Articles | Volume 8, issue 7
https://doi.org/10.5194/gmd-8-2355-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-8-2355-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Methods for assessment of models
| 
31 Jul 2015
Methods for assessment of models |
| 31 Jul 2015
Three-dimensional visualization of ensemble weather forecasts – Part 2: Forecasting warm conveyor belt situations for aircraft-based field campaigns
Computer Graphics & Visualization Group, Technische Universität München, Garching, Germany
C. M. Grams
Institute for Atmospheric and Climate Science, ETH Zürich, Zurich, Switzerland
A. Schäfler
Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, Germany
R. Westermann
Computer Graphics & Visualization Group, Technische Universität München, Garching, Germany
Related authors
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-60, https://doi.org/10.5194/gmd-2024-60, 2024
Preprint under review for GMD
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the used AI and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Oriol Tintó Prims, Robert Redl, Marc Rautenhaus, Tobias Selz, Takumi Matsunobu, Kameswar Rao Modali, and George Craig
EGUsphere, https://doi.org/10.5194/egusphere-2024-753, https://doi.org/10.5194/egusphere-2024-753, 2024
Short summary
Short summary
Advanced compression techniques can drastically reduce the size of meteorological datasets (by 5x to 150x) without compromising the data's scientific value. We developed a user-friendly tool called 'enstools-compression' that makes this compression simple for Earth scientists. This tool works seamlessly with common weather and climate data formats. Our work shows that lossy compression can significantly improve how researchers store and analyze large meteorological datasets.
Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, and Rüdiger Westermann
Geosci. Model Dev., 16, 4617–4638, https://doi.org/10.5194/gmd-16-4617-2023, https://doi.org/10.5194/gmd-16-4617-2023, 2023
Short summary
Short summary
Numerical weather prediction models rely on parameterizations for sub-grid-scale processes, which are a source of uncertainty. We present novel visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along trajectories regarding similarities in temporal development and spatiotemporal relationships. The proposed workflow is applied to cloud microphysical sensitivities along coherent strongly ascending trajectories.
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450, https://doi.org/10.5194/gmd-16-4427-2023, https://doi.org/10.5194/gmd-16-4427-2023, 2023
Short summary
Short summary
We investigate the benefit of objective 3-D front detection with modern interactive visual analysis techniques for case studies of extra-tropical cyclones and comparisons of frontal structures between different numerical weather prediction models. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment them in the vertical dimension. We see great potential for more complex studies of atmospheric dynamics and for operational weather forecasting.
Andreas Alexander Beckert, Lea Eisenstein, Annika Oertel, Timothy Hewson, George C. Craig, and Marc Rautenhaus
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-36, https://doi.org/10.5194/wcd-2022-36, 2022
Preprint withdrawn
Short summary
Short summary
This study revises and extends a previously presented 3-D objective front detection method and demonstrates its benefits to analyse weather dynamics in numerical simulation data. Based on two case studies of extratropical cyclones, we demonstrate the evaluation of conceptual models from dynamic meteorology, illustrate the benefits of our interactive analysis approach by comparing fronts in data with different model resolutions, and study the impact of convection on fronts.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Roderick van der Linden, Michael Maier-Gerber, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 15, 4447–4468, https://doi.org/10.5194/gmd-15-4447-2022, https://doi.org/10.5194/gmd-15-4447-2022, 2022
Short summary
Short summary
Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics. For example, anomalies in the PV field near the tropopause are linked to extreme weather events. In this study, an objective strategy to identify these anomalies is presented and evaluated. As a novel concept, it can be applied to three-dimensional (3-D) data sets. Supported by 3-D visualizations, we illustrate advantages of this new analysis over existing studies along a case study.
Marcel Meyer, Iuliia Polkova, Kameswar Rao Modali, Laura Schaffer, Johanna Baehr, Stephan Olbrich, and Marc Rautenhaus
Weather Clim. Dynam., 2, 867–891, https://doi.org/10.5194/wcd-2-867-2021, https://doi.org/10.5194/wcd-2-867-2021, 2021
Short summary
Short summary
Novel techniques from computer science are used to study extreme weather events. Inspired by the interactive 3-D visual analysis of the recently released ERA5 reanalysis data, we improve commonly used metrics for measuring polar winter storms and outbreaks of cold air. The software (Met.3D) that we have extended and applied as part of this study is freely available and can be used generically for 3-D visualization of a broad variety of atmospheric processes in weather and climate data.
M. Rautenhaus, M. Kern, A. Schäfler, and R. Westermann
Geosci. Model Dev., 8, 2329–2353, https://doi.org/10.5194/gmd-8-2329-2015, https://doi.org/10.5194/gmd-8-2329-2015, 2015
Short summary
Short summary
This article presents "Met.3D", a new open-source tool for the interactive 3D visualization of numerical ensemble weather predictions. Met.3D builds a bridge from proven 2D visualization methods commonly used in meteorology to 3D visualization and implements approaches to using the ensemble to allow the user to assess forecast uncertainty. The article is the first part of a two-paper study discussing how 3D and ensemble visualization can be used in a meaningful way suited to weather forecasting.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Luise J. Fischer, David N. Bresch, Dominik Büeler, Christian M. Grams, Matthias Röthlisberger, and Heini Wernli
EGUsphere, https://doi.org/10.5194/egusphere-2024-1253, https://doi.org/10.5194/egusphere-2024-1253, 2024
This preprint is open for discussion and under review for Weather and Climate Dynamics (WCD).
Short summary
Short summary
Atmospheric flows over the North Atlantic can be meaningfully classified into weather regimes, and climate simulations suggest that the regime frequencies might change in the future. We provide a quantitative framework that helps assessing whether these regime frequency changes are relevant for understanding climate change signals in precipitation. At least in our example application, this is not the case, i.e., regime frequency changes explain little of the projected precipitation changes.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-60, https://doi.org/10.5194/gmd-2024-60, 2024
Preprint under review for GMD
Short summary
Short summary
In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the used AI and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Seraphine Hauser, Franziska Teubler, Michael Riemer, Peter Knippertz, and Christian M. Grams
Weather Clim. Dynam., 5, 633–658, https://doi.org/10.5194/wcd-5-633-2024, https://doi.org/10.5194/wcd-5-633-2024, 2024
Short summary
Short summary
Blocking over Greenland has substantial impacts on the weather and climate in mid- and high latitudes. This study applies a quasi-Lagrangian thinking on the dynamics of Greenland blocking and reveals two pathways of anticyclonic anomalies linked to the block. Moist processes were found to play a dominant role in the formation and maintenance of blocking. This emphasizes the necessity of the correct representation of moist processes in weather and climate models to realistically depict blocking.
Oriol Tintó Prims, Robert Redl, Marc Rautenhaus, Tobias Selz, Takumi Matsunobu, Kameswar Rao Modali, and George Craig
EGUsphere, https://doi.org/10.5194/egusphere-2024-753, https://doi.org/10.5194/egusphere-2024-753, 2024
Short summary
Short summary
Advanced compression techniques can drastically reduce the size of meteorological datasets (by 5x to 150x) without compromising the data's scientific value. We developed a user-friendly tool called 'enstools-compression' that makes this compression simple for Earth scientists. This tool works seamlessly with common weather and climate data formats. Our work shows that lossy compression can significantly improve how researchers store and analyze large meteorological datasets.
Konstantin Krüger, Andreas Schäfler, Martin Weissmann, and George C. Craig
Weather Clim. Dynam., 5, 491–509, https://doi.org/10.5194/wcd-5-491-2024, https://doi.org/10.5194/wcd-5-491-2024, 2024
Short summary
Short summary
Initial conditions of current numerical weather prediction models insufficiently represent the sharp vertical gradients across the midlatitude tropopause. Observation-space data assimilation output is used to study the influence of assimilated radiosondes on the tropopause. The radiosondes reduce systematic biases of the model background and sharpen temperature and wind gradients in the analysis. Tropopause sharpness is still underestimated in the analysis, which may impact weather forecasts.
Joshua Dorrington, Marta Wenta, Federico Grazzini, Linus Magnusson, Frederic Vitart, and Christian Grams
EGUsphere, https://doi.org/10.5194/egusphere-2024-415, https://doi.org/10.5194/egusphere-2024-415, 2024
Short summary
Short summary
Extreme rainfall is the leading weather-related source of damages in Europe, but is still difficult to predict on long time scales. A recent example of this were the devastating floods in the Italian region of Emiglia Romagna in May 2023. We present perspectives based on large-scale dynamical information that allow us to better understand and predict such events.
Marta Wenta, Christian M. Grams, Lukas Papritz, and Marc Federer
Weather Clim. Dynam., 5, 181–209, https://doi.org/10.5194/wcd-5-181-2024, https://doi.org/10.5194/wcd-5-181-2024, 2024
Short summary
Short summary
Our study links air–sea interactions over the Gulf Stream to an atmospheric block in February 2019. We found that over 23 % of air masses that were lifted into the block by cyclones interacted with the Gulf Stream. As cyclones pass over the Gulf Stream, they cause intense surface evaporation events, preconditioning the environment for the development of cyclones. This implies that air–sea interactions over the Gulf Stream affect the large-scale dynamics in the North Atlantic–European region.
