Articles | Volume 17, issue 7
https://doi.org/10.5194/gmd-17-2617-2024
© Author(s) 2024. 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-17-2617-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
10 Apr 2024
Model description paper |
| 10 Apr 2024
| 10 Apr 2024
Decision Support System version 1.0 (DSS v1.0) for air quality management in Delhi, India
Gaurav Govardhan
CORRESPONDING AUTHOR
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
National Centre for Medium-Range Weather Forecasting, Ministry of Earth Sciences, Noida, Uttar Pradesh, India
Sachin D. Ghude
CORRESPONDING AUTHOR
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Rajesh Kumar
NSF National Center for Atmospheric Research, Boulder, CO, United States of America
Sumit Sharma
The Energy and Resources Institute, Delhi, India
Preeti Gunwani
India Meteorology Department, Ministry of Earth Sciences, Delhi, India
Chinmay Jena
India Meteorology Department, Ministry of Earth Sciences, Delhi, India
Prafull Yadav
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, Maharashtra, India
Shubhangi Ingle
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Sreyashi Debnath
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, Maharashtra, India
Pooja Pawar
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Department of Chemical Technology, Kalinga Institute of Industrial Technology (KIIT), Bhubaneshwar, India
Prodip Acharja
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Department of Atmospheric and Space Sciences, Savitribai Phule Pune University, Pune, Maharashtra, India
Rajmal Jat
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Gayatry Kalita
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Rupal Ambulkar
Indian Institute of Tropical Meteorology, Ministry of Earth Sciences, Pune, Maharashtra, India
Department of Environmental Sciences, Savitribai Phule Pune University, Pune, India
Santosh Kulkarni
Centre for Development of Advanced Computing, Innovation Park, Pune, Maharashtra, India
Akshara Kaginalkar
Centre for Development of Advanced Computing, Innovation Park, Pune, Maharashtra, India
Vijay K. Soni
India Meteorology Department, Ministry of Earth Sciences, Delhi, India
Ravi S. Nanjundiah
Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bengaluru, India
Divecha Centre for Climate Change, Indian Institute of Science, Bengaluru, India
Madhavan Rajeevan
National Centre for Earth Science Studies, Thiruvananthapuram, Kerala, India
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Pooja V. Pawar, Sachin D. Ghude, Chinmay Jena, Andrea Móring, Mark A. Sutton, Santosh Kulkarni, Deen Mani Lal, Divya Surendran, Martin Van Damme, Lieven Clarisse, Pierre-François Coheur, Xuejun Liu, Gaurav Govardhan, Wen Xu, Jize Jiang, and Tapan Kumar Adhya
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Chinmay Jena, Sachin D. Ghude, Rachana Kulkarni, Sreyashi Debnath, Rajesh Kumar, Vijay Kumar Soni, Prodip Acharja, Santosh H. Kulkarni, Manoj Khare, Akshara J. Kaginalkar, Dilip M. Chate, Kaushar Ali, Ravi S. Nanjundiah, and Madhavan N. Rajeevan
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2020-673, https://doi.org/10.5194/acp-2020-673, 2020
Publication in ACP not foreseen
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Teruyuki Nakajima, Monica Campanelli, Huizheng Che, Victor Estellés, Hitoshi Irie, Sang-Woo Kim, Jhoon Kim, Dong Liu, Tomoaki Nishizawa, Govindan Pandithurai, Vijay Kumar Soni, Boossarasiri Thana, Nas-Urt Tugjsurn, Kazuma Aoki, Sujung Go, Makiko Hashimoto, Akiko Higurashi, Stelios Kazadzis, Pradeep Khatri, Natalia Kouremeti, Rei Kudo, Franco Marenco, Masahiro Momoi, Shantikumar S. Ningombam, Claire L. Ryder, Akihiro Uchiyama, and Akihiro Yamazaki
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Meng Gao, Jinhui Gao, Bin Zhu, Rajesh Kumar, Xiao Lu, Shaojie Song, Yuzhong Zhang, Beixi Jia, Peng Wang, Gufran Beig, Jianlin Hu, Qi Ying, Hongliang Zhang, Peter Sherman, and Michael B. McElroy
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Suvarna Fadnavis, Rolf Müller, Gayatry Kalita, Matthew Rowlinson, Alexandru Rap, Jui-Lin Frank Li, Blaž Gasparini, and Anton Laakso
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This paper highlights the impact of Asian anthropogenic emission changes in SO2 on sulfate loading in the Asian upper troposphere–lower stratosphere from a global chemistry–climate model and satellite remote sensing. Estimated seasonal mean direct radiative forcing at the top of the atmosphere induced by the increase in Indian SO2 is −0.2–−1.5 W m2 over India. Chinese SO2 emission reduction leads to a positive radiative forcing of ~0.6–6 W m2 over China. It will likely decrease Indian rainfall.
Zainab Q. Hakim, Scott Archer-Nicholls, Gufran Beig, Gerd A. Folberth, Kengo Sudo, Nathan Luke Abraham, Sachin Ghude, Daven K. Henze, and Alexander T. Archibald
Atmos. Chem. Phys., 19, 6437–6458, https://doi.org/10.5194/acp-19-6437-2019, https://doi.org/10.5194/acp-19-6437-2019, 2019
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Surface ozone is an important air pollutant and recent work has calculated that large numbers of people die prematurely because of exposure to high levels of surface ozone in India. However, these calculations require model simulations of ozone as key inputs.
Here we perform the most thorough evaluation of global model surface ozone over India to date. These analyses of model simulations and observations highlight some successes and shortcomings and the need for further process-based studies.
Marianne Tronstad Lund, Gunnar Myhre, Amund Søvde Haslerud, Ragnhild Bieltvedt Skeie, Jan Griesfeller, Stephen Matthew Platt, Rajesh Kumar, Cathrine Lund Myhre, and Michael Schulz
Geosci. Model Dev., 11, 4909–4931, https://doi.org/10.5194/gmd-11-4909-2018, https://doi.org/10.5194/gmd-11-4909-2018, 2018
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Atmospheric aerosols play a key role in the climate system, but their exact impact on the energy balance remains uncertain. Accurate representation of the geographical distribution and properties of aerosols in global models is key to reduce this uncertainty. Here we use a new emission inventory and a range of observations to carefully validate a state-of-the-art model and present an updated estimate of the net direct effect of anthropogenic aerosols since the preindustrial era.
Piyush Bhardwaj, Manish Naja, Maheswar Rupakheti, Aurelia Lupascu, Andrea Mues, Arnico Kumar Panday, Rajesh Kumar, Khadak Singh Mahata, Shyam Lal, Harish C. Chandola, and Mark G. Lawrence
Atmos. Chem. Phys., 18, 11949–11971, https://doi.org/10.5194/acp-18-11949-2018, https://doi.org/10.5194/acp-18-11949-2018, 2018
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This study provides information about the regional variabilities in some of the pollutants using observations in Nepal and India. It is shown that agricultural crop residue burning leads to a significant enhancement in ozone and CO over a wider region. Further, the wintertime higher ozone levels are shown to be largely due to local emissions, while regional transport could be important in spring and hence shows the role of regional sources versus local sources in the Kathmandu Valley.
