Articles | Volume 16, issue 1
https://doi.org/10.5194/gmd-16-1-2023
© Author(s) 2023. 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-16-1-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
02 Jan 2023
Model evaluation paper |
| 02 Jan 2023
| 02 Jan 2023
Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model: RegCM
Sudipta Ghosh
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Centre of Excellence for Research on Clean Air, Indian Institute of
Technology Delhi, New Delhi, India
Sushant Das
Earth System Physics Section, International Centre for Theoretical
Physics (ICTP), Trieste, Italy
Nicole Riemer
Department of Atmospheric Sciences, University of Illinois at
Urbana-Champaign, Urbana, IL, USA
Graziano Giuliani
Earth System Physics Section, International Centre for Theoretical
Physics (ICTP), Trieste, Italy
Dilip Ganguly
Centre for Atmospheric Sciences, Indian Institute of Technology Delhi, New Delhi, India
Chandra Venkataraman
Department of Chemical Engineering, Indian Institute of Technology
Bombay, Mumbai, India
Filippo Giorgi
Earth System Physics Section, International Centre for Theoretical
Physics (ICTP), Trieste, Italy
Sachchida Nand Tripathi
Department of Civil Engineering, Indian Institute of Technology
Kanpur, Kanpur, India
Srikanthan Ramachandran
Space and Atmospheric Sciences Division, Physical Research Laboratory, Ahmedabad, India
Thazhathakal Ayyappen Rajesh
Space and Atmospheric Sciences Division, Physical Research Laboratory, Ahmedabad, India
Harish Gadhavi
Space and Atmospheric Sciences Division, Physical Research Laboratory, Ahmedabad, India
Atul Kumar Srivastava
Indian Institute of Tropical Meteorology, New Delhi Branch, New Delhi, India
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Ashutosh K. Shukla, Sachchida N. Tripathi, Shamitaksha Talukdar, Vishnu Murari, Sreenivas Gaddamidi, Manousos-Ioannis Manousakas, Vipul Lalchandani, Kuldeep Dixit, Vinayak M. Ruge, Peeyush Khare, Mayank Kumar, Vikram Singh, Neeraj Rastogi, Suresh Tiwari, Atul K. Srivastava, Dilip Ganguly, Kaspar Rudolf Daellenbach, and André S. H. Prévôt
Atmos. Chem. Phys., 25, 3765–3784, https://doi.org/10.5194/acp-25-3765-2025, https://doi.org/10.5194/acp-25-3765-2025, 2025
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Our study delves into the elemental composition of aerosols at three sites across the Indo-Gangetic Plain (IGP), revealing distinct patterns during pollution episodes. We found significant increases in chlorine (Cl)-rich and solid fuel combustion (SFC) sources, indicating dynamic emission sources, agricultural burning impacts, and meteorological influences. Surges in Cl-rich particles during cold periods highlight their role in particle growth under high-relative-humidity conditions.
Zhouyang Zhang, Jiandong Wang, Jiaping Wang, Nicole Riemer, Chao Liu, Yuzhi Jin, Zeyuan Tian, Jing Cai, Yueyue Cheng, Ganzhen Chen, Bin Wang, Shuxiao Wang, and Aijun Ding
Atmos. Chem. Phys., 25, 1869–1881, https://doi.org/10.5194/acp-25-1869-2025, https://doi.org/10.5194/acp-25-1869-2025, 2025
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Black carbon (BC) exerts notable warming effects. We use a particle-resolved model to investigate the long-term behavior of the BC mixing state, revealing its compositions, coating thickness distribution, and optical properties all stabilize with a characteristic time of less than 1 d. This study can effectively simplify the description of the BC mixing state, which facilitates the precise assessment of the optical properties of BC aerosols in global and chemical transport models.
Eric Martial Yao, Fabien Solmon, Marcellin Adon, Claire Delon, Corinne Galy-Lacaux, Graziano Giuliani, Bastien Sauvage, and Véronique Yoboue
EGUsphere, https://doi.org/10.5194/egusphere-2024-3179, https://doi.org/10.5194/egusphere-2024-3179, 2025
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As climate change and human activities intensify in Africa, understanding how air pollution, climate, and natural cycles interact is crucial. This study explores how nitrogen oxide emissions from African soils, especially in dry regions, contribute to atmospheric pollution. By using a climate-chemistry model, we show that considering these emissions improves predictions of nitrogen dioxide, nitric acid and ozone, although some discrepancies remain compared to observations.
Chimurkar Navinya, Taveen Singh Kapoor, Gupta Anurag, Chandra Venkataraman, Harish C. Phuleria, and Rajan K. Chakrabarty
Atmos. Chem. Phys., 24, 13285–13297, https://doi.org/10.5194/acp-24-13285-2024, https://doi.org/10.5194/acp-24-13285-2024, 2024
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Brown carbon (BrC) aerosols show an order-of-magnitude variation in their light absorption strength. Our understanding of BrC from real-world biomass burning remains limited, complicating the determination of its radiative impact. Our study reports absorption properties of BrC emitted from four major biomass burning sources using field measurements in India. It develops an absorption parameterization for BrC and examines the spatial variability in BrC's absorption strength across India.
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 17, 8399–8420, https://doi.org/10.5194/gmd-17-8399-2024, https://doi.org/10.5194/gmd-17-8399-2024, 2024
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This paper introduces a numerical method for simulating particle-based aerosol transport in atmospheric models. We detail the various numerical properties of the advection order method and demonstrate its implementation in a 3D weather prediction model (WRF) for the first time. Particle-based techniques improve the accuracy of aerosol size and composition predictions, which are key for aerosol–cloud and aerosol–radiation interactions.
Harish Shivraj Gadhavi, Akanksha Arora, Chaithanya Jain, Mahesh Kumar Sha, Frank Hase, Matthias Frey, Srikanthan Ramachandran, and Achuthan Jayaraman
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-167, https://doi.org/10.5194/amt-2024-167, 2024
Preprint under review for AMT
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We used a ground-based Fourier Transform Spectrometer to measure columnar greenhouse gas mixing ratios and validate methane observations from the GOSAT satellite and carbon dioxide observations from GOSAT and OCO-2 over India. Both satellites provide high precision and accuracy, making them suitable for emission flux estimates. Simulations using a Lagrangian dispersion model showed that background mixing ratio variations play a larger role than local source changes.