Julian F. Quinting, Christian M. Grams, Edmund Kar-Man Chang, Stephan Pfahl, and Heini Wernli
Weather Clim. Dynam., 5, 65–85, https://doi.org/10.5194/wcd-5-65-2024, https://doi.org/10.5194/wcd-5-65-2024, 2024
Short summary
Short summary
Research in the last few decades has revealed that rapidly ascending airstreams in extratropical cyclones have an important effect on the evolution of downstream weather and predictability. In this study, we show that the occurrence of these airstreams over the North Pacific is modulated by tropical convection. Depending on the modulation, known atmospheric circulation patterns evolve quite differently, which may affect extended-range predictions in the Atlantic–European region.
Moritz Deinhard and Christian M. Grams
EGUsphere, https://doi.org/10.5194/egusphere-2023-1938, https://doi.org/10.5194/egusphere-2023-1938, 2023
Short summary
Short summary
Stochastic perturbations are a frequently used technique to represent model uncertainties in numerical weather prediction. While such schemes are beneficial for the forecast skill, they can also change the mean state of the model. We focus on how different schemes modulate rapidly ascending air streams, such as warm conveyor belts, and whether the changes to these weather systems are projected onto larger scales. We thereby provide a process chain how perturbations affect the model climate.
Christoph Neuhauser, Maicon Hieronymus, Michael Kern, Marc Rautenhaus, Annika Oertel, and Rüdiger Westermann
Geosci. Model Dev., 16, 4617–4638, https://doi.org/10.5194/gmd-16-4617-2023, https://doi.org/10.5194/gmd-16-4617-2023, 2023
Short summary
Short summary
Numerical weather prediction models rely on parameterizations for sub-grid-scale processes, which are a source of uncertainty. We present novel visual analytics solutions to analyze interactively the sensitivities of a selected prognostic variable to multiple model parameters along trajectories regarding similarities in temporal development and spatiotemporal relationships. The proposed workflow is applied to cloud microphysical sensitivities along coherent strongly ascending trajectories.
Andreas A. Beckert, Lea Eisenstein, Annika Oertel, Tim Hewson, George C. Craig, and Marc Rautenhaus
Geosci. Model Dev., 16, 4427–4450, https://doi.org/10.5194/gmd-16-4427-2023, https://doi.org/10.5194/gmd-16-4427-2023, 2023
Short summary
Short summary
We investigate the benefit of objective 3-D front detection with modern interactive visual analysis techniques for case studies of extra-tropical cyclones and comparisons of frontal structures between different numerical weather prediction models. The 3-D frontal structures show agreement with 2-D fronts from surface analysis charts and augment them in the vertical dimension. We see great potential for more complex studies of atmospheric dynamics and for operational weather forecasting.
Annika Oertel, Annette K. Miltenberger, Christian M. Grams, and Corinna Hoose
Atmos. Chem. Phys., 23, 8553–8581, https://doi.org/10.5194/acp-23-8553-2023, https://doi.org/10.5194/acp-23-8553-2023, 2023
Short summary
Short summary
Warm conveyor belts (WCBs) are cloud- and precipitation-producing airstreams in extratropical cyclones that are important for the large-scale flow and cloud radiative forcing. We analyze cloud formation processes during WCB ascent in a two-moment microphysics scheme. Quantification of individual diabatic heating rates shows the importance of condensation, vapor deposition, rain evaporation, melting, and cloud-top radiative cooling for total heating and WCB-related potential vorticity structure.
Axel Seifert, Vanessa Bachmann, Florian Filipitsch, Jochen Förstner, Christian M. Grams, Gholam Ali Hoshyaripour, Julian Quinting, Anika Rohde, Heike Vogel, Annette Wagner, and Bernhard Vogel
Atmos. Chem. Phys., 23, 6409–6430, https://doi.org/10.5194/acp-23-6409-2023, https://doi.org/10.5194/acp-23-6409-2023, 2023
Short summary
Short summary
We investigate how mineral dust can lead to the formation of cirrus clouds. Dusty cirrus clouds lead to a reduction in solar radiation at the surface and, hence, a reduced photovoltaic power generation. Current weather prediction systems are not able to predict this interaction between mineral dust and cirrus clouds. We have developed a new physical description of the formation of dusty cirrus clouds. Overall we can show a considerable improvement in the forecast quality of clouds and radiation.
Seraphine Hauser, Franziska Teubler, Michael Riemer, Peter Knippertz, and Christian M. Grams
Weather Clim. Dynam., 4, 399–425, https://doi.org/10.5194/wcd-4-399-2023, https://doi.org/10.5194/wcd-4-399-2023, 2023
Short summary
Short summary
Blocking describes a flow configuration in the midlatitudes where stationary high-pressure systems block the propagation of weather systems. This study combines three individual perspectives that capture the dynamics and importance of various processes in the formation of a major blocking in 2016 from a weather regime perspective. In future work, this framework will enable a holistic view of the dynamics and the role of moist processes in different life cycle stages of blocked weather regimes.
Franziska Teubler, Michael Riemer, Christopher Polster, Christian M. Grams, Seraphine Hauser, and Volkmar Wirth
Weather Clim. Dynam., 4, 265–285, https://doi.org/10.5194/wcd-4-265-2023, https://doi.org/10.5194/wcd-4-265-2023, 2023
Short summary
Short summary
Weather regimes govern an important part of the sub-seasonal variability of the mid-latitude circulation. The year-round dynamics of blocked regimes in the Atlantic European region are investigated in over 40 years of data. We show that the dynamics between the regimes are on average very similar. Within the regimes, the main variability – starting from the characteristics of dynamical processes alone – dominates and transcends the variability in season and types of transitions.
Andreas Schäfler, Michael Sprenger, Heini Wernli, Andreas Fix, and Martin Wirth
Atmos. Chem. Phys., 23, 999–1018, https://doi.org/10.5194/acp-23-999-2023, https://doi.org/10.5194/acp-23-999-2023, 2023
Short summary
Short summary
In this study, airborne lidar profile measurements of H2O and O3 across a midlatitude jet stream are combined with analyses in tracer–trace space and backward trajectories. We highlight that transport and mixing processes in the history of the observed air masses are governed by interacting tropospheric weather systems on synoptic timescales. We show that these weather systems play a key role in the high variability of the paired H2O and O3 distributions near the tropopause.
Konstantin Krüger, Andreas Schäfler, Martin Wirth, Martin Weissmann, and George C. Craig
Atmos. Chem. Phys., 22, 15559–15577, https://doi.org/10.5194/acp-22-15559-2022, https://doi.org/10.5194/acp-22-15559-2022, 2022
Short summary
Short summary
A comprehensive data set of airborne lidar water vapour profiles is compared with ERA5 reanalyses for a robust characterization of the vertical structure of the mid-latitude lower-stratospheric moist bias. We confirm a moist bias of up to 55 % at 1.3 km altitude above the tropopause and uncover a decreasing bias beyond. Collocated O3 and H2O observations reveal a particularly strong bias in the mixing layer, indicating insufficiently modelled transport processes fostering the bias.
Benjamin Witschas, Christian Lemmerz, Alexander Geiß, Oliver Lux, Uwe Marksteiner, Stephan Rahm, Oliver Reitebuch, Andreas Schäfler, and Fabian Weiler
Atmos. Meas. Tech., 15, 7049–7070, https://doi.org/10.5194/amt-15-7049-2022, https://doi.org/10.5194/amt-15-7049-2022, 2022
Short summary
Short summary
In August 2018, the first wind lidar Aeolus was launched into space and has since then been providing data of the global wind field. The primary goal of Aeolus was the improvement of numerical weather prediction. To verify the quality of Aeolus wind data, DLR performed four airborne validation campaigns with two wind lidar systems. In this paper, we report on results from the two later campaigns, performed in Iceland and the tropics.
Oliver Lux, Benjamin Witschas, Alexander Geiß, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Stephan Rahm, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 6467–6488, https://doi.org/10.5194/amt-15-6467-2022, https://doi.org/10.5194/amt-15-6467-2022, 2022
Short summary
Short summary
We discuss the influence of different quality control schemes on the results of Aeolus wind product validation and present statistical tools for ensuring consistency and comparability among diverse validation studies with regard to the specific error characteristics of the Rayleigh-clear and Mie-cloudy winds. The developed methods are applied for the validation of Aeolus winds against an ECMWF model background and airborne wind lidar data from the Joint Aeolus Tropical Atlantic Campaign.
Andreas Alexander Beckert, Lea Eisenstein, Annika Oertel, Timothy Hewson, George C. Craig, and Marc Rautenhaus
Weather Clim. Dynam. Discuss., https://doi.org/10.5194/wcd-2022-36, https://doi.org/10.5194/wcd-2022-36, 2022
Preprint withdrawn
Short summary
Short summary
This study revises and extends a previously presented 3-D objective front detection method and demonstrates its benefits to analyse weather dynamics in numerical simulation data. Based on two case studies of extratropical cyclones, we demonstrate the evaluation of conceptual models from dynamic meteorology, illustrate the benefits of our interactive analysis approach by comparing fronts in data with different model resolutions, and study the impact of convection on fronts.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Roderick van der Linden, Michael Maier-Gerber, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 15, 4447–4468, https://doi.org/10.5194/gmd-15-4447-2022, https://doi.org/10.5194/gmd-15-4447-2022, 2022
Short summary
Short summary
Potential vorticity (PV) analysis plays a central role in studying atmospheric dynamics. For example, anomalies in the PV field near the tropopause are linked to extreme weather events. In this study, an objective strategy to identify these anomalies is presented and evaluated. As a novel concept, it can be applied to three-dimensional (3-D) data sets. Supported by 3-D visualizations, we illustrate advantages of this new analysis over existing studies along a case study.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Alexander Geiß, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 15, 1303–1331, https://doi.org/10.5194/amt-15-1303-2022, https://doi.org/10.5194/amt-15-1303-2022, 2022
Short summary
Short summary
The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.