Matthieu Pommier, Hilde Fagerli, Michael Gauss, David Simpson, Sumit Sharma, Vinay Sinha, Sachin D. Ghude, Oskar Landgren, Agnes Nyiri, and Peter Wind
Atmos. Chem. Phys., 18, 103–127, https://doi.org/10.5194/acp-18-103-2018, https://doi.org/10.5194/acp-18-103-2018, 2018
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India has to cope with a poor air quality, and this work shows a predicted increase in pollution (O3 & PM2.5) if no further policy efforts are made in the future. Climate change will modify the soil moisture leading to changes in O3. Changes in PM2.5 are related to changes in precipitation, biogenic emissions and wind speed. It is also shown that in the 2050s, the secondary inorganic aerosols will become the main component of PM2.5 over India related to the increase in anthropogenic emissions.
Youhua Tang, Mariusz Pagowski, Tianfeng Chai, Li Pan, Pius Lee, Barry Baker, Rajesh Kumar, Luca Delle Monache, Daniel Tong, and Hyun-Cheol Kim
Geosci. Model Dev., 10, 4743–4758, https://doi.org/10.5194/gmd-10-4743-2017, https://doi.org/10.5194/gmd-10-4743-2017, 2017
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In order to evaluate the data assimilation tools for regional real-time PM2.5 forecasts, we applied a 3D-Var assimilation tool to adjust the aerosol initial condition by assimilating satellite-retrieved aerosol optical depth and surface PM2.5 observations for a regional air quality model, which is compared to another assimilation method, optimal interpolation. We discuss the pros and cons of these two assimilation methods based on the comparison of their 1-month four-cycles-per-day runs.
Suvarna Fadnavis, Gayatry Kalita, K. Ravi Kumar, Blaž Gasparini, and Jui-Lin Frank Li
Atmos. Chem. Phys., 17, 11637–11654, https://doi.org/10.5194/acp-17-11637-2017, https://doi.org/10.5194/acp-17-11637-2017, 2017
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In this study, the model simulations show that monsoon convection over the Bay of Bengal, the South China Sea and southern flanks of the Himalayas transports Asian carbonaceous aerosol into the UTLS. Carbonaceous aerosol induces enhancement in heating rate, vertical velocity and water vapor transport in the UTLS. Doubling of carbonaceous aerosols creates an anomalous warming over the TP. It generates monsoon Hadley circulation and thus increases precipitation over India and northeast China.
Sarah Safieddine, Anne Boynard, Nan Hao, Fuxiang Huang, Lili Wang, Dongsheng Ji, Brice Barret, Sachin D. Ghude, Pierre-François Coheur, Daniel Hurtmans, and Cathy Clerbaux
Atmos. Chem. Phys., 16, 10489–10500, https://doi.org/10.5194/acp-16-10489-2016, https://doi.org/10.5194/acp-16-10489-2016, 2016
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The Asian Summer Monsoon has implication on the weather and climate system as well as pollutants concentration over the monsoon regions leading to effects on the global air quality. Our results, combining satellite, aircraft and ground station data, show that tropospheric ozone, decrease during the period May–August over East and South Asia due to the Monsoon. The magnitude of this drop depends largely on meteorology and geographic location.
R. Kumar, M. C. Barth, V. S. Nair, G. G. Pfister, S. Suresh Babu, S. K. Satheesh, K. Krishna Moorthy, G. R. Carmichael, Z. Lu, and D. G. Streets
Atmos. Chem. Phys., 15, 5415–5428, https://doi.org/10.5194/acp-15-5415-2015, https://doi.org/10.5194/acp-15-5415-2015, 2015
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We examine differences in the surface BC between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identify dominant sources of BC in South Asia during ICARB. Anthropogenic emissions were the main source of BC during ICARB and had about 5 times stronger influence on the BoB compared to the AS. Regional-scale transport contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions.
S. Fadnavis, M. G. Schultz, K. Semeniuk, A. S. Mahajan, L. Pozzoli, S. Sonbawne, S. D. Ghude, M. Kiefer, and E. Eckert
Atmos. Chem. Phys., 14, 12725–12743, https://doi.org/10.5194/acp-14-12725-2014, https://doi.org/10.5194/acp-14-12725-2014, 2014
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The Asian summer monsoon transports pollutants from local emission sources to the upper troposphere and lower stratosphere (UTLS). The increasing trend of these pollutants may have climatic impact. This study addresses the impact of convectively lifted Indian and Chinese emissions on the ULTS. Sensitivity experiments with emission changes in particular regions show that Chinese emissions have a greater impact on the concentrations of NOY species than Indian emissions.
R. Kumar, M. C. Barth, S. Madronich, M. Naja, G. R. Carmichael, G. G. Pfister, C. Knote, G. P. Brasseur, N. Ojha, and T. Sarangi
Atmos. Chem. Phys., 14, 6813–6834, https://doi.org/10.5194/acp-14-6813-2014, https://doi.org/10.5194/acp-14-6813-2014, 2014
R. Kumar, M. C. Barth, G. G. Pfister, M. Naja, and G. P. Brasseur
Atmos. Chem. Phys., 14, 2431–2446, https://doi.org/10.5194/acp-14-2431-2014, https://doi.org/10.5194/acp-14-2431-2014, 2014
Related subject area
Atmospheric sciences
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Air quality modeling intercomparison and multiscale ensemble chain for Latin America
Recommended coupling to global meteorological fields for long-term tracer simulations with WRF-GHG
Selecting CMIP6 global climate models (GCMs) for Coordinated Regional Climate Downscaling Experiment (CORDEX) dynamical downscaling over Southeast Asia using a standardised benchmarking framework
Improved definition of prior uncertainties in CO2 and CO fossil fuel fluxes and its impact on multi-species inversion with GEOS-Chem (v12.5)
RASCAL v1.0: an open-source tool for climatological time series reconstruction and extension
Introducing graupel density prediction in Weather Research and Forecasting (WRF) double-moment 6-class (WDM6) microphysics and evaluation of the modified scheme during the ICE-POP field campaign
Enabling high-performance cloud computing for the Community Multiscale Air Quality Model (CMAQ) version 5.3.3: performance evaluation and benefits for the user community
Atmospheric-river-induced precipitation in California as simulated by the regionally refined Simple Convective Resolving E3SM Atmosphere Model (SCREAM) Version 0
Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model
GPU-HADVPPM4HIP V1.0: using the heterogeneous-compute interface for portability (HIP) to speed up the piecewise parabolic method in the CAMx (v6.10) air quality model on China's domestic GPU-like accelerator
Preliminary evaluation of the effect of electro-coalescence with conducting sphere approximation on the formation of warm cumulus clouds using SCALE-SDM version 0.2.5–2.3.0
Exploring the footprint representation of microwave radiance observations in an Arctic limited-area data assimilation system
Orbital-Radar v1.0.0: A tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
Analysis of model error in forecast errors of extended atmospheric Lorenz 05 systems and the ECMWF system
Description and validation of Vehicular Emissions from Road Traffic (VERT) 1.0, an R-based framework for estimating road transport emissions from traffic flows
AeroMix v1.0.1: a Python package for modeling aerosol optical properties and mixing states
Impact of ITCZ width on global climate: ITCZ-MIP
Deep-learning-driven simulations of boundary layer clouds over the Southern Great Plains
Mixed-precision computing in the GRIST dynamical core for weather and climate modelling
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project
Objective identification of meteorological fronts and climatologies from ERA-Interim and ERA5
TAMS: a tracking, classifying, and variable-assigning algorithm for mesoscale convective systems in simulated and satellite-derived datasets
Development of the adjoint of the unified tropospheric–stratospheric chemistry extension (UCX) in GEOS-Chem adjoint v36
New explicit formulae for the settling speed of prolate spheroids in the atmosphere: theoretical background and implementation in AerSett v2.0.2
ZJU-AERO V0.5: an Accurate and Efficient Radar Operator designed for CMA-GFS/MESO with the capability to simulate non-spherical hydrometeors
The Year of Polar Prediction site Model Intercomparison Project (YOPPsiteMIP) phase 1: project overview and Arctic winter forecast evaluation
Evaluating CHASER V4.0 global formaldehyde (HCHO) simulations using satellite, aircraft, and ground-based remote-sensing observations
Global variable-resolution simulations of extreme precipitation over Henan, China, in 2021 with MPAS-Atmosphere v7.3
The CHIMERE chemistry-transport model v2023r1
tobac v1.5: introducing fast 3D tracking, splits and mergers, and other enhancements for identifying and analysing meteorological phenomena
Merged Observatory Data Files (MODFs): an integrated observational data product supporting process-oriented investigations and diagnostics
Simulation of marine stratocumulus using the super-droplet method: numerical convergence and comparison to a double-moment bulk scheme using SCALE-SDM 5.2.6-2.3.1
Modeling of PAHs From Global to Regional Scales: Model Development and Investigation of Health Risks from 2013 to 2018 in China
WRF-Comfort: simulating microscale variability in outdoor heat stress at the city scale with a mesoscale model
Representing effects of surface heterogeneity in a multi-plume eddy diffusivity mass flux boundary layer parameterization
Can TROPOMI NO2 satellite data be used to track the drop in and resurgence of NOx emissions in Germany between 2019–2021 using the multi-source plume method (MSPM)?
