Articles | Volume 14, issue 9
https://doi.org/10.5194/gmd-14-5435-2021
© Author(s) 2021. 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-14-5435-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
03 Sep 2021
Model description paper |
| 03 Sep 2021
| 03 Sep 2021
Mesoscale nesting interface of the PALM model system 6.0
Eckhard Kadasch
CORRESPONDING AUTHOR
Deutscher Wetterdienst, Offenbach, Germany
Matthias Sühring
Institute of Meteorology and Climatology, Leibniz University Hannover, Hanover, Germany
Tobias Gronemeier
Institute of Meteorology and Climatology, Leibniz University Hannover, Hanover, Germany
Siegfried Raasch
Institute of Meteorology and Climatology, Leibniz University Hannover, Hanover, Germany
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EGUsphere, https://doi.org/10.5194/egusphere-2024-1231, https://doi.org/10.5194/egusphere-2024-1231, 2024
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Detailed modeling of urban air quality in stable conditions represents a challenge. This study shows sensitivity of the LES model to meteorological boundary conditions and selected model parameters in a real urban environment in strongly stable conditions. The results show the crucial role of the precise boundary conditions for the comparability of the results with observations as well as the strongly increased sensitivity of the model to studied processes during such stable conditions.
Sreenath Paleri, Luise Wanner, Matthias Sühring, Ankur Desai, and Matthias Mauder
EGUsphere, https://doi.org/10.5194/egusphere-2023-1721, https://doi.org/10.5194/egusphere-2023-1721, 2023
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We present a description and evaluation of numerical simulations of field experiment days during the CHEESEHEAD19 field campaign, conducted over a heterogeneous forested domain in Northern Wisconsin, USA. Diurnal simulations, informed and constrained by field measurements for two days during the summer and autumn were performed. The model could simulate near surface time series and profiles of atmospheric state variables and fluxes that matched relatively well with observations.
Charlotte Rahlves, Frank Beyrich, and Siegfried Raasch
Atmos. Meas. Tech., 15, 2839–2856, https://doi.org/10.5194/amt-15-2839-2022, https://doi.org/10.5194/amt-15-2839-2022, 2022
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Lidars can measure the wind profile in the lower part of the atmosphere, provided that the wind field is horizontally uniform and does not change during the time of the measurement. These requirements are mostly not fulfilled in reality, and the lidar wind measurement will thus hold a certain error. We investigate different strategies for lidar wind profiling using a lidar simulator implemented in a numerical simulation of the wind field. Our findings can help to improve wind measurements.
Oliver Maas and Siegfried Raasch
Wind Energ. Sci., 7, 715–739, https://doi.org/10.5194/wes-7-715-2022, https://doi.org/10.5194/wes-7-715-2022, 2022
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In the future there will be very large wind farm clusters in the German Bight. This study investigates how the wind field is affected by these very large wind farms and how much energy can be extracted by the wind turbines. Very large wind farms do not only reduce the wind speed but can also cause a change in wind direction or temperature. The extractable energy per wind turbine is much smaller for large wind farms than for small wind farms due to the reduced wind speed inside the wind farms.
Mohamed H. Salim, Sebastian Schubert, Jaroslav Resler, Pavel Krč, Björn Maronga, Farah Kanani-Sühring, Matthias Sühring, and Christoph Schneider
Geosci. Model Dev., 15, 145–171, https://doi.org/10.5194/gmd-15-145-2022, https://doi.org/10.5194/gmd-15-145-2022, 2022
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Radiative transfer processes are the main energy transport mechanism in urban areas which influence the surface energy budget and drive local convection. We show here the importance of each process to help modellers decide on how much detail they should include in their models to parameterize radiative transfer in urban areas. We showed how the flow field may change in response to these processes and the essential processes needed to assure acceptable quality of the numerical simulations.
Stefan Metzger, David Durden, Sreenath Paleri, Matthias Sühring, Brian J. Butterworth, Christopher Florian, Matthias Mauder, David M. Plummer, Luise Wanner, Ke Xu, and Ankur R. Desai
Atmos. Meas. Tech., 14, 6929–6954, https://doi.org/10.5194/amt-14-6929-2021, https://doi.org/10.5194/amt-14-6929-2021, 2021
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The key points are the following. (i) Integrative observing system design can multiply the information gain of surface–atmosphere field measurements. (ii) Catalyzing numerical simulations and first-principles machine learning open up observing system simulation experiments to novel applications. (iii) Use cases include natural climate solutions, emission inventory validation, urban air quality, and industry leak detection.
