Articles | Volume 13, issue 11
https://doi.org/10.5194/gmd-13-5549-2020
© 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-13-5549-2020
© 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
| 
12 Nov 2020
Model description paper |
| 12 Nov 2020
| 12 Nov 2020
Modeling lightning observations from space-based platforms (CloudScat.jl 1.0)
Instituto de Astrofísica de Andalucía (IAA, CSIC), Granada, Spain
Francisco José Gordillo-Vázquez
Instituto de Astrofísica de Andalucía (IAA, CSIC), Granada, Spain
Dongshuai Li
Instituto de Astrofísica de Andalucía (IAA, CSIC), Granada, Spain
Alejandro Malagón-Romero
Instituto de Astrofísica de Andalucía (IAA, CSIC), Granada, Spain
Francisco Javier Pérez-Invernón
Institut für Physik der Atmosphäre, Deutsches Zentrum für Luft- und Raumfahrt, Wessling, Germany
Anthony Schmalzried
Instituto de Astrofísica de Andalucía (IAA, CSIC), Granada, Spain
Sergio Soler
Instituto de Astrofísica de Andalucía (IAA, CSIC), Granada, Spain
Olivier Chanrion
National Space Institute, Technical University of Denmark (DTU Space), Kongens Lyngby, Denmark
Matthias Heumesser
National Space Institute, Technical University of Denmark (DTU Space), Kongens Lyngby, Denmark
Torsten Neubert
National Space Institute, Technical University of Denmark (DTU Space), Kongens Lyngby, Denmark
Víctor Reglero
Image Processing Laboratory, University of Valencia, Valencia, Spain
Nikolai Østgaard
Birkeland Centre for Space Science, Department of Physics and Technology, University of Bergen, Bergen, Norway
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Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
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Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
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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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
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.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
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.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
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Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
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.
Lucas A. Estrada, Daniel J. Varon, Melissa Sulprizio, Hannah Nesser, Zichong Chen, Nicholas Balasus, Sarah E. Hancock, Megan He, James D. East, Todd A. Mooring, Alexander Oort Alonso, Joannes D. Maasakkers, Ilse Aben, Sabour Baray, Kevin W. Bowman, John R. Worden, Felipe J. Cardoso-Saldaña, Emily Reidy, and Daniel J. Jacob
EGUsphere, https://doi.org/10.5194/egusphere-2024-2700, https://doi.org/10.5194/egusphere-2024-2700, 2024
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Reducing methane emissions, a powerful greenhouse gas, is a top policy concern for mitigating anthropogenic climate change. The Integrated Methane Inversion (IMI) is an advanced, cloud-based software that translates satellite observations into actionable emissions data. Here we present IMI version 2.0 with vastly expanded capabilities. These updates enable a wider range of scientific and stakeholder applications from regional to global scales and allow continuous emissions monitoring.
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.
Cited articles
Adachi, T., Sato, M., Ushio, T., Yamazaki, A., Suzuki, M., Kikuchi,
M., Takahashi, Y., Inan, U. S., Linscott, I., Hobara, Y., Frey,
H. U., Mende, S. B., Chen, A. B., Hsu, R.-R., and Kusunoki, K.:
Identifying the occurrence of lightning and transient luminous events by
nadir spectrophotometric observation, J. Atmos. Solar-Terr. Phy., 145, 85,
https://doi.org/10.1016/j.jastp.2016.04.010, 2016. a
Bates, D. R.: Rayleigh scattering by air, Planet. Space Sci., 32, 785,
https://doi.org/10.1016/0032-0633(84)90102-8, 1984. a
Berk, A., Anderson, G. P., Acharya, P. K., Bernstein, L. S., Muratov,
L., Lee, J., Fox, M., Adler-Golden, S. M., Chetwynd, J. H., Hoke,
M. L., Lockwood, R. B., Gardner, J. A., Cooley, T. W., Borel, C. C.,
and Lewis, P. E.: MODTRAN 5: a reformulated atmospheric band model with
auxiliary species and practical multiple scattering options: update, vol.
5806 of Society of Photo-Optical Instrumentation Engineers (SPIE)
Conference Series, p. 662, https://doi.org/10.1117/12.606026, 2005. a
Blakeslee, R. J.: Non-Quality Controlled Lightning Imaging Sensor (LIS) on
International Space Station (ISS) Science Data, NASA Earth Data,
https://doi.org/10.5067/LIS/ISSLIS/DATA107,
2019. a
Blakeslee, R. J., Christian, H. J., J., Mach, D. M., Buechler, D. E.,
Koshak, W. J., Walker, T. D., Bateman, M. G., Stewart, M. F.,
O'Brien, S., Wilson, T. O., Pavelitz, S. D., and Coker, C.:
Lightning Imaging Sensor (LIS) on the International Space Station (ISS):
Launch, Installation, Activation, and First Results, in: AGU Fall Meeting
Abstracts, vol. 2016, p. AE23A, 2016. a
Boccippio, D. J., Koshak, W. J., and Blakeslee, R. J.: Performance
Assessment of the Optical Transient Detector and Lightning Imaging Sensor.