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
A spatiotemporally separated framework for reconstructing the sources of atmospheric radionuclide releases
A parameterization scheme for the floating wind farm in a coupled atmosphere–wave model (COAWST v3.7)
RoadSurf 1.1: open-source road weather model library
Calibrating and validating the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) urban cooling model: case studies in France and the United States
The ddeq Python library for point source quantification from remote sensing images (version 1.0)
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
Incorporating Oxygen Isotopes of Oxidized Reactive Nitrogen in the Regional Atmospheric Chemistry Mechanism, version 2 (ICOIN-RACM2)
Development of the MPAS-CMAQ Coupled System (V1.0) for Multiscale Global Air Quality Modeling
A general comprehensive evaluation method for cross-scale precipitation forecasts
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
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The Next-generation Emissions InVentory expansion of Akagi (NEIVA) v.1.0 is a comprehensive biomass burning emissions database that allows integration of new data and flexible querying. Data are stored in connected datasets, including recommended averages of ~1500 constituents for 14 globally relevant fire types. Individual compounds were mapped to common model species to allow better attribution of emissions in modeling studies that predict the effects of fires on air quality and climate.
Lucie Bakels, Daria Tatsii, Anne Tipka, Rona Thompson, Marina Dütsch, Michael Blaschek, Petra Seibert, Katharina Baier, Silvia Bucci, Massimo Cassiani, Sabine Eckhardt, Christine Groot Zwaaftink, Stephan Henne, Pirmin Kaufmann, Vincent Lechner, Christian Maurer, Marie D. Mulder, Ignacio Pisso, Andreas Plach, Rakesh Subramanian, Martin Vojta, and Andreas Stohl
Geosci. Model Dev., 17, 7595–7627, https://doi.org/10.5194/gmd-17-7595-2024, https://doi.org/10.5194/gmd-17-7595-2024, 2024
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Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
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Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
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.
Phuong Loan Nguyen, Lisa V. Alexander, Marcus J. Thatcher, Son C. H. Truong, Rachael N. Isphording, and John L. McGregor
Geosci. Model Dev., 17, 7285–7315, https://doi.org/10.5194/gmd-17-7285-2024, https://doi.org/10.5194/gmd-17-7285-2024, 2024
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We use a comprehensive approach to select a subset of CMIP6 models for dynamical downscaling over Southeast Asia, taking into account model performance, model independence, data availability and the range of future climate projections. The standardised benchmarking framework is applied to assess model performance through both statistical and process-based metrics. Ultimately, we identify two independent model groups that are suitable for dynamical downscaling in the Southeast Asian region.
Ingrid Super, Tia Scarpelli, Arjan Droste, and Paul I. Palmer
Geosci. Model Dev., 17, 7263–7284, https://doi.org/10.5194/gmd-17-7263-2024, https://doi.org/10.5194/gmd-17-7263-2024, 2024
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Monitoring greenhouse gas emission reductions requires a combination of models and observations, as well as an initial emission estimate. Each component provides information with a certain level of certainty and is weighted to yield the most reliable estimate of actual emissions. We describe efforts for estimating the uncertainty in the initial emission estimate, which significantly impacts the outcome. Hence, a good uncertainty estimate is key for obtaining reliable information on emissions.
Álvaro González-Cervera and Luis Durán
Geosci. Model Dev., 17, 7245–7261, https://doi.org/10.5194/gmd-17-7245-2024, https://doi.org/10.5194/gmd-17-7245-2024, 2024
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RASCAL is an open-source Python tool designed for reconstructing daily climate observations, especially in regions with complex local phenomena. It merges large-scale weather patterns with local weather using the analog method. Evaluations in central Spain show that RASCAL outperforms ERA20C reanalysis in reconstructing precipitation and temperature. RASCAL offers opportunities for broad scientific applications, from short-term forecasts to local-scale climate change scenarios.
Sun-Young Park, Kyo-Sun Sunny Lim, Kwonil Kim, Gyuwon Lee, and Jason A. Milbrandt
Geosci. Model Dev., 17, 7199–7218, https://doi.org/10.5194/gmd-17-7199-2024, https://doi.org/10.5194/gmd-17-7199-2024, 2024
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We enhance the WDM6 scheme by incorporating predicted graupel density. The modification affects graupel characteristics, including fall velocity–diameter and mass–diameter relationships. Simulations highlight changes in graupel distribution and precipitation patterns, potentially influencing surface snow amounts. The study underscores the significance of integrating predicted graupel density for a more realistic portrayal of microphysical properties in weather models.
Christos I. Efstathiou, Elizabeth Adams, Carlie J. Coats, Robert Zelt, Mark Reed, John McGee, Kristen M. Foley, Fahim I. Sidi, David C. Wong, Steven Fine, and Saravanan Arunachalam
Geosci. Model Dev., 17, 7001–7027, https://doi.org/10.5194/gmd-17-7001-2024, https://doi.org/10.5194/gmd-17-7001-2024, 2024
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We present a summary of enabling high-performance computing of the Community Multiscale Air Quality Model (CMAQ) – a state-of-the-science community multiscale air quality model – on two cloud computing platforms through documenting the technologies, model performance, scaling and relative merits. This may be a new paradigm for computationally intense future model applications. We initiated this work due to a need to leverage cloud computing advances and to ease the learning curve for new users.
Peter A. Bogenschutz, Jishi Zhang, Qi Tang, and Philip Cameron-Smith
Geosci. Model Dev., 17, 7029–7050, https://doi.org/10.5194/gmd-17-7029-2024, https://doi.org/10.5194/gmd-17-7029-2024, 2024
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Using high-resolution and state-of-the-art modeling techniques we simulate five atmospheric river events for California to test the capability to represent precipitation for these events. We find that our model is able to capture the distribution of precipitation very well but suffers from overestimating the precipitation amounts over high elevation. Increasing the resolution further has no impact on reducing this bias, while increasing the domain size does have modest impacts.