Julian F. Quinting and Christian M. Grams
Geosci. Model Dev., 15, 715–730, https://doi.org/10.5194/gmd-15-715-2022, https://doi.org/10.5194/gmd-15-715-2022, 2022
Short summary
Short summary
Physical processes in weather systems importantly affect the midlatitude large-scale circulation. This study introduces an artificial-intelligence-based framework which allows the identification of an important weather system – the so-called warm conveyor belt (WCB) – at comparably low computational costs and from data at low spatial and temporal resolution. The framework thus newly enables the systematic investigation of WCBs in large data sets such as climate model projections.
Julian F. Quinting, Christian M. Grams, Annika Oertel, and Moritz Pickl
Geosci. Model Dev., 15, 731–744, https://doi.org/10.5194/gmd-15-731-2022, https://doi.org/10.5194/gmd-15-731-2022, 2022
Short summary
Short summary
This study applies novel artificial-intelligence-based models that allow the identification of one specific weather system which affects the midlatitude circulation. We show that the models yield similar results as their trajectory-based counterpart, which requires data at higher spatiotemporal resolution and is computationally more expensive. Overall, we aim to show how deep learning methods can be used efficiently to support process understanding of biases in weather prediction models.
Marcel Meyer, Iuliia Polkova, Kameswar Rao Modali, Laura Schaffer, Johanna Baehr, Stephan Olbrich, and Marc Rautenhaus
Weather Clim. Dynam., 2, 867–891, https://doi.org/10.5194/wcd-2-867-2021, https://doi.org/10.5194/wcd-2-867-2021, 2021
Short summary
Short summary
Novel techniques from computer science are used to study extreme weather events. Inspired by the interactive 3-D visual analysis of the recently released ERA5 reanalysis data, we improve commonly used metrics for measuring polar winter storms and outbreaks of cold air. The software (Met.3D) that we have extended and applied as part of this study is freely available and can be used generically for 3-D visualization of a broad variety of atmospheric processes in weather and climate data.
Maxi Boettcher, Andreas Schäfler, Michael Sprenger, Harald Sodemann, Stefan Kaufmann, Christiane Voigt, Hans Schlager, Donato Summa, Paolo Di Girolamo, Daniele Nerini, Urs Germann, and Heini Wernli
Atmos. Chem. Phys., 21, 5477–5498, https://doi.org/10.5194/acp-21-5477-2021, https://doi.org/10.5194/acp-21-5477-2021, 2021
Short summary
Short summary
Warm conveyor belts (WCBs) are important airstreams in extratropical cyclones, often leading to the formation of intense precipitation. We present a case study that involves aircraft, lidar and radar observations of water and clouds in a WCB ascending from western Europe across the Alps towards the Baltic Sea during the field campaigns HyMeX and T-NAWDEX-Falcon in October 2012. A probabilistic trajectory measure and an airborne tracer experiment were used to confirm the long pathway of the WCB.
Andreas Schäfler, Andreas Fix, and Martin Wirth
Atmos. Chem. Phys., 21, 5217–5234, https://doi.org/10.5194/acp-21-5217-2021, https://doi.org/10.5194/acp-21-5217-2021, 2021
Short summary
Short summary
First-ever, collocated ozone and water vapor lidar observations across the tropopause are applied to investigate the extratropical transition layer (ExTL). The combined view of a quasi-instantaneous cross section and its tracer–tracer depiction allows us to analyze the ExTL shape and composition and the formation of mixing lines in relation to the dynamic situation. Such lidar data are relevant for future upper-tropospheric and lower-stratospheric investigations and model validations.
Daniela I. V. Domeisen, Christian M. Grams, and Lukas Papritz
Weather Clim. Dynam., 1, 373–388, https://doi.org/10.5194/wcd-1-373-2020, https://doi.org/10.5194/wcd-1-373-2020, 2020
Short summary
Short summary
We cannot currently predict the weather over Europe beyond 2 weeks. The stratosphere provides a promising opportunity to go beyond that limit by providing a change in probability of certain weather regimes at the surface. However, not all stratospheric extreme events are followed by the same surface weather evolution. We show that this weather evolution is related to the tropospheric weather regime around the onset of the stratospheric extreme event for many stratospheric events.
Susanna Mohr, Jannik Wilhelm, Jan Wandel, Michael Kunz, Raphael Portmann, Heinz Jürgen Punge, Manuel Schmidberger, Julian F. Quinting, and Christian M. Grams
Weather Clim. Dynam., 1, 325–348, https://doi.org/10.5194/wcd-1-325-2020, https://doi.org/10.5194/wcd-1-325-2020, 2020
Short summary
Short summary
We investigated an exceptional thunderstorm episode in 2018, in which atmospheric blocking provided large-scale environmental conditions favouring convection. Furthermore, blocking was accompanied by a high cut-off frequency on its upstream side, which together with filaments of high PV provided the mesoscale setting for deep moist convection. The exceptional persistence of low stability combined with weak wind speed in the mid-troposphere over more than 3 weeks has never been observed before.
Oliver Lux, Christian Lemmerz, Fabian Weiler, Uwe Marksteiner, Benjamin Witschas, Stephan Rahm, Andreas Schäfler, and Oliver Reitebuch
Atmos. Meas. Tech., 11, 3297–3322, https://doi.org/10.5194/amt-11-3297-2018, https://doi.org/10.5194/amt-11-3297-2018, 2018
Short summary
Short summary
This work reports airborne wind lidar observations performed in a recent field campaign. The deployed lidar system serves as a demonstrator for the satellite instrument ALADIN on board Aeolus, which is scheduled for launch in 2018 and will become the first wind lidar in space. After presenting the measurement principle, operation procedures and wind retrieval algorithm, the obtained wind results are validated and discussed, providing valuable information in preparation for the satellite mission.
Benedikt Urbanek, Silke Groß, Andreas Schäfler, and Martin Wirth
Atmos. Meas. Tech., 10, 1653–1664, https://doi.org/10.5194/amt-10-1653-2017, https://doi.org/10.5194/amt-10-1653-2017, 2017
Short summary
Short summary
Cirrus evolution from nucleation to cloud breakup can be investigated with a novel classification scheme based on airborne lidar data. Applying it to a case study from the ML-CIRRUS campaign, we investigate the impact of large-scale dynamics and small-scale gravity lee waves on the detailed spatial distribution of evolution stages in individual clouds. Our scheme may help to gain more insights in optical and radiative properties of cirrus under various formation and life cycle conditions.
Manuel Gutleben, Silke Gross, Martin Wirth, and Andreas Schäfler
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-333, https://doi.org/10.5194/amt-2016-333, 2016
Revised manuscript not accepted
Short summary
Short summary
Shallow marine cumulus convection over the Atlantic ocean is studied with observations by airborne and spaceborne lidar instruments. Cloud top height as well as cloud length and cloud gap length distributions are calculated by use of a newly developed algorithm. The distribution of cloud top heights during wintertime measurements shows a two-layer structure. However, significant differences in cloud top height distributions compared to summertime measurements are found.
Thomas Trickl, Hannes Vogelmann, Andreas Fix, Andreas Schäfler, Martin Wirth, Bertrand Calpini, Gilbert Levrat, Gonzague Romanens, Arnoud Apituley, Keith M. Wilson, Robert Begbie, Jens Reichardt, Holger Vömel, and Michael Sprenger
Atmos. Chem. Phys., 16, 8791–8815, https://doi.org/10.5194/acp-16-8791-2016, https://doi.org/10.5194/acp-16-8791-2016, 2016
Short summary
Short summary
A rather homogeneous deep stratospheric intrusion event was mapped by vertical sounding over central Europe and by model calculations along the transport path. The very low minimum H2O mixing ratios demonstrate almost negligible mixing with tropospheric air during the downward transport. The vertical distributions of O3 and aerosol were transferred from the source region to Europe without major change. A rather shallow outflow from the stratosphere was found.
S. Groß, V. Freudenthaler, K. Schepanski, C. Toledano, A. Schäfler, A. Ansmann, and B. Weinzierl
Atmos. Chem. Phys., 15, 11067–11080, https://doi.org/10.5194/acp-15-11067-2015, https://doi.org/10.5194/acp-15-11067-2015, 2015
Short summary
Short summary
In June and July 2013 dual-wavelength lidar measurements were performed in Barbados to study long-range transported Saharan dust across the Atlantic Ocean and investigate transport-induced changes. The focus of our measurements is the intensive optical properties, the lidar ratio and the particle linear depolarization ratio. While the lidar ratio shows no differences compared to the values of fresh Saharan dust, the particle linear depolarization ratio shows slight differences.
M. Rautenhaus, M. Kern, A. Schäfler, and R. Westermann
Geosci. Model Dev., 8, 2329–2353, https://doi.org/10.5194/gmd-8-2329-2015, https://doi.org/10.5194/gmd-8-2329-2015, 2015
Short summary
Short summary
This article presents "Met.3D", a new open-source tool for the interactive 3D visualization of numerical ensemble weather predictions. Met.3D builds a bridge from proven 2D visualization methods commonly used in meteorology to 3D visualization and implements approaches to using the ensemble to allow the user to assess forecast uncertainty. The article is the first part of a two-paper study discussing how 3D and ensemble visualization can be used in a meaningful way suited to weather forecasting.
