a Cell-Tracking Algorithm, Mon. Weather Rev., 141,
557–581, https://doi.org/10.1175/MWR-D-11-00274.1, 2013. a, b
Caldas-Alvarez, A., Augenstein, M., Ayzel, G., Barfus, K., Cherian, R., Dillenardt, L., Fauer, F., Feldmann, H., Heistermann, M., Karwat, A., Kaspar, F., Kreibich, H., Lucio-Eceiza, E. E., Meredith, E. P., Mohr, S., Niermann, D., Pfahl, S., Ruff, F., Rust, H. W., Schoppa, L., Schwitalla, T., Steidl, S., Thieken, A. H., Tradowsky, J. S., Wulfmeyer, V., and Quaas, J.: Meteorological, impact and climate perspectives of the 29 June 2017 heavy precipitation event in the Berlin metropolitan area, Nat. Hazards Earth Syst. Sci., 22, 3701–3724, https://doi.org/10.5194/nhess-22-3701-2022, 2022. a
Chen, D., Guo, J., Yao, D., Lin, Y., Zhao, C., Min, M., Xu, H., Liu, L., Huang,
X., Chen, T., and Zhai, P.: Mesoscale Convective Systems in the Asian
Monsoon Region From Advanced Himawari Imager: Algorithms and Preliminary
Results, J. Geophys. Res.-Atmos., 124, 2210–2234,
https://doi.org/10.1029/2018JD029707, 2019. a
Clark, A. J., Bullock, R. G., Jensen, T. L., Xue, M., and Kong, F.:
Application of Object-Based Time-Domain Diagnostics for Tracking
Precipitation Systems in Convection-Allowing Models, Weather
Forecast., 29, 517–542, https://doi.org/10.1175/WAF-D-13-00098.1, 2014. a
Davis, C., Brown, B., and Bullock, R.: Object-Based Verification of
Precipitation Forecasts. Part I: Methodology and Application to Mesoscale
Rain Areas, Mon. Weather Rev., 134, 1772–1784,
https://doi.org/10.1175/MWR3145.1, 2006. a
Davison, A. C. and Hinkley, D. V.: Bootstrap Methods and their Application,
Cambridge Series in Statistical and Probabilistic Mathematics, Cambridge
University Press, https://doi.org/10.1017/CBO9780511802843, 1997. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and
Vitart, F.: The ERA-Interim reanalysis: configuration and performance of
the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011 (data available at: https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim, last access: 30 January 2023). a, b
Dixon, M. and Wiener, G.: TITAN: Thunderstorm Identification, Tracking,
Analysis, and Nowcasting – A Radar-based Methodology, J.
Atmos. Ocean. Technol., 10, 785–797,
https://doi.org/10.1175/1520-0426(1993)010<0785:TTITAA>2.0.CO;2, 1993. a, b
DWD: Deutscher Wetterdienst – Glossar – Niederschlagsintensität,
https://www.dwd.de/DE/service/lexikon/Functions/glossar.html?lv2=101812&lv3=101906,
last access: 15 December 2022. a
Einfalt, T., Denoeux, T., and Jacquet, G.: A radar rainfall forecasting method
designed for hydrological purposes, J. Hydrol., 114, 229–244,
https://doi.org/10.1016/0022-1694(90)90058-6, 1990. a, b
Fosser, G., Khodayar, S., and Berg, P.: Benefit of convection permitting
climate model simulations in the representation of convective precipitation,
Clim. Dynam., 44, 45–60, https://doi.org/10.1007/s00382-014-2242-1, 2015. a
Fowler, H. J., Lenderink, G., Prein, A. F., Westra, S., Allan, R. P., Ban, N.,
Barbero, R., Berg, P., Blenkinsop, S., Do, H. X., Guerreiro, S., Haerter,
J. O., Kendon, E. J., Lewis, E., Schär, C., Sharma, A., Villarini, G.,
Wasko, C., and Zhang, X.: Anthropogenic intensification of short-duration
rainfall extremes, Nat. Rev. Earth Environ., 2, 107–122,
https://doi.org/10.1038/s43017-020-00128-6, 2021. a
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L.,
Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A.,
da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D.,
Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert,
S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis
for Research and Applications, Version 2 (MERRA-2), J. Climate, 30,
5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017 (data available at: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/, last access: 30 January 2023). a, b
Germann, U. and Zawadzki, I.: Scale-Dependence of the Predictability of
Precipitation from Continental Radar Images. Part I: Description of the
Methodology, Mon. Weather Rev., 130, 2859–2873,
https://doi.org/10.1175/1520-0493(2002)130<2859:SDOTPO>2.0.CO;2, 2002. a
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader,
J., Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K.,
Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U.,
Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and Stevens, B.:
Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations
for the Coupled Model Intercomparison Project phase 5, J. Adv.