Manu Anna Thomas, Klaus Wyser, Shiyu Wang, Marios Chatziparaschos, Paraskevi Georgakaki, Montserrat Costa-Surós, Maria Gonçalves Ageitos, Maria Kanakidou, Carlos Pérez García-Pando, Athanasios Nenes, Twan van Noije, Philippe Le Sager, and Abhay Devasthale
Geosci. Model Dev., 17, 6903–6927, https://doi.org/10.5194/gmd-17-6903-2024, https://doi.org/10.5194/gmd-17-6903-2024, 2024
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Aerosol–cloud interactions occur at a range of spatio-temporal scales. While evaluating recent developments in EC-Earth3-AerChem, this study aims to understand the extent to which the Twomey effect manifests itself at larger scales. We find a reduction in the warm bias over the Southern Ocean due to model improvements. While we see footprints of the Twomey effect at larger scales, the negative relationship between cloud droplet number and liquid water drives the shortwave radiative effect.
Kai Cao, Qizhong Wu, Lingling Wang, Hengliang Guo, Nan Wang, Huaqiong Cheng, Xiao Tang, Dongxing Li, Lina Liu, Dongqing Li, Hao Wu, and Lanning Wang
Geosci. Model Dev., 17, 6887–6901, https://doi.org/10.5194/gmd-17-6887-2024, https://doi.org/10.5194/gmd-17-6887-2024, 2024
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AMD’s heterogeneous-compute interface for portability was implemented to port the piecewise parabolic method solver from NVIDIA GPUs to China's GPU-like accelerators. The results show that the larger the model scale, the more acceleration effect on the GPU-like accelerator, up to 28.9 times. The multi-level parallelism achieves a speedup of 32.7 times on the heterogeneous cluster. By comparing the results, the GPU-like accelerators have more accuracy for the geoscience numerical models.
Ruyi Zhang, Limin Zhou, Shin-ichiro Shima, and Huawei Yang
Geosci. Model Dev., 17, 6761–6774, https://doi.org/10.5194/gmd-17-6761-2024, https://doi.org/10.5194/gmd-17-6761-2024, 2024
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Solar activity weakly ionises Earth's atmosphere, charging cloud droplets. Electro-coalescence is when oppositely charged droplets stick together. We introduce an analytical expression of electro-coalescence probability and use it in a warm-cumulus-cloud simulation. Results show that charge cases increase rain and droplet size, with the new method outperforming older ones. The new method requires longer computation time, but its impact on rain justifies inclusion in meteorology models.
Máté Mile, Stephanie Guedj, and Roger Randriamampianina
Geosci. Model Dev., 17, 6571–6587, https://doi.org/10.5194/gmd-17-6571-2024, https://doi.org/10.5194/gmd-17-6571-2024, 2024
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Satellite observations provide crucial information about atmospheric constituents in a global distribution that helps to better predict the weather over sparsely observed regions like the Arctic. However, the use of satellite data is usually conservative and imperfect. In this study, a better spatial representation of satellite observations is discussed and explored by a so-called footprint function or operator, highlighting its added value through a case study and diagnostics.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-129, https://doi.org/10.5194/gmd-2024-129, 2024
Revised manuscript accepted for GMD
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Orbital-radar is a Python tool transferring sub-orbital radar data (ground-based, airborne, and forward-simulated NWP) into synthetical space-borne cloud profiling radar data mimicking the platform characteristics, e.g. EarthCARE or CloudSat CPR. The novelty of orbital-radar is the simulation platform characteristic noise floors and errors. By this long time data sets can be transformed into synthetic observations for Cal/Valor sensitivity studies for new or future satellite missions.
Hynek Bednář and Holger Kantz
Geosci. Model Dev., 17, 6489–6511, https://doi.org/10.5194/gmd-17-6489-2024, https://doi.org/10.5194/gmd-17-6489-2024, 2024
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The forecast error growth of atmospheric phenomena is caused by initial and model errors. When studying the initial error growth, it may turn out that small-scale phenomena, which contribute little to the forecast product, significantly affect the ability to predict this product. With a negative result, we investigate in the extended Lorenz (2005) system whether omitting these phenomena will improve predictability. A theory explaining and describing this behavior is developed.
Giorgio Veratti, Alessandro Bigi, Sergio Teggi, and Grazia Ghermandi
Geosci. Model Dev., 17, 6465–6487, https://doi.org/10.5194/gmd-17-6465-2024, https://doi.org/10.5194/gmd-17-6465-2024, 2024
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In this study, we present VERT (Vehicular Emissions from Road Traffic), an R package designed to estimate transport emissions using traffic estimates and vehicle fleet composition data. Compared to other tools available in the literature, VERT stands out for its user-friendly configuration and flexibility of user input. Case studies demonstrate its accuracy in both urban and regional contexts, making it a valuable tool for air quality management and transport scenario planning.
Sam P. Raj, Puna Ram Sinha, Rohit Srivastava, Srinivas Bikkina, and Damu Bala Subrahamanyam
Geosci. Model Dev., 17, 6379–6399, https://doi.org/10.5194/gmd-17-6379-2024, https://doi.org/10.5194/gmd-17-6379-2024, 2024
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A Python successor to the aerosol module of the OPAC model, named AeroMix, has been developed, with enhanced capabilities to better represent real atmospheric aerosol mixing scenarios. AeroMix’s performance in modeling aerosol mixing states has been evaluated against field measurements, substantiating its potential as a versatile aerosol optical model framework for next-generation algorithms to infer aerosol mixing states and chemical composition.
Angeline G. Pendergrass, Michael P. Byrne, Oliver Watt-Meyer, Penelope Maher, and Mark J. Webb
Geosci. Model Dev., 17, 6365–6378, https://doi.org/10.5194/gmd-17-6365-2024, https://doi.org/10.5194/gmd-17-6365-2024, 2024
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The width of the tropical rain belt affects many aspects of our climate, yet we do not understand what controls it. To better understand it, we present a method to change it in numerical model experiments. We show that the method works well in four different models. The behavior of the width is unexpectedly simple in some ways, such as how strong the winds are as it changes, but in other ways, it is more complicated, especially how temperature increases with carbon dioxide.
Tianning Su and Yunyan Zhang
Geosci. Model Dev., 17, 6319–6336, https://doi.org/10.5194/gmd-17-6319-2024, https://doi.org/10.5194/gmd-17-6319-2024, 2024
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Using 2 decades of field observations over the Southern Great Plains, this study developed a deep-learning model to simulate the complex dynamics of boundary layer clouds. The deep-learning model can serve as the cloud parameterization within reanalysis frameworks, offering insights into improving the simulation of low clouds. By quantifying biases due to various meteorological factors and parameterizations, this deep-learning-driven approach helps bridge the observation–modeling divide.
Siyuan Chen, Yi Zhang, Yiming Wang, Zhuang Liu, Xiaohan Li, and Wei Xue
Geosci. Model Dev., 17, 6301–6318, https://doi.org/10.5194/gmd-17-6301-2024, https://doi.org/10.5194/gmd-17-6301-2024, 2024
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This study explores strategies and techniques for implementing mixed-precision code optimization within an atmosphere model dynamical core. The coded equation terms in the governing equations that are sensitive (or insensitive) to the precision level have been identified. The performance of mixed-precision computing in weather and climate simulations was analyzed.
Sam O. Owens, Dipanjan Majumdar, Chris E. Wilson, Paul Bartholomew, and Maarten van Reeuwijk
Geosci. Model Dev., 17, 6277–6300, https://doi.org/10.5194/gmd-17-6277-2024, https://doi.org/10.5194/gmd-17-6277-2024, 2024
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Designing cities that are resilient, sustainable, and beneficial to health requires an understanding of urban climate and air quality. This article presents an upgrade to the multi-physics numerical model uDALES, which can simulate microscale airflow, heat transfer, and pollutant dispersion in urban environments. This upgrade enables it to resolve realistic urban geometries more accurately and to take advantage of the resources available on current and future high-performance computing systems.