S. Groß, M. Wirth, A. Schäfler, A. Fix, S. Kaufmann, and C. Voigt
Atmos. Meas. Tech., 7, 2745–2755, https://doi.org/10.5194/amt-7-2745-2014, https://doi.org/10.5194/amt-7-2745-2014, 2014
C. M. Grams, H. Binder, S. Pfahl, N. Piaget, and H. Wernli
Nat. Hazards Earth Syst. Sci., 14, 1691–1702, https://doi.org/10.5194/nhess-14-1691-2014, https://doi.org/10.5194/nhess-14-1691-2014, 2014
Related subject area
Atmospheric sciences
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
A general comprehensive evaluation method for cross-scale precipitation forecasts
Implementation of a Simple Actuator Disk for Large-Eddy Simulation in the Weather Research and Forecasting Model (WRF-SADLES v1.2) for wind turbine wake simulation
WRF-PDAF v1.0: implementation and application of an online localized ensemble data assimilation framework
Implementation and evaluation of diabatic advection in the Lagrangian transport model MPTRAC 2.6
An improved and extended parameterization of the CO2 15 µm cooling in the middle and upper atmosphere (CO2_cool_fort-1.0)
Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)
Application of regional meteorology and air quality models based on the microprocessor without interlocked piped stages (MIPS) and LoongArch CPU platforms
Investigating ground-level ozone pollution in semi-arid and arid regions of Arizona using WRF-Chem v4.4 modeling
An objective identification technique for potential vorticity structures associated with African easterly waves
Importance of microphysical settings for climate forcing by stratospheric SO2 injections as modeled by SOCOL-AERv2
Assessment of surface ozone products from downscaled CAMS reanalysis and CAMS daily forecast using urban air quality monitoring stations in Iran
Open boundary conditions for atmospheric large-eddy simulations and their implementation in DALES4.4
Efficient and stable coupling of the SuperdropNet deep-learning-based cloud microphysics (v0.1.0) with the ICON climate and weather model (v2.6.5)
Three-dimensional variational assimilation with a multivariate background error covariance for the Model for Prediction Across Scales – Atmosphere with the Joint Effort for Data assimilation Integration (JEDI-MPAS 2.0.0-beta)
FUME 2.0 – Flexible Universal processor for Modeling Emissions
DEUCE v1.0: a neural network for probabilistic precipitation nowcasting with aleatoric and epistemic uncertainties
Evaluation of multi-season convection-permitting atmosphere – mixed-layer ocean simulations of the Maritime Continent
Investigating the impact of coupling HARMONIE-WINS50 (cy43) meteorology to LOTOS-EUROS (v2.2.002) on a simulation of NO2 concentrations over the Netherlands
Balloon drift estimation and improved position estimates for radiosondes
Emission ensemble approach to improve the development of multi-scale emission inventories
What is the relative impact of nudging and online coupling on meteorological variables, pollutant concentrations and aerosol optical properties?
Diagnosing drivers of PM2.5 simulation biases in China from meteorology, chemical composition, and emission sources using an efficient machine learning method
Validation and analysis of the Polair3D v1.11 chemical transport model over Quebec
Assimilation of GNSS tropospheric gradients into the Weather Research and Forecasting (WRF) model version 4.4.1
Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1
Assessing acetone for the GISS ModelE2.1 Earth system model
Bergen metrics: composite error metrics for assessing performance of climate models using EURO-CORDEX simulations
A dynamic approach to three-dimensional radiative transfer in subkilometer-scale numerical weather prediction models: the dynamic TenStream solver v1.0
Evaluation and development of surface layer scheme representation of temperature inversions over boreal forests in Arctic wintertime conditions
Modelling wind farm effects in HARMONIE–AROME (cycle 43.2.2) – Part 1: Implementation and evaluation
Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)
Challenges of constructing and selecting the “perfect” boundary conditions for the large-eddy simulation model PALM
A machine learning approach for evaluating Southern Ocean cloud radiative biases in a global atmosphere model
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
How non-equilibrium aerosol chemistry impacts particle acidity: the GMXe AERosol CHEMistry (GMXe–AERCHEM, v1.0) sub-submodel of MESSy
A grid model for vertical correction of precipitable water vapor over the Chinese mainland and surrounding areas using random forest
MEXPLORER 1.0.0 – a mechanism explorer for analysis and visualization of chemical reaction pathways based on graph theory
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote sensing observations
Advances and prospects of deep learning for medium-range extreme weather forecasting
An overview of the Western United States Dynamically Downscaled Dataset (WUS-D3)
cloudbandPy 1.0: an automated algorithm for the detection of tropical–extratropical cloud bands
PyRTlib: an educational Python-based library for non-scattering atmospheric microwave radiative transfer computations
TAMS: A Tracking, Classifying, and Variable-Assigning Algorithm for Mesoscale Convective Systems in Simulated and Satellite-Derived Datasets
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
Short summary
Short summary
Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
Short summary
Short summary
Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
Short summary
Short summary
Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
Short summary
Short summary
RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
Short summary
Short summary
The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
Short summary
Short summary
We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
Short summary
Short summary
The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
Short summary
Short summary
By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Hai Bui, Mostafa Bakhoday-Paskyabi, and Mohammadreza Mohammadpour-Penchah
Geosci. Model Dev., 17, 4447–4465, https://doi.org/10.5194/gmd-17-4447-2024, https://doi.org/10.5194/gmd-17-4447-2024, 2024
Short summary
Short summary
We developed a new wind turbine wake model, the Simple Actuator Disc for Large Eddy Simulation (SADLES), integrated with the widely used Weather Research and Forecasting (WRF) model. WRF-SADLES accurately simulates wind turbine wakes at resolutions of a few dozen meters, aligning well with idealized simulations and observational measurements. This makes WRF-SADLES a promising tool for wind energy research, offering a balance between accuracy, computational efficiency, and ease of implementation.
Changliang Shao and Lars Nerger
Geosci. Model Dev., 17, 4433–4445, https://doi.org/10.5194/gmd-17-4433-2024, https://doi.org/10.5194/gmd-17-4433-2024, 2024
Short summary
Short summary
This paper introduces and evaluates WRF-PDAF, a fully online-coupled ensemble data assimilation (DA) system. A key advantage of the WRF-PDAF configuration is its ability to concurrently integrate all ensemble states, eliminating the need for time-consuming distribution and collection of ensembles during the coupling communication. The extra time required for DA amounts to only 20.6 % per cycle. Twin experiment results underscore the effectiveness of the WRF-PDAF system.
Jan Clemens, Lars Hoffmann, Bärbel Vogel, Sabine Grießbach, and Nicole Thomas
Geosci. Model Dev., 17, 4467–4493, https://doi.org/10.5194/gmd-17-4467-2024, https://doi.org/10.5194/gmd-17-4467-2024, 2024
Short summary
Short summary
Lagrangian transport models simulate the transport of air masses in the atmosphere. For example, one model (CLaMS) is well suited to calculating transport as it uses a special coordinate system and special vertical wind. However, it only runs inefficiently on modern supercomputers. Hence, we have implemented the benefits of CLaMS into a new model (MPTRAC), which is already highly efficient on modern supercomputers. Finally, in extensive tests, we showed that CLaMS and MPTRAC agree very well.
Manuel López-Puertas, Federico Fabiano, Victor Fomichev, Bernd Funke, and Daniel R. Marsh
Geosci. Model Dev., 17, 4401–4432, https://doi.org/10.5194/gmd-17-4401-2024, https://doi.org/10.5194/gmd-17-4401-2024, 2024
Short summary
Short summary
The radiative infrared cooling of CO2 in the middle atmosphere is crucial for computing its thermal structure. It requires one however to include non-local thermodynamic equilibrium processes which are computationally very expensive, which cannot be afforded by climate models. In this work, we present an updated, efficient, accurate and very fast (~50 µs) parameterization of that cooling able to cope with CO2 abundances from half the pre-industrial values to 10 times the current abundance.
Felix Wieser, Rolf Sander, Changmin Cho, Hendrik Fuchs, Thorsten Hohaus, Anna Novelli, Ralf Tillmann, and Domenico Taraborrelli
Geosci. Model Dev., 17, 4311–4330, https://doi.org/10.5194/gmd-17-4311-2024, https://doi.org/10.5194/gmd-17-4311-2024, 2024
Short summary
Short summary
The chemistry scheme of the atmospheric box model CAABA/MECCA is expanded to achieve an improved aerosol formation from emitted organic compounds. In addition to newly added reactions, temperature-dependent partitioning of all new species between the gas and aqueous phases is estimated and included in the pre-existing scheme. Sensitivity runs show an overestimation of key compounds from isoprene, which can be explained by a lack of aqueous-phase degradation reactions and box model limitations.
Zehua Bai, Qizhong Wu, Kai Cao, Yiming Sun, and Huaqiong Cheng
Geosci. Model Dev., 17, 4383–4399, https://doi.org/10.5194/gmd-17-4383-2024, https://doi.org/10.5194/gmd-17-4383-2024, 2024
Short summary
Short summary
There is relatively limited research on the application of scientific computing on RISC CPU platforms. The MIPS architecture CPUs, a type of RISC CPUs, have distinct advantages in energy efficiency and scalability. The air quality modeling system can run stably on the MIPS and LoongArch platforms, and the experiment results verify the stability of scientific computing on the platforms. The work provides a technical foundation for the scientific application based on MIPS and LoongArch.