Katrin Frieda Gehrke, Matthias Sühring, and Björn Maronga
Geosci. Model Dev., 14, 5307–5329, https://doi.org/10.5194/gmd-14-5307-2021, https://doi.org/10.5194/gmd-14-5307-2021, 2021
Jaroslav Resler, Kryštof Eben, Jan Geletič, Pavel Krč, Martin Rosecký, Matthias Sühring, Michal Belda, Vladimír Fuka, Tomáš Halenka, Peter Huszár, Jan Karlický, Nina Benešová, Jana Ďoubalová, Kateřina Honzáková, Josef Keder, Šárka Nápravníková, and Ondřej Vlček
Geosci. Model Dev., 14, 4797–4842, https://doi.org/10.5194/gmd-14-4797-2021, https://doi.org/10.5194/gmd-14-4797-2021, 2021
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We describe validation of the PALM model v6.0 against measurements collected during two observational campaigns in Dejvice, Prague. The study focuses on the evaluation of the newly developed or improved radiative and energy balance modules in PALM related to urban modelling. In addition to the energy-related quantities, it also evaluates air flow and air quality under street canyon conditions.
Michal Belda, Jaroslav Resler, Jan Geletič, Pavel Krč, Björn Maronga, Matthias Sühring, Mona Kurppa, Farah Kanani-Sühring, Vladimír Fuka, Kryštof Eben, Nina Benešová, and Mikko Auvinen
Geosci. Model Dev., 14, 4443–4464, https://doi.org/10.5194/gmd-14-4443-2021, https://doi.org/10.5194/gmd-14-4443-2021, 2021
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The analysis summarizes how sensitive the modelling of urban environment is to changes in physical parameters describing the city (e.g. reflectivity of surfaces) and to several heat island mitigation scenarios in a city quarter in Prague, Czech Republic. We used the large-eddy simulation modelling system PALM 6.0. Surface parameters connected to radiation show the highest sensitivity in this configuration. For heat island mitigation, urban vegetation is shown to be the most effective measure.
Jens Pfafferott, Sascha Rißmann, Matthias Sühring, Farah Kanani-Sühring, and Björn Maronga
Geosci. Model Dev., 14, 3511–3519, https://doi.org/10.5194/gmd-14-3511-2021, https://doi.org/10.5194/gmd-14-3511-2021, 2021
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The building model is integrated via an urban surface model into the urban climate model.
There is a strong interaction between the built environment and the urban climate.
According to the building energy concept, the energy demand results in a waste heat; this is directly transferred to the urban environment.
The impact of buildings on the urban climate is defined by different physical building parameters with different technical facilities for ventilation, heating and cooling.
Tobias Gronemeier, Kerstin Surm, Frank Harms, Bernd Leitl, Björn Maronga, and Siegfried Raasch
Geosci. Model Dev., 14, 3317–3333, https://doi.org/10.5194/gmd-14-3317-2021, https://doi.org/10.5194/gmd-14-3317-2021, 2021
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We demonstrate the capability of the PALM model system version 6.0 to simulate urban boundary layers. The studied situation includes a real-world building setup of the HafenCity area in Hamburg, Germany. We evaluate the simulation results against wind-tunnel measurements utilizing PALM's virtual measurement module. The comparison reveals an overall high agreement between simulation results and wind-tunnel measurements including mean wind speed and direction as well as turbulence statistics.
Antti Hellsten, Klaus Ketelsen, Matthias Sühring, Mikko Auvinen, Björn Maronga, Christoph Knigge, Fotios Barmpas, Georgios Tsegas, Nicolas Moussiopoulos, and Siegfried Raasch
Geosci. Model Dev., 14, 3185–3214, https://doi.org/10.5194/gmd-14-3185-2021, https://doi.org/10.5194/gmd-14-3185-2021, 2021
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Large-eddy simulation (LES) of the urban atmospheric boundary layer involves a large separation of turbulent scales, leading to prohibitive computational costs. An online LES–LES nesting scheme is implemented into the PALM model system 6.0 to overcome this problem. Test results show that the accuracy within the high-resolution nest domains approach the non-nested high-resolution reference results. The nesting can reduce the CPU by time up to 80 % compared to the fine-resolution reference runs.
