Articles | Volume 13, issue 7
https://doi.org/10.5194/gmd-13-3055-2020
© Author(s) 2020. 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-13-3055-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
09 Jul 2020
Model description paper |
| 09 Jul 2020
| 09 Jul 2020
Calculating human thermal comfort and thermal stress in the PALM model system 6.0
Dominik Fröhlich
CORRESPONDING AUTHOR
Deutscher Wetterdienst (DWD), Research Centre Human Biometeorology,
Stefan-Meier-Str. 4, 79104 Freiburg, Germany
Andreas Matzarakis
Deutscher Wetterdienst (DWD), Research Centre Human Biometeorology,
Stefan-Meier-Str. 4, 79104 Freiburg, Germany
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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.
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.
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Determination of heat requirements in the first developing phases of plants has been expressed as Growing Degree Days (GDD) and is useful in order to understand the flowering season development in plant species, and forecast when flowering will occur. The study dealt with the estimation of GDD in Crete Island in Greece. Results indicated that in the future, GDD will be increased and the existing cultivations can reach maturity sooner. Neverthelless, rough topography will act as an inhibitor.
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Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
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The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
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Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
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
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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.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
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This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
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Latin America (LAC) has some of the most populated urban areas in the world, with high levels of air pollution. Air quality management in LAC has been traditionally focused on surveillance and building emission inventories. This study performed the first intercomparison and model evaluation in LAC, with interesting and insightful findings for the region. A multiscale modeling ensemble chain was assembled as a first step towards an air quality forecasting system.
David Ho, Michał Gałkowski, Friedemann Reum, Santiago Botía, Julia Marshall, Kai Uwe Totsche, and Christoph Gerbig
Geosci. Model Dev., 17, 7401–7422, https://doi.org/10.5194/gmd-17-7401-2024, https://doi.org/10.5194/gmd-17-7401-2024, 2024
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Atmospheric model users often overlook the impact of the land–atmosphere interaction. This study accessed various setups of WRF-GHG simulations that ensure consistency between the model and driving reanalysis fields. We found that a combination of nudging and frequent re-initialization allows certain improvement by constraining the soil moisture fields and, through its impact on atmospheric mixing, improves atmospheric transport.
Jie Gao, Yi Huang, Jonathon S. Wright, Ke Li, Tao Geng, and Qiurun Yu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2815, https://doi.org/10.5194/egusphere-2024-2815, 2024
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The aerosol in the upper troposphere and stratosphere is highly variable, and its radiative effect is poorly understood. To estimate that effect, the radiative kernel is constructed and applied. The results show that the kernels can reproduce aerosol radiative effects and are expected to simulate stratospheric aerosol radiative effects. This approach reduces computational expense and consists well with radiative model calculations and can be applied to atmospheric models with speed requirements.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-145, https://doi.org/10.5194/gmd-2024-145, 2024
Revised manuscript accepted for GMD
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements in 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Hilda Sandström and Patrick Rinke
EGUsphere, https://doi.org/10.48550/arXiv.2406.18171, https://doi.org/10.48550/arXiv.2406.18171, 2024
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Machine learning has the potential to aid the identification organic molecules involved in aerosol formation. Yet, progress is stalled by a lack of curated atmospheric molecular datasets. Here, we compared atmospheric compounds with large molecular datasets used in machine learning and found minimal overlap with similarity algorithms. Our result underlines the need for collaborative efforts to curate atmospheric molecular data to facilitate machine learning model in atmospheric sciences.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-99, https://doi.org/10.5194/gmd-2024-99, 2024
Revised manuscript accepted for GMD
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rainfall. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and then the model skill is evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with 4 open-source models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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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.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Cited articles
ASHRAE: Fundamentals, chap. 8, in: Thermal comfort, Tech. rep., American Society
of Heating and Air-Conditioning Engineers, Atlanta, 2001. a
Błażejczyk, K., Epstein, Y., Jendritzky, G., Staiger, H., and Tinz, B.:
Comparison of UTCI to selected thermal indices, Int. J.
Biometeorol., 56, 515–535, https://doi.org/10.1007/s00484-011-0453-2, 2012. a
Bröde, P., Fiala, D., Błażejczyk, K., Holmér, I., Jendritzky,
G., Kampmann, B., Tinz, B., and Havenith, G.: Deriving the operational
procedure for the Universal Thermal Climate Index (UTCI),
Int. J. Biometeorol., 56, 481–494,
https://doi.org/10.1007/s00484-011-0454-1, 2012. a, b, c
Brown, R. D. and Gillespie, T. J.: Estimating outdoor thermal comfort using a
cylindrical radiation thermometer and an energy budget model, Int.