Yafang Guo, Chayan Roychoudhury, Mohammad Amin Mirrezaei, Rajesh Kumar, Armin Sorooshian, and Avelino F. Arellano
Geosci. Model Dev., 17, 4331–4353, https://doi.org/10.5194/gmd-17-4331-2024, https://doi.org/10.5194/gmd-17-4331-2024, 2024
Short summary
Short summary
This research focuses on surface ozone (O3) pollution in Arizona, a historically air-quality-challenged arid and semi-arid region in the US. The unique characteristics of this kind of region, e.g., intense heat, minimal moisture, and persistent desert shrubs, play a vital role in comprehending O3 exceedances. Using the WRF-Chem model, we analyzed O3 levels in the pre-monsoon month, revealing the model's skill in capturing diurnal and MDA8 O3 levels.
Christoph Fischer, Andreas H. Fink, Elmar Schömer, Marc Rautenhaus, and Michael Riemer
Geosci. Model Dev., 17, 4213–4228, https://doi.org/10.5194/gmd-17-4213-2024, https://doi.org/10.5194/gmd-17-4213-2024, 2024
Short summary
Short summary
This study presents a method for identifying and tracking 3-D potential vorticity structures within African easterly waves (AEWs). Each identified structure is characterized by descriptors, including its 3-D position and orientation, which have been validated through composite comparisons. A trough-centric perspective on the descriptors reveals the evolution and distinct characteristics of AEWs. These descriptors serve as valuable statistical inputs for the study of AEW-related phenomena.
Sandro Vattioni, Andrea Stenke, Beiping Luo, Gabriel Chiodo, Timofei Sukhodolov, Elia Wunderlin, and Thomas Peter
Geosci. Model Dev., 17, 4181–4197, https://doi.org/10.5194/gmd-17-4181-2024, https://doi.org/10.5194/gmd-17-4181-2024, 2024
Short summary
Short summary
We investigate the sensitivity of aerosol size distributions in the presence of strong SO2 injections for climate interventions or after volcanic eruptions to the call sequence and frequency of the routines for nucleation and condensation in sectional aerosol models with operator splitting. Using the aerosol–chemistry–climate model SOCOL-AERv2, we show that the radiative and chemical outputs are sensitive to these settings at high H2SO4 supersaturations and how to obtain reliable results.
Najmeh Kaffashzadeh and Abbas-Ali Aliakbari Bidokhti
Geosci. Model Dev., 17, 4155–4179, https://doi.org/10.5194/gmd-17-4155-2024, https://doi.org/10.5194/gmd-17-4155-2024, 2024
Short summary
Short summary
This paper assesses the capability of two state-of-the-art global datasets in simulating surface ozone over Iran using a new methodology. It is found that the global model data need to be downscaled for regulatory purposes or policy applications at local scales. The method can be useful not only for the evaluation but also for the prediction of other chemical species, such as aerosols.
Franciscus Liqui Lung, Christian Jakob, A. Pier Siebesma, and Fredrik Jansson
Geosci. Model Dev., 17, 4053–4076, https://doi.org/10.5194/gmd-17-4053-2024, https://doi.org/10.5194/gmd-17-4053-2024, 2024
Short summary
Short summary
Traditionally, high-resolution atmospheric models employ periodic boundary conditions, which limit simulations to domains without horizontal variations. In this research open boundary conditions are developed to replace the periodic boundary conditions. The implementation is tested in a controlled setup, and the results show minimal disturbances. Using these boundary conditions, high-resolution models can be forced by a coarser model to study atmospheric phenomena in realistic background states.
Caroline Arnold, Shivani Sharma, Tobias Weigel, and David S. Greenberg
Geosci. Model Dev., 17, 4017–4029, https://doi.org/10.5194/gmd-17-4017-2024, https://doi.org/10.5194/gmd-17-4017-2024, 2024
Short summary
Short summary
In atmospheric models, rain formation is simplified to be computationally efficient. We trained a machine learning model, SuperdropNet, to emulate warm-rain formation based on super-droplet simulations. Here, we couple SuperdropNet with an atmospheric model in a warm-bubble experiment and find that the coupled simulation runs stable and produces reasonable results, making SuperdropNet a viable ML proxy for droplet simulations. We also present a comprehensive benchmark for coupling architectures.
Byoung-Joo Jung, Benjamin Ménétrier, Chris Snyder, Zhiquan Liu, Jonathan J. Guerrette, Junmei Ban, Ivette Hernández Baños, Yonggang G. Yu, and William C. Skamarock
Geosci. Model Dev., 17, 3879–3895, https://doi.org/10.5194/gmd-17-3879-2024, https://doi.org/10.5194/gmd-17-3879-2024, 2024
Short summary
Short summary
We describe the multivariate static background error covariance (B) for the JEDI-MPAS 3D-Var data assimilation system. With tuned B parameters, the multivariate B gives physically balanced analysis increment fields in the single-observation test framework. In the month-long cycling experiment with a global 60 km mesh, 3D-Var with static B performs stably. Due to its simple workflow and minimal computational requirements, JEDI-MPAS 3D-Var can be useful for the research community.
Michal Belda, Nina Benešová, Jaroslav Resler, Peter Huszár, Ondřej Vlček, Pavel Krč, Jan Karlický, Pavel Juruš, and Kryštof Eben
Geosci. Model Dev., 17, 3867–3878, https://doi.org/10.5194/gmd-17-3867-2024, https://doi.org/10.5194/gmd-17-3867-2024, 2024
Short summary
Short summary
For modeling atmospheric chemistry, it is necessary to provide data on emissions of pollutants. These can come from various sources and in various forms, and preprocessing of the data to be ingestible by chemistry models can be quite challenging. We developed the FUME processor to use a database layer that internally transforms all input data into a rigid structure, facilitating further processing to allow for emission processing from the continental to the street scale.
Bent Harnist, Seppo Pulkkinen, and Terhi Mäkinen
Geosci. Model Dev., 17, 3839–3866, https://doi.org/10.5194/gmd-17-3839-2024, https://doi.org/10.5194/gmd-17-3839-2024, 2024
Short summary
Short summary
Probabilistic precipitation nowcasting (local forecasting for 0–6 h) is crucial for reducing damage from events like flash floods. For this goal, we propose the DEUCE neural-network-based model which uses data and model uncertainties to generate an ensemble of potential precipitation development scenarios for the next hour. Trained and evaluated with Finnish precipitation composites, DEUCE was found to produce more skillful and reliable nowcasts than established models.
Emma Howard, Steven Woolnough, Nicholas Klingaman, Daniel Shipley, Claudio Sanchez, Simon C. Peatman, Cathryn E. Birch, and Adrian J. Matthews
Geosci. Model Dev., 17, 3815–3837, https://doi.org/10.5194/gmd-17-3815-2024, https://doi.org/10.5194/gmd-17-3815-2024, 2024
Short summary
Short summary
This paper describes a coupled atmosphere–mixed-layer ocean simulation setup that will be used to study weather processes in Southeast Asia. The set-up has been used to compare high-resolution simulations, which are able to partially resolve storms, to coarser simulations, which cannot. We compare the model performance at representing variability of rainfall and sea surface temperatures across length scales between the coarse and fine models.
Andrés Yarce Botero, Michiel van Weele, Arjo Segers, Pier Siebesma, and Henk Eskes
Geosci. Model Dev., 17, 3765–3781, https://doi.org/10.5194/gmd-17-3765-2024, https://doi.org/10.5194/gmd-17-3765-2024, 2024
Short summary
Short summary
HARMONIE WINS50 reanalysis data with 0.025° × 0.025° resolution from 2019 to 2021 were coupled with the LOTOS-EUROS Chemical Transport Model. HARMONIE and ECMWF meteorology configurations against Cabauw observations (52.0° N, 4.9° W) were evaluated as simulated NO2 concentrations with ground-level sensors. Differences in crucial meteorological input parameters (boundary layer height, vertical diffusion coefficient) between the hydrostatic and non-hydrostatic models were analysed.
Ulrich Voggenberger, Leopold Haimberger, Federico Ambrogi, and Paul Poli
Geosci. Model Dev., 17, 3783–3799, https://doi.org/10.5194/gmd-17-3783-2024, https://doi.org/10.5194/gmd-17-3783-2024, 2024
Short summary
Short summary
This paper presents a method for calculating balloon drift from historical radiosonde ascent data. The drift can reach distances of several hundred kilometres and is often neglected. Verification shows the beneficial impact of the more accurate balloon position on model assimilation. The method is not limited to radiosondes but would also work for dropsondes, ozonesondes, or any other in situ sonde carried by the wind in the pre-GNSS era, provided the necessary information is available.
Philippe Thunis, Jeroen Kuenen, Enrico Pisoni, Bertrand Bessagnet, Manjola Banja, Lech Gawuc, Karol Szymankiewicz, Diego Guizardi, Monica Crippa, Susana Lopez-Aparicio, Marc Guevara, Alexander De Meij, Sabine Schindlbacher, and Alain Clappier
Geosci. Model Dev., 17, 3631–3643, https://doi.org/10.5194/gmd-17-3631-2024, https://doi.org/10.5194/gmd-17-3631-2024, 2024
Short summary
Short summary
An ensemble emission inventory is created with the aim of monitoring the status and progress made with the development of EU-wide inventories. This emission ensemble serves as a common benchmark for the screening and allows for the comparison of more than two inventories at a time. Because the emission “truth” is unknown, the approach does not tell which inventory is the closest to reality, but it identifies inconsistencies that require special attention.