Pavel Krč, Jaroslav Resler, Matthias Sühring, Sebastian Schubert, Mohamed H. Salim, and Vladimír Fuka
Geosci. Model Dev., 14, 3095–3120, https://doi.org/10.5194/gmd-14-3095-2021, https://doi.org/10.5194/gmd-14-3095-2021, 2021
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The adverse effects of an urban environment, e.g. heat stress and air pollution, pose a risk to health and well-being. Precise modelling of the urban climate is crucial to mitigate these effects. Conventional atmospheric models are inadequate for modelling the complex structures of the urban environment; in particular, they lack a 3-D model of radiation and its interaction with surfaces and the plant canopy. The new RTM simulates these processes within the PALM-4U urban climate model.
Basit Khan, Sabine Banzhaf, Edward C. Chan, Renate Forkel, Farah Kanani-Sühring, Klaus Ketelsen, Mona Kurppa, Björn Maronga, Matthias Mauder, Siegfried Raasch, Emmanuele Russo, Martijn Schaap, and Matthias Sühring
Geosci. Model Dev., 14, 1171–1193, https://doi.org/10.5194/gmd-14-1171-2021, https://doi.org/10.5194/gmd-14-1171-2021, 2021
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An atmospheric chemistry model has been implemented in the microscale PALM model system 6.0. This article provides a detailed description of the model, its structure, input requirements, various features and limitations. Several pre-compiled ready-to-use chemical mechanisms are included in the chemistry model code; however, users can also easily implement other mechanisms. A case study is presented to demonstrate the application of the new chemistry model in the urban environment.
Wieke Heldens, Cornelia Burmeister, Farah Kanani-Sühring, Björn Maronga, Dirk Pavlik, Matthias Sühring, Julian Zeidler, and Thomas Esch
Geosci. Model Dev., 13, 5833–5873, https://doi.org/10.5194/gmd-13-5833-2020, https://doi.org/10.5194/gmd-13-5833-2020, 2020
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For realistic microclimate simulations in urban areas with PALM 6.0, detailed description of surface types, buildings and vegetation is required. This paper shows how such input data sets can be derived with the example of three German cities. Various data sources are used, including remote sensing, municipal data collections and open data such as OpenStreetMap. The collection and preparation of input data sets is tedious. Future research aims therefore at semi-automated tools to support users.
Björn Maronga, Sabine Banzhaf, Cornelia Burmeister, Thomas Esch, Renate Forkel, Dominik Fröhlich, Vladimir Fuka, Katrin Frieda Gehrke, Jan Geletič, Sebastian Giersch, Tobias Gronemeier, Günter Groß, Wieke Heldens, Antti Hellsten, Fabian Hoffmann, Atsushi Inagaki, Eckhard Kadasch, Farah Kanani-Sühring, Klaus Ketelsen, Basit Ali Khan, Christoph Knigge, Helge Knoop, Pavel Krč, Mona Kurppa, Halim Maamari, Andreas Matzarakis, Matthias Mauder, Matthias Pallasch, Dirk Pavlik, Jens Pfafferott, Jaroslav Resler, Sascha Rissmann, Emmanuele Russo, Mohamed Salim, Michael Schrempf, Johannes Schwenkel, Gunther Seckmeyer, Sebastian Schubert, Matthias Sühring, Robert von Tils, Lukas Vollmer, Simon Ward, Björn Witha, Hauke Wurps, Julian Zeidler, and Siegfried Raasch
Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, https://doi.org/10.5194/gmd-13-1335-2020, 2020
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In this paper, we describe the PALM model system 6.0. PALM is a Fortran-based turbulence-resolving code and has been applied for studying a variety of atmospheric and oceanic boundary layers for about 20 years. The model is optimized for use on massively parallel computer architectures. During the last years, PALM has been significantly improved and now offers a variety of new components that are especially designed to simulate the urban atmosphere at building-resolving resolution.
Sadiq Huq, Frederik De Roo, Siegfried Raasch, and Matthias Mauder
Geosci. Model Dev., 12, 2523–2538, https://doi.org/10.5194/gmd-12-2523-2019, https://doi.org/10.5194/gmd-12-2523-2019, 2019
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To study turbulence in heterogeneous terrain, high-resolution LES is desired. However, the desired resolution is often restricted by computational constraints. We present a two-way interactive vertical grid nesting technique that enables high-resolution LES of the surface layer. By employing a finer grid only close to the surface layer, the total computational memory requirement is reduced. We demonstrate the accuracy and performance of the method for a convective boundary layer simulation.
