Articles | Volume 14, issue 2
https://doi.org/10.5194/gmd-14-1171-2021
© 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-14-1171-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany
Sabine Banzhaf
Freie Universität Berlin (FUB), Institute of Meteorology, TrUmF, Berlin, Germany
Edward C. Chan
Freie Universität Berlin (FUB), Institute of Meteorology, TrUmF, Berlin, Germany
Institute for Advanced Sustainability Studies (IASS), Potsdam, Germany
Renate Forkel
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany
Farah Kanani-Sühring
Leibniz University Hannover (LUH), Institute of Meteorology and Climatology, Hannover, Germany
Harz Energie GmbH & Co. KG, Goslar, Germany
Klaus Ketelsen
Independent Software Consultant, Hannover, Germany
Mona Kurppa
University of Helsinki, Helsinki, Finland
Björn Maronga
Leibniz University Hannover (LUH), Institute of Meteorology and Climatology, Hannover, Germany
University of Bergen, Geophysical Institute, Bergen, Norway
Matthias Mauder
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, 82467 Garmisch-Partenkirchen, Germany
Siegfried Raasch
Leibniz University Hannover (LUH), Institute of Meteorology and Climatology, Hannover, Germany
Emmanuele Russo
Freie Universität Berlin (FUB), Institute of Meteorology, TrUmF, Berlin, Germany
Climate and Environmental Physics, Physics Institute, University of Bern, Sidlerstrasse 5, 3012, Bern, Switzerland
Oeschger Centre for Climate Change Research, University of Bern, Hochschulstrasse 4, 3012 Bern, Switzerland
Martijn Schaap
Freie Universität Berlin (FUB), Institute of Meteorology, TrUmF, Berlin, Germany
Matthias Sühring
Leibniz University Hannover (LUH), Institute of Meteorology and Climatology, Hannover, Germany
Related authors
Hengheng Zhang, Wei Huang, Xiaoli Shen, Ramakrishna Ramisetty, Junwei Song, Olga Kiseleva, Christopher Claus Holst, Basit Khan, Thomas Leisner, and Harald Saathoff
Atmos. Chem. Phys., 24, 10617–10637, https://doi.org/10.5194/acp-24-10617-2024, https://doi.org/10.5194/acp-24-10617-2024, 2024
Short summary
Short summary
Our study unravels how stagnant winter conditions elevate aerosol levels in Stuttgart. Cloud cover at night plays a pivotal role, impacting morning air quality. Validating a key model, our findings aid accurate air quality predictions, crucial for effective pollution mitigation in urban areas.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
Short summary
Short summary
GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Dongqi Lin, Marwan Katurji, Laura E. Revell, Basit Khan, and Andrew Sturman
Atmos. Chem. Phys., 23, 14451–14479, https://doi.org/10.5194/acp-23-14451-2023, https://doi.org/10.5194/acp-23-14451-2023, 2023
Short summary
Short summary
Accurate fog forecasting is difficult in a complex environment. Spatial variations in soil moisture could impact fog. Here, we carried out fog simulations with spatially different soil moisture in complex topography. The soil moisture was calculated using satellite observations. The results show that the spatial variations in soil moisture do not have a significant impact on where fog occurs but do impact how long fog lasts. This finding could improve fog forecasts in the future.
Dongqi Lin, Basit Khan, Marwan Katurji, Leroy Bird, Ricardo Faria, and Laura E. Revell
Geosci. Model Dev., 14, 2503–2524, https://doi.org/10.5194/gmd-14-2503-2021, https://doi.org/10.5194/gmd-14-2503-2021, 2021
Short summary
Short summary
We present an open-source toolbox WRF4PALM, which enables weather dynamics simulation within urban landscapes. WRF4PALM passes meteorological information from the popular Weather Research and Forecasting (WRF) model to the turbulence-resolving PALM model system 6.0. WRF4PALM can potentially extend the use of WRF and PALM with realistic boundary conditions to any part of the world. WRF4PALM will help study air pollution dispersion, wind energy prospecting, and high-impact wind forecasting.
Sasu Karttunen, Matthias Sühring, Ewan O'Connor, and Leena Järvi
Geosci. Model Dev., 18, 5725–5757, https://doi.org/10.5194/gmd-18-5725-2025, https://doi.org/10.5194/gmd-18-5725-2025, 2025
Short summary
Short summary
This paper presents PALM-SLUrb, a single-layer urban canopy model for the PALM model system, designed to simulate urban–atmosphere interactions without resolving flow around individual buildings. The model is described in detail and evaluated against grid-resolved urban canopy simulations, demonstrating its ability to model urban surfaces accurately. By bridging the gap between computational efficiency and physical detail, PALM-SLUrb broadens PALM's potential for urban climate research.
Rico Kronenberg, Ivan Vorobevskii, Thi Thanh Luong, Uwe Spank, Dongkyun Kim, and Matthias Mauder
EGUsphere, https://doi.org/10.5194/egusphere-2025-2084, https://doi.org/10.5194/egusphere-2025-2084, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
We developed an improved model to better understand how water and energy move through natural landscapes (forest, grasslands, croplands, etc) throughout the day. By using detailed data from study-site in Germany, we tested the model and found its good agreement with micro-meteorological measurements. Unlike many other tools, this model works without needing new adjustments and offers a powerful way to study fast-changing water processes in different environments.
Stefanie Fischer, Ronald Queck, Christian Bernhofer, and Matthias Mauder
EGUsphere, https://doi.org/10.5194/egusphere-2025-2118, https://doi.org/10.5194/egusphere-2025-2118, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Accurate estimates of interception are important to assess the water availability in ecosystems. We analyzed rainfall interception for a forest site from plot to stand scale. During interception, eddy-covariance measurements of evaporation were systematically underestimated accounting for 24% of precipitation, while modelled interception evaporation accounted for 45%. As a consequence, we developed a hybrid correction approach to fit the evaporation data to both the energy and the water balance.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
Short summary
Short summary
We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Johannes Speidel, Hannes Vogelmann, Andreas Behrendt, Diego Lange, Matthias Mauder, Jens Reichardt, and Kevin Wolz
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-168, https://doi.org/10.5194/amt-2024-168, 2024
Revised manuscript accepted for AMT
Short summary
Short summary
Humidity transport from the Earth's surface into the atmosphere is relevant for many processes. However, knowledge on the actual distribution of humidity concentrations is sparse – mainly due to technological limitations. With the herein presented lidar, it is possible to measure humidity concentrations and their vertical fluxes up to altitudes of >3 km with high spatio-temporal resolution, opening new possibilities for detailed process understanding and, ultimately, better model representation.