Laurent Menut, Bertrand Bessagnet, Arineh Cholakian, Guillaume Siour, Sylvain Mailler, and Romain Pennel
Geosci. Model Dev., 17, 3645–3665, https://doi.org/10.5194/gmd-17-3645-2024, https://doi.org/10.5194/gmd-17-3645-2024, 2024
Short summary
Short summary
This study is about the modelling of the atmospheric composition in Europe during the summer of 2022, when massive wildfires were observed. It is a sensitivity study dedicated to the relative impacts of two modelling processes that are able to modify the meteorology used for the calculation of the atmospheric chemistry and transport of pollutants.
Shuai Wang, Mengyuan Zhang, Yueqi Gao, Peng Wang, Qingyan Fu, and Hongliang Zhang
Geosci. Model Dev., 17, 3617–3629, https://doi.org/10.5194/gmd-17-3617-2024, https://doi.org/10.5194/gmd-17-3617-2024, 2024
Short summary
Short summary
Numerical models are widely used in air pollution modeling but suffer from significant biases. The machine learning model designed in this study shows high efficiency in identifying such biases. Meteorology (relative humidity and cloud cover), chemical composition (secondary organic components and dust aerosols), and emission sources (residential activities) are diagnosed as the main drivers of bias in modeling PM2.5, a typical air pollutant. The results will help to improve numerical models.
Shoma Yamanouchi, Shayamilla Mahagammulla Gamage, Sara Torbatian, Jad Zalzal, Laura Minet, Audrey Smargiassi, Ying Liu, Ling Liu, Forood Azargoshasbi, Jinwoong Kim, Youngseob Kim, Daniel Yazgi, and Marianne Hatzopoulou
Geosci. Model Dev., 17, 3579–3597, https://doi.org/10.5194/gmd-17-3579-2024, https://doi.org/10.5194/gmd-17-3579-2024, 2024
Short summary
Short summary
Air pollution is a major health hazard, and chemical transport models (CTMs) are valuable tools that aid in our understanding of the risks of air pollution at both local and regional scales. In this study, the Polair3D CTM of the Polyphemus air quality modeling platform was set up over Quebec, Canada, to assess the model’s capability in predicting key air pollutant species over the region, at seasonal temporal scales and at regional spatial scales.
Rohith Thundathil, Florian Zus, Galina Dick, and Jens Wickert
Geosci. Model Dev., 17, 3599–3616, https://doi.org/10.5194/gmd-17-3599-2024, https://doi.org/10.5194/gmd-17-3599-2024, 2024
Short summary
Short summary
Global Navigation Satellite Systems (GNSS) provides moisture observations through its densely distributed ground station network. In this research, we assimilate a new type of observation called tropospheric gradient observations, which has never been incorporated into a weather model. We develop a forward operator for gradient-based observations and conduct an assimilation impact study. The study shows significant improvements in the model's humidity fields.
Ankur Mahesh, Travis A. O'Brien, Burlen Loring, Abdelrahman Elbashandy, William Boos, and William D. Collins
Geosci. Model Dev., 17, 3533–3557, https://doi.org/10.5194/gmd-17-3533-2024, https://doi.org/10.5194/gmd-17-3533-2024, 2024
Short summary
Short summary
Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. We train convolutional neural networks (CNNs) to detect ARs with an estimate of the uncertainty. We present a framework to generalize these CNNs to a variety of datasets of past, present, and future climate. Using a simplified simulation of the Earth's atmosphere, we validate the CNNs. We explore the role of ARs in maintaining energy balance in the Earth system.
Alexandra Rivera, Kostas Tsigaridis, Gregory Faluvegi, and Drew Shindell
Geosci. Model Dev., 17, 3487–3505, https://doi.org/10.5194/gmd-17-3487-2024, https://doi.org/10.5194/gmd-17-3487-2024, 2024
Short summary
Short summary
This paper describes and evaluates an improvement to the representation of acetone in the GISS ModelE2.1 Earth system model. We simulate acetone's concentration and transport across the atmosphere as well as its dependence on chemistry, the ocean, and various global emissions. Comparisons of our model’s estimates to past modeling studies and field measurements have shown encouraging results. Ultimately, this paper contributes to a broader understanding of acetone's role in the atmosphere.
Alok K. Samantaray, Priscilla A. Mooney, and Carla A. Vivacqua
Geosci. Model Dev., 17, 3321–3339, https://doi.org/10.5194/gmd-17-3321-2024, https://doi.org/10.5194/gmd-17-3321-2024, 2024
Short summary
Short summary
Any interpretation of climate model data requires a comprehensive evaluation of the model performance. Numerous error metrics exist for this purpose, and each focuses on a specific aspect of the relationship between reference and model data. Thus, a comprehensive evaluation demands the use of multiple error metrics. However, this can lead to confusion. We propose a clustering technique to reduce the number of error metrics needed and a composite error metric to simplify the interpretation.
Richard Maier, Fabian Jakub, Claudia Emde, Mihail Manev, Aiko Voigt, and Bernhard Mayer
Geosci. Model Dev., 17, 3357–3383, https://doi.org/10.5194/gmd-17-3357-2024, https://doi.org/10.5194/gmd-17-3357-2024, 2024
Short summary
Short summary
Based on the TenStream solver, we present a new method to accelerate 3D radiative transfer towards the speed of currently used 1D solvers. Using a shallow-cumulus-cloud time series, we evaluate the performance of this new solver in terms of both speed and accuracy. Compared to a 3D benchmark simulation, we show that our new solver is able to determine much more accurate irradiances and heating rates than a 1D δ-Eddington solver, even when operated with a similar computational demand.
Julia Maillard, Jean-Christophe Raut, and François Ravetta
Geosci. Model Dev., 17, 3303–3320, https://doi.org/10.5194/gmd-17-3303-2024, https://doi.org/10.5194/gmd-17-3303-2024, 2024
Short summary
Short summary
Atmospheric models struggle to reproduce the strong temperature inversions in the vicinity of the surface over forested areas in the Arctic winter. In this paper, we develop modified simplified versions of surface layer schemes widely used by the community. Our modifications are used to correct the fact that original schemes place strong limits on the turbulent collapse, leading to a lower surface temperature gradient at low wind speeds. Modified versions show a better performance.
Jana Fischereit, Henrik Vedel, Xiaoli Guo Larsén, Natalie E. Theeuwes, Gregor Giebel, and Eigil Kaas
Geosci. Model Dev., 17, 2855–2875, https://doi.org/10.5194/gmd-17-2855-2024, https://doi.org/10.5194/gmd-17-2855-2024, 2024
Short summary
Short summary
Wind farms impact local wind and turbulence. To incorporate these effects in weather forecasting, the explicit wake parameterization (EWP) is added to the forecasting model HARMONIE–AROME. We evaluate EWP using flight data above and downstream of wind farms, comparing it with an alternative wind farm parameterization and another weather model. Results affirm the correct implementation of EWP, emphasizing the necessity of accounting for wind farm effects in accurate weather forecasting.
Clément Bouvier, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair
Geosci. Model Dev., 17, 2961–2986, https://doi.org/10.5194/gmd-17-2961-2024, https://doi.org/10.5194/gmd-17-2961-2024, 2024
Short summary
Short summary
An analytical initial background state has been developed for moist baroclinic wave simulation on an aquaplanet and implemented into OpenIFS. Seven parameters can be controlled, which are used to generate the background states and the development of baroclinic waves. The meteorological and numerical stability has been assessed. Resulting baroclinic waves have proven to be realistic and sensitive to the jet's width.
Jelena Radović, Michal Belda, Jaroslav Resler, Kryštof Eben, Martin Bureš, Jan Geletič, Pavel Krč, Hynek Řezníček, and Vladimír Fuka
Geosci. Model Dev., 17, 2901–2927, https://doi.org/10.5194/gmd-17-2901-2024, https://doi.org/10.5194/gmd-17-2901-2024, 2024
Short summary
Short summary
Boundary conditions are of crucial importance for numerical model (e.g., PALM) validation studies and have a large influence on the model results, especially when studying the atmosphere of real, complex, and densely built urban environments. Our experiments with different driving conditions for the large-eddy simulation model PALM show its strong dependency on boundary conditions, which is important for the proper separation of errors coming from the boundary conditions and the model itself.
Sonya L. Fiddes, Marc D. Mallet, Alain Protat, Matthew T. Woodhouse, Simon P. Alexander, and Kalli Furtado
Geosci. Model Dev., 17, 2641–2662, https://doi.org/10.5194/gmd-17-2641-2024, https://doi.org/10.5194/gmd-17-2641-2024, 2024
Short summary
Short summary
In this study we present an evaluation that considers complex, non-linear systems in a holistic manner. This study uses XGBoost, a machine learning algorithm, to predict the simulated Southern Ocean shortwave radiation bias in the ACCESS model using cloud property biases as predictors. We then used a novel feature importance analysis to quantify the role that each cloud bias plays in predicting the radiative bias, laying the foundation for advanced Earth system model evaluation and development.