Johannes Schwenkel, Fabian Hoffmann, and Siegfried Raasch
Geosci. Model Dev., 11, 3929–3944, https://doi.org/10.5194/gmd-11-3929-2018, https://doi.org/10.5194/gmd-11-3929-2018, 2018
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Lagrangian cloud models are a powerful tool to understand cloud microphysics and are increasingly used in the cloud physics community. In this study we present a method designed to improve the warm cloud precipitation process in such models. Our results indicate that using this method is essential for a proper representation of the collisional process of warm clouds, while maintaining an appropriate computational demand.
Rieke Heinze, Christopher Moseley, Lennart Nils Böske, Shravan Kumar Muppa, Vera Maurer, Siegfried Raasch, and Bjorn Stevens
Atmos. Chem. Phys., 17, 7083–7109, https://doi.org/10.5194/acp-17-7083-2017, https://doi.org/10.5194/acp-17-7083-2017, 2017
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High-resolution multi-week simulations of a measurement campaign are evaluated with respect to mean boundary layer quantities and turbulence statistics. Two models are used in a semi-idealized setup through forcing, with output from a coarser-scale model to account for the larger-scale conditions. The boundary layer depth is in principal agreement with observations. Turbulence statistics like variance profiles agree satisfactorily with measurements.
B. Maronga, M. Gryschka, R. Heinze, F. Hoffmann, F. Kanani-Sühring, M. Keck, K. Ketelsen, M. O. Letzel, M. Sühring, and S. Raasch
Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, https://doi.org/10.5194/gmd-8-2515-2015, 2015
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The paper gives a detailed description of the PArallelized Large-eddy simulation Model (PALM) version 4.0 for the simulation of turbulent atmospheric and oceanic boundary layer flows. The model is optimized for use on massively parallel computer architectures and has been applied for various boundary-layer research studies over the last 15 years by various work groups all over the world. Besides the model description, we outline past PALM applications and also discuss future perspectives.
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-68, https://doi.org/10.5194/gmd-2024-68, 2024
Revised manuscript accepted for GMD
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The equation terms in the governing equations that are sensitive (insensitive) to the precision level have been identified. The performance of mixed-precision computing for weather and climate simulations was analyzed.
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
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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
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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
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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
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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.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-195, https://doi.org/10.5194/gmd-2023-195, 2024
Revised manuscript accepted for GMD
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The satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator highlighting its added value through a case study and diagnostics.
Cited articles
André, J. C., De Moor, G., Lacarrère, P., and du Vachat, R.: Modeling the
24-Hour Evolution of the Mean and Turbulent Structures of the Planetary
Boundary Layer, J. Atmos. Sci., 35, 1861–1883,
https://doi.org/10.1175/1520-0469(1978)035<1861:MTHEOT>2.0.CO;2, 1978. a
Baldauf, M., Seifert, A., Förstner, J., Majewski, D., Raschendorfer, M., and