Hengheng Zhang, Wei Huang, Xiaoli Shen, Ramakrishna Ramisetty, Junwei Song, Olga Kiseleva, Christopher Claus Holst, Basit Khan, Thomas Leisner, and Harald Saathoff
Atmos. Chem. Phys., 24, 10617–10637, https://doi.org/10.5194/acp-24-10617-2024, https://doi.org/10.5194/acp-24-10617-2024, 2024
Short summary
Short summary
Our study unravels how stagnant winter conditions elevate aerosol levels in Stuttgart. Cloud cover at night plays a pivotal role, impacting morning air quality. Validating a key model, our findings aid accurate air quality predictions, crucial for effective pollution mitigation in urban areas.
Basil A. S. Davis, Marc Fasel, Jed O. Kaplan, Emmanuele Russo, and Ariane Burke
Clim. Past, 20, 1939–1988, https://doi.org/10.5194/cp-20-1939-2024, https://doi.org/10.5194/cp-20-1939-2024, 2024
Short summary
Short summary
During the last ice age (21 000 yr BP) in Europe, the composition and extent of forest and its associated climate remain unclear, with models indicating more forest north of the Alps and a warmer and somewhat wetter climate than suggested by the data. A new compilation of pollen records with improved dating suggests greater agreement with model climates but still suggests models overestimate forest cover, especially in the west.
Kevin Wolz, Christopher Holst, Frank Beyrich, Eileen Päschke, and Matthias Mauder
Geosci. Instrum. Method. Data Syst., 13, 205–223, https://doi.org/10.5194/gi-13-205-2024, https://doi.org/10.5194/gi-13-205-2024, 2024
Short summary
Short summary
We compared wind measurements using different lidar setups at various heights. The triple Doppler lidar, sonic anemometer, and two single Doppler lidars were tested. Overall, the lidar methods showed good agreement with the sonic anemometer. The triple Doppler lidar performed better than single Doppler lidars, especially at higher altitudes. We also developed a new filtering approach for virtual tower scanning strategies. Single Doppler lidars provide reliable wind data over flat terrain.
Changxing Lan, Matthias Mauder, Stavros Stagakis, Benjamin Loubet, Claudio D'Onofrio, Stefan Metzger, David Durden, and Pedro-Henrique Herig-Coimbra
Atmos. Meas. Tech., 17, 2649–2669, https://doi.org/10.5194/amt-17-2649-2024, https://doi.org/10.5194/amt-17-2649-2024, 2024
Short summary
Short summary
Using eddy-covariance systems deployed in three cities, we aimed to elucidate the sources of discrepancies in flux estimations from different software packages. One crucial finding is the impact of low-frequency spectral loss corrections on tall-tower flux estimations. Our findings emphasize the significance of a standardized measurement setup and consistent postprocessing configurations in minimizing the systematic flux uncertainty resulting from the usage of different software packages.
Sinikka J. Paulus, Rene Orth, Sung-Ching Lee, Anke Hildebrandt, Martin Jung, Jacob A. Nelson, Tarek Sebastian El-Madany, Arnaud Carrara, Gerardo Moreno, Matthias Mauder, Jannis Groh, Alexander Graf, Markus Reichstein, and Mirco Migliavacca
Biogeosciences, 21, 2051–2085, https://doi.org/10.5194/bg-21-2051-2024, https://doi.org/10.5194/bg-21-2051-2024, 2024
Short summary
Short summary
Porous materials are known to reversibly trap water from the air, even at low humidity. However, this behavior is poorly understood for soils. In this analysis, we test whether eddy covariance is able to measure the so-called adsorption of atmospheric water vapor by soils. We find that this flux occurs frequently during dry nights in a Mediterranean ecosystem, while EC detects downwardly directed vapor fluxes. These results can help to map moisture uptake globally.
Emmanuele Russo, Jonathan Buzan, Sebastian Lienert, Guillaume Jouvet, Patricio Velasquez Alvarez, Basil Davis, Patrick Ludwig, Fortunat Joos, and Christoph C. Raible
Clim. Past, 20, 449–465, https://doi.org/10.5194/cp-20-449-2024, https://doi.org/10.5194/cp-20-449-2024, 2024
Short summary
Short summary
We present a series of experiments conducted for the Last Glacial Maximum (~21 ka) over Europe using the regional climate Weather Research and Forecasting model (WRF) at convection-permitting resolutions. The model, with new developments better suited to paleo-studies, agrees well with pollen-based climate reconstructions. This agreement is improved when considering different sources of uncertainty. The effect of convection-permitting resolutions is also assessed.
Dongqi Lin, Jiawei Zhang, Basit Khan, Marwan Katurji, and Laura E. Revell
Geosci. Model Dev., 17, 815–845, https://doi.org/10.5194/gmd-17-815-2024, https://doi.org/10.5194/gmd-17-815-2024, 2024
Short summary
Short summary
GEO4PALM is an open-source tool to generate static input for the Parallelized Large-Eddy Simulation (PALM) model system. Geospatial static input is essential for realistic PALM simulations. However, existing tools fail to generate PALM's geospatial static input for most regions. GEO4PALM is compatible with diverse geospatial data sources and provides access to free data sets. In addition, this paper presents two application examples, which show successful PALM simulations using GEO4PALM.
Dongqi Lin, Marwan Katurji, Laura E. Revell, Basit Khan, and Andrew Sturman
Atmos. Chem. Phys., 23, 14451–14479, https://doi.org/10.5194/acp-23-14451-2023, https://doi.org/10.5194/acp-23-14451-2023, 2023
Short summary
Short summary
Accurate fog forecasting is difficult in a complex environment. Spatial variations in soil moisture could impact fog. Here, we carried out fog simulations with spatially different soil moisture in complex topography. The soil moisture was calculated using satellite observations. The results show that the spatial variations in soil moisture do not have a significant impact on where fog occurs but do impact how long fog lasts. This finding could improve fog forecasts in the future.