Zhenyu Zhang, Jing Li, Huizheng Che, Yueming Dong, Oleg Dubovik, Thomas Eck, Pawan Gupta, Brent Holben, Jhoon Kim, Elena Lind, Trailokya Saud, Sachchida Nand Tripathi, and Tong Ying
EGUsphere, https://doi.org/10.5194/egusphere-2024-2533, https://doi.org/10.5194/egusphere-2024-2533, 2024
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We used ground-based remote sensing data from the Aerosol Robotic Network to examine long-term trends in aerosol characteristics. We found aerosol loadings generally decreased globally, and aerosols became more scattering. These changes are closely related to variations in aerosol compositions, such as decreased anthropogenic emissions over East Asia, Europe, and North America, increased anthropogenic source over North India, increased dust activities over the Arabian Peninsula, etc.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
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For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Nishant Ajnoti, Hemant Gehlot, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 17, 1651–1664, https://doi.org/10.5194/amt-17-1651-2024, https://doi.org/10.5194/amt-17-1651-2024, 2024
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This research focuses on the optimal placement of hybrid instruments (sensors and monitors) to maximize satisfaction function considering population, PM2.5 concentration, budget, and other factors. Two algorithms are developed in this study: a genetic algorithm and a greedy algorithm. We tested these algorithms on various regions. The insights of this work aid in quantitative placement of air quality monitoring instruments in large cities, moving away from ad hoc approaches.
Piyushkumar N. Patel, Jonathan H. Jiang, Ritesh Gautam, Harish Gadhavi, Olga Kalashnikova, Michael J. Garay, Lan Gao, Feng Xu, and Ali Omar
Atmos. Chem. Phys., 24, 2861–2883, https://doi.org/10.5194/acp-24-2861-2024, https://doi.org/10.5194/acp-24-2861-2024, 2024
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Global measurements of cloud condensation nuclei (CCN) are essential for understanding aerosol–cloud interactions and predicting climate change. To address this gap, we introduced a remote sensing algorithm that retrieves vertically resolved CCN number concentrations from airborne and spaceborne lidar systems. This innovation offers a global distribution of CCN concentrations from space, facilitating model evaluation and precise quantification of aerosol climate forcing.
Wei Huang, Cheng Wu, Linyu Gao, Yvette Gramlich, Sophie L. Haslett, Joel Thornton, Felipe D. Lopez-Hilfiker, Ben H. Lee, Junwei Song, Harald Saathoff, Xiaoli Shen, Ramakrishna Ramisetty, Sachchida N. Tripathi, Dilip Ganguly, Feng Jiang, Magdalena Vallon, Siegfried Schobesberger, Taina Yli-Juuti, and Claudia Mohr
Atmos. Chem. Phys., 24, 2607–2624, https://doi.org/10.5194/acp-24-2607-2024, https://doi.org/10.5194/acp-24-2607-2024, 2024
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We present distinct molecular composition and volatility of oxygenated organic aerosol particles in different rural, urban, and mountain environments. We do a comprehensive investigation of the relationship between the chemical composition and volatility of oxygenated organic aerosol particles across different systems and environments. This study provides implications for volatility descriptions of oxygenated organic aerosol particles in different model frameworks.
Susanna Strada, Andrea Pozzer, Graziano Giuliani, Erika Coppola, Fabien Solmon, Xiaoyan Jiang, Alex Guenther, Efstratios Bourtsoukidis, Dominique Serça, Jonathan Williams, and Filippo Giorgi
Atmos. Chem. Phys., 23, 13301–13327, https://doi.org/10.5194/acp-23-13301-2023, https://doi.org/10.5194/acp-23-13301-2023, 2023
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Water deficit modifies emissions of isoprene, an aromatic compound released by plants that influences the production of an air pollutant such as ozone. Numerical modelling shows that, during the warmest and driest summers, isoprene decreases between −20 and −60 % over the Euro-Mediterranean region, while near-surface ozone only diminishes by a few percent. Decreases in isoprene emissions not only happen under dry conditions, but also could occur after prolonged or repeated water deficits.
Matthias Kohl, Jos Lelieveld, Sourangsu Chowdhury, Sebastian Ehrhart, Disha Sharma, Yafang Cheng, Sachchida Nand Tripathi, Mathew Sebastian, Govindan Pandithurai, Hongli Wang, and Andrea Pozzer
Atmos. Chem. Phys., 23, 13191–13215, https://doi.org/10.5194/acp-23-13191-2023, https://doi.org/10.5194/acp-23-13191-2023, 2023
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Knowledge on atmospheric ultrafine particles (UFPs) with a diameter smaller than 100 nm is crucial for public health and the hydrological cycle. We present a new global dataset of UFP concentrations at the Earth's surface derived with a comprehensive chemistry–climate model and evaluated with ground-based observations. The evaluation results are combined with high-resolution primary emissions to downscale UFP concentrations to an unprecedented horizontal resolution of 0.1° × 0.1°.
Costanza Del Gobbo, Renato R. Colucci, Giovanni Monegato, Manja Žebre, and Filippo Giorgi
Clim. Past, 19, 1805–1823, https://doi.org/10.5194/cp-19-1805-2023, https://doi.org/10.5194/cp-19-1805-2023, 2023
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We studied atmosphere–cryosphere interaction during the last phase of the Last Glacial Maximum in the Alpine region, using a high-resolution regional climate model. We analysed the climate south and north of the Alps, using a detailed map of the Alpine equilibrium line altitude (ELA) to study the mechanism that sustained the Alpine glaciers at 21 ka. The Genoa low and a mild Mediterranean Sea led to frequent snowfall in the southern Alps, thus preserving the glaciers and lowering the ELA.