Gaurav Govardhan, Sachin D. Ghude, Rajesh Kumar, Sumit Sharma, Preeti Gunwani, Chinmay Jena, Prafull Yadav, Shubhangi Ingle, Sreyashi Debnath, Pooja Pawar, Prodip Acharja, Rajmal Jat, Gayatry Kalita, Rupal Ambulkar, Santosh Kulkarni, Akshara Kaginalkar, Vijay K. Soni, Ravi S. Nanjundiah, and Madhavan Rajeevan
Geosci. Model Dev., 17, 2617–2640, https://doi.org/10.5194/gmd-17-2617-2024, https://doi.org/10.5194/gmd-17-2617-2024, 2024
Short summary
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
Simon Rosanka, Holger Tost, Rolf Sander, Patrick Jöckel, Astrid Kerkweg, and Domenico Taraborrelli
Geosci. Model Dev., 17, 2597–2615, https://doi.org/10.5194/gmd-17-2597-2024, https://doi.org/10.5194/gmd-17-2597-2024, 2024
Short summary
Short summary
The capabilities of the Modular Earth Submodel System (MESSy) are extended to account for non-equilibrium aqueous-phase chemistry in the representation of deliquescent aerosols. When applying the new development in a global simulation, we find that MESSy's bias in modelling routinely observed reduced inorganic aerosol mass concentrations, especially in the United States. Furthermore, the representation of fine-aerosol pH is particularly improved in the marine boundary layer.
Junyu Li, Yuxin Wang, Lilong Liu, Yibin Yao, Liangke Huang, and Feijuan Li
Geosci. Model Dev., 17, 2569–2581, https://doi.org/10.5194/gmd-17-2569-2024, https://doi.org/10.5194/gmd-17-2569-2024, 2024
Short summary
Short summary
In this study, we have developed a model (RF-PWV) to characterize precipitable water vapor (PWV) variation with altitude in the study area. RF-PWV can significantly reduce errors in vertical correction, enhance PWV fusion product accuracy, and provide insights into PWV vertical distribution, thereby contributing to climate research.
Rolf Sander
Geosci. Model Dev., 17, 2419–2425, https://doi.org/10.5194/gmd-17-2419-2024, https://doi.org/10.5194/gmd-17-2419-2024, 2024
Short summary
Short summary
The open-source software MEXPLORER 1.0.0 is presented here. The program can be used to analyze, reduce, and visualize complex chemical reaction mechanisms. The mathematics behind the tool is based on graph theory: chemical species are represented as vertices, and reactions as edges. MEXPLORER is a community model published under the GNU General Public License.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
EGUsphere, https://doi.org/10.22541/essoar.169903618.82717612/v2, https://doi.org/10.22541/essoar.169903618.82717612/v2, 2024
Short summary
Short summary
Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate of the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 2347–2358, https://doi.org/10.5194/gmd-17-2347-2024, https://doi.org/10.5194/gmd-17-2347-2024, 2024
Short summary
Short summary
In the last decades, weather forecasting up to 15 d into the future has been dominated by physics-based numerical models. Recently, deep learning models have challenged this paradigm. However, the latter models may struggle when forecasting weather extremes. In this article, we argue for deep learning models specifically designed to handle extreme events, and we propose a foundational framework to develop such models.
Stefan Rahimi, Lei Huang, Jesse Norris, Alex Hall, Naomi Goldenson, Will Krantz, Benjamin Bass, Chad Thackeray, Henry Lin, Di Chen, Eli Dennis, Ethan Collins, Zachary J. Lebo, Emily Slinskey, Sara Graves, Surabhi Biyani, Bowen Wang, Stephen Cropper, and the UCLA Center for Climate Science Team
Geosci. Model Dev., 17, 2265–2286, https://doi.org/10.5194/gmd-17-2265-2024, https://doi.org/10.5194/gmd-17-2265-2024, 2024
Short summary
Short summary
Here, we project future climate across the western United States through the end of the 21st century using a regional climate model, embedded within 16 latest-generation global climate models, to provide the community with a high-resolution physically based ensemble of climate data for use at local scales. Strengths and weaknesses of the data are frankly discussed as we overview the downscaled dataset.
Romain Pilon and Daniela I. V. Domeisen
Geosci. Model Dev., 17, 2247–2264, https://doi.org/10.5194/gmd-17-2247-2024, https://doi.org/10.5194/gmd-17-2247-2024, 2024
Short summary
Short summary
This paper introduces a new method for detecting atmospheric cloud bands to identify long convective cloud bands that extend from the tropics to the midlatitudes. The algorithm allows for easy use and enables researchers to study the life cycle and climatology of cloud bands and associated rainfall. This method provides insights into the large-scale processes involved in cloud band formation and their connections between different regions, as well as differences across ocean basins.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev., 17, 2053–2076, https://doi.org/10.5194/gmd-17-2053-2024, https://doi.org/10.5194/gmd-17-2053-2024, 2024
Short summary
Short summary
PyRTlib is an attractive educational tool because it provides a flexible and user-friendly way to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols, and hydrometeors). PyRTlib is a so-called radiative transfer model; these are commonly used to simulate and understand remote sensing observations from ground-based, airborne, or satellite instruments.
Kelly M. Núñez Ocasio and Zachary L. Moon
EGUsphere, https://doi.org/10.5194/egusphere-2024-259, https://doi.org/10.5194/egusphere-2024-259, 2024
Short summary
Short summary
TAMS is an open-source mesoscale convective system tracking and classifying Python-based package that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Cited articles
Blakeslee, R., Hall, J., Goodman, M., Parker, P., Freudinger, L., and He, M.: The Real Time Mission Monitor – A Situational Awareness Tool For Managing Experiment Assets, in: NASA Science and Technology Conference 2007, 19–21 June 2007, College Park, MD, 2007.
Browning, K. A.: Radar measurements of air motion near fronts, Weather, 26, 320–340, 1971.
Browning, K. A.: Conceptual models of precipitation systems, Weather Forecast., 1, 23–41, 1986.
Browning, K. A.: Organization of clouds and precipitation in extratropical cyclones, in: Extratropical Cyclones: The Erik Palmén Memorial Volume, edited by Newton, C. W. and Holopainen, E. O., 129–153, Amer. Meteor. Soc., 1990.
Browning, K. A. and Roberts, N. M.: Structure of a frontal cyclone, Q. J. Roy. Meteor. Soc., 120, 1535–1557, 1994.
Buizza, R., Bidlot, J.-R., Wedi, N., Fuentes, M., Hamrud, M., Holt, G., Palmer, T., and Vitart, F.: The ECMWF Variable Resolution Ensemble Prediction System VAREPS, ECMWF Newsletter, 108, 14–20, 2006.
Carlson, T. N.: Airflow through midlatitude cyclones and the comma cloud pattern, Mon. Weather Rev., 108, 1498–1509, 1980.
Ducrocq, V., Braud, I., Davolio, S., Ferretti, R., Flamant, C., Jansa, A., Kalthoff, N., Richard, E., Taupier-Letage, I., Ayral, P.-A., Belamari, S., Berne, A., Borga, M., Boudevillain, B., Bock, O., Boichard, J.-L., Bouin, M.-N., Bousquet, O., Bouvier, C., Chiggiato, J., Cimini, D., Corsmeier, U., Coppola, L., Cocquerez, P., Defer, E., Delanoë, J., Di Girolamo, P., Doerenbecher, A., Drobinski, P., Dufournet, Y., Fourrié, N., Gourley, J. J., Labatut, L., Lambert, D., Le Coz, J., Marzano, F. S., Molinié, G., Montani, A., Nord, G., Nuret, M., Ramage, K., Rison, W., Roussot, O., Said, F., Schwarzenboeck, A., Testor, P., Van Baelen, J., Vincendon, B., Aran, M., and Tamayo, J.: HyMeX-SOP1: The Field Campaign Dedicated to Heavy Precipitation and Flash Flooding in the Northwestern Mediterranean, Bull. Amer. Meteor. Soc., 95, 1083–1100, 2014.
Dyer, J. and Amburn, P.: Desktop Visualization of Meteorological Data Using Paraview, Kitware Source, 14, 7–10, 2010.
Eckhardt, S., Stohl, A., Wernli, H., James, P., Forster, C., and Spichtinger, N.: A 15-year climatology of warm conveyor belts, J. Climate, 17, 218–237, 2004.
Elsberry, R. L. and Harr, P. A.: Tropical cyclone structure (TCS08) field experiment science basis, observational platforms, and strategy, Asia-Pacific Journal of Atmospheric Sciences, 44, 209–231, 2008.
Flatøy, F., Hov, Ø., and Schlager, H.: Chemical forecasts used for measurement flight planning during POLINAT 2, Geophys. Res. Lett., 27, 951–958, 2000.
Gneiting, T. and Raftery, A. E.: Weather forecasting with ensemble methods, Science, 310, 248–249, 2005.
Grams, C. M., Wernli, H., Böttcher, M., Čampa, J., Corsmeier, U., Jones, S. C., Keller, J. H., Lenz, C.-J., and Wiegand, L.: The key role of diabatic processes in modifying the upper-tropospheric wave guide: a North Atlantic case-study, Q. J. Roy. Meteor. Soc., 137, 2174–2193, 2011.
Grotjahn, R. and Chervin, R. M.: Animated Graphics in Meteorological Research and Presentations, Bull. Amer. Meteor. Soc., 65, 1201–1208, 1984.
Harrold, T. W.: Mechanisms influencing the distribution of precipitation within baroclinic disturbances, Q. J. Roy. Meteor. Soc., 99, 232–251, 1973.
He, M., Goodman, H. M., Blakeslee, R., and Hall, J. M.: The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science, in: American Geophysical Union 2010 Fall Meeting, #IN31A-1279, San Francisco, CA, 13–17 December 2010.
Heizenrieder, D. and Haucke, S.: D}as meteorologische Visualisierungs- und Produktionssystem {NinJo, Promet, 35, 57–69, 2009.
Hibbard, W. L.: Computer-Generated Imagery for 4-D Meteorological Data, Bull. Amer. Meteor. Soc., 67, 1362–1369, 1986.