Model. Earth Sy., 5, 572–597, 2013. a
Golding, B. W.: Nimrod: a system for generating automated very short range
forecasts, Meteorol. Appl., 5, 1–16,
https://doi.org/10.1017/S1350482798000577, 1998. a
Goldstein, H. and Healy, M. J. R.: The Graphical Presentation of a Collection
of Means, J. Roy. Stat. Soc. A, 158, 175–177, https://doi.org/10.2307/2983411, 1995. a, b
Hazeleger, W., Wang, X., Severijns, C., Ştefănescu, S., Bintanja,
R., Sterl, A., Wyser, K., Semmler, T., Yang, S., Van den Hurk, B., van Noije, T.,
van der Linden, E., and
van der Wiel, K:
EC-Earth V2. 2: description and validation of a new seamless earth system
prediction model, Clim. Dynam., 39, 2611–2629,
https://doi.org/10.1007/s00382-011-1228-5, 2012. a
He, T., Einfalt, T., Zhang, J., Hua, J., and Cai, Y.: New Algorithm for Rain
Cell Identification and Tracking in Rainfall Event Analysis, Atmosphere, 10,
532, https://doi.org/10.3390/atmos10090532, 2019. a
Hering, A., Morel, C., Galli, G., Sénési, S., Ambrosetti, P., and
Boscacci, M.: Nowcasting thunderstorms in the Alpine region using a radar
based adaptive thresholding scheme, in: Proceedings of ERAD, Copernicus GmbH, 1,
206–211, 2004. a
Hibino, K., Takayabu, I., Wakazuki, Y., and Ogata, T.: Physical responses of
convective heavy rainfall to future warming condition: Case study of the
Hiroshima event, Front. Earth Sci., 6, 35,
https://doi.org/10.3389/feart.2018.00035, 2018. a
Hirt, M. and Craig, G. C.: A cold pool perturbation scheme to improve
convective initiation in convection-permitting models, Q. J. Roy. Meteor. Soc., 147, 2429–2447, https://doi.org/10.1002/qj.4032,
2021. a, b
Hirt, M., Rasp, S., Blahak, U., and Craig, G. C.: Stochastic Parameterization
of Processes Leading to Convective Initiation in Kilometer-Scale Models,
Mon. Weather Rev., 147, 3917–3934, https://doi.org/10.1175/MWR-D-19-0060.1,
2019. a
Jacob, D., Petersen, J., Eggert, B., Alias, A., Christensen, O. B., Bouwer,
L. M., Braun, A., Colette, A., Déqué, M., Georgievski, G.,
Georgopoulou, E., Gobiet, A., Menut, L., Nikulin, G., Haensler, A.,
Hempelmann, N., Jones, C., Keuler, K., Kovats, S., Kröner, N., Kotlarski,
S., Kriegsmann, A., Martin, E., van Meijgaard, E., Moseley, C., Pfeifer, S.,
Preuschmann, S., Radermacher, C., Radtke, K., Rechid, D., Rounsevell, M.,
Samuelsson, P., Somot, S., Soussana, J.-F., Teichmann, C., Valentini, R.,
Vautard, R., Weber, B., and Yiou, P.: EURO-CORDEX: new high-resolution
climate change projections for European impact research, Reg. Environ.