Sophie L. Haslett, David M. Bell, Varun Kumar, Jay G. Slowik, Dongyu S. Wang, Suneeti Mishra, Neeraj Rastogi, Atinderpal Singh, Dilip Ganguly, Joel Thornton, Feixue Zheng, Yuanyuan Li, Wei Nie, Yongchun Liu, Wei Ma, Chao Yan, Markku Kulmala, Kaspar R. Daellenbach, David Hadden, Urs Baltensperger, Andre S. H. Prevot, Sachchida N. Tripathi, and Claudia Mohr
Atmos. Chem. Phys., 23, 9023–9036, https://doi.org/10.5194/acp-23-9023-2023, https://doi.org/10.5194/acp-23-9023-2023, 2023
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In Delhi, some aspects of daytime and nighttime atmospheric chemistry are inverted, and parodoxically, vehicle emissions may be limiting other forms of particle production. This is because the nighttime emissions of nitrogen oxide (NO) by traffic and biomass burning prevent some chemical processes that would otherwise create even more particles and worsen the urban haze.
Vaishali Jain, Nidhi Tripathi, Sachchida N. Tripathi, Mansi Gupta, Lokesh K. Sahu, Vishnu Murari, Sreenivas Gaddamidi, Ashutosh K. Shukla, and Andre S. H. Prevot
Atmos. Chem. Phys., 23, 3383–3408, https://doi.org/10.5194/acp-23-3383-2023, https://doi.org/10.5194/acp-23-3383-2023, 2023
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This research chemically characterises 173 different NMVOCs (non-methane volatile organic compounds) measured in real time for three seasons in the city of the central Indo-Gangetic basin of India, Lucknow. Receptor modelling is used to analyse probable sources of NMVOCs and their crucial role in forming ozone and secondary organic aerosols. It is observed that vehicular emissions and solid fuel combustion are the highest contributors to the emission of primary and secondary NMVOCs.
Hazel Vernier, Neeraj Rastogi, Hongyu Liu, Amit Kumar Pandit, Kris Bedka, Anil Patel, Madineni Venkat Ratnam, Buduru Suneel Kumar, Bo Zhang, Harish Gadhavi, Frank Wienhold, Gwenael Berthet, and Jean-Paul Vernier
Atmos. Chem. Phys., 22, 12675–12694, https://doi.org/10.5194/acp-22-12675-2022, https://doi.org/10.5194/acp-22-12675-2022, 2022
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The chemical composition of the stratospheric aerosols collected aboard high-altitude balloons above the summer Asian monsoon reveals the presence of nitrate/nitrite. Using numerical simulations and satellite observations, we found that pollution as well as lightning could explain some of our observations.
Yu Yao, Jeffrey H. Curtis, Joseph Ching, Zhonghua Zheng, and Nicole Riemer
Atmos. Chem. Phys., 22, 9265–9282, https://doi.org/10.5194/acp-22-9265-2022, https://doi.org/10.5194/acp-22-9265-2022, 2022
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Investigating the impacts of aerosol mixing state on aerosol optical properties has a long history from both the modeling and experimental perspective. In this study, we used particle-resolved simulations as a benchmark to determine the error in optical properties when using simplified aerosol representations. We found that errors in single scattering albedo due to the internal mixture assumptions can have substantial effects on calculating aerosol direct radiative forcing.
Varun Kumar, Stamatios Giannoukos, Sophie L. Haslett, Yandong Tong, Atinderpal Singh, Amelie Bertrand, Chuan Ping Lee, Dongyu S. Wang, Deepika Bhattu, Giulia Stefenelli, Jay S. Dave, Joseph V. Puthussery, Lu Qi, Pawan Vats, Pragati Rai, Roberto Casotto, Rangu Satish, Suneeti Mishra, Veronika Pospisilova, Claudia Mohr, David M. Bell, Dilip Ganguly, Vishal Verma, Neeraj Rastogi, Urs Baltensperger, Sachchida N. Tripathi, André S. H. Prévôt, and Jay G. Slowik
Atmos. Chem. Phys., 22, 7739–7761, https://doi.org/10.5194/acp-22-7739-2022, https://doi.org/10.5194/acp-22-7739-2022, 2022
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Here we present source apportionment results from the first field deployment in Delhi of an extractive electrospray ionization time-of-flight mass spectrometer (EESI-TOF). The EESI-TOF is a recently developed instrument capable of providing uniquely detailed online chemical characterization of organic aerosol (OA), in particular the secondary OA (SOA) fraction. Here, we are able to apportion not only primary OA but also SOA to specific sources, which is performed for the first time in Delhi.
Pawan Gupta, Prakash Doraiswamy, Jashwanth Reddy, Palak Balyan, Sagnik Dey, Ryan Chartier, Adeel Khan, Karmann Riter, Brandon Feenstra, Robert C. Levy, Nhu Nguyen Minh Tran, Olga Pikelnaya, Kurinji Selvaraj, Tanushree Ganguly, and Karthik Ganesan
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2022-140, https://doi.org/10.5194/amt-2022-140, 2022
Revised manuscript not accepted
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The use of low-cost sensors in air quality monitoring has been gaining interest across all walks of society. We present the results of evaluations of the PurpleAir against regulatory-grade PM2.5. The results indicate that with proper calibration, we can achieve bias-corrected PM2.5 data using PA sensors. Our study also suggests that pre-deployment calibrations developed at local or regional scales are required for the PA sensors to correct data from the field for scientific data analysis.
Matthew L. Dawson, Christian Guzman, Jeffrey H. Curtis, Mario Acosta, Shupeng Zhu, Donald Dabdub, Andrew Conley, Matthew West, Nicole Riemer, and Oriol Jorba
Geosci. Model Dev., 15, 3663–3689, https://doi.org/10.5194/gmd-15-3663-2022, https://doi.org/10.5194/gmd-15-3663-2022, 2022
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Progress in identifying complex, mixed-phase physicochemical processes has resulted in an advanced understanding of the evolution of atmospheric systems but has also introduced a level of complexity that few atmospheric models were designed to handle. We present a flexible treatment for multiphase chemical processes for models of diverse scale, from box up to global models. This enables users to build a customized multiphase mechanism that is accessible to a much wider community.
Himadri Sekhar Bhowmik, Ashutosh Shukla, Vipul Lalchandani, Jay Dave, Neeraj Rastogi, Mayank Kumar, Vikram Singh, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 15, 2667–2684, https://doi.org/10.5194/amt-15-2667-2022, https://doi.org/10.5194/amt-15-2667-2022, 2022
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This study presents comparisons between online and offline measurements of both refractory and non-refractory aerosol. This study shows differences between the measurements, related to either the limitations of the instrument (e.g., aerosol mass spectrometer only observing non-refractory aerosol) or known interferences with the technique (e.g., volatilization or reactions). The findings highlight the measurement methods' accuracy and imply the particular type of measurements needed.