Reinhardt, T.: Operational Convective-Scale Numerical Weather Prediction with
the COSMO Model: Description and Sensitivities, Mon. Weather Rev., 139,
3887–3905, https://doi.org/10.1175/MWR-D-10-05013.1, 2011. a, b, c, d
Baldauf, M., Förstner, J., Klink, S., Reinhardt, T., Schraff, C., Seifert, A., and Stephan, K.: Kurze Beschreibung des Lokal-Modells Kürzestfrist COSMO-DE (LMK) und seiner Datenbanken auf dem Datenserver des DWD, Tech. rep., Deutscher Wetterdienst, available at:
https://www.dwd.de/SharedDocs/downloads/DE/modelldokumentationen/nwv/cosmo_de/cosmo_de_dbbeschr_version_2_3_201406.pdf?__blob=publicationFile&v=5 (last access: 13 August 2021),
version 2.3, 2014. a, b, c
Baldauf, M., Gebhardt, C., Theis, S., Ritter, B., and Schraff, C.: Beschreibung des operationellen Kürzesfristvorhersagemodells COSMO-D2 und
COSMO-D2-EPS und seiner Ausgabe in die Datenbanken des DWD, Tech. rep., Deutscher Wetterdienst, available at:
https://www.dwd.de/SharedDocs/downloads/DE/modelldokumentationen/nwv/cosmo_d2/cosmo_d2_dbbeschr_version_1_0_201805.pdf?__blob=publicationFile&v=3 (last access: 13 August 2021),
version 1.0, 2018. a, b
Ching, J., Rotunno, R., LeMone, M., Martilli, A., Kosovic, B., Jimenez, P. A.,
and Dudhia, J.: Convectively Induced Secondary Circulations in Fine-Grid
Mesoscale Numerical Weather Prediction Models, Mon. Weather Rev., 142,
3284–3302, https://doi.org/10.1175/MWR-D-13-00318.1, 2014. a, b
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J.,
Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative
transfer modeling: A summary of the AER codes, Short Communication, J. Quant. Spectrosc. Ra., 91, 233–244, 2005. a
Davies, H. C. and Turner, R. E.: Updating prediction models by dynamical
relaxation: an examination of the technique, Q. J. Roy. Meteor. Soc., 103, 225–245,
https://doi.org/10.1002/qj.49710343602, 1977. a
Emes, M. J., Arjomandi, M., Kelso, R. M., and Ghanadi, F.: Turbulence length
scales in a low-roughness near-neutral atmospheric surface layer, J. Turbul., 20, 545–562, https://doi.org/10.1080/14685248.2019.1677908, 2019. a
Flay, R. and Stevenson, D.: Integral length scales in strong winds below 20 m,
J. Wind Eng. Ind. Aerod., 28, 21–30,
https://doi.org/10.1016/0167-6105(88)90098-0, 1988. a
Gehrke, K. F., Sühring, M., and Maronga, B.: Modeling of land-surface interactions in the PALM model system 6.0: Land surface model description, first evaluation, and sensitivity to model parameters, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-197, in review, 2020. a
Gronemeier, T., Inagaki, A., Gryschka, M., and Kanda, M.: Large-eddy simulation
of an urban canopy using a synthetic turbulence inflow generation method,
Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering),
71, I_43–I_48, https://doi.org/10.2208/jscejhe.71.I_43, 2015. a
Gronemeier, T., Raasch, S., and Ng, E.: Effects of Unstable Stratification on
Ventilation in Hong Kong, Atmosphere, 8, 168, https://doi.org/10.3390/atmos8090168, 2017. a
Gryning, S., Holtslag, A., Irwin, J., and Sivertsen, B.: Applied dispersion
modelling based on meteorological scaling parameters, Atmos. Environ., 21, 79–89, https://doi.org/10.1016/0004-6981(87)90273-3, 1987. a, b
Heinze, R., Moseley, C., Böske, L. N., Muppa, S. K., Maurer, V., Raasch, S., and Stevens, B.: Evaluation of large-eddy simulations forced with mesoscale model output for a multi-week period during a measurement campaign, Atmos. Chem. Phys., 17, 7083–7109, https://doi.org/10.5194/acp-17-7083-2017, 2017. a, b, c, d, e
Hellsten, A., Ketelsen, K., Sühring, M., Auvinen, M., Maronga, B., Knigge, C.,
Barmpas, F., Tsegas, G., Moussiopoulos, N., and Raasch, S.: A nested
multi-scale system implemented in the large-eddy simulation model PALM model
system 6.0, Geosci. Model Dev., 14, 3185–3214, https://doi.org/10.5194/gmd-14-3185-2021, 2021. a, b, c, d