Change, 14, 563–578, https://doi.org/10.1007/s10113-013-0499-2, 2014. a
Keil, C., Heinlein, F., and Craig, G. C.: The convective adjustment time-scale
as indicator of predictability of convective precipitation, Q. J. Roy. Meteor. Soc., 140, 480–490, https://doi.org/10.1002/qj.2143,
2014. a
Keil, C., Baur, F., Bachmann, K., Rasp, S., Schneider, L., and Barthlott, C.:
Relative contribution of soil moisture, boundary-layer and microphysical
perturbations on convective predictability in different weather regimes,
Q. J. Roy. Meteor. Soc., 145, 3102–3115,
https://doi.org/10.1002/qj.3607, 2019. a
Keller, M., Kröner, N., Fuhrer, O., Lüthi, D., Schmidli, J., Stengel, M., Stöckli, R., and Schär, C.: The sensitivity of Alpine summer convection to surrogate climate change: an intercomparison between convection-parameterizing and convection-resolving models, Atmos. Chem. Phys., 18, 5253–5264, https://doi.org/10.5194/acp-18-5253-2018, 2018. a
Knist, S., Goergen, K., and Simmer, C.: Evaluation and projected changes of
precipitation statistics in convection-permitting WRF climate simulations
over Central Europe, Clim. Dynam., 55, 1–17,
https://doi.org/10.1007/s00382-018-4147-x, 2018. a
Kröner, N., Kotlarski, S., Fischer, E., Lüthi, D., Zubler, E., and
Schär, C.: Separating climate change signals into thermodynamic,
lapse-rate and circulation effects: theory and application to the European
summer climate, Clim. Dynam., 48, 3425–3440,
https://doi.org/10.1007/s00382-016-3276-3, 2017. a
Lackmann, G. M.: The south-central US flood of May 2010: Present and future,
J. Climate, 26, 4688–4709, https://doi.org/10.1175/JCLI-D-12-00392.1, 2013. a
Li, L., Li, Y., and Li, Z.: Object-based tracking of precipitation systems in
western Canada: the importance of temporal resolution of source data,
Clim. Dynam., 55, 2421–2437, https://doi.org/10.1007/s00382-020-05388-y, 2020. a, b
Lucas-Picher, P., Argüeso, D., Brisson, E., Tramblay, Y., Berg, P.,
Lemonsu, A., Kotlarski, S., and Caillaud, C.: Convection-permitting modeling
with regional climate models: Latest developments and next steps, Wiley
Interdisciplinary Reviews: Climate Change, 12, e731, https://doi.org/10.1002/wcc.731,
2021. a
Mandapaka, P. V., Germann, U., Panziera, L., and Hering, A.: Can Lagrangian
extrapolation of radar fields be used for precipitation nowcasting over
complex alpine orography?, Weather Forecast., 27, 28–49,
https://doi.org/10.1175/WAF-D-11-00050.1, 2012. a
Mazza, E., Ulbrich, U., and Klein, R.: The tropical transition of the October
1996 medicane in the western Mediterranean Sea: A warm seclusion event,
Mon. Weather Rev., 145, 2575–2595, https://doi.org/10.1175/MWR-D-16-0474.1, 2017. a
Meredith, E. P., Ulbrich, U., and Rust, H. W.: The Diurnal Nature of Future
Extreme Precipitation Intensification, Geophys. Res. Lett., 46,
7680–7689, https://doi.org/10.1029/2019GL082385, 2019. a
Meredith, E. P., Ulbrich, U., and Rust, H. W.: Subhourly rainfall in a
convection-permitting model, Environ. Res. Lett., 15, 034031,
https://doi.org/10.1088/1748-9326/ab6787, 2020. a
Meredith, E. P., Ulbrich, U., Rust, H. W., and Truhetz, H.: Present and future
diurnal hourly precipitation in 0.11∘ EURO-CORDEX models and at
convection-permitting resolution, Environmental Research Communications, 3,
055002, https://doi.org/10.1088/2515-7620/abf15e, 2021. a
Meredith, E. P., Ulbrich, U., and Rust, H. W.: Pseudo global-warming
simulations with COSMO-CLM of a period of high convective activity over
Germany, World Data Centre for Climate [data set],
https://www.wdc-climate.de/ui/entry?acronym=DKRZ_LTA_1152_ds00302 (last access: 30 January 2023),
2022a. a
Meredith, E. P., Ulbrich, U., and Rust, H. W.: Data from “Cell tracking of
convective rainfall: sensitivity of climate-change signal to tracking
algorithm and cell definition (Cell-TAO v1.0)”, Zenodo [code],
https://doi.org/10.5281/zenodo.6977074, 2022b. a
Morel, C. and Senesi, S.: A climatology of mesoscale convective systems over
Europe using satellite infrared imagery. I: Methodology, Q. J. Roy. Meteor. Soc., 128, 1953–1971,
https://doi.org/10.1256/003590002320603485, 2002. a
Moseley, C., Berg, P., and Haerter, J. O.: Probing the precipitation life cycle
by iterative rain cell tracking, J. Geophys. Res.-Atmos., 118, 13361–13370, https://doi.org/10.1002/2013JD020868, 2013. a, b, c, d
Müller, S. K., Caillaud, C., Chan, S., de Vries, H., Bastin, S.,
Berthou, S., Brisson, E., Demory, M.-E., Feldmann, H., Goergen, K., Kartsios, S., Lind, P., Keuler, K., Pichelli, E., Raffa, M., Tölle, M.