Allison A. Wing, Levi G. Silvers, and Kevin A. Reed
Geosci. Model Dev., 17, 6195–6225, https://doi.org/10.5194/gmd-17-6195-2024, https://doi.org/10.5194/gmd-17-6195-2024, 2024
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This paper presents the experimental design for a model intercomparison project to study tropical clouds and climate. It is a follow-up from a prior project that used a simplified framework for tropical climate. The new project adds one new component – a specified pattern of sea surface temperatures as the lower boundary condition. We provide example results from one cloud-resolving model and one global climate model and test the sensitivity to the experimental parameters.
Philip G. Sansom and Jennifer L. Catto
Geosci. Model Dev., 17, 6137–6151, https://doi.org/10.5194/gmd-17-6137-2024, https://doi.org/10.5194/gmd-17-6137-2024, 2024
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Weather fronts bring a lot of rain and strong winds to many regions of the mid-latitudes. We have developed an updated method of identifying these fronts in gridded data that can be used on new datasets with small grid spacing. The method can be easily applied to different datasets due to the use of open-source software for its development and shows improvements over similar previous methods. We present an updated estimate of the average frequency of fronts over the past 40 years.
Kelly M. Núñez Ocasio and Zachary L. Moon
Geosci. Model Dev., 17, 6035–6049, https://doi.org/10.5194/gmd-17-6035-2024, https://doi.org/10.5194/gmd-17-6035-2024, 2024
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TAMS is an open-source Python-based package for tracking and classifying mesoscale convective systems that can be used to study observed and simulated systems. Each step of the algorithm is described in this paper with examples showing how to make use of visualization and post-processing tools within the package. A unique and valuable feature of this tracker is its support for unstructured grids in the identification stage and grid-independent tracking.
Irene C. Dedoussi, Daven K. Henze, Sebastian D. Eastham, Raymond L. Speth, and Steven R. H. Barrett
Geosci. Model Dev., 17, 5689–5703, https://doi.org/10.5194/gmd-17-5689-2024, https://doi.org/10.5194/gmd-17-5689-2024, 2024
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Atmospheric model gradients provide a meaningful tool for better understanding the underlying atmospheric processes. Adjoint modeling enables computationally efficient gradient calculations. We present the adjoint of the GEOS-Chem unified chemistry extension (UCX). With this development, the GEOS-Chem adjoint model can capture stratospheric ozone and other processes jointly with tropospheric processes. We apply it to characterize the Antarctic ozone depletion potential of active halogen species.
Sylvain Mailler, Sotirios Mallios, Arineh Cholakian, Vassilis Amiridis, Laurent Menut, and Romain Pennel
Geosci. Model Dev., 17, 5641–5655, https://doi.org/10.5194/gmd-17-5641-2024, https://doi.org/10.5194/gmd-17-5641-2024, 2024
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We propose two explicit expressions to calculate the settling speed of solid atmospheric particles with prolate spheroidal shapes. The first formulation is based on theoretical arguments only, while the second one is based on computational fluid dynamics calculations. We show that the first method is suitable for virtually all atmospheric aerosols, provided their shape can be adequately described as a prolate spheroid, and we provide an implementation of the first method in AerSett v2.0.2.
Hejun Xie, Lei Bi, and Wei Han
Geosci. Model Dev., 17, 5657–5688, https://doi.org/10.5194/gmd-17-5657-2024, https://doi.org/10.5194/gmd-17-5657-2024, 2024
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A radar operator plays a crucial role in utilizing radar observations to enhance numerical weather forecasts. However, developing an advanced radar operator is challenging due to various complexities associated with the wave scattering by non-spherical hydrometeors, radar beam propagation, and multiple platforms. In this study, we introduce a novel radar operator named the Accurate and Efficient Radar Operator developed by ZheJiang University (ZJU-AERO) which boasts several unique features.
Jonathan J. Day, Gunilla Svensson, Barbara Casati, Taneil Uttal, Siri-Jodha Khalsa, Eric Bazile, Elena Akish, Niramson Azouz, Lara Ferrighi, Helmut Frank, Michael Gallagher, Øystein Godøy, Leslie M. Hartten, Laura X. Huang, Jareth Holt, Massimo Di Stefano, Irene Suomi, Zen Mariani, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Teresa Remes, Rostislav Fadeev, Amy Solomon, Johanna Tjernström, and Mikhail Tolstykh
Geosci. Model Dev., 17, 5511–5543, https://doi.org/10.5194/gmd-17-5511-2024, https://doi.org/10.5194/gmd-17-5511-2024, 2024
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The YOPP site Model Intercomparison Project (YOPPsiteMIP), which was designed to facilitate enhanced weather forecast evaluation in polar regions, is discussed here, focussing on describing the archive of forecast data and presenting a multi-model evaluation at Arctic supersites during February and March 2018. The study highlights an underestimation in boundary layer temperature variance that is common across models and a related inability to forecast cold extremes at several of the sites.
Hossain Mohammed Syedul Hoque, Kengo Sudo, Hitoshi Irie, Yanfeng He, and Md Firoz Khan
Geosci. Model Dev., 17, 5545–5571, https://doi.org/10.5194/gmd-17-5545-2024, https://doi.org/10.5194/gmd-17-5545-2024, 2024
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Using multi-platform observations, we validated global formaldehyde (HCHO) simulations from a chemistry transport model. HCHO is a crucial intermediate in the chemical catalytic cycle that governs the ozone formation in the troposphere. The model was capable of replicating the observed spatiotemporal variability in HCHO. In a few cases, the model's capability was limited. This is attributed to the uncertainties in the observations and the model parameters.
Zijun Liu, Li Dong, Zongxu Qiu, Xingrong Li, Huiling Yuan, Dongmei Meng, Xiaobin Qiu, Dingyuan Liang, and Yafei Wang
Geosci. Model Dev., 17, 5477–5496, https://doi.org/10.5194/gmd-17-5477-2024, https://doi.org/10.5194/gmd-17-5477-2024, 2024
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In this study, we completed a series of simulations with MPAS-Atmosphere (version 7.3) to study the extreme precipitation event of Henan, China, during 20–22 July 2021. We found the different performance of two built-in parameterization scheme suites (mesoscale and convection-permitting suites) with global quasi-uniform and variable-resolution meshes. This study holds significant implications for advancing the understanding of the scale-aware capability of MPAS-Atmosphere.
Laurent Menut, Arineh Cholakian, Romain Pennel, Guillaume Siour, Sylvain Mailler, Myrto Valari, Lya Lugon, and Yann Meurdesoif
Geosci. Model Dev., 17, 5431–5457, https://doi.org/10.5194/gmd-17-5431-2024, https://doi.org/10.5194/gmd-17-5431-2024, 2024
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A new version of the CHIMERE model is presented. This version contains both computational and physico-chemical changes. The computational changes make it easy to choose the variables to be extracted as a result, including values of maximum sub-hourly concentrations. Performance tests show that the model is 1.5 to 2 times faster than the previous version for the same setup. Processes such as turbulence, transport schemes and dry deposition have been modified and updated.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Taneil Uttal, Leslie M. Hartten, Siri Jodha Khalsa, Barbara Casati, Gunilla Svensson, Jonathan Day, Jareth Holt, Elena Akish, Sara Morris, Ewan O'Connor, Roberta Pirazzini, Laura X. Huang, Robert Crawford, Zen Mariani, Øystein Godøy, Johanna A. K. Tjernström, Giri Prakash, Nicki Hickmon, Marion Maturilli, and Christopher J. Cox
Geosci. Model Dev., 17, 5225–5247, https://doi.org/10.5194/gmd-17-5225-2024, https://doi.org/10.5194/gmd-17-5225-2024, 2024
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A Merged Observatory Data File (MODF) format to systematically collate complex atmosphere, ocean, and terrestrial data sets collected by multiple instruments during field campaigns is presented. The MODF format is also designed to be applied to model output data, yielding format-matching Merged Model Data Files (MMDFs). MODFs plus MMDFs will augment and accelerate the synergistic use of model results with observational data to increase understanding and predictive skill.