Gina C. Jozef, Robert Klingel, John J. Cassano, Björn Maronga, Gijs de Boer, Sandro Dahlke, and Christopher J. Cox
Earth Syst. Sci. Data, 15, 4983–4995, https://doi.org/10.5194/essd-15-4983-2023, https://doi.org/10.5194/essd-15-4983-2023, 2023
Short summary
Short summary
Observations from the MOSAiC expedition relating to lower-atmospheric temperature, wind, stability, moisture, and surface radiation budget from radiosondes, a meteorological tower, radiation station, and ceilometer were compiled to create a dataset which describes the thermodynamic and kinematic state of the central Arctic lower atmosphere between October 2019 and September 2020. This paper describes the methods used to develop this lower-atmospheric properties dataset.
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
Preprint archived
Short summary
Short summary
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.
Jonathan Robert Buzan, Emmanuele Russo, Woon Mi Kim, and Christoph C. Raible
EGUsphere, https://doi.org/10.5194/egusphere-2023-324, https://doi.org/10.5194/egusphere-2023-324, 2023
Preprint archived
Short summary
Short summary
Paleoclimate is used to test climate models to verify that simulations accurately project both future and past climate states. We present fully coupled climate sensitivity simulations of Preindustrial, Last Glacial Maximum, and the Quaternary climate periods. We show distinct climate states derived from non-linear responses to ice sheet heights and orbits. The implication is that as paleo proxy data become more reliable, they may constrain the specific climate states produced by climate models.
Edward C. Chan, Joana Leitão, Andreas Kerschbaumer, and Timothy M. Butler
Geosci. Model Dev., 16, 1427–1444, https://doi.org/10.5194/gmd-16-1427-2023, https://doi.org/10.5194/gmd-16-1427-2023, 2023
Short summary
Short summary
Yeti is a Handbook Emission Factors for Road Transport-based traffic emission inventory written in the Python 3 scripting language, which adopts a generalized treatment for activity data using traffic information of varying levels of detail introduced in a systematic and consistent manner, with the ability to maximize reusability. Thus, Yeti has been conceived and implemented with a high degree of data and process symmetry, allowing scalable and flexible execution while affording ease of use.
Chao Yan, Yicheng Shen, Dominik Stolzenburg, Lubna Dada, Ximeng Qi, Simo Hakala, Anu-Maija Sundström, Yishuo Guo, Antti Lipponen, Tom V. Kokkonen, Jenni Kontkanen, Runlong Cai, Jing Cai, Tommy Chan, Liangduo Chen, Biwu Chu, Chenjuan Deng, Wei Du, Xiaolong Fan, Xu-Cheng He, Juha Kangasluoma, Joni Kujansuu, Mona Kurppa, Chang Li, Yiran Li, Zhuohui Lin, Yiliang Liu, Yuliang Liu, Yiqun Lu, Wei Nie, Jouni Pulliainen, Xiaohui Qiao, Yonghong Wang, Yifan Wen, Ye Wu, Gan Yang, Lei Yao, Rujing Yin, Gen Zhang, Shaojun Zhang, Feixue Zheng, Ying Zhou, Antti Arola, Johanna Tamminen, Pauli Paasonen, Yele Sun, Lin Wang, Neil M. Donahue, Yongchun Liu, Federico Bianchi, Kaspar R. Daellenbach, Douglas R. Worsnop, Veli-Matti Kerminen, Tuukka Petäjä, Aijun Ding, Jingkun Jiang, and Markku Kulmala
Atmos. Chem. Phys., 22, 12207–12220, https://doi.org/10.5194/acp-22-12207-2022, https://doi.org/10.5194/acp-22-12207-2022, 2022
Short summary
Short summary
Atmospheric new particle formation (NPF) is a dominant source of atmospheric ultrafine particles. In urban environments, traffic emissions are a major source of primary pollutants, but their contribution to NPF remains under debate. During the COVID-19 lockdown, traffic emissions were significantly reduced, providing a unique chance to examine their relevance to NPF. Based on our comprehensive measurements, we demonstrate that traffic emissions alone are not able to explain the NPF in Beijing.
Benjamin Foreback, Lubna Dada, Kaspar R. Daellenbach, Chao Yan, Lili Wang, Biwu Chu, Ying Zhou, Tom V. Kokkonen, Mona Kurppa, Rosaria E. Pileci, Yonghong Wang, Tommy Chan, Juha Kangasluoma, Lin Zhuohui, Yishou Guo, Chang Li, Rima Baalbaki, Joni Kujansuu, Xiaolong Fan, Zemin Feng, Pekka Rantala, Shahzad Gani, Federico Bianchi, Veli-Matti Kerminen, Tuukka Petäjä, Markku Kulmala, Yongchun Liu, and Pauli Paasonen
Atmos. Chem. Phys., 22, 11089–11104, https://doi.org/10.5194/acp-22-11089-2022, https://doi.org/10.5194/acp-22-11089-2022, 2022
Short summary
Short summary
This study analyzed air quality in Beijing during the Chinese New Year over 7 years, including data from a new in-depth measurement station. This is one of few studies to look at long-term impacts, including the outcome of firework restrictions starting in 2018. Results show that firework pollution has gone down since 2016, indicating a positive result from the restrictions. Results of this study may be useful in making future decisions about the use of fireworks to improve air quality.
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
Short summary
Short summary
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.
Emmanuele Russo, Bijan Fallah, Patrick Ludwig, Melanie Karremann, and Christoph C. Raible
Clim. Past, 18, 895–909, https://doi.org/10.5194/cp-18-895-2022, https://doi.org/10.5194/cp-18-895-2022, 2022
Short summary
Short summary
In this study a set of simulations are performed with the regional climate model COSMO-CLM for Europe, for the mid-Holocene and pre-industrial periods. The main aim is to better understand the drivers of differences between models and pollen-based summer temperatures. Results show that a fundamental role is played by spring soil moisture availability. Additionally, results suggest that model bias is not stationary, and an optimal configuration could not be the best under different forcing.
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
Short summary
Short summary
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.
Shang Gao, Mona Kurppa, Chak K. Chan, and Keith Ngan
Atmos. Chem. Phys., 22, 2703–2726, https://doi.org/10.5194/acp-22-2703-2022, https://doi.org/10.5194/acp-22-2703-2022, 2022
Short summary
Short summary
The contribution of cooking emissions to organic aerosols may exceed that of motor vehicles. However, little is known about how cooking-generated aerosols evolve in the outdoor environment. In this paper, we present a numerical study of the dispersion of cooking emissions. For plausible choices of the emission strength, cooking can yield much higher concentrations than traffic. This has important implications for public health and city planning.