Chandan Sarangi, TC Chakraborty, Sachchidanand Tripathi, Mithun Krishnan, Ross Morrison, Jonathan Evans, and Lina M. Mercado
Atmos. Chem. Phys., 22, 3615–3629, https://doi.org/10.5194/acp-22-3615-2022, https://doi.org/10.5194/acp-22-3615-2022, 2022
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Transpiration fluxes by vegetation are reduced under heat stress to conserve water. However, in situ observations over northern India show that the strength of the inverse association between transpiration and atmospheric vapor pressure deficit is weakening in the presence of heavy aerosol loading. This finding not only implicates the significant role of aerosols in modifying the evaporative fraction (EF) but also warrants an in-depth analysis of the aerosol–plant–temperature–EF continuum.
Erika Coppola, Paolo Stocchi, Emanuela Pichelli, Jose Abraham Torres Alavez, Russell Glazer, Graziano Giuliani, Fabio Di Sante, Rita Nogherotto, and Filippo Giorgi
Geosci. Model Dev., 14, 7705–7723, https://doi.org/10.5194/gmd-14-7705-2021, https://doi.org/10.5194/gmd-14-7705-2021, 2021
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In this work we describe the development of a non-hydrostatic version of the regional climate model RegCM4-NH, implemented to allow simulations at convection-permitting scales of <4 km for climate applications. The new core is described, and three case studies of intense convection are carried out to illustrate the model performances. Comparison with observations is much improved with respect to with coarse grid runs. RegCM4-NH offers a promising tool for climate investigations at a local scale.
Zhonghua Zheng, Matthew West, Lei Zhao, Po-Lun Ma, Xiaohong Liu, and Nicole Riemer
Atmos. Chem. Phys., 21, 17727–17741, https://doi.org/10.5194/acp-21-17727-2021, https://doi.org/10.5194/acp-21-17727-2021, 2021
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Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
Karn Vohra, Eloise A. Marais, Shannen Suckra, Louisa Kramer, William J. Bloss, Ravi Sahu, Abhishek Gaur, Sachchida N. Tripathi, Martin Van Damme, Lieven Clarisse, and Pierre-F. Coheur
Atmos. Chem. Phys., 21, 6275–6296, https://doi.org/10.5194/acp-21-6275-2021, https://doi.org/10.5194/acp-21-6275-2021, 2021
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We find satellite observations of atmospheric composition generally reproduce variability in surface air pollution, so we use their long record to estimate air quality trends in major UK and Indian cities. Our trend analysis shows that pollutants targeted with air quality policies have not declined in Delhi and Kanpur but have in London and Birmingham, with the exception of a recent and dramatic increase in reactive volatile organics in London. Unregulated ammonia has increased only in Delhi.
Pragati Rai, Jay G. Slowik, Markus Furger, Imad El Haddad, Suzanne Visser, Yandong Tong, Atinderpal Singh, Günther Wehrle, Varun Kumar, Anna K. Tobler, Deepika Bhattu, Liwei Wang, Dilip Ganguly, Neeraj Rastogi, Ru-Jin Huang, Jaroslaw Necki, Junji Cao, Sachchida N. Tripathi, Urs Baltensperger, and André S. H. Prévôt
Atmos. Chem. Phys., 21, 717–730, https://doi.org/10.5194/acp-21-717-2021, https://doi.org/10.5194/acp-21-717-2021, 2021
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We present a simple conceptual framework based on elemental size distributions and enrichment factors that allows for a characterization of major sources, site-to-site similarities, and local differences and the identification of key information required for efficient policy development. Absolute concentrations are by far the highest in Delhi, followed by Beijing, and then the European cities.
Ravi Sahu, Ayush Nagal, Kuldeep Kumar Dixit, Harshavardhan Unnibhavi, Srikanth Mantravadi, Srijith Nair, Yogesh Simmhan, Brijesh Mishra, Rajesh Zele, Ronak Sutaria, Vidyanand Motiram Motghare, Purushottam Kar, and Sachchida Nand Tripathi
Atmos. Meas. Tech., 14, 37–52, https://doi.org/10.5194/amt-14-37-2021, https://doi.org/10.5194/amt-14-37-2021, 2021
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A unique feature of our low-cost sensor deployment is a swap-out experiment wherein four of the six sensors were relocated to different sites in the two phases. The swap-out experiment is crucial in investigating the efficacy of calibration models when applied to weather and air quality conditions vastly different from those present during calibration. We developed a novel local calibration algorithm based on metric learning that offers stable and accurate calibration performance.
Erin E. McDuffie, Steven J. Smith, Patrick O'Rourke, Kushal Tibrewal, Chandra Venkataraman, Eloise A. Marais, Bo Zheng, Monica Crippa, Michael Brauer, and Randall V. Martin
Earth Syst. Sci. Data, 12, 3413–3442, https://doi.org/10.5194/essd-12-3413-2020, https://doi.org/10.5194/essd-12-3413-2020, 2020
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Global emission inventories are vital to understanding the impacts of air pollution on the environment, human health, and society. We update the open-source Community Emissions Data System (CEDS) to provide global gridded emissions of seven key air pollutants from 1970–2017 for 11 source sectors and multiple fuel types, including coal, solid biofuel, and liquid oil and natural gas. This dataset includes both monthly global gridded emissions and annual national totals.
Goutam Choudhury, Bhishma Tyagi, Naresh Krishna Vissa, Jyotsna Singh, Chandan Sarangi, Sachchida Nand Tripathi, and Matthias Tesche
Atmos. Chem. Phys., 20, 15389–15399, https://doi.org/10.5194/acp-20-15389-2020, https://doi.org/10.5194/acp-20-15389-2020, 2020
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This study uses 17 years (2001–2017) of observed rain rate, aerosol optical depth (AOD), meteorological reanalysis fields and outgoing long-wave radiation to investigate high precipitation events at the foothills of the Himalayas. Composite analysis of all data sets for high precipitation events (daily rainfall > 95th percentile) indicates clear and robust associations between high precipitation events, high aerosol loading and high moist static energy values.