Chongzhi Yin, Shin-ichiro Shima, Lulin Xue, and Chunsong Lu
Geosci. Model Dev., 17, 5167–5189, https://doi.org/10.5194/gmd-17-5167-2024, https://doi.org/10.5194/gmd-17-5167-2024, 2024
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We investigate numerical convergence properties of a particle-based numerical cloud microphysics model (SDM) and a double-moment bulk scheme for simulating a marine stratocumulus case, compare their results with model intercomparison project results, and present possible explanations for the different results of the SDM and the bulk scheme. Aerosol processes can be accurately simulated using SDM, and this may be an important factor affecting the behavior and morphology of marine stratocumulus.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-1437, https://doi.org/10.5194/egusphere-2024-1437, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can well reproduce the distribution of PAHs. 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 of BaP is less than PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although "the Action Plan" has been implemented.
Alberto Martilli, Negin Nazarian, E. Scott Krayenhoff, Jacob Lachapelle, Jiachen Lu, Esther Rivas, Alejandro Rodriguez-Sanchez, Beatriz Sanchez, and José Luis Santiago
Geosci. Model Dev., 17, 5023–5039, https://doi.org/10.5194/gmd-17-5023-2024, https://doi.org/10.5194/gmd-17-5023-2024, 2024
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Here, we present a model that quantifies the thermal stress and its microscale variability at a city scale with a mesoscale model. This tool can have multiple applications, from early warnings of extreme heat to the vulnerable population to the evaluation of the effectiveness of heat mitigation strategies. It is the first model that includes information on microscale variability in a mesoscale model, something that is essential for fully evaluating heat stress.
Nathan P. Arnold
Geosci. Model Dev., 17, 5041–5056, https://doi.org/10.5194/gmd-17-5041-2024, https://doi.org/10.5194/gmd-17-5041-2024, 2024
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Earth system models often represent the land surface at smaller scales than the atmosphere, but surface–atmosphere coupling uses only aggregated surface properties. This study presents a method to allow heterogeneous surface properties to modify boundary layer updrafts. The method is tested in single column experiments. Updraft properties are found to reasonably covary with surface conditions, and simulated boundary layer variability is enhanced over more heterogeneous land surfaces.
Enrico Dammers, Janot Tokaya, Christian Mielke, Kevin Hausmann, Debora Griffin, Chris McLinden, Henk Eskes, and Renske Timmermans
Geosci. Model Dev., 17, 4983–5007, https://doi.org/10.5194/gmd-17-4983-2024, https://doi.org/10.5194/gmd-17-4983-2024, 2024
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Nitrogen dioxide (NOx) is produced by sources such as industry and traffic and is directly linked to negative impacts on health and the environment. The current construction of emission inventories to keep track of NOx emissions is slow and time-consuming. Satellite measurements provide a way to quickly and independently estimate emissions. In this study, we apply a consistent methodology to derive NOx emissions over Germany and illustrate the value of having such a method for fast projections.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-109, https://doi.org/10.5194/gmd-2024-109, 2024
Revised manuscript accepted for GMD
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This study updates CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosols (SOA) formation. Dust emission modifications make deflation areas more continuous, improving results in North America and the subarctic. 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 CESM's aerosol modelling results.
Yuhan Xu, Sheng Fang, Xinwen Dong, and Shuhan Zhuang
Geosci. Model Dev., 17, 4961–4982, https://doi.org/10.5194/gmd-17-4961-2024, https://doi.org/10.5194/gmd-17-4961-2024, 2024
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Recent atmospheric radionuclide leakages from unknown sources have posed a new challenge in nuclear emergency assessment. Reconstruction via environmental observations is the only feasible way to identify sources, but simultaneous reconstruction of the source location and release rate yields high uncertainties. We propose a spatiotemporally separated reconstruction strategy that avoids these uncertainties and outperforms state-of-the-art methods with respect to accuracy and uncertainty ranges.
Shaokun Deng, Shengmu Yang, Shengli Chen, Daoyi Chen, Xuefeng Yang, and Shanshan Cui
Geosci. Model Dev., 17, 4891–4909, https://doi.org/10.5194/gmd-17-4891-2024, https://doi.org/10.5194/gmd-17-4891-2024, 2024
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Global offshore wind power development is moving from offshore to deeper waters, where floating offshore wind turbines have an advantage over bottom-fixed turbines. However, current wind farm parameterization schemes in mesoscale models are not applicable to floating turbines. We propose a floating wind farm parameterization scheme that accounts for the attenuation of the significant wave height by floating turbines. The results indicate that it has a significant effect on the power output.
Virve Eveliina Karsisto
Geosci. Model Dev., 17, 4837–4853, https://doi.org/10.5194/gmd-17-4837-2024, https://doi.org/10.5194/gmd-17-4837-2024, 2024
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RoadSurf is an open-source library that contains functions from the Finnish Meteorological Institute’s road weather model. The evaluation of the library shows that it is well suited for making road surface temperature forecasts. The evaluation was done by making forecasts for about 400 road weather stations in Finland with the library. Accurate forecasts help road authorities perform salting and plowing operations at the right time and keep roads safe for drivers.
Perrine Hamel, Martí Bosch, Léa Tardieu, Aude Lemonsu, Cécile de Munck, Chris Nootenboom, Vincent Viguié, Eric Lonsdorf, James A. Douglass, and Richard P. Sharp
Geosci. Model Dev., 17, 4755–4771, https://doi.org/10.5194/gmd-17-4755-2024, https://doi.org/10.5194/gmd-17-4755-2024, 2024
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The InVEST Urban Cooling model estimates the cooling effect of vegetation in cities. We further developed an algorithm to facilitate model calibration and evaluation. Applying the algorithm to case studies in France and in the United States, we found that nighttime air temperature estimates compare well with reference datasets. Estimated change in temperature from a land cover scenario compares well with an alternative model estimate, supporting the use of the model for urban planning decisions.
Gerrit Kuhlmann, Erik Koene, Sandro Meier, Diego Santaren, Grégoire Broquet, Frédéric Chevallier, Janne Hakkarainen, Janne Nurmela, Laia Amorós, Johanna Tamminen, and Dominik Brunner
Geosci. Model Dev., 17, 4773–4789, https://doi.org/10.5194/gmd-17-4773-2024, https://doi.org/10.5194/gmd-17-4773-2024, 2024
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We present a Python software library for data-driven emission quantification (ddeq). It can be used to determine the emissions of hot spots (cities, power plants and industry) from remote sensing images using different methods. ddeq can be extended for new datasets and methods, providing a powerful community tool for users and developers. The application of the methods is shown using Jupyter notebooks included in the library.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
EGUsphere, https://doi.org/10.5194/egusphere-2024-946, https://doi.org/10.5194/egusphere-2024-946, 2024
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We have developed a complete 2-moment version of the LIMA 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 parameterisations 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 idealised case.