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
Short summary
Short summary
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.
Ian Boutle, Wayne Angevine, Jian-Wen Bao, Thierry Bergot, Ritthik Bhattacharya, Andreas Bott, Leo Ducongé, Richard Forbes, Tobias Goecke, Evelyn Grell, Adrian Hill, Adele L. Igel, Innocent Kudzotsa, Christine Lac, Bjorn Maronga, Sami Romakkaniemi, Juerg Schmidli, Johannes Schwenkel, Gert-Jan Steeneveld, and Benoît Vié
Atmos. Chem. Phys., 22, 319–333, https://doi.org/10.5194/acp-22-319-2022, https://doi.org/10.5194/acp-22-319-2022, 2022
Short summary
Short summary
Fog forecasting is one of the biggest problems for numerical weather prediction. By comparing many models used for fog forecasting with others used for fog research, we hoped to help guide forecast improvements. We show some key processes that, if improved, will help improve fog forecasting, such as how water is deposited on the ground. We also showed that research models were not themselves a suitable baseline for comparison, and we discuss what future observations are required to improve them.
Matthias Mauder, Andreas Ibrom, Luise Wanner, Frederik De Roo, Peter Brugger, Ralf Kiese, and Kim Pilegaard
Atmos. Meas. Tech., 14, 7835–7850, https://doi.org/10.5194/amt-14-7835-2021, https://doi.org/10.5194/amt-14-7835-2021, 2021
Short summary
Short summary
Turbulent flux measurements suffer from a general systematic underestimation. One reason for this bias is non-local transport by large-scale circulations. A recently developed model for this additional transport of sensible and latent energy is evaluated for three different test sites. Different options on how to apply this correction are presented, and the results are evaluated against independent measurements.
Moritz Lange, Henri Suominen, Mona Kurppa, Leena Järvi, Emilia Oikarinen, Rafael Savvides, and Kai Puolamäki
Geosci. Model Dev., 14, 7411–7424, https://doi.org/10.5194/gmd-14-7411-2021, https://doi.org/10.5194/gmd-14-7411-2021, 2021
Short summary
Short summary
This study aims to replicate computationally expensive high-resolution large-eddy simulations (LESs) with regression models to simulate urban air quality and pollutant dispersion. The model development, including feature selection, model training and cross-validation, and detection of concept drift, has been described in detail. Of the models applied, log-linear regression shows the best performance. A regression model can replace LES unless high accuracy is needed.
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
Short summary
Short summary
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.
Eckhard Kadasch, Matthias Sühring, Tobias Gronemeier, and Siegfried Raasch
Geosci. Model Dev., 14, 5435–5465, https://doi.org/10.5194/gmd-14-5435-2021, https://doi.org/10.5194/gmd-14-5435-2021, 2021
Short summary
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.
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
Silje Lund Sørland, Roman Brogli, Praveen Kumar Pothapakula, Emmanuele Russo, Jonas Van de Walle, Bodo Ahrens, Ivonne Anders, Edoardo Bucchignani, Edouard L. Davin, Marie-Estelle Demory, Alessandro Dosio, Hendrik Feldmann, Barbara Früh, Beate Geyer, Klaus Keuler, Donghyun Lee, Delei Li, Nicole P. M. van Lipzig, Seung-Ki Min, Hans-Jürgen Panitz, Burkhardt Rockel, Christoph Schär, Christian Steger, and Wim Thiery
Geosci. Model Dev., 14, 5125–5154, https://doi.org/10.5194/gmd-14-5125-2021, https://doi.org/10.5194/gmd-14-5125-2021, 2021
Short summary
Short summary
We review the contribution from the CLM-Community to regional climate projections following the CORDEX framework over Europe, South Asia, East Asia, Australasia, and Africa. How the model configuration, horizontal and vertical resolutions, and choice of driving data influence the model results for the five domains is assessed, with the purpose of aiding the planning and design of regional climate simulations in the future.
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
Short summary
Short summary
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.
Edward C. Chan and Timothy M. Butler
Geosci. Model Dev., 14, 4555–4572, https://doi.org/10.5194/gmd-14-4555-2021, https://doi.org/10.5194/gmd-14-4555-2021, 2021
Short summary
Short summary
A large-eddy simulation based chemical transport model is implemented for an idealized street canyon. The dynamics of the model are evaluated using stationary measurements. A transient model run is also conducted over a 24 h period, where variations of pollutant concentrations indicate dependence on emissions, background concentrations, and solar state. Comparison stationary model runs show changes in flow structure concentrations.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
Dongqi Lin, Basit Khan, Marwan Katurji, Leroy Bird, Ricardo Faria, and Laura E. Revell
Geosci. Model Dev., 14, 2503–2524, https://doi.org/10.5194/gmd-14-2503-2021, https://doi.org/10.5194/gmd-14-2503-2021, 2021
Short summary
Short summary
We present an open-source toolbox WRF4PALM, which enables weather dynamics simulation within urban landscapes. WRF4PALM passes meteorological information from the popular Weather Research and Forecasting (WRF) model to the turbulence-resolving PALM model system 6.0. WRF4PALM can potentially extend the use of WRF and PALM with realistic boundary conditions to any part of the world. WRF4PALM will help study air pollution dispersion, wind energy prospecting, and high-impact wind forecasting.
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
Short summary
Short summary
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.
Emmanuele Russo, Silje Lund Sørland, Ingo Kirchner, Martijn Schaap, Christoph C. Raible, and Ulrich Cubasch
Geosci. Model Dev., 13, 5779–5797, https://doi.org/10.5194/gmd-13-5779-2020, https://doi.org/10.5194/gmd-13-5779-2020, 2020
Short summary
Short summary
The parameter space of the COSMO-CLM RCM is investigated for the Central Asia CORDEX domain using a perturbed physics ensemble (PPE) with different parameter values. Results show that only a subset of model parameters presents relevant changes in model performance and these changes depend on the considered region and variable: objective calibration methods are highly necessary in this case. Additionally, the results suggest the need for calibrating an RCM when targeting different domains.