J. Biometeorol., 30, 43–52, https://doi.org/10.1007/BF02192058, 1986. a
Charalampopoulos, I., Tsiros, I., Chronopoulou-Sereli, A., and Matzarakis, A.: Analysis of thermal bioclimate in various urban configurations in Athens, Greece, Urban Ecosyst., 16, 217–233, https://doi.org/10.1007/s11252-012-0252-5, 2013. a
Charalampopoulos, I., Tsiros, I., Chronopoulou-Sereli, A., and Matzarakis, A.: A note on the evolution of the daily pattern of thermal comfort-related
micrometeorological parameters in small urban sites in Athens,
Int. J. Biometeorol., 59, 1223–1236,
https://doi.org/10.1007/s00484-014-0934-1, 2015. a
Chen, Y.-C. and Matzarakis, A.: Modified physiologically equivalent
temperature–basics and applications for western European climate,
Theor. Appl. Climatol., 132, 1275–1289,
https://doi.org/10.1007/s00704-017-2158-x, 2018. a, b, c, d
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, J. Quant. Spectrosc. Ra., 91, 233–244,
https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005. a, b
Conti, S., Meli, P., Minelli, G., Solimini, R., Toccaceli, V., Vichi, M.,
Beltrano, C., and Perini, L.: Epidemiologic study of mortality during the
Summer 2003 heat wave in Italy, Environ. Res., 98, 390–399,
https://doi.org/10.1016/j.envres.2004.10.009, 2005. a, b
Fiala, D., Havenith, G., Broede, P., Kampmann, B., and Jendritzky, G.:
UTCI-Fiala multi-node model of human heat transfer and temperature
regulation, Int. J. Biometeorol., 56, 429–441,
https://doi.org/10.1007/s00484-011-0424-7, 2012. a
Fröhlich, D.: Development of a microscale model for the thermal environment in complex areas, PhD thesis, Albert-Ludwigs-Universität, Freiburg,
https://doi.org/10.6094/UNIFR/11614, 2017. a, b
Fröhlich, D.: Modified “test_urban” dataset for thermal comfort in PALM, Zenodo, https://doi.org/10.5281/zenodo.3567814, 2019. a, b, c, d
Fröhlich, D. and Matzarakis, A.: Thermal bioclimate and urban planning in
Freiburg – Examples based on urban spaces, Theoretical and Applied
Climatology, 111, 547–558, 2013. a
Fröhlich, D. and Matzarakis, A.: A quantitative sensitivity analysis on the
behaviour of common thermal indices under hot and windy conditions in Doha,
Qatar, Theor. Appl. Climatol., 124, 179–187,
https://doi.org/10.1007/s00704-015-1410-5, 2016. a, b, c
Fröhlich, D., Gangwisch, M., and Matzarakis, A.: Effect of radiation and wind
on thermal comfort in urban environments – Application of the RayMan and
SkyHelios model, Urban Climate, 27, 1–7,
https://doi.org/10.1016/j.uclim.2018.10.006, 2019. a
Gronemeier, T., Kanani-Sühring, F., and Raasch, S.: Do Shallow Cumulus
Clouds have the Potential to Trigger Secondary Circulations Via
Shading?, Bound.-Lay. Meteorol., 162, 143–169,
https://doi.org/10.1007/s10546-016-0180-7, 2017. a
Havenith, G., Fiala, D., Błazejczyk, K., Richards, M., Bröde, P., Holmér,
I., Rintamaki, H., Benshabat, Y., and Jendritzky, G.: The UTCI-clothing
model, Int. J. Biometeorol., 56, 461–470, https://doi.org/10.1007/s00484-011-0451-4,
2012. a, b
Hellsten, A., Ketelsen, K., Barmpas, F., Tsegas, G., Moussiopoulos, N., and
Raasch, S.: Nested Multi-scale System in the PALM Large-Eddy
Simulation Model, in: Air Pollution Modeling and its Application
XXV, edited by: Mensink, C. and Kallos, G., Springer
International Publishing, Cham, 287–292, https://doi.org/10.1007/978-3-319-57645-9_45, 2018. a, b
Höppe, P. R.: Heat balance modelling, Experientia, 49, 741–746,
https://doi.org/10.1007/BF01923542, 1993. a, b, c
Kanani, F., Träumner, K., Ruck, B., and Raasch, S.: What determines the
differences found in forest edge flow between physical models and atmospheric
measurements? An LES study, Meteorol. Z., 23, 33–49,
https://doi.org/10.1127/0941-2948/2014/0542, 2014. a
Kanani-Sühring, F. and Raasch, S.: Spatial Variability of Scalar
Concentrations and Fluxes Downstream of a Clearing-to-Forest
Transition: A Large-Eddy Simulation Study, Bound.-Lay.