Part I: Predicted Diurnal Variability, J. Atmos. Ocean.
Tech., 19, 1318, https://doi.org/10.1175/1520-0426(2002)019<1318:PAOTOT>2.0.CO;2,
2002. a
Bodhaine, B. A., Wood, N. B., Dutton, E. G., and Slusser, J. R.: On
Rayleigh Optical Depth Calculations, J. Atmos. Ocean.
Tech., 16, 1854, https://doi.org/10.1175/1520-0426(1999)016<1854:ORODC>2.0.CO;2,
1999. a, b
Bohren, C. and Huffman, D. R.: Absorption and Scattering of Light by Small
Particles, John Wiley & Sons, New York, USA, 1983. a
Bozem, H., Fischer, H., Gurk, C., Schiller, C. L., Parchatka, U., Koenigstedt, R., Stickler, A., Martinez, M., Harder, H., Kubistin, D., Williams, J., Eerdekens, G., and Lelieveld, J.: Influence of corona discharge on the ozone budget in the tropical free troposphere: a case study of deep convection during GABRIEL, Atmos. Chem. Phys., 14, 8917–8931, https://doi.org/10.5194/acp-14-8917-2014, 2014. a
Brunner, K. N. and Bitzer, P. M.: A first look at cloud inhomogeneity and its
effect on lightning optical emission, Geophys. Res. Lett., 47,
e2020GL087094, https://doi.org/10.1029/2020GL087094,
2019. a
Cecil, D. J., Buechler, D. E., and Blakeslee, R. J.: Gridded lightning
climatology from TRMM-LIS and OTD: Dataset description, Atmos.
Res., 135, 404, https://doi.org/10.1016/j.atmosres.2012.06.028, 2014. a
Chanrion, O., Neubert, T., Mogensen, A., Yair, Y., Stendel, M.,
Singh, R., and Siingh, D.: Profuse activity of blue electrical
discharges at the tops of thunderstorms, Geophys. Res. Lett., 44, 496,
https://doi.org/10.1002/2016GL071311, 2017. a
Chanrion, O., Neubert, T., Lundgaard Rasmussen, I., Stoltze, C.,
Tcherniak, D., Jessen, N. C., Polny, J., Brauer, P., Balling,
J. E., Savstrup Kristensen, S., Forchhammer, S., Hofmeyer, P.,
Davidsen, P., Mikkelsen, O., Bo Hansen, D., Bhanderi, D. D. V.,
Petersen, C. G., and Lorenzen, M.: The Modular Multispectral Imaging
Array (MMIA) of the ASIM Payload on the International Space Station, Space
Sci. Rev., 215, 28, https://doi.org/10.1007/s11214-019-0593-y, 2019. a
Chern, J. L., Hsu, R. R., Su, H. T., Mende, S. B., Fukunishi, H.,
Takahashi, Y., and Lee, L. C.: Global survey of upper atmospheric
transient luminous events on the ROCSAT-2 satellite, J. Atmos. Solar-Terr.
Phy., 65, 647, https://doi.org/10.1016/S1364-6826(02)00317-6, 2003. a
Christian, H. J., Blakeslee, R. J., Boccippio, D. J., Boeck, W. L.,
Buechler, D. E., Driscoll, K. T., Goodman, S. J., Hall, J. M.,
Koshak, W. J., Mach, D. M., and Stewart, M. F.: Global frequency and
distribution of lightning as observed from space by the Optical Transient
Detector, J. Geophys. Res.-Atmos., 108, 4005, https://doi.org/10.1029/2002JD002347,
2003. a, b
Dwyer, J. R., Smith, D. M., and Cummer, S. A.: High-Energy Atmospheric
Physics: Terrestrial Gamma-Ray Flashes and Related Phenomena, Space Sci.