Vijayakumar Sivadasan Nair, Filippo Giorgi, and Usha Keshav Hasyagar
Atmos. Chem. Phys., 20, 14457–14471, https://doi.org/10.5194/acp-20-14457-2020, https://doi.org/10.5194/acp-20-14457-2020, 2020
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Air pollution and wintertime fog over South Asia is a major concern due to its significant implications on air quality, visibility and health. Coupled model simulations show that hygroscopic growth of aerosols contributes significantly to the aerosol-induced cooling at the surface. Our analysis demonstrates that the aerosol–moisture interaction is the most significant contributor favouring and strengthening the high-aerosol conditions (poor air quality) prevailing over South Asia during winter.
Liwei Wang, Jay G. Slowik, Nidhi Tripathi, Deepika Bhattu, Pragati Rai, Varun Kumar, Pawan Vats, Rangu Satish, Urs Baltensperger, Dilip Ganguly, Neeraj Rastogi, Lokesh K. Sahu, Sachchida N. Tripathi, and André S. H. Prévôt
Atmos. Chem. Phys., 20, 9753–9770, https://doi.org/10.5194/acp-20-9753-2020, https://doi.org/10.5194/acp-20-9753-2020, 2020
Amit Misra, Sachchida Tripathi, Harjinder Sembhi, and Hartmut Boesch
Ann. Geophys. Discuss., https://doi.org/10.5194/angeo-2020-40, https://doi.org/10.5194/angeo-2020-40, 2020
Publication in ANGEO not foreseen
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In this work we validated Copernicus Aerosol Monitoring Service (CAMS) derived aerosol optical depth (AOD) at four sites in Indo-Gangetic Basin and used it to study aerosol climatology and trend in AOD at these sites. We find that sulphate AOD has largest influence on total aerosol climatology. Comparison of CAMS AOD with AERONET AOD shows better correlation when aerosol climatology is dominated by coarse particles. Trend analysis shows largest increase in organic matter and least in sea salt.
Havala O. T. Pye, Athanasios Nenes, Becky Alexander, Andrew P. Ault, Mary C. Barth, Simon L. Clegg, Jeffrey L. Collett Jr., Kathleen M. Fahey, Christopher J. Hennigan, Hartmut Herrmann, Maria Kanakidou, James T. Kelly, I-Ting Ku, V. Faye McNeill, Nicole Riemer, Thomas Schaefer, Guoliang Shi, Andreas Tilgner, John T. Walker, Tao Wang, Rodney Weber, Jia Xing, Rahul A. Zaveri, and Andreas Zuend
Atmos. Chem. Phys., 20, 4809–4888, https://doi.org/10.5194/acp-20-4809-2020, https://doi.org/10.5194/acp-20-4809-2020, 2020
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Acid rain is recognized for its impacts on human health and ecosystems, and programs to mitigate these effects have had implications for atmospheric acidity. Historical measurements indicate that cloud and fog droplet acidity has changed in recent decades in response to controls on emissions from human activity, while the limited trend data for suspended particles indicate acidity may be relatively constant. This review synthesizes knowledge on the acidity of atmospheric particles and clouds.
Rita Nogherotto, Adriano Fantini, Francesca Raffaele, Fabio Di Sante, Francesco Dottori, Erika Coppola, and Filippo Giorgi
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2019-356, https://doi.org/10.5194/nhess-2019-356, 2019
Revised manuscript not accepted
Kunal Bali, Sagnik Dey, Dilip Ganguly, and Krik R. Smith
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2019-731, https://doi.org/10.5194/acp-2019-731, 2019
Revised manuscript not accepted
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The ambient PM2.5 concentration has been observed using various in-situ instruments and satellites over India. But none of these observations have been able to cover the complete spatiotemporal coverage. So, here we tried to cover these gaps by using the hourly MERRA-2 aerosol reanalysis data over the Indian region. We hope these results will help formulate better air pollution mitigation plans so that the national burden of disease attributed to ambient air pollution could be decreased.
Tongshu Zheng, Michael H. Bergin, Ronak Sutaria, Sachchida N. Tripathi, Robert Caldow, and David E. Carlson
Atmos. Meas. Tech., 12, 5161–5181, https://doi.org/10.5194/amt-12-5161-2019, https://doi.org/10.5194/amt-12-5161-2019, 2019
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Here we present a simultaneous Gaussian process regression (GPR) and linear regression pipeline to calibrate and monitor dense wireless low-cost particulate matter sensor networks (WLPMSNs) on the fly by using all available reference monitors across an area. Our approach can achieve an overall 30 % prediction error at a 24 h scale, can differentiate malfunctioning nodes, and track drift. Our solution can substantially reduce manual labor for managing WLPMSNs and prolong their lifetimes.
Erika Brattich, Encarnación Serrano Castillo, Fabrizio Giulietti, Jean-Baptiste Renard, Sachi N. Tripathi, Kunal Ghosh, Gwenael Berthet, Damien Vignelles, and Laura Tositti
Ann. Geophys., 37, 389–403, https://doi.org/10.5194/angeo-37-389-2019, https://doi.org/10.5194/angeo-37-389-2019, 2019
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This paper describes the aerosol measurement setup and results obtained from the BEXUS18 stratospheric balloon within the A5-Unib (Advanced Atmospheric Aerosol Acquisition and Analysis) experiment performed on 10 October 2014 in northern Sweden (Kiruna). The experiment and the results here presented broaden the understanding of the processes linking the presence of charges with particles all over the vertical heights from the ground to the stratosphere.
Filippo Giorgi, Francesca Raffaele, and Erika Coppola
Earth Syst. Dynam., 10, 73–89, https://doi.org/10.5194/esd-10-73-2019, https://doi.org/10.5194/esd-10-73-2019, 2019
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The paper revisits the critical issue of precipitation characteristics in response to global warming through a new analysis of global and regional climate projections and a summary of previous work. Robust responses are identified and the underlying processes investigated. Examples of applications are given, such as the evaluation of risks associated with extremes. The paper, solicited by the EGU executive office, is based on the 2018 EGU Alexander von Humboldt medal lecture by Filippo Giorgi.