Hibbard, W. L.: Vis5D, Cave5D, and VisAD, in: The Visualization Handbook, edited byL Hansen, C. D. and Johnson, C., Chapt. 34, 673–688, Academic Press, 2005.
Hibbard, W. L., Santek, D., Uccellini, L., and Brill, K.: Application of the 4-D McIDAS to a Model Diagnostic Study of the Presidents' Day Cyclone, Bull. Amer. Meteor. Soc., 70, 1394–1403, 1989.
Koppert, H. J., Schröder, F., Hergenröther, E., Lux, M., and Trembilski, A.: 3D visualisation in daily operation at the DWD, in: Proceedings of the 6th ECMWF Workshop on Meteorological Operational Systems, 17–21 November 1997, Reading, England, 101–125, 1998.
Kuo, Y.-H., Reed, R. J., and Low-Nam, S.: Thermal Structure and Airflow in a Model Simulation of an Occluded Marine Cyclone, Mon. Weather Rev., 120, 2280–2297, 1992.
Leutbecher, M. and Palmer, T.: Ensemble forecasting, J. Comput. Phys., 227, 3515–3539, 2008.
Madonna, E., Wernli, H., Joos, H., and Martius, O.: Warm Conveyor Belts in the ERA-Interim Dataset (1979–2010). Part I: Climatology and potential vorticity evolution, J. Climate, 27, 3–26, 2014.
Mass, C. F. and Schultz, D. M.: The Structure and Evolution of a Simulated Midlatitude Cyclone over Land, Mon. Weather Rev., 121, 889–917, 1993.
McCaslin, P. T., McDonald, P. A., and Szoke, E. J.: 3D visualization development at NOAA forecast systems laboratory, ACM SIGGRAPH Comput. Graph., 34, 41–44, 2000.
Murray, D. and McWhirter, J.: Evolving IDV – creating better tools for the community, in: 23th Conference on International Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, 15–18 January 2007, San Antonio, TX, American Meteorological Society, 3B.5, 2007.
Norton, A. and Clyne, J.: The VAPOR Visualization Application, in: High Performance Visualization, edited by: Bethel, E. W., Childs, H., and Hansen, C., Chapt. 20, CRC Press, 415–428, 2012.
Pfahl, S., Madonna, E., Boettcher, M., Joos, H., and Wernli, H.: Warm conveyor belts in the ERA-interim dataset (1979–2010). Part II: Moisture origin and relevance for precipitation, J. Climate, 27, 27–40, 2014.
Pomroy, H. R. and Thorpe, A. J.: The evolution and dynamical role of reduced upper-tropospheric potential vorticity in intensive observing period one of FASTEX, Mon. Weather Rev., 128, 1817–1834, 2000.
Rautenhaus, M., Bauer, G., and Dörnbrack, A.: A web service based tool to plan atmospheric research flights, Geosci. Model Dev., 5, 55–71, https://doi.org/10.5194/gmd-5-55-2012, 2012.
Rautenhaus, M., Kern, M., Schäfler, A., and Westermann, R.: Three-dimensional visualization of ensemble weather forecasts – Part 1: The visualization tool Met.3D (version 1.0), Geosci. Model Dev., 8, 2329–2353, https://doi.org/10.5194/gmd-8-2329-2015, 2015.
Reed, R. J., Kuo, Y.-H., and Low-Nam, S.: An Adiabatic Simulation of the ERICA IOP 4 Storm: An Example of Quasi-Ideal Frontal Cyclone Development, Mon. Weather Rev., 122, 2688–2708, 1994.
Russell, I., Siemen, S., Ii, F., Kertész, S., Lamy-Thépaut, S., and Karhila, V.: Metview 4 – ECMWF's latest generation meteorological workstation, ECMWF Newslett., 126, 23–27, 2010.
Schäfler, A., Dörnbrack, A., Wernli, H., Kiemle, C., and Pfahl, S.: Airborne lidar observations in the inflow region of a warm conveyor belt, Q. J. Roy. Meteor. Soc., 137, 1257–1272, 2011.
Schäfler, A., Boettcher, M., Grams, C. M., Rautenhaus, M., Sodemann, H., and Wernli, H.: Planning aircraft measurements within a warm conveyor belt, Weather, 69, 161–166, 2014.
Schultz, D. M. and Mass, C. F.: The Occlusion Process in a Midlatitude Cyclone over Land, Mon. Weather Rev., 121, 918–940, 1993.
Spichtinger, P., Gierens, K., and Wernli, H.: A case study on the formation and evolution of ice supersaturation in the vicinity of a warm conveyor belt's outflow region, Atmos. Chem. Phys., 5, 973–987, https://doi.org/10.5194/acp-5-973-2005, 2005.
Sprenger, M. and Wernli, H.: The Lagrangian analysis tool LAGRANTO – version 2.0, Geosci. Model Dev. Discuss., 8, 1893–1943, https://doi.org/10.5194/gmdd-8-1893-2015, 2015.
Stohl, A.: A 1-year Lagrangian "climatology" of airstreams in the Northern Hemisphere troposphere and lowermost stratosphere, J. Geophys. Res., 106, 7263–7279, 2001.
Trafton, J. G. and Hoffman, R. R.: Computer-aided visualization in meteorology, in: Expertise Out of Context: Proceedings of the Sixth International Conference on Naturalistic Decision Making, edited by: Hoffman, R. R., Chapt. 15, Psychology Press, 337–357, 2007.
Treinish, L. A. and Rothfusz, L. P.: Three-dimensional visualization for support of operational forecasting at the 1996 Centennial Olympic Games, in: Proceedings of the 13th IIPS Conference, 2–7 February 1997, Long Beach, CA, 2–8, 1997.
Untch, A. and Hortal, M.: A finite-element scheme for the vertical discretization of the semi-Lagrangian version of the ECMWF forecast model, Q. J. Roy. Meteor. Soc., 130, 1505–1530, 2004.
Vaughan, G., Garland, W. E., Dewey, K. J., and Gerbig, C.: Aircraft measurements of a warm conveyor belt – a case study, J. Atmos. Chem., 46, 117–129, 2003.
Vaughan, G., Methven, J., Anderson, D., Antonescu, B., Baker, L., Baker, T. P., Ballard, S. P., Bower, K. N., Brown, P. R. A., Chagnon, J., Choularton, T. W., Chylik, J., Connolly, P. J., Cook, P. A., Cotton, R. J., Crosier, J., Dearden, C., Dorsey, J. R., Frame, T. H. A., Gallagher, M. W., Goodliff, M., Gray, S. L., Harvey, B. J., Knippertz, P., Lean, H. W., Li, D., Lloyd, G., Martínez–Alvarado, O., Nicol, J., Norris, J., Öström, E., Owen, J., Parker, D. J., Plant, R. S., Renfrew, I. A., Roberts, N. M., Rosenberg, P., Rudd, A. C., Schultz, D. M., Taylor, J. P., Trzeciak, T., Tubbs, R., Vance, A. K., van Leeuwen, P. J., Wellpott, A., and Woolley, A.: Cloud Banding and Winds in Intense European Cyclones: Results from the DIAMET Project, Bull. Amer. Meteor. Soc., 96, 249–265, 2015.
Wallace, J. M. and Hobbs, P. V.: Atmospheric Science: An Introductory Survey, Academic Press, 2nd Edn., Amsterdam, 2006.
Wernli, H.: A Lagrangian-based analysis of extratropical cyclones. II: A detailed case-study, Q. J. Roy. Meteor. Soc., 123, 1677–1706, 1997.
Wernli, H. and Davies, H. C.: A Lagrangian-based analysis of extratropical cyclones. I: The method and some applications, Q. J. Roy. Meteor. Soc., 123, 467–489, 1997.
Whitaker, J. S., Uccellini, L. W., and Brill, K. F.: A Model-Based Diagnostic Study of the Rapid Development Phase of the Presidents's Day Cyclone, Mon. Weather Rev., 116, 2337–2365, 1988.
Wilhelmson, R. B., Jewett, B. F., Shaw, C., Wicker, L. J., Arrott, M., Bushell, C. B., Bajuk, M., Thingvold, J., and Yost, J. B.: A Study of the Evolution of a Numerically Modeled Severe Storm, Int. J. High Perform. C., 4, 20–36, 1990.
Wulfmeyer, V., Behrendt, A., Bauer, H.-S., Kottmeier, C., Corsmeier, U., Blyth, A., Craig, G., Schumann, U., Hagen, M., Crewell, S., Di Girolamo, P., Flamant, C., Miller, M., Montani, A., Mobbs, S., Richard, E., Rotach, M. W., Arpagaus, M., Russchenberg, H., Schlüssel, P., König, M., Gärtner, V., Steinacker, R., Dorninger, M., Turner, D. D., Weckwerth, T., Hense, A., and Simmer, C.: RESEARCH CAMPAIGN: The Convective and Orographically Induced Precipitation Study, Bull. Am. Meteorol. Soc., 89, 1477–1486, 2008.
Short summary
This article presents the application of interactive 3D visualization of ensemble
weather predictions to forecasting warm conveyor belt situations during aircraft-based atmospheric research campaigns. A method to predict 3D probabilities of the spatial occurrence of WCBs is developed and integrated into the 3D visualization tool "Met.3D", introduced in the first part of this two-paper study. A case study demonstrates the use of 3D and uncertainty visualization for weather forecasting.
This article presents the application of interactive 3D visualization of ensemble
weather...