Mona Kurppa, Pontus Roldin, Jani Strömberg, Anna Balling, Sasu Karttunen, Heino Kuuluvainen, Jarkko V. Niemi, Liisa Pirjola, Topi Rönkkö, Hilkka Timonen, Antti Hellsten, and Leena Järvi
Geosci. Model Dev., 13, 5663–5685, https://doi.org/10.5194/gmd-13-5663-2020, https://doi.org/10.5194/gmd-13-5663-2020, 2020
Short summary
Short summary
High-resolution modelling is needed to solve the aerosol concentrations in a complex urban area. Here, the performance of an aerosol module within the PALM model to simulate the detailed horizontal and vertical distribution of aerosol particles is studied. Further, sensitivity to the meteorological and aerosol boundary conditions is assessed using both model and observation data. The horizontal distribution is sensitive to the wind speed and stability, and the vertical to the wind direction.
Cited articles
Baker, J., Walker, H. L., and Cai, X.: A study of the dispersion and transport
of reactive pollutants in and above street canyons – A large eddy
simulation, Atmos. Environ., 38, 6883–6892,
https://doi.org/10.1016/j.atmosenv.2004.08.051, 2004. a, b, c, d
Baklanov, A., Schlünzen, K., Suppan, P., Baldasano, J., Brunner, D., Aksoyoglu, S., Carmichael, G., Douros, J., Flemming, J., Forkel, R., Galmarini, S., Gauss, M., Grell, G., Hirtl, M., Joffre, S., Jorba, O., Kaas, E., Kaasik, M., Kallos, G., Kong, X., Korsholm, U., Kurganskiy, A., Kushta, J., Lohmann, U., Mahura, A., Manders-Groot, A., Maurizi, A., Moussiopoulos, N., Rao, S. T., Savage, N., Seigneur, C., Sokhi, R. S., Solazzo, E., Solomos, S., Sørensen, B., Tsegas, G., Vignati, E., Vogel, B., and Zhang, Y.: Online coupled regional meteorology chemistry models in Europe: current status and prospects, Atmos. Chem. Phys., 14, 317–398, https://doi.org/10.5194/acp-14-317-2014, 2014. 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, 2011. a
Barbaro, E., Krol, M. C., and de Arellano, J. V.-G.: Numerical simulation of
the interaction between ammonium nitrate aerosol and convective
boundary-layer, Atmos. Environ., 105, 202–211,
https://doi.org/10.1016/j.atmosenv.2015.01.048, 2015. a
Blocken, B.: LES over RANS in building simulation for outdoor and indoor
applications: a foregone conclusion?, in: Building Simulation,
Springer, Berlin Heidelberg, 821–870, 2018. a
Cao, L., Li, S., Yi, Z., and Gao, M.: Simplification of Carbon Bond Mechanism
IV (CBM-IV) under Different Initial Conditions by Using Concentration
Sensitivity Analysis, Molecules, 24, 2463, https://doi.org/10.3390/molecules24132463, 2019. a, b
Cheng, W. C. and Liu, C.-H.: Large-Eddy Simulation of Flow and Pollutant
Transports in and Above Two-Dimensional Idealized Street Canyons,
Bound.-Lay. Meteorol., 139, 411–437, https://doi.org/10.1007/s10546-010-9584-y,
2011. a
Chung, T. N. and Liu, C.-H.: Large-eddy simulation of reactive pollutant
dispersion for the spatial instability of photostationary state over
idealised 2D urban street canyons, Int. J. Environ.
Pollut., 50, 411–419, 2012. a
Clough, S., Shephard, M., Mlawer, E., Delamere, J., Iacono, M., Cady-Pereira,
K., Boukabara, S., and Brown, P.: Atmospheric radiative transfer modeling: a summary of the AER codes, J. Quant. Spectrosc. Ra., 91, 233–244, 2005. a
Cui, Z., Cai, X., and Baker, C. J.: Large-eddy simulation of turbulent flow in a street canyon, Q. J. Roy. Meteor. Soc., 130,
1373–1394, https://doi.org/10.1256/qj.02.150, 2004. a
Deardorff, J. W.: Stratocumulus-capped mixed layers derived from a
three-dimensional model, Bound.-Lay. Meteorol., 18, 495–527, 1980. a
Deutscher Wetterdienst: Climate and Environment, Climate Data Center (CDC), available at: https://opendata.dwd.de/climate_environment/CDC/observations_germany/climate/ (last access: 12 July 2020),
2020. a
Geiß, A., Wiegner, M., Bonn, B., Schäfer, K., Forkel, R., von Schneidemesser, E., Münkel, C., Chan, K. L., and Nothard, R.: Mixing layer height as an indicator for urban air quality?, Atmos. Meas. Tech., 10, 2969–2988, https://doi.org/10.5194/amt-10-2969-2017, 2017. a
Górska, M., De Arellano, J. V. G., and LeMone, M. A.: The exchange of
carbon dioxide between the atmospheric boundary layer and the free
atmosphere: Observational and les study, 17th Symposium on Boundary Layers
and Turbulence, 27th Conference on Agricultural and Forest Meteorology, 17th Conference on Biometeorology and Aerobiology, San Diego, CA,
1–4, 2006. a
Gronemeier, T., Inagaki, A., Gryschka, M., and Kanda, M.: Large-Eddy
Simulation of an Urban Canopy Using a Synthetic Turbulence Inflow Generation
Method, Annu. J. Hydraulic Eng, 71, 43–48,
https://doi.org/10.2208/jscejhe.71.I_43, 2015. a
Gronemeier, T., Surm, K., Harms, F., Leitl, B., Maronga, B., and Raasch, S.: Validation of the Dynamic Core of the PALM Model System 6.0 in Urban Environments: LES andWind-tunnel Experiments, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-172, in review, 2020. a
Gross, G.: ASMUS – Ein numerisches Modell zur Berechnung der Strömung und
der Schadstoffverteilung im Bereich einzelner Gebäude. II:
Schadstoffausbreitung und Anwendung, Meteorol. Z., 6,
130–136, https://doi.org/10.1127/metz/6/1997/130, 1997. a
Grylls, T., Corneca, C. M. L., Salizzoni, P., Soulhac, L., Stettler, M. E., and
van Reeuwijk, M.: Evaluation of an operational air quality model using
large-eddy simulation, Atmos. Environ., 3, 100041,
https://doi.org/10.1016/j.aeaoa.2019.100041, 2019. a
Han, B.-S., Baik, J.-J., Kwak, K.-H., and Park, S.-B.: Large-eddy simulation of reactive pollutant exchange at the top of a street canyon, Atmos.