Brahima Koné, Arona Diedhiou, N'datchoh Evelyne Touré, Mouhamadou Bamba Sylla, Filippo Giorgi, Sandrine Anquetin, Adama Bamba, Adama Diawara, and Arsene Toka Kobea
Earth Syst. Dynam., 9, 1261–1278, https://doi.org/10.5194/esd-9-1261-2018, https://doi.org/10.5194/esd-9-1261-2018, 2018
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Simulations of regional climate are very sensitive to physical parameterization schemes, particularly over the tropics where convection plays a major role in monsoon dynamics. The latest version of RegCM4 was used to assess the performance and sensitivity of the simulated West African climate system to different convection schemes. The configuration of RegCM4 with CLM4.5 as a land surface model and the Emanuel convective scheme is recommended for the study of the West African climate.
Tongshu Zheng, Michael H. Bergin, Karoline K. Johnson, Sachchida N. Tripathi, Shilpa Shirodkar, Matthew S. Landis, Ronak Sutaria, and David E. Carlson
Atmos. Meas. Tech., 11, 4823–4846, https://doi.org/10.5194/amt-11-4823-2018, https://doi.org/10.5194/amt-11-4823-2018, 2018
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Low-cost particulate matter sensors are promising tools for supplementing existing air quality monitoring networks but their performance under field conditions is not well understood. We characterized how well Plantower PMS3003 sensors measure PM2.5 in a wide range of ambient conditions against different reference sensors. When a more precise reference method is used for calibration and proper RH corrections are made, our work suggests PMS3003's can measure PM2.5 within ~ 10 % of ambient values.
Chandra Venkataraman, Michael Brauer, Kushal Tibrewal, Pankaj Sadavarte, Qiao Ma, Aaron Cohen, Sreelekha Chaliyakunnel, Joseph Frostad, Zbigniew Klimont, Randall V. Martin, Dylan B. Millet, Sajeev Philip, Katherine Walker, and Shuxiao Wang
Atmos. Chem. Phys., 18, 8017–8039, https://doi.org/10.5194/acp-18-8017-2018, https://doi.org/10.5194/acp-18-8017-2018, 2018
Brent N. Holben, Jhoon Kim, Itaru Sano, Sonoyo Mukai, Thomas F. Eck, David M. Giles, Joel S. Schafer, Aliaksandr Sinyuk, Ilya Slutsker, Alexander Smirnov, Mikhail Sorokin, Bruce E. Anderson, Huizheng Che, Myungje Choi, James H. Crawford, Richard A. Ferrare, Michael J. Garay, Ukkyo Jeong, Mijin Kim, Woogyung Kim, Nichola Knox, Zhengqiang Li, Hwee S. Lim, Yang Liu, Hal Maring, Makiko Nakata, Kenneth E. Pickering, Stuart Piketh, Jens Redemann, Jeffrey S. Reid, Santo Salinas, Sora Seo, Fuyi Tan, Sachchida N. Tripathi, Owen B. Toon, and Qingyang Xiao
Atmos. Chem. Phys., 18, 655–671, https://doi.org/10.5194/acp-18-655-2018, https://doi.org/10.5194/acp-18-655-2018, 2018
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Aerosol particles, such as smoke, vary over space and time. This paper describes a series of very high-resolution ground-based aerosol measurement networks and associated studies that contributed new understanding of aerosol processes and detailed comparisons to satellite aerosol validation. Significantly, these networks also provide an opportunity to statistically relate grab samples of an aerosol parameter to companion satellite observations, a step toward air quality assessment from space.
Jeffrey H. Curtis, Nicole Riemer, and Matthew West
Geosci. Model Dev., 10, 4057–4079, https://doi.org/10.5194/gmd-10-4057-2017, https://doi.org/10.5194/gmd-10-4057-2017, 2017
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Traditional aerosol representations rely on simplifying assumptions about the aerosol composition in order to reduce computational cost. This introduces errors in estimates of aerosol impacts on climate. In contrast, the WRF-PartMC-MOSAIC-SCM model, presented here, uses a particle-resolved aerosol representation. It is made feasible by the development of efficient numerical methods, and allows for the capture of complex aerosol mixing states with altitude.
Joseph Ching, Jerome Fast, Matthew West, and Nicole Riemer
Atmos. Chem. Phys., 17, 7445–7458, https://doi.org/10.5194/acp-17-7445-2017, https://doi.org/10.5194/acp-17-7445-2017, 2017
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The composition of individual aerosols affects their cloud condensation nuclei (CCN) properties, but is challenging to represent in models. This study quantifies the error in CCN calculations when per-particle information is neglected by using a metric for the composition diversity within a population. With more particle-level measurements from field campaigns, the approach is useful for quantifying uncertainties in composition-dependent quantities regarding aerosol–cloud–climate interactions.
Chandan Sarangi, Sachchida Nand Tripathi, Vijay P. Kanawade, Ilan Koren, and D. Sivanand Pai
Atmos. Chem. Phys., 17, 5185–5204, https://doi.org/10.5194/acp-17-5185-2017, https://doi.org/10.5194/acp-17-5185-2017, 2017
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Aerosol-induced perturbations in cloud systems and rainfall are very uncertain. This study provides observational evidence of a robust positive association between aerosol–cloud–rainfall properties over the Indian summer monsoon region. Observed and modeled aerosol–cloud microphysical changes illustrate that cloud invigoration under a high AOD scenario can explain most of the aerosol-associated changes in cloud fraction, cloud top pressure, and surface rainfall over this region.
William J. Gutowski Jr., Filippo Giorgi, Bertrand Timbal, Anne Frigon, Daniela Jacob, Hyun-Suk Kang, Krishnan Raghavan, Boram Lee, Christopher Lennard, Grigory Nikulin, Eleanor O'Rourke, Michel Rixen, Silvina Solman, Tannecia Stephenson, and Fredolin Tangang
Geosci. Model Dev., 9, 4087–4095, https://doi.org/10.5194/gmd-9-4087-2016, https://doi.org/10.5194/gmd-9-4087-2016, 2016
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The Coordinated Regional Downscaling Experiment (CORDEX) is a diagnostic MIP in CMIP6. CORDEX builds on a foundation of previous downscaling intercomparison projects to provide a common framework for downscaling activities around the world. The CORDEX Regional Challenges provide a focus for downscaling research and a basis for making use of CMIP6 global output to produce downscaled projected changes in regional climates, and assess sources of uncertainties in the projections.