Rev., 173, 133, https://doi.org/10.1007/s11214-012-9894-0, 2012. a
Ebert, U., Nijdam, S., Li, C., Luque, A., Briels, T., and van
Veldhuizen, E.: Review of recent results on streamer discharges and
discussion of their relevance for sprites and lightning, J. Geophys. Res.-Space Phys., 115, A00E43, https://doi.org/10.1029/2009JA014867, 2010. a
Goodman, S. J., Blakeslee, R. J., Koshak, W. J., Mach, D., Bailey,
J., Buechler, D., Carey, L., Schultz, C., Bateman, M., McCaul, E.,
and Stano, G.: The GOES-R Geostationary Lightning Mapper (GLM),
Atmos. Res., 125, 34, https://doi.org/10.1016/j.atmosres.2013.01.006, 2013. a
Hale, G. M. and Querry, M. R.: Optical constants of water in the 200-nm to
200-micrometer wavelength region, Appl. Optics, 12, 555, https://doi.org/10.1364/AO.12.000555,
1973. a
Haynes, W.: CRC Handbook of Chemistry and Physics, 97th edition, CRC Press, Boca Raton, FL, USA, 2016. a
Iwabuchi, H.: Efficient Monte Carlo Methods for Radiative Transfer
Modeling, J. Atmos. Sci., 63, 2324,
https://doi.org/10.1175/JAS3755.1, 2006. a, b
Kneizys, F. X., Shettle, E. P., Gallery, W. O., Chetwynd, J. H., J.,
Abreu, L. W., McClatchey, R. A., Fenn, R. W., and Selby, J. E. A.:
Atmospheric transmittance/radiance: Computer code LOWTRAN 5, Unknow, 1980. a
Koshak, W. J., Solakiewicz, R. J., Phanord, D. D., and Blakeslee,
R. J.: Diffusion model for lightning radiative transfer, J. Geophys. Res., 99,
14361–14371, https://doi.org/10.1029/94JD00022, 1994. a, b, c
Krapivsky, P., Redner, S., and Ben-Naim, E.: A Kinetic View of Statistical
Physics, Cambridge University Press, Cambridge, UK, 2010. a
Le Vine, D. M.: Sources of the strongest RF radiation from lightning, J. Geophys. Res.,
85, 4091, https://doi.org/10.1029/JC085iC07p04091, 1980. a
Light, T. E., Suszcynsky, D. M., Kirkland, M. W., and Jacobson, A. R.:
Simulations of lightning optical waveforms as seen through clouds by
satellites, J. Geophys. Res., 106, 17103–17114, https://doi.org/10.1029/2001JD900051, 2001. a, b
Liu, F., Zhu, B., Lu, G., Qin, Z., Lei, J., Peng, K.-M., Chen,
A. B., Huang, A., Cummer, S. A., Chen, M., Ma, M., Lyu, F., and
Zhou, H.: Observations of Blue Discharges Associated With Negative Narrow
Bipolar Events in Active Deep Convection, Geophys. Res. Lett., 45, 2842,
https://doi.org/10.1002/2017GL076207, 2018. a
Luque, A.: aluque/CloudScat.jl: 1.0 release candidate 1 (Version 1.0rc1), Zenodo, https://doi.org/10.5281/zenodo.3842787, 2020. a
Mach, D. M., Christian, H. J., Blakeslee, R. J., Boccippio, D. J.,
Goodman, S. J., and Boeck, W. L.: Performance assessment of the Optical
Transient Detector and Lightning Imaging Sensor, J. Geophys. Res.-Atmos.,
112, D09210, https://doi.org/10.1029/2006JD007787, 2007. a
Minschwaner, K., Anderson, G. P., Hall, L. A., and Yoshino, K.:
Polynomial coefficients for calculating O2 Schumann-Runge cross
sections at 0.5 cm−1 resolution, J. Geophys. Res., 97, 10103,
https://doi.org/10.1029/92JD00661, 1992. a
Molina, L. T. and Molina, M. J.: Absolute absorption cross sections of
ozone in the 185- to 350-nm wavelength range, J. Geophys. Res., 91, 14501,
https://doi.org/10.1029/JD091iD13p14501, 1986. a, b
Neubert, T., Østgaard, N., Reglero, V., Chanrion, O., Heumesser,
M., Dimitriadou, K., Christiansen, F., Budtz-Jorgensen, C., Kuvvetli,
I., Rasmussen, I. L., Mezentsev, A., Marisaldi, M., Ullaland, K.,
Genov, G., Yang, S., Kochkin, P., Navarro-Gonzalez, J., Connell,
P. H., and Eyles, C. J.: A terrestrial gamma-ray flash and ionospheric
ultraviolet emissions powered by lightning, Science, 367, 183,
https://doi.org/10.1126/science.aax3872, 2020. a, b, c
Pan, L. L., Homeyer, C. R., Honomichl, S., Ridley, B. A., Weisman,
M., Barth, M. C., Hair, J. W., Fenn, M. A., Butler, C., Diskin,
G. S., Crawford, J. H., Ryerson, T. B., Pollack, I., Peischl, J., and
Huntrieser, H.: Thunderstorms enhance tropospheric ozone by wrapping and
shedding stratospheric air, Geophys. Res. Lett., 41, 7785,
https://doi.org/10.1002/2014GL061921, 2014. a
Pasko, V. P., Yair, Y., and Kuo, C.-L.: Lightning Related Transient
Luminous Events at High Altitude in the Earth's Atmosphere: Phenomenology,
Mechanisms and Effects, Space Sci. Rev., 168, 475,
https://doi.org/10.1007/s11214-011-9813-9, 2012. a
Peck, E. R. and Reeder, K.: Dispersion of Air, J. Opt.