H., and Warrach-Sagi, K.: Evaluation
of Alpine-Mediterranean precipitation events in convection-permitting
regional climate models using a set of tracking algorithms, Clim. Dynam., 1–19, https://doi.org/10.1007/s00382-022-06555-z, 2022. a, b
Muñoz, C., Wang, L.-P., and Willems, P.: Enhanced object-based tracking
algorithm for convective rain storms and cells, Atmos. Res., 201,
144–158, https://doi.org/10.1016/j.atmosres.2017.10.027, 2018. a
NCL: The NCAR Command Language (Version 6.5.0), Boulder,
Colorado, UCAR/NCAR/CISL/TDD [code], https://doi.org/10.5065/D6WD3XH5, 2018. a
Nissen, K. M. and Ulbrich, U.: Increasing frequencies and changing characteristics of heavy precipitation events threatening infrastructure in Europe under climate change, Nat. Hazards Earth Syst. Sci., 17, 1177–1190, https://doi.org/10.5194/nhess-17-1177-2017, 2017. a
Novo, S., Martínez, D., and Puentes, O.: Tracking, analysis, and nowcasting of
Cuban convective cells as seen by radar, Meteorol. Appl., 21,
585–595, https://doi.org/10.1002/met.1380, 2014. a
Noyelle, R., Ulbrich, U., Becker, N., and Meredith, E. P.: Assessing the impact of sea surface temperatures on a simulated medicane using ensemble simulations, Nat. Hazards Earth Syst. Sci., 19, 941–955, https://doi.org/10.5194/nhess-19-941-2019, 2019. a
Pardowitz, T., Befort, D. J., Leckebusch, G. C., and Ulbrich, U.: Estimating
uncertainties from high resolution simulations of extreme wind storms and
consequences for impacts, Meteorol. Z., 25, 531–541,
https://doi.org/10.1127/metz/2016/0582, 2016. a
Parodi, A., Ferraris, L., Gallus, W., Maugeri, M., Molini, L., Siccardi, F., and Boni, G.: Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915, Clim. Past, 13, 455–472, https://doi.org/10.5194/cp-13-455-2017, 2017. a
Piper, D., Kunz, M., Ehmele, F., Mohr, S., Mühr, B., Kron, A., and Daniell, J.: Exceptional sequence of severe thunderstorms and related flash floods in May and June 2016 in Germany – Part 1: Meteorological background, Nat. Hazards Earth Syst. Sci., 16, 2835–2850, https://doi.org/10.5194/nhess-16-2835-2016, 2016. a, b
Poujol, B., Prein, A. F., and Newman, A. J.: Kilometer-scale modeling projects
a tripling of Alaskan convective storms in future climate, Clim.
Dynam., 55, 3543–3564, https://doi.org/10.1007/s00382-020-05466-1,
2020a. a, b
Poujol, B., Sobolowski, S., Mooney, P., and Berthou, S.: A physically based
precipitation separation algorithm for convection-permitting models over
complex topography, Q. J. Roy. Meteor. Soc.,
146, 748–761, https://doi.org/10.1002/qj.3706, 2020b. a, b
Purr, C., Brisson, E., and Ahrens, B.: Convective rain cell characteristics and
scaling in climate projections for Germany, Int. J.
Climatol., 41, 3174–3185, https://doi.org/10.1002/joc.7012, 2021. a, b, c, d
Rasmussen, R., Ikeda, K., Liu, C., Gochis, D., Clark, M., Dai, A., Gutmann,
E., Dudhia, J., Chen, F., Barlage, M., Yates, D., and Zhang, G.: Climate change impacts on the
water balance of the Colorado headwaters: High-resolution regional climate
model simulations, J. Hydrometeorol., 15, 1091–1116,
https://doi.org/10.1175/JHM-D-13-0118.1, 2014. a
Rasp, S., Selz, T., and Craig, G. C.: Variability and Clustering of
Midlatitude Summertime Convection: Testing the Craig and Cohen Theory in a
Convection-Permitting Ensemble with Stochastic Boundary Layer Perturbations,
J. Atmos. Sci., 75, 691–706,
https://doi.org/10.1175/JAS-D-17-0258.1, 2018.