Amit Misra, Vijay P. Kanawade, and Sachchida Nand Tripathi
Ann. Geophys., 34, 657–671, https://doi.org/10.5194/angeo-34-657-2016, https://doi.org/10.5194/angeo-34-657-2016, 2016
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For an accurate understanding of earth climate system, it is necessary to evaluate the performance of the climate models used to perform these simulations. In this work we have examined aerosol optical depths simulated by 17 models by comparing them with satellite-derived aerosol optical depth. Our results indicate the role of dust aerosols and biogeochemistry in the simulation of aerosols by models.
Graydon Snider, Crystal L. Weagle, Kalaivani K. Murdymootoo, Amanda Ring, Yvonne Ritchie, Emily Stone, Ainsley Walsh, Clement Akoshile, Nguyen Xuan Anh, Rajasekhar Balasubramanian, Jeff Brook, Fatimah D. Qonitan, Jinlu Dong, Derek Griffith, Kebin He, Brent N. Holben, Ralph Kahn, Nofel Lagrosas, Puji Lestari, Zongwei Ma, Amit Misra, Leslie K. Norford, Eduardo J. Quel, Abdus Salam, Bret Schichtel, Lior Segev, Sachchida Tripathi, Chien Wang, Chao Yu, Qiang Zhang, Yuxuan Zhang, Michael Brauer, Aaron Cohen, Mark D. Gibson, Yang Liu, J. Vanderlei Martins, Yinon Rudich, and Randall V. Martin
Atmos. Chem. Phys., 16, 9629–9653, https://doi.org/10.5194/acp-16-9629-2016, https://doi.org/10.5194/acp-16-9629-2016, 2016
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We examine the chemical composition of fine particulate matter (PM2.5) collected on filters at traditionally undersampled, globally dispersed urban locations. Several PM2.5 chemical components (e.g. ammonium sulfate, ammonium nitrate, and black carbon) vary by more than an order of magnitude between sites while aerosol hygroscopicity varies by a factor of 2. Enhanced anthropogenic dust fractions in large urban areas are apparent from high Zn : Al ratios.
Rita Nogherotto, Adrian Mark Tompkins, Graziano Giuliani, Erika Coppola, and Filippo Giorgi
Geosci. Model Dev., 9, 2533–2547, https://doi.org/10.5194/gmd-9-2533-2016, https://doi.org/10.5194/gmd-9-2533-2016, 2016
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The paper presents a new cloud scheme for regional climate model RegCM4.5. The new scheme treats microphysical processes occurring within stratiform clouds and with respect to the pre-existing scheme is able to allow a more physically realistic representation of cloud microphysics and distribution, improving the representation of the longwave and shortwave components of the cloud radiative forcing.
Li Liu, Fabien Solmon, Robert Vautard, Lynda Hamaoui-Laguel, Csaba Zsolt Torma, and Filippo Giorgi
Biogeosciences, 13, 2769–2786, https://doi.org/10.5194/bg-13-2769-2016, https://doi.org/10.5194/bg-13-2769-2016, 2016
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To study the distribution of airborne ragweed pollen in changing environments and associated health risks over Europe, we introduce an approach with explicit treatment of pollen ripening, release and dispersion due to environmental drivers in an online modelling framework where climate is integrated with dispersion and vegetation production. From a simulated pollen season and concentration pattern health risks are evaluated through calculation of exposure time above health-relevant threshold levels.
Megan D. Willis, Robert M. Healy, Nicole Riemer, Matthew West, Jon M. Wang, Cheol-Heon Jeong, John C. Wenger, Greg J. Evans, Jonathan P. D. Abbatt, and Alex K. Y. Lee
Atmos. Chem. Phys., 16, 4693–4706, https://doi.org/10.5194/acp-16-4693-2016, https://doi.org/10.5194/acp-16-4693-2016, 2016
A. Arola, G. L. Schuster, M. R. A. Pitkänen, O. Dubovik, H. Kokkola, A. V. Lindfors, T. Mielonen, T. Raatikainen, S. Romakkaniemi, S. N. Tripathi, and H. Lihavainen
Atmos. Chem. Phys., 15, 12731–12740, https://doi.org/10.5194/acp-15-12731-2015, https://doi.org/10.5194/acp-15-12731-2015, 2015
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There have been relatively few measurement-based estimates for the direct radiative effect of brown carbon so far. This is first time that the direct radiative effect of brown carbon is estimated by exploiting the AERONET-retrieved imaginary indices. We estimated it for four sites in the Indo-Gangetic Plain: Karachi, Lahore,
Kanpur and Gandhi College.
C. Chaudhuri, S. Tripathi, R. Srivastava, and A. Misra
Ann. Geophys., 33, 671–686, https://doi.org/10.5194/angeo-33-671-2015, https://doi.org/10.5194/angeo-33-671-2015, 2015
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In this paper a Himalayan cloudburst event is investigated. The conditions of formation, evolution, and triggering mechanisms of this cloudburst are studied, looking at varieties of observed data sets and simulation with the Weather Research and Forecasting (WRF) model. This cloudburst event is attributed to two mesoscale convective systems originating from Madhya Pradesh and Tibet which interacted over Uttarkashi, and under orographic uplifting in the presence of favorable moisture conditions.
L. Fierce, N. Riemer, and T. C. Bond
Atmos. Chem. Phys., 15, 3173–3191, https://doi.org/10.5194/acp-15-3173-2015, https://doi.org/10.5194/acp-15-3173-2015, 2015
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The timescale for particles containing black carbon to age from hydrophobic to hygroscopic strongly influences black carbon's atmospheric lifetime and climate impact. This paper identifies the minimal set of independent variables needed to explain variance in this aging timescale. This work distills the complex interactions captured by a particle-resolved aerosol model to a few input variables and is a first step toward developing physically based parameterizations of aerosol aging.