Wendell W. Walters, Masayuki Takeuchi, Nga L. Ng, and Meredith G. Hastings
Geosci. Model Dev., 17, 4673–4687, https://doi.org/10.5194/gmd-17-4673-2024, https://doi.org/10.5194/gmd-17-4673-2024, 2024
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The study introduces a novel chemical mechanism for explicitly tracking oxygen isotope transfer in oxidized reactive nitrogen and odd oxygen using the Regional Atmospheric Chemistry Mechanism, version 2. This model enhances our ability to simulate and compare oxygen isotope compositions of reactive nitrogen, revealing insights into oxidation chemistry. The approach shows promise for improving atmospheric chemistry models and tropospheric oxidation capacity predictions.
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. Discuss., https://doi.org/10.5194/gmd-2024-52, https://doi.org/10.5194/gmd-2024-52, 2024
Revised manuscript accepted for GMD
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This work describe how we linked 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 in a global scale. This new model scales well on high performance computing environment and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Bing Zhang, Mingjian Zeng, Anning Huang, Zhengkun Qin, Couhua Liu, Wenru Shi, Xin Li, Kefeng Zhu, Chunlei Gu, and Jialing Zhou
Geosci. Model Dev., 17, 4579–4601, https://doi.org/10.5194/gmd-17-4579-2024, https://doi.org/10.5194/gmd-17-4579-2024, 2024
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By directly analyzing the proximity of precipitation forecasts and observations, a precipitation accuracy score (PAS) method was constructed. This method does not utilize a traditional contingency-table-based classification verification; however, it can replace the threat score (TS), equitable threat score (ETS), and other skill score methods, and it can be used to calculate the accuracy of numerical models or quantitative precipitation forecasts.
Cited articles
Banerjee, P., Satheesh, S. K., and Moorthy, K. K.: The unusual severe dust storm of May 2018 over northern India: Genesis, propagation, and associated conditions, J. Geophys. Res.-Atmos., 126, 1–25, https://doi.org/10.1029/2020JD032369, 2021.
Bhardwaj, P., Kumar, R., and Seddon, J.: Interstate transport of carbon monoxide and black carbon over India, Atmos. Environ., 251, 118268, https://doi.org/10.1016/j.atmosenv.2021.118268, 2021.
Bikkina, S., Andersson, A., Kirillova, E. N., Holmstrand, H., Tiwari, S., Srivastava, A. K., Bisht, D. S., and Gustafsson, Ö.: Air quality in megacity Delhi affected by countryside biomass burning, Nat. Sustain., 2, 200–205, https://doi.org/10.1038/s41893-019-0219-0, 2019.
Bray, C. D., Battye, W. H., and Aneja, V. P.: The role of biomass burning agricultural emissions in the Indo-Gangetic Plains on the air quality in New Delhi, India, Atmos. Environ., 218, 116983, https://doi.org/10.1016/j.atmosenv.2019.116983, 2019.
CAQM (Commision for Air Quality Management in the National Capital Region and the adjoining areas): Policy to Curb Air Pollution in the National Capital Region, https://caqm.nic.in/WriteReadData/LINKS/0031dcb806e-8af7-4b38-a9bc-65b91f2704cd.pdf (last access: 8 April 2024), 2022.
Census Of India 2011: Population Projections For India And States 2011–2036, in: Report Of The Technical Group On Population Projections, National Commission On Population Ministry Of Health & Family Welfare Nirman Bhawan, New Delhi – 110011, https://main.mohfw.gov.in/sites/default/files/Population Projection Report 2011-2036 - upload_compressed_0.pdf (last access: 1 April 2024), 2020.
Central Pollution Control Board: Central Control Room for Air Quality Management – All India, Central Pollution Control Board [data set], https://app.cpcbccr.com/ccr/#/caaqm-dashboard-all/caaqm-landing/caaqm-data-repository, last access: 4 April 2024.
Chakravarty, K., Vincent, V., Vellore, R., Srivastava, A. K., Rastogi, A., and Soni, V. K.: Revisiting Andhi in northern India: A case study of severe dust-storm over the urban megacity of New Delhi, Urban Climate, 37, 100825, https://doi.org/10.1016/j.uclim.2021.100825, 2021.
Chin, M., Rood, R. B., Lin, S.-J., Müller, J.-F., and Thompson, A. M.: Atmospheric sulfur cycle simulated in the global model GOCART: Model description and global properties, J. Geophys. Res., 105, 24671–24687, https://doi.org/10.1029/2000JD900384, 2000.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B. N., Duncan, B. N., Martin, R. V., Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and Sun photometer measurements, J. Atmos. Sci., 59, 461–483, https://doi.org/10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2, 2002.
Chopra, R.: Environmental degradation in India: causes and consequences, Int. J. Appl. Environ. Sci., 11, 1593–1601, 2016.
Chowdhury, S., Dey, S., Di Girolamo, L., Smith, K. R., Pillarisetti, A., and Lyapustin, A.: Tracking ambient PM2.5 build-up in Delhi national capital region during the dry season over 15 years using a high-resolution (1km) satellite aerosol dataset, Atmos. Environ., 204, 142–150, https://doi.org/10.1016/j.atmosenv.2019.02.029, 2019.
Clough, S. A., Shephard, M. W., Mlawer, E. J., Delamere, J. S., Iacono, M. J., Cady-Pereira, K., Boukabara, S., and Brown, P. D.: Atmospheric radiative transfer modeling: A summary of the AER codes, J. Quant. Spectrosc. Ra, 91, 233–244, https://doi.org/10.1016/j.jqsrt.2004.05.058, 2005.
Colette, A., Rouïl, L., Meleux, F., Lemaire, V., and Raux, B.: Air Control Toolbox (ACT_v1.0): a flexible surrogate model to explore mitigation scenarios in air quality forecasts, Geosci. Model Dev., 15, 1441–1465, https://doi.org/10.5194/gmd-15-1441-2022, 2022.
Cusworth, D. H., Mickley, L. J., Sulprizio, M. P., Liu, T., Marlier, M. E., DeFries, R. S., Guttikunda, S. K., and Gupta, P.: Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India, Environ. Res. Lett., 13, 044018, https://doi.org/10.1088/1748-9326/aab303, 2018.
Debnath, S., Jena, C., Ghude, S. D., Kumar, R., Govardhan, G., Gunwani, P., Saha, S. K., Hazra, A., and Pokhrel, S.: Simulation of Indian Summer Monsoon Rainfall (ISMR) with fully coupled regional chemistry transport model: A case study for 2017, Atmos. Environ., 268, 118785, https://doi.org/10.1016/j.atmosenv.2021.118785, 2022.
Denby, B. R., Gauss, M., Wind, P., Mu, Q., Grøtting Wærsted, E., Fagerli, H., Valdebenito, A., and Klein, H.: Description of the uEMEP_v5 downscaling approach for the EMEP MSC-W chemistry transport model, Geosci. Model Dev., 13, 6303–6323, https://doi.org/10.5194/gmd-13-6303-2020, 2020.
Ek, M. B., Mitchell, K. E., Lin, Y., Rogers, E., Grunmann, P., Koren, V., Gayno, G., and Tarpley, J. D.: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model, J. Geophys. Res.-Atmos., 108, 8851, https://doi.org/10.1029/2002JD003296, 2003.