Holtslag, A. A. M. and Boville, B. A.: Local Versus Nonlocal Boundary-Layer
Diffusion in a Global Climate Model, J. Climate, 6, 1825–1842,
https://doi.org/10.1175/1520-0442(1993)006<1825:LVNBLD>2.0.CO;2, 1993. a
Honnert, R., Masson, V., and Couvreux, F.: A Diagnostic for Evaluating the
Representation of Turbulence in Atmospheric Models at the Kilometric Scale,
J. Atmos. Sci., 68, 3112–3131,
https://doi.org/10.1175/JAS-D-11-061.1, 2011. a
Jähn, M., Muñoz-Esparza, D., Chouza, F., Reitebuch, O., Knoth, O., Haarig, M., and Ansmann, A.: Investigations of boundary layer structure, cloud characteristics and vertical mixing of aerosols at Barbados with large eddy simulations, Atmos. Chem. Phys., 16, 651–674, https://doi.org/10.5194/acp-16-651-2016, 2016. a
Jiang, P., Wen, Z., Sha, W., and Chen, G.: Interaction between turbulent flow
and sea breeze front over urban-like coast in large-eddy simulation, J. Geophys. Res.-Atmos., 122, 5298–5315,
https://doi.org/10.1002/2016JD026247, 2017. a
Kadasch, E.: INIFOR [code], available at: https://palm.muk.uni-hannover.de/trac/browser/palm/trunk/ UTIL/inifor, last access: 13 August 2021. a
Kadasch, E. and Sühring, M.: Supplementary material to “Mesoscale nesting interface of the PALM model system 6.0”, Leibniz Universität Hannover [data set], https://doi.org/10.25835/0084787, 2020. a
Kataoka, H. and Mizuno, M.: Numerical flow computation around aeroelastic 3D
square cylinder using inflow turbulence, Wind Struct., 5, 379–392,
https://doi.org/10.12989/WAS.2002.5.2_3_4.379, 2002. a, b
Kim, Y., Castro, I. P., and Xie, Z.-T.: Divergence-free turbulence inflow
conditions for large-eddy simulations with incompressible flow solvers,
Comput. Fluids, 84, 56–68,
https://doi.org/10.1016/j.compfluid.2013.06.001, 2013. a
Klein, M., Sadiki, A., and Janicka, J.: A digital filter based generation of
inflow data for spatially developing direct numerical or large eddy
simulations, J. Comput. Phys., 186, 652–665,
https://doi.org/10.1016/S0021-9991(03)00090-1, 2003. a
Lee, G.-J., Muñoz-Esparza, D., Yi, C., and Choe, H. J.: Application of the
Cell Perturbation Method to Large-Eddy Simulations of a Real Urban Area,
J. Appl. Meteorol. Clim., 58, 1125–1139,
https://doi.org/10.1175/JAMC-D-18-0185.1, 2019. a, b
Letzel, M. O., Helmke, C., Ng, E., An, X., Lai, A., and Raasch, S.: LES case
study on pedestrian level ventilation in two neighbourhoods in Hong Kong,
Meteorol. Z. 21, 575–589, https://doi.org/10.1127/0941-2948/2012/0356,
2012. a
Li, S., Hu, Z., Chan, P., and Hu, G.: A study on the profile of the turbulence
length scale in the near-neutral atmospheric boundary for sea (homogeneous)
and hilly land (inhomogeneous) fetches, J. Wind Eng. Ind. Aerod., 168, 200–210,
https://doi.org/10.1016/j.jweia.2017.06.008, 2017. a
Lund, T. S., Wu, X., and Squires, K. D.: Generation of Turbulent Inflow Data
for Spatially-Developing Boundary Layer Simulations, J. Comput. Phys., 140, 233–258, https://doi.org/10.1006/jcph.1998.5882, 1998. a
Maronga, B. and Raasch, S.: Large-Eddy Simulations of Surface Heterogeneity
Effects on the Convective Boundary Layer During the LITFASS-2003 Experiment,
Bound.-Lay. Meteorol., 146, 17–44, https://doi.org/10.1007/s10546-012-9748-z,
2013. a
Maronga, B., Gryschka, M., Heinze, R., Hoffmann, F., Kanani-Sühring, F.,
Keck, M., Ketelsen, K., Letzel, M. O., Sühring, M., and Raasch, S.: The
Parallelized Large-Eddy Simulation Model (PALM) version 4.0 for atmospheric
and oceanic flows: model formulation, recent developments, and future
perspectives, Geosci. Model Dev., 8, 2515–2551, https://doi.org/10.5194/gmd-8-2515-2015, 2015. a, b