Environ., 187, 381–389, 2018. a
Han, B.-S., Baik, J.-J., Park, S.-B., and Kwak, K.-H.: Large-Eddy Simulations
of Reactive Pollutant Dispersion in the Convective Boundary Layer over Flat
and Urban-Like Surfaces, Bound.-Lay. Meteorol., 172, 271–289,
https://doi.org/10.1007/s10546-019-00447-2, 2019. a, b
Hausberger, S. and Matzer, C.: Update of Emission Factors for EURO 4, EURO 5
and EURO 6 Diesel Passenger Cars for the HBEFA Version 3.3, Tech. Rep.
I-09/17/ CM EM 16/26/679 from 01.06.2017, Institute for International
Combustion Engines and Thermodynamics, available at: http://www.hbefa.net/e/documents/HBEFA3-3_TUG_finalreport_01062016.pdf (last access: 24 February 2021), 2017. a
Heldens, W., Burmeister, C., Kanani-Sühring, F., Maronga, B., Pavlik, D., Sühring, M., Zeidler, J., and Esch, T.: Geospatial input data for the PALM model system 6.0: model requirements, data sources and processing, Geosci. Model Dev., 13, 5833–5873, https://doi.org/10.5194/gmd-13-5833-2020, 2020. a
Henn, D. and Sykes, R.: Large-eddy simulation of dispersion in the convective
boundary layer, Atmos. Environ., 26, 3145–3159, 1992. a
Hidalgo, J., Masson, V., Baklanov, A., Pigeon, G., and Gimeno, L.: Advances in
urban climate modeling, Ann. NY Acad. Sci., 1146,
354–374, https://doi.org/10.1196/annals.1446.015, 2008. a
Jacob, D. J. and Winner, D. A.: Effect of climate change on air quality,
Atmos. Environ., 43, 51–63, 2009. a
Jöckel, P., Kerkweg, A., Pozzer, A., Sander, R., Tost, H., Riede, H., Baumgaertner, A., Gromov, S., and Kern, B.: Development cycle 2 of the Modular Earth Submodel System (MESSy2), Geosci. Model Dev., 3, 717–752, https://doi.org/10.5194/gmd-3-717-2010, 2010. a, b, c
Kadasch, E., Sühring, M., Gronemeier, T., and Raasch, S.: Mesoscale nesting interface of the PALM model system 6.0, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2020-285, in review, 2020. a
Keck, M., Raasch, S., Letzel, M. O., and Ng, E.: First Results of High
Resolution Large-Eddy Simulations of the Atmospheric Boundary Layer, J. Heat Island Institute International, 9, 39–43, 2014. a
Khan, B.: Input data for performing chemistry coupled PALM model system 6.0
simulations with different chemical mechanisms, Zenodo,
https://doi.org/10.5281/zenodo.4020561, 2020. a
Khan, B.: PALM model system 6.0 source code, revisions r4450 and r4601, Zenodo, https://doi.org/10.5281/zenodo.4559550, 2021. a
Kim, S.-W., Barth, M. C., and M, T.: Influence of fair-weather cumulus clouds
on isoprene chemistry, J. Geophys. Res.-Atmos., 117, 1–26,
https://doi.org/10.1029/2011JD017099, 2012. a
Kokkola, H., Korhonen, H., Lehtinen, K. E. J., Makkonen, R., Asmi, A., Järvenoja, S., Anttila, T., Partanen, A.-I., Kulmala, M., Järvinen, H., Laaksonen, A., and Kerminen, V.-M.: SALSA – a Sectional Aerosol module for Large Scale Applications, Atmos. Chem. Phys., 8, 2469–2483, https://doi.org/10.5194/acp-8-2469-2008, 2008. a, b
Kurppa, M., Hellsten, A., Roldin, P., Kokkola, H., Tonttila, J., Auvinen, M., Kent, C., Kumar, P., Maronga, B., and Järvi, L.: Implementation of the sectional aerosol module SALSA2.0 into the PALM model system 6.0: model development and first evaluation, Geosci. Model Dev., 12, 1403–1422, https://doi.org/10.5194/gmd-12-1403-2019, 2019. a, b, c, d, e
Lenschow, D. H., Gurarie, D., and Patton, E. G.: Modeling the diurnal cycle of conserved and reactive species in the convective boundary layer using SOMCRUS, Geosci. Model Dev., 9, 979–996, https://doi.org/10.5194/gmd-9-979-2016, 2016. a
Letzel, M. O., Krane, M., and Raasch, S.: High resolution urban large-eddy
simulation studies from street canyon to neighbourhood scale, Atmos.
Environ., 42, 8770–8784, https://doi.org/10.1016/j.atmosenv.2008.08.001, 2008. a, b
Li, X.-X., Liu, C.-H., and Leung, D. Y. C.: Large-Eddy Simulation of Flow and Pollutant Dispersion in High-Aspect-Ratio Urban Street Canyons with Wall
Model, Bound.-Lay. Meteorol., 129, 249–268,
https://doi.org/10.1007/s10546-008-9313-y, 2008. a, b, c
Li, Y., Barth, M. C., Chen, G., Patton, E. G., Kim, S.-W., Wisthaler, A.,
Mikoviny, T., Fried, A., Clark, R., and Steiner, A. L.: Large-eddy simulation of biogenic VOC chemistry during the DISCOVER-AQ 2011 campaign, J. Geophys. Res.-Atmos., 121, 8083–8105,
https://doi.org/10.1002/2016JD024942, 2016. a
Liu, C.-H., Barth, M. C., Liu, C.-H., and Barth, M. C.: Large-Eddy Simulation
of Flow and Scalar Transport in a Modeled Street Canyon, J. Appl.