Soc. Am., 62, 958–962, 1972. a
Peterson, M.: Using Lightning Flashes to Image Thunderclouds, J. Geophys.
Res.-Atmos., 124, 10175–10185, https://doi.org/10.1029/2019JD031055, 2019. a, b, c
Peterson, M. and Rudlosky, S.: The Time Evolution of Optical Lightning
Flashes, J. Geophys. Res.-Atmos., 124, 333, https://doi.org/10.1029/2018JD028741,
2019. a
Rison, W., Krehbiel, P. R., Stock, M. G., Edens, H. E., Shao, X.-M.,
Thomas, R. J., Stanley, M. A., and Zhang, Y.: Observations of narrow
bipolar events reveal how lightning is initiated in thunderstorms, Nat.
Commun., 7, 10721, https://doi.org/10.1038/ncomms10721, 2016. a, b
Sato, M., Takahashi, Y., Kikuchi, M., Suzuki, M., Yamazaki, A., and
Ushio, T.: Lightning and Sprite Imager (LSI) Onboard JEM-GLIMS, IEEJ
Transactions on Fundamentals and Materials, 131, 994,
https://doi.org/10.1541/ieejfms.131.994, 2011. a
Smith, D. A., Shao, X. M., Holden, D. N., Rhodes, C. T., Brook, M.,
Krehbiel, P. R., Stanley, M., Rison, W., and Thomas, R. J.: A
distinct class of isolated intracloud lightning discharges and their
associated radio emissions, J. Geophys. Res., 104, 4189, https://doi.org/10.1029/1998JD200045,
1999. a
Soler, S., Pérez-Invernón, F. J., Gordillo-Vázquez, F. J., Luque, A., Li,
D., Malagón-Romero, A., Neubert, T., Chanrion, O., Reglero, V.,
Navarro-Gonzalez, J., Lu, G., Zhang, H., Huang, A., and Østgaard, N.: Blue
Optical Observations of Narrow Bipolar Events by ASIM Suggest Corona Streamer
Activity in Thunderstorms, J. Geophys. Res.-Atmos., 125,
e2020JD032708, https://doi.org/10.1029/2020JD032708, 2020. a
Thomason, L. W. and Krider, E. P.: The Effects of Clouds on the Light
Produced by Lightning., J. Atmos. Sci., 39, 2051,
https://doi.org/10.1175/1520-0469(1982)039<2051:TEOCOT>2.0.CO;2, 1982. a, b, c
Tilles, J. N., Liu, N., Stanley, M. A., Krehbiel, P. R., Rison, W.,
Stock, M. G., Dwyer, J. R., Brown, R., and Wilson, J.: Fast negative
breakdown in thunderstorms, Nat. Commun., 10, 1648,
https://doi.org/10.1038/s41467-019-09621-z, 2019.
a
United States Committee on Extension to the Standard Atmosphere: U.S.
standard atmosphere, 1976, National Oceanic and Amospheric [sic]
Administration: for sale by the Supt. of Docs., U.S. Govt. Print. Off., Washington D.C., USA,
1976. a
van de Hulst, H.: Light Scattering by Small Particles, Dover Books on Physics,
Dover Publications, New York, USA, 1981. a
Warren, S. G. and Brandt, R. E.: Optical constants of ice from the
ultraviolet to the microwave: A revised compilation, J. Geophys. Res.-Atmos., 113, D14220, https://doi.org/10.1029/2007JD009744, 2008. a
Wilkman, O.: MieScatter,
available at: https://github.com/dronir/MieScatter.jl (last access: 10 November 2020), 2013. a
Zhang, D., Cummins, K. L., Bitzer, P., and Koshak, W. J.: Evaluation
of the Performance Characteristics of the Lightning Imaging Sensor, J. Atmos. Ocean. Tech., 36, 1015,
https://doi.org/10.1175/JTECH-D-18-0173.1, 2019. a
Short summary
Lightning flashes are often recorded from space-based platforms. Besides being valuable inputs for weather forecasting, these observations also enable research into fundamental questions regarding lightning physics. To exploit them, it is essential to understand how light propagates from a lightning flash to a space-based observation instrument. Here, we present an open-source software tool to model this process that extends on previous work and overcomes some of the existing limitations.
Lightning flashes are often recorded from space-based platforms. Besides being valuable inputs...