Maronga, B., Banzhaf, S., Burmeister, C., Esch, T., Forkel, R., Fröhlich, D., Fuka, V., Gehrke, K. F., Geletič, J., Giersch, S., Gronemeier, T., Groß, G., Heldens, W., Hellsten, A., Hoffmann, F., Inagaki, A., Kadasch, E., Kanani-Sühring, F., Ketelsen, K., Khan, B. A., Knigge, C., Knoop, H., Krč, P., Kurppa, M., Maamari, H., Matzarakis, A., Mauder, M., Pallasch, M., Pavlik, D., Pfafferott, J., Resler, J., Rissmann, S., Russo, E., Salim, M., Schrempf, M., Schwenkel, J., Seckmeyer, G., Schubert, S., Sühring, M., von Tils, R., Vollmer, L., Ward, S., Witha, B., Wurps, H., Zeidler, J., and Raasch, S.: Overview of the PALM model system 6.0, Geosci. Model Dev., 13, 1335–1372, https://doi.org/10.5194/gmd-13-1335-2020, 2020. a, b, c, d, e, f, g
Mazzaro, L. J., Koo, E., Muñoz-Esparza, D., Lundquist, J. K., and Linn, R. R.:
Random Force Perturbations: A New Extension of the Cell Perturbation Method
for Turbulence Generation in Multiscale Atmospheric Boundary Layer
Simulations, J. Adv. Model. Earth Sy., 11, 2311–2329,
https://doi.org/10.1029/2019MS001608, 2019. a, b, c
Mirocha, J., Kosović, B., and Kirkil, G.: Resolved Turbulence Characteristics
in Large-Eddy Simulations Nested within Mesoscale Simulations Using the
Weather Research and Forecasting Model, Mon. Weather Rev., 142,
806–831, https://doi.org/10.1175/MWR-D-13-00064.1, 2014. a, b, c, d
Moeng, C.-H. and Rotunno, R.: Vertical-Velocity Skewness in the Buoyancy-Driven
Boundary Layer, J. Atmos. Sci., 47, 1149–1162,
https://doi.org/10.1175/1520-0469(1990)047<1149:VVSITB>2.0.CO;2, 1990. a
Mordant, N., Metz, P., Michel, O., and Pinton, J.-F.: Measurement of Lagrangian
Velocity in Fully Developed Turbulence, Phys. Rev. Lett., 87, 214501,
https://doi.org/10.1103/PhysRevLett.87.214501, 2001. a
Munters, W., Meneveau, C., and Meyers, J.: Shifted periodic boundary conditions
for simulations of wall-bounded turbulent flows, Phys. Fluids, 28,
025112, https://doi.org/10.1063/1.4941912, 2016. a, b
Muñoz-Esparza, D., Kosović, B., Mirocha, J., and van Beeck, J.: Bridging
the Transition from Mesoscale to Microscale Turbulence in Numerical Weather
Prediction Models, Bound.-Lay. Meteorol., 153, 409–440,
https://doi.org/10.1007/s10546-014-9956-9, 2014. a
Muñoz-Esparza, D., Kosović, B., van Beeck, J., and Mirocha, J.: A stochastic
perturbation method to generate inflow turbulence in large-eddy simulation
models: Application to neutrally stratified atmospheric boundary layers,
Phys. Fluids, 27, 035102, https://doi.org/10.1063/1.4913572, 2015. a, b
Muñoz-Esparza, D., Lundquist, J. K., Sauer, J. A., Kosović, B., and
Linn, R. R.: Coupled mesoscale-LES modeling of a diurnal cycle during the
CWEX-13 field campaign: From weather to boundary-layer eddies, J. Adv. Model. Earth Sy., 9, 1572–1594, https://doi.org/10.1002/2017MS000960, 2017. a, b, c
PALM: The PALM model system web pages [code], available at: http://palm-model.org, last access: 13 August 2021. a
Park, S.-B., Baik, J.-J., and Lee, S.-H.: Impacts of Mesoscale Wind on
Turbulent Flow and Ventilation in a Densely Built-up Urban Area, J. Appl. Meteorol. Clim., 54, 811–824,
https://doi.org/10.1175/JAMC-D-14-0044.1, 2015. a
Reinert, D., Prill, F., Frank, H., Denhard, M., Baldauf, M., Schraff, C., Gebhardt, C., Marsigli, C., and Zängl, G.: DWD Database Reference for the
Global and Regional ICON and ICON-EPS Forecasting System, Tech. rep., Deutscher Wetterdienst, available at:
https://www.dwd.de/DWD/forschung/nwv/fepub/icon_database_main.pdf,
version 2.1.1, last access: 6 June 2020. a, b
Salesky, S. T., Katul, G. G., and Chamecki, M.: Buoyancy effects on the
integral lengthscales and mean velocity profile in atmospheric surface layer
flows, Phys. Fluids, 25, 105101, https://doi.org/10.1063/1.4823747, 2013. a
Schalkwijk, J., Jonker, H. J. J., Siebesma, A. P., and Van Meijgaard, E.: Weather Forecasting Using GPU-Based Large-Eddy Simulations, B. Am. Meteorol. Soc., 96, 715–723,