Meteorol., 41, 660–673,
https://doi.org/10.1175/1520-0450(2002)041<0660:LESOFA>2.0.CO;2, 2002. a
Lo, K. and Ngan, K.: Characterizing ventilation and exposure in street canyons using Lagrangian particles, J. Appl. Meteorol. Climatol.,
56, 1177–1194, 2017. a
Manders, A. M. M., Builtjes, P. J. H., Curier, L., Denier van der Gon, H. A. C., Hendriks, C., Jonkers, S., Kranenburg, R., Kuenen, J. J. P., Segers, A. J., Timmermans, R. M. A., Visschedijk, A. J. H., Wichink Kruit, R. J., van Pul, W. A. J., Sauter, F. J., van der Swaluw, E., Swart, D. P. J., Douros, J., Eskes, H., van Meijgaard, E., van Ulft, B., van Velthoven, P., Banzhaf, S., Mues, A. C., Stern, R., Fu, G., Lu, S., Heemink, A., van Velzen, N., and Schaap, M.: Curriculum vitae of the LOTOS–EUROS (v2.0) chemistry transport model, Geosci. Model Dev., 10, 4145–4173, https://doi.org/10.5194/gmd-10-4145-2017, 2017. 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, c, d, e
Maronga, B., Gross, G., Raasch, S., Banzhaf, S., Forkel, R., Heldens, W.,
Kanani-Sühring, F., Matzarakis, A., Mauder, M., Pavlik, D., Pfafferott, J.,
Schubert, S., Seckmeyer, G., Sieker, H., and Winderlich, K.: Development of a new urban climate model based on the model PALM – Project overview, planned work, and first achievements, Meteorol. Z., 28, 105–119,
https://doi.org/10.1127/metz/2019/0909, 2019. a, b, c, d, e
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, h, i, j, k
Meroney, R. N., Neff, D. E., and Birdsall, J. B.: Wind-tunnel simulation of
infiltration across permeable building envelopes: energy and air pollution
exchange rates, Tech. rep., American Society of Mechanical Engineers, New
York, NY (United States), 1995. a
Meroney, R. N., Rafailidis, S., and Pavageau, M.: Dispersion in idealized urban
street canyons, in: Air Pollution Modeling and Its Application XI, Springer, Plenum Press, New York, 451–458, 1996. a
Middleton, P., Stockwell, W. R., and Carter, W. P. L.: Aggregation and analysis of volatile organic compound emissions for regional modeling, Atmos. Environ., 24, 1107–1133, https://doi.org/10.1016/0960-1686(90)90077-Z, 1990. a
Moonen, P., Gromke, C., and Dorer, V.: Performance assessment of Large Eddy
Simulation (LES) for modeling dispersion in an urban street canyon with tree planting, Atmos. Environ., 75, 66–76,
https://doi.org/10.1016/J.ATMOSENV.2013.04.016, 2013. a
Nakayama, H., Takemi, T., and Nagai, H.: Large-eddy simulation of plume
dispersion under various thermally stratified boundary layers, Adv.
Sci. Res., 11, 75–81, 2014. a
N'Riain, C., Fisher, B., Martin, C., and Littler, J.: Flow field and pollution dispersion in a central London street, Environ. Monit.
Assess., 52, 299–314, 1998. a
Oolman, L.: Upper Air Data Soundings, University of Wyoming, College of
Engineering, Department of Atmospheric Science, available at: http://weather.uwyo.edu/upperair/sounding.html (last access: 24 February 2021), 2017. a
Ouwersloot, H. G., Vilà-Guerau de Arellano, J., van Heerwaarden, C. C., Ganzeveld, L. N., Krol, M. C., and Lelieveld, J.: On the segregation of chemical species in a clear boundary layer over heterogeneous land surfaces, Atmos. Chem. Phys., 11, 10681–10704, https://doi.org/10.5194/acp-11-10681-2011, 2011. a
Park, S.-B., Baik, J.-J., Raasch, S., and Letzel, M. O.: A Large-Eddy
Simulation Study of Thermal Effects on Turbulent Flow and Dispersion in and
above a Street Canyon, J. Appl. Meteorol. Clim., 51,
829–841, https://doi.org/10.1175/JAMC-D-11-0180.1, 2012. a
Raasch, S. and Schröter, M.: PALM – A large-eddy simulation model
performing on massively parallel computers, Meteorol. Z., 10,
363–372, https://doi.org/10.1127/0941-2948/2001/0010-0363, 2001. a
Resler, J., Krč, P., Belda, M., Juruš, P., Benešová, N., Lopata, J., Vlček, O., Damašková, D., Eben, K., Derbek, P., Maronga, B., and Kanani-Sühring, F.: PALM-USM v1.0: A new urban surface model integrated into the PALM large-eddy simulation model, Geosci. Model Dev., 10, 3635–3659, https://doi.org/10.5194/gmd-10-3635-2017, 2017. a, b
Salim, M. H., Schlünzen, K. H., Grawe, D., Boettcher, M., Gierisch, A. M. U., and Fock, B. H.: The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory, Geosci. Model Dev., 11, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018, 2018. a
Sandu, A. and Sander, R.: Technical note: Simulating chemical systems in Fortran90 and Matlab with the Kinetic PreProcessor KPP-2.1, Atmos. Chem. Phys., 6, 187–195, https://doi.org/10.5194/acp-6-187-2006, 2006. a, b
Sandu, A., Daescu, D., and Carmichael, G. R.: Direct and adjoint sensitivity
analysis of chemical kinetic systems with KPP: Part I – theory and software
tools, Atmos. Environ., 37, 5083–5096, https://doi.org/10.1016/j.atmosenv.2003.08.019,
2003. a
Saunders, S. M., Jenkin, M. E., Derwent, R. G., and Pilling, M. J.: Protocol for the development of the Master Chemical Mechanism, MCM v3 (Part A): tropospheric degradation of non-aromatic volatile organic compounds, Atmos. Chem. Phys., 3, 161–180, https://doi.org/10.5194/acp-3-161-2003, 2003. a, b
Sauter, F., van Zanten, M., van der Swaluw, E., Aben, J., de Leeuw, F., and van Jaarsveld, H.: The OPS-model, Description of OPS 4.50, National Institute for Public Health and the Environment (RIVM) Bilthoven, 775, 1–115, 2016. a
Scherer, D., Ament, F., Emeis, S., Fehrenbach, U., Leitl, B., Scherber, K.,
Schneider, C., and Vogt, U.: Three-Dimensional Observation of Atmospheric
Processes in Cities, Meteorol. Z., 28, 121–138,
https://doi.org/10.1127/metz/2019/0911, 2019a. a
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, 2019b. a
Seaman, N. L.: Meteorological modeling for air-quality assessments,
Atmos. Environ., 34, 2231–2259, https://doi.org/10.1016/S1352-2310(99)00466-5,
2000. a
Senatsverwaltung für Stadtentwicklung und Wohnen: Senate Department for
Urban Development and Housing; Maps, data, services – online, available at:
https://www.stadtentwicklung.berlin.de/geoinformation/fis-broker/, last access: 25 July
2020 (in German). a
Sharma, A., Fernando, H. J., Hamlet, A. F., Hellmann, J. J., Barlage, M., and
Chen, F.: Urban meteorological modeling using WRF: a sensitivity study,
Int. J. Climatol., 37, 1885–1900, https://doi.org/10.1002/joc.4819,
2017. a
Simpson, D., Tuovinen, J.-P., Emberson, L., and Ashmore, M.: Characteristics of an ozone deposition module II: Sensitivity analysis, Water Air Soil
Pollut., 143, 123–137, 2003. a
Skamarock, W. C.: Positive-definite and monotonic limiters for
unrestricted-time-step transport schemes, Mon. Weather Rev., 134,
2241–2250, 2006. a
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric
model for weather research and forecasting applications, J.