a
Raupach, T. H., Martynov, A., Nisi, L., Hering, A., Barton, Y., and Martius, O.: Object-based analysis of simulated thunderstorms in Switzerland: application and validation of automated thunderstorm tracking with simulation data, Geosci. Model Dev., 14, 6495–6514, https://doi.org/10.5194/gmd-14-6495-2021, 2021. a, b
Rezacova, D., Zacharov, P., and Sokol, Z.: Uncertainty in the area-related QPF
for heavy convective precipitation, Atmos. Res., 93, 238–246,
https://doi.org/10.1016/j.atmosres.2008.12.005, 2009. a, b
Rockel, B., Will, A., and Hense, A.: The regional climate model COSMO-CLM
(CCLM), Meteorol. Z., 17, 347–348, https://doi.org/10.1127/0941-2948/2008/0309,
2008. a, b
Schär, C., Frei, C., Lüthi, D., and Davies, H. C.: Surrogate
climate-change scenarios for regional climate models, Geophys. Res.
Lett., 23, 669–672, https://doi.org/10.1029/96GL00265, 1996. a, b
Skinner, P. S., Wheatley, D. M., Knopfmeier, K. H., Reinhart, A. E., Choate,
J. J., Jones, T. A., Creager, G. J., Dowell, D. C., Alexander, C. R., Ladwig,
T. T., Wicker, L. J., Heinselman, P. L., Minnis, P., and Palikonda, R.:
Object-Based Verification of a Prototype Warn-on-Forecast System, Weather
Forecast., 33, 1225–1250, https://doi.org/10.1175/WAF-D-18-0020.1, 2018. a
Stein, T. H. M., Hogan, R. J., Hanley, K. E., Nicol, J. C., Lean, H. W., Plant,
R. S., Clark, P. A., and Halliwell, C. E.: The Three-Dimensional Morphology
of Simulated and Observed Convective Storms over Southern England, Mon. Weather Rev., 142, 3264–3283, https://doi.org/10.1175/MWR-D-13-00372.1, 2014. a, b
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and
the experiment design, B. Am. Meteorol. Soc., 93, 485,
https://doi.org/10.1175/BAMS-D-11-00094.1, 2012. a
Tiedtke, M.: A comprehensive mass flux scheme for cumulus parameterization in
large-scale models, Mon. Weather Rev., 117, 1779–1800,
https://doi.org/10.1175/1520-0493(1989)117<1779:ACMFSF>2.0.CO;2, 1989. a
Van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard,
K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T.,
Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The
representative concentration pathways: an overview, Clim. Change, 109,
5–31, https://doi.org/10.1007/s10584-011-0148-z, 2011. a
Voldoire, A., Sanchez-Gomez, E., Salas y Mélia, D., Decharme, B., Cassou, C., Sénési, S., Valcke, S., Beau, I., Alias, A., Chevallier, M., Déqué, M., Deshayes, J., Douville, H., Fernandez, E., Madec, G., Maisonnave, E., Moine, M.-P., Planton, S., Saint-Martin, D., Szopa, S., Tyteca, S., Alkama, R., Belamari, S., Braun, A., Coquart, L., and Chauvin, F.:
The CNRM-CM5. 1 global climate model: description and basic evaluation,
Clim. Dynam., 40, 2091–2121, https://doi.org/10.1007/s00382-011-1259-y, 2013. a
Wasko, C., Sharma, A., and Westra, S.: Reduced spatial extent of extreme storms
at higher temperatures, Geophys. Res. Lett., 43, 4026–4032, 2016. a
Woo, W.-C. and Wong, W.-K.: Operational Application of Optical Flow Techniques
to Radar-Based Rainfall Nowcasting, Atmosphere, 8, 48,
https://doi.org/10.3390/atmos8030048, 2017. a
Short summary
Cell-tracking algorithms allow for the study of properties of a convective cell across its lifetime and, in particular, how these respond to climate change. We investigated whether the design of the algorithm can affect the magnitude of the climate-change signal. The algorithm's criteria for identifying a cell were found to have a strong impact on the warming response. The sensitivity of the warming response to different algorithm settings and cell types should thus be fully explored.
Cell-tracking algorithms allow for the study of properties of a convective cell across its...