https://doi.org/10.1175/BAMS-D-14-00114.1, 2015. a, b
Scherer, D., Antretter, F., Bender, S., Cortekar, J., Emeis, S.,
Fehrenbach, U., Gross, G., Halbig, G., Hasse, J., Maronga, B., Raasch, S., and
Scherber, K.: Urban Climate Under Change [UC]2 – A National Research Programme for
Developing a Building-Resolving Atmospheric Model for Entire City Regions,
Meteorol. Z. 28, 95–104, https://doi.org/10.1127/metz/2019/0913, 2019. a
Shin, H. H. and Dudhia, J.: Evaluation of PBL Parameterizations in WRF at
Subkilometer Grid Spacings: Turbulence Statistics in the Dry Convective
Boundary Layer, Mon. Weather Rev., 144, 1161–1177,
https://doi.org/10.1175/MWR-D-15-0208.1, 2016. a, b
Skamarock, W. C., Klemp, J. B., Dudhia, J., Gill, D. O., Barker, D., Duda, M. G., Huang, X., Wang, W., and Powers, J. G.: A Description of the Advanced
Research WRF Version 3 (No. NCAR/TN-475+STR), Tech. rep., University
Corporation for Atmospheric Research, https://doi.org/10.5065/D68S4MVH, 2008. a, b
Tennekes, H. and Lumley, J.: A first course in turbulence, The MIT Press, Cambridge, Mass.,
1972. a
Troen, I. B. and Mahrt, L.: A simple model of the atmospheric boundary layer;
sensitivity to surface evaporation, Bound.-Lay. Meteorol., 37, 129–148,
https://doi.org/10.1007/BF00122760, 1986. a
Wan, H., Giorgetta, M. A., Zängl, G., Restelli, M., Majewski, D., Bonaventura, L., Fröhlich, K., Reinert, D., Rípodas, P., Kornblueh, L., and Förstner, J.: The ICON-1.2 hydrostatic atmospheric dynamical core on triangular grids Part 1: Formulation and performance of the baseline version, Geosci. Model Dev., 6, 735–763, https://doi.org/10.5194/gmd-6-735-2013, 2013. a
Wicker, L. J. and Skamarock, W. C.: Time-Splitting Methods for Elastic Models
Using Forward Time Schemes, Mon. Weather Rev., 130, 2088–2097,
https://doi.org/10.1175/1520-0493(2002)130<2088:TSMFEM>2.0.CO;2,
2002. a
Williamson, J. H.: Low-storage Runge-Kutta schemes, J. Comput. Phys., 35, 48–56, https://doi.org/10.1016/0021-9991(80)90033-9,
1980. a
Willis, G. E. and Deardorff, J. W.: A laboratory model of diffusion into the
convective planetary boundary layer, Q. J. Roy. Meteor. Soc., 102, 427–445, https://doi.org/10.1002/qj.49710243212, 1976. a
Wu, X.: Inflow Turbulence Generation Methods, Annu. Rev. Fluid Mech., 49, 23–49, https://doi.org/10.1146/annurev-fluid-010816-060322, 2017. a
Wyngaard, J. C.: Toward Numerical Modeling in the “Terra Incognita”,
J. Atmos. Sci., 61, 1816–1826,
https://doi.org/10.1175/1520-0469(2004)061<1816:TNMITT>2.0.CO;2, 2004. a
Zhong, J., Cai, X., and Xie, Z.-T.: Implementation of a synthetic inflow turbulence generator in idealised WRF v3.6.1 large eddy simulations under neutral atmospheric conditions, Geosci. Model Dev., 14, 323–336, https://doi.org/10.5194/gmd-14-323-2021, 2021. a
Zhou, B., Simon, J. S., and Chow, F. K.: The Convective Boundary Layer in the
Terra Incognita, J. Atmos. Sci., 71, 2545–2563,
https://doi.org/10.1175/JAS-D-13-0356.1, 2014.
a, b
Zängl, G., Reinert, D., Rípodas, P., and Baldauf, M.: The ICON (ICOsahedral
Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the
non-hydrostatic dynamical core, Q. J. Roy. Meteor. Soc., 141, 563–579, https://doi.org/10.1002/qj.2378, 2015. a, b
Short summary
In this paper, we provide a technical description of a newly developed interface for coupling the PALM model system 6.0 to the weather prediction model COSMO. The interface allows users of PALM to simulate the detailed atmospheric flow for relatively small regions of tens of kilometres under specific weather conditions, for instance, periods around observation campaigns or extreme weather situations. We demonstrate the interface using a benchmark simulation.
In this paper, we provide a technical description of a newly developed interface for coupling...