Comput. Phys., 227, 3465–3485, https://doi.org/10.1016/J.JCP.2007.01.037,
2008. a
Toja-Silva, F., Chen, J., Hachinger, S., and Hase, F.: CFD simulation of
CO2 dispersion from urban thermal power plant: Analysis of turbulent Schmidt
number and comparison with Gaussian plume model and measurements, J. Wind Eng. Ind. Aerod., 169, 177–193,
https://doi.org/10.1016/j.jweia.2017.07.015, 2017. a
United Nations: World Urbanization Prospects, Tech. rep., Department of
Economic and Social Affairs, Population Division, available at:
https://esa.un.org/unpd/wup/publications/files/wup2014-highlights.pdf (last access: 20 February 2020),
2014. a
Van Zanten, M., Sauter, F., Wichink Kruit, R., Van Jaarsveld, J., and
Van Pul, W.: Description of the DEPAC module: Dry deposition modelling
with DEPAC GCN2010, Tech. Rep. October 2010, National Institute for Public
Health and the Environment (RIVM), available at:
http://www.scopus.com/inward/record.url?eid=2-s2.0-84871391562&partnerID=tZOtx3y1 (last access: 12 July 2020),
2010.
a, b
Vardoulakis, S., Fisher, B. E., Pericleous, K., and Gonzalez-Flesca, N.:
Modelling air quality in street canyons: a review, Atmos. Environ.,
37, 155–182, https://doi.org/10.1016/S1352-2310(02)00857-9, 2003. a
Verwer, W. G., Spee, E. J., Blom, J. G., and Hundsdorfer, W.: A second order
Rosenbrock method applied the photochenmical dispersion problems, SIAM
J. Sci. Comput., 20, 1456–1480,
https://doi.org/10.1137/S1064827597326651, 1999. a
Vilà-Guerau De Arellano, J. and Duynkerke, P. G.: Exchange of chemical species between the atmospheric boundary layer and the reservoir layer: An analytical interpretation, Appl. Sci. Res., 59,
219–227, https://doi.org/10.1023/A:1001135505790, 1997. a
Vilà-Guerau de Arellano, J., Dosio, A., Vinuesa, J. F., Holtslag,
A. M., and Galmarini, S.: The dispersion of chemically reactive species in
the atmospheric boundary layer, Meteorol. Atmos. Phys., 87,
23–38, https://doi.org/10.1007/s00703-003-0059-2, 2004a. a
Vilà-Guerau de Arellano, J., Gioli, B., Miglietta, F., Jonker, H. J.,
Baltink, H. K., Hutjes, R. W., and Holtslag, A. A.: Entrainment process of
carbon dioxide in the atmospheric boundary layer, J. Geophys.
Res.-Atmos., 109, 1–16, https://doi.org/10.1029/2004JD004725,
2004b. a
Vilà-Guerau de Arellano, J., Kim, S.-W., Barth, M. C., and Patton, E. G.: Transport and chemical transformations influenced by shallow cumulus over land, Atmos. Chem. Phys., 5, 3219–3231, https://doi.org/10.5194/acp-5-3219-2005, 2005. a
Walton, A. and Cheng, A.: Large-eddy simulation of pollution dispersion in an
urban street canyon – Part II: idealised canyon simulation, Atmos.
Environ., 36, 3615–3627, https://doi.org/10.1016/S1352-2310(02)00260-1, 2002. a, b
Walton, A., Cheng, A. Y., and Yeung, W. C.: Large-eddy simulation of pollution dispersion in an urban street canyon – Part I: Comparison with field data, Atmos. Environ., 36, 3601–3613, https://doi.org/10.1016/S1352-2310(02)00259-5, 2002. a, b
Wicker, L. J. and Skamarock, W. C.: Time-splitting methods for elastic models
using forward time schemes, Mon. Weather Rev., 130, 2088–2097, 2002. a
Wiegner, M., Geiß, A., Mattis, I., Meier, F., and Ruhtz, T.: On the spatial variability of the regional aerosol distribution as determined from ceilometers, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-332, in review, 2020. a
Wild, O., Zhu, X., and Prather, M. J.: Fast-J: Accurate Simulation of In-
and Below-Cloud Photolysis in Tropospheric Chemical Models, J.
Atmos. Chem., 37, 245–282, https://doi.org/10.1023/A:1006415919030, 2000. a
Williamson, J.: Low-storage runge-kutta schemes, J. Comput.
Phys., 35, 48–56, 1980. a
Xie, Z. and Castro, I. P.: LES and RANS for turbulent flow over arrays of
wall-mounted obstacles, Flow Turbulence Combust., 76, 291–312,
https://doi.org/10.1007/s10494-006-9018-6, 2006. a
Zhang, L., Gong, S., Padro, J., and Barrie, L.: A size-segregated particle dry
deposition scheme for an atmosphericaerosol module, Atmos. Environ.,
35.3, 549–560, https://doi.org/10.1016/S1352-2310(00)00326-5, 2001. a, b
Short summary
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.
An atmospheric chemistry model has been implemented in the microscale PALM model system 6.0....