G. Snider, C. L. Weagle, R. V. Martin, A. van Donkelaar, K. Conrad, D. Cunningham, C. Gordon, M. Zwicker, C. Akoshile, P. Artaxo, N. X. Anh, J. Brook, J. Dong, R. M. Garland, R. Greenwald, D. Griffith, K. He, B. N. Holben, R. Kahn, I. Koren, N. Lagrosas, P. Lestari, Z. Ma, J. Vanderlei Martins, E. J. Quel, Y. Rudich, A. Salam, S. N. Tripathi, C. Yu, Q. Zhang, Y. Zhang, M. Brauer, A. Cohen, M. D. Gibson, and Y. Liu
Atmos. Meas. Tech., 8, 505–521, https://doi.org/10.5194/amt-8-505-2015, https://doi.org/10.5194/amt-8-505-2015, 2015
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We have initiated a global network of ground-level monitoring stations to measure concentrations of fine aerosols in urban environments. Our findings include major ions species, total mass, and total scatter at three wavelengths. Results will be used to further evaluate and enhance satellite remote sensing estimates.
M. A. H. Zaroug, F. Giorgi, E. Coppola, G. M. Abdo, and E. A. B. Eltahir
Hydrol. Earth Syst. Sci., 18, 4311–4323, https://doi.org/10.5194/hess-18-4311-2014, https://doi.org/10.5194/hess-18-4311-2014, 2014
R. M. Healy, N. Riemer, J. C. Wenger, M. Murphy, M. West, L. Poulain, A. Wiedensohler, I. P. O'Connor, E. McGillicuddy, J. R. Sodeau, and G. J. Evans
Atmos. Chem. Phys., 14, 6289–6299, https://doi.org/10.5194/acp-14-6289-2014, https://doi.org/10.5194/acp-14-6289-2014, 2014
J. Huttunen, A. Arola, G. Myhre, A. V. Lindfors, T. Mielonen, S. Mikkonen, J. S. Schafer, S. N. Tripathi, M. Wild, M. Komppula, and K. E. J. Lehtinen
Atmos. Chem. Phys., 14, 6103–6110, https://doi.org/10.5194/acp-14-6103-2014, https://doi.org/10.5194/acp-14-6103-2014, 2014
J. C. Kaiser, J. Hendricks, M. Righi, N. Riemer, R. A. Zaveri, S. Metzger, and V. Aquila
Geosci. Model Dev., 7, 1137–1157, https://doi.org/10.5194/gmd-7-1137-2014, https://doi.org/10.5194/gmd-7-1137-2014, 2014
J. Tian, N. Riemer, M. West, L. Pfaffenberger, H. Schlager, and A. Petzold
Atmos. Chem. Phys., 14, 5327–5347, https://doi.org/10.5194/acp-14-5327-2014, https://doi.org/10.5194/acp-14-5327-2014, 2014
M. A. H. Zaroug, E. A. B. Eltahir, and F. Giorgi
Hydrol. Earth Syst. Sci., 18, 1239–1249, https://doi.org/10.5194/hess-18-1239-2014, https://doi.org/10.5194/hess-18-1239-2014, 2014
J. M. Livingston, J. Redemann, Y. Shinozuka, R. Johnson, P. B. Russell, Q. Zhang, S. Mattoo, L. Remer, R. Levy, L. Munchak, and S. Ramachandran
Atmos. Chem. Phys., 14, 2015–2038, https://doi.org/10.5194/acp-14-2015-2014, https://doi.org/10.5194/acp-14-2015-2014, 2014
M. Michael, A. Yadav, S. N. Tripathi, V. P. Kanawade, A. Gaur, P. Sadavarte, and C. Venkataraman
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmdd-7-431-2014, https://doi.org/10.5194/gmdd-7-431-2014, 2014
Revised manuscript not accepted
N. Riemer and M. West
Atmos. Chem. Phys., 13, 11423–11439, https://doi.org/10.5194/acp-13-11423-2013, https://doi.org/10.5194/acp-13-11423-2013, 2013
J.-B. Renard, S. N. Tripathi, M. Michael, A. Rawal, G. Berthet, M. Fullekrug, R. G. Harrison, C. Robert, M. Tagger, and B. Gaubicher
Atmos. Chem. Phys., 13, 11187–11194, https://doi.org/10.5194/acp-13-11187-2013, https://doi.org/10.5194/acp-13-11187-2013, 2013
A. Arola, T. F. Eck, J. Huttunen, K. E. J. Lehtinen, A. V. Lindfors, G. Myhre, A. Smirnov, S. N. Tripathi, and H. Yu
Atmos. Chem. Phys., 13, 7895–7901, https://doi.org/10.5194/acp-13-7895-2013, https://doi.org/10.5194/acp-13-7895-2013, 2013
M. Michael, A. Yadav, S. N. Tripathi, V. P. Kanawade, A. Gaur, P. Sadavarte, and C. Venkataraman
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-13-12287-2013, https://doi.org/10.5194/acpd-13-12287-2013, 2013
Revised manuscript has not been submitted
U. U. Turuncoglu, G. Giuliani, N. Elguindi, and F. Giorgi
Geosci. Model Dev., 6, 283–299, https://doi.org/10.5194/gmd-6-283-2013, https://doi.org/10.5194/gmd-6-283-2013, 2013
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Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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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 rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
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
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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.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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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 at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
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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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
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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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
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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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
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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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
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.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
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.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
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.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
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
Short summary
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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.
Juan Zhao, Jianping Guo, and Xiaohui Zheng
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-194, https://doi.org/10.5194/gmd-2024-194, 2024
Revised manuscript accepted for GMD
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A series of observing system simulation experiments are conducted to assess the impact of multiple radar wind profiler (RWP) networks on convective scale numerical weather prediction. Results from three southwest-type heavy rainfall cases in the Beijing-Tianjin-Hebei region suggest the added forecast skill of ridge and foothill networks associated with the Taihang Mountains over the existing RWP network. This research provides valuable guidance for designing optimal RWP networks in the region.
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.
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Short summary
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty in climate projections. Here, we implement region-specific emission fluxes and a more accurate scheme for carbonaceous aerosol ageing processes in a regional climate model (RegCM4) and show that it improves model performance significantly against in situ, reanalysis, and satellite data over the Indian subcontinent. We recommend improving the model performance before using them for climate studies.
Accurate representation of aerosols in climate models is critical for minimizing the uncertainty...