Meteorol., 155, 1–27, https://doi.org/10.1007/s10546-014-9986-3, 2015. a
Koppe, C., Kovats, S., Jendritzky, G., and Menne, B.: Heat-waves: risks and
responses, vol. 2, World Health Organization, Copenhagen, 2004. a
Lin, T.-P., Matzarakis, A., and Hwang, R.-L.: Shading effect on long-term
outdoor thermal comfort, Build. Environ., 45, 213–221,
https://doi.org/10.1016/j.buildenv.2009.06.002, 2010a. 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
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, 2020a. 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, 2019b. a, b, c
Matzarakis, A.: Die thermische Komponente des Stadtklimas, no. 6 in
Berichte des Meteorologischen Institutes der Universität Freiburg,
2001. a
Matzarakis, A. and Endler, C.: Climate change and thermal bioclimate in cities: impacts and options for adaptation in Freiburg, Germany, Int. J.
Biometeorol., 54, 479–483, https://doi.org/10.1007/s00484-009-0296-2, 2010. a
Matzarakis, A., Rutz, F., and Mayer, H.: Modelling radiation fluxes in simple
and complex environments – application of the RayMan model, Int. J.
Biometeorol., 51, 323–334, https://doi.org/10.1007/s00484-006-0061-8, 2007. a, b
Matzarakis, A., Rutz, F., and Mayer, H.: Modelling radiation fluxes in simple
and complex environments: basics of the RayMan model, Int. J. Biometeorol.,
54, 131–139, https://doi.org/10.1007/s00484-009-0261-0, 2010. a, b
Mayer, H. and Höppe, P.: Thermal Comfort of Man in Different Urban
Environments, Theor. Appl. Climatol., 38, 43–49, 1987. a
Muthers, S., Matzarakis, A., and Koch, E.: Summer climate and mortality in
Vienna – a human-biometeorological approach of heat-related mortality
during the heat waves in 2003, Wien. Klin. Wochenschr., 122, 525–531,
https://doi.org/10.1007/s00508-010-1424-z, 2010. a
Muthers, S., Laschewski, G., and Matzarakis, A.: The Summers 2003 and 2015 in South-West Germany: Heat Waves and Heat-Related Mortality in the Context of Climate Change, Atmosphere, 8, 224,
https://doi.org/10.3390/atmos8110224, 2017. a
Nastos, P. and Matzarakis, A.: The effect of air temperature and
Physiologically Equivalent Temperature on mortality in Athens,
Greece, Theor. Appl. Climatol., 108, 591–599, 2012. a
Nouri, A. S., Fröhlich, D., Silva, M. M., and Matzarakis, A.: The Impact of
Tipuana tipu Species on Local Human Thermal Comfort Thresholds
in Different Urban Canyon Cases in Mediterranean Climates:
Lisbon, Portugal, Atmosphere, 9, 12, https://doi.org/10.3390/atmos9010012, 2018. a, b
Pincus, R., Barker, H. W., and Morcrette, J.-J.: A fast, flexible, approximate
technique for computing radiative transfer in inhomogeneous cloud fields, J.
Geophys. Res.-Atmos., 108, 4376, https://doi.org/10.1029/2002JD003322, 2003. 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, b
Reis, C. and Lopes, A.: Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon, Sustainability, 11, 2480, https://doi.org/10.3390/su11092480, 2019. a, b
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, c, d
Shashua-Bar, L., Pearlmutter, D., and Erell, E.: The influence of trees and
grass on outdoor thermal comfort in a hot-arid environment, Int.
J. Climatol., 31, 1498–1506, https://doi.org/10.1002/joc.2177, 2011. a
Staiger, H., Laschewski, G., and Matzarakis, A.: Selection of Appropriate
Thermal Indices for Applications in Human Biometeorological
Studies, Atmosphere, 10, 18, https://doi.org/10.3390/atmos10010018, 2019. a, b
Thorsson, S., Lindberg, F., Eliasson, I., and Holmer, B.: Different methods for estimating the mean radiant temperature in an outdoor urban setting, Int. J. Climatol., 27, 1983–1993, https://doi.org/10.1002/joc.1537, 2007. a
Tromp, S.: Biometeorology – The impact of the weather and climate on humans
and their environment (animals and plants), Heyden & Son Ltd, London,
Philadelphia, Rheine, 1980. a
Wang, W., Ng, E., Yuan, C., and Raasch, S.: Large-eddy simulations of
ventilation for thermal comfort – A parametric study of generic urban
configurations with perpendicular approaching winds, Urban Climate, 20,
202–227, https://doi.org/10.1016/j.uclim.2017.04.007, 2017. a
Short summary
In the frame of the project "MOSAIK - Model-based city planning and application in climate change", a biometeorology module was implemented into the Parallelized Large-Eddy Simulation Model (PALM). It is comprised of methods for the estimation of three popular thermal indices for the assessment of human thermal comfort or thermal stress. Results of the new module are compared to those by the SkyHelios model as well as the version of the indices published in VDI guideline 3787, part 2.
In the frame of the project "MOSAIK - Model-based city planning and application in climate...