Emery, C., Liu, Z., Russell, A. G., Odman, M. T., Yarwood, G., and Kumar, N.: Recommendations on statistics and benchmarks to assess photochemical model performance, JAPCA J. Air Waste Ma., 67, 582–598, https://doi.org/10.1080/10962247.2016.1265027,2017.
Emmons, L. K., Walters, S., Hess, P. G., Lamarque, J.-F., Pfister, G. G., Fillmore, D., Granier, C., Guenther, A., Kinnison, D., Laepple, T., Orlando, J., Tie, X., Tyndall, G., Wiedinmyer, C., Baughcum, S. L., and Kloster, S.: Description and evaluation of the Model for Ozone and Related chemical Tracers, version 4 (MOZART-4), Geosci. Model Dev., 3, 43–67, https://doi.org/10.5194/gmd-3-43-2010, 2010.
Gadi, R., Shivani, Sharma, S. K., and Mandal, T. K.: Source apportionment and health risk assessment of organic constituents in fine ambient aerosols (PM2.5): a complete year study over National Capital Region of India, Chemosphere, 221, 583–596, https://doi.org/10.1016/j.chemosphere.2019.01.067, 2019.
Ghude, S. D., Chate, D. M., Jena, C., Beig, G., Kumar, R., Barth, M. C., Pfister, G. G., Fadnavis, S., and Pithani, P.: Premature mortality in India due to PM2.5 and ozone exposure, Geophys. Res. Lett., 43, 4650–4658, https://doi.org/10.1002/2016GL068949, 2016.
Ghude, S. D., Kumar, R., Jena, C., Debnath, S., Kulkarni, R. G., Alessandrini, S., Biswas, M., Kulkrani, S., Pithani, P., Kelkar, S., and Sajjan, V.: Evaluation of PM2.5 forecast using chemical data assimilation in the WRF-Chem model: A novel initiative under the Ministry of Earth Sciences Air Quality Early Warning System for Delhi India, Curr. Sci., 118, 1803–1815, https://doi.org/10.18520/cs/v118/i11/1803-1815, 2020.
Ghude, S. D., Kumar, R., Govardhan, G., Jena, C., Nanjundiah, R. S., and Rajeevan, M.: New Delhi: air-quality warning system cuts peak pollution, Nature, 602, 211–211, https://doi.org/10.1038/d41586-022-00332-y, 2022.
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., and Lin, S.-J.: Sources and distributions of dust aerosols simulated with the GOCART model. J. Geophys. Res., 106, 20255–20273, https://doi.org/10.1029/2000JD000053, 2001.
Govardhan, G.: WRF-Chem-DSS-Model, figshare [software], https://doi.org/10.6084/m9.figshare.21655883.v1, 2022.
Govardhan, G.: User manual for WRF-Chem based DSS for air quality management, figshare [software], https://doi.org/10.6084/m9.figshare.22335424.v1, 2023.
Govardhan, G., Nanjundiah, R. S., Satheesh, S. K., Krishnamoorthy, K., and Kotamarthi, V. R.: Performance of WRF-Chem over Indian region: Comparison with measurements, J. Earth Syst. Sci., 124, 875–896, https://www.ias.ac.in/article/fulltext/jess/124/04/0875-0896 (last access: 4 April 2024), 2015.
Govardhan, G., Satheesh, S. K., Moorthy, K. K., and Nanjundiah, R.: Simulations of black carbon over the Indian region: improvements and implications of diurnality in emissions, Atmos. Chem. Phys., 19, 8229–8241, https://doi.org/10.5194/acp-19-8229-2019, 2019.
Govardhan, G., Ambulkar, R., Kulkarni, S., Vishnoi, A., Yadav, P., Chowdhury, B. A., Khare, M., and Ghude, S. D.: Stubble-burning activities in north-western India in 2021: Contribution to air pollution in Delhi, Heliyon, 9, e16939, https://doi.org/10.1016/J.HELIYON.2023.E16939, 2023.
Govardhan, G. R., Nanjundiah, R. S., Satheesh, S. K., Moorthy, K. K., and Takemura, T.: Inter-comparison and performance evaluation of chemistry transport models over Indian region, Atmos. Environ., 125, 486–504, https://doi.org/10.1016/j.atmosenv.2015.10.065, 2016.
Grell, G. A. and Freitas, S. R.: A scale and aerosol aware stochastic convective parameterization for weather and air quality modeling, Atmos. Chem. Phys., 14, 5233–5250, https://doi.org/10.5194/acp-14-5233-2014, 2014.
Grell, G. A., Peckham, S. E., Schmitz, R., McKeen, S. A., Frost, G., Skamarock, W. C., and Eder, B.: Fully coupled “online” chemistry within the WRF model, Atmos. Environ., 39, 6957–6975, 2005.
Guo, H., Kota, S. H., Chen, K., Sahu, S. K., Hu, J., Ying, Q., Wang, Y., and Zhang, H.: Source contributions and potential reductions to health effects of particulate matter in India, Atmos. Chem. Phys., 18, 15219–15229, https://doi.org/10.5194/acp-18-15219-2018, 2018.
Guo, H., Kota, S. H., Sahu, S. K., and Zhang, H.: Contributions of local and regional sources to PM2.5 and its health effects in north India, Atmos. Environ., 214, 116867, https://doi.org/10.1016/j.atmosenv.2019.116867, 2019.
Guttikunda, S. K. and Goel, R.: Health impacts of particulate pollution in a megacity-Delhi, India, Environ. Dev., 6, 8–20, https://doi.org/10.1016/j.envdev.2012.12.002, 2013.
Guttikunda, S. K. and Gurjar, B. R.: Role of meteorology in seasonality of air pollution in megacity Delhi, India, Environ. Monit. Assess., 184, 3199–3211, https://doi.org/10.1007/s10661-011-2182-8, 2012.
Hama, S., Kumar, P., Alam, M. S., Rooney, D. J., Bloss, W. J., Shi, Z., Harrison, R. M., Crilley, L. R., Khare, M., and Gupta, S. K.: Chemical source profiles of fine particles for five different sources in Delhi, Chemosphere, 274, https://doi.org/10.1016/j.chemosphere.2021.129913, 2021.
Hodzic, A. and Jimenez, J. L.: Modeling anthropogenically controlled secondary organic aerosols in a megacity: a simplified framework for global and climate models, Geosci. Model Dev., 4, 901–917, https://doi.org/10.5194/gmd-4-901-2011, 2011.
Hong, S. Y. and Lim, J. O. J.: The WRF single-moment 6-class microphysics scheme (WSM6), Asia-Pac. J. Atmos. Sci., 42, 129–151, 2006.
Iacono, M. J., Mlawer, E. J., Clough, S. A., and Morcrette, J.-J.: Impact of an improved longwave radiation model, rrtm, on the energy budget and thermodynamic properties of the ncar community climate model ccm3, J. Geophys. Res., 105, 14873–14890, https://doi.org/10.1029/2000JD900091, 2000.
Iacono, M. J., Delamere, J. S., Mlawer, E. J., Shephard, M. W., Clough, S. A., and Collins, W. D.: Radiative forcing by long-lived greenhouse gases: Calculations with the aer radiative transfer models, J. Geophys. Res., 113, 1–8, https://doi.org/10.1029/2008JD009944, 2008.
Jain, S., Sharma, S. K., Vijayan, N., and Mandal, T. K.: Seasonal characteristics of aerosols (PM2.5 and PM10) and their source apportionment using PMF: a four year study over Delhi, India, Environ. Pollut., 262, 114337, https://doi.org/10.1016/j.envpol.2020.114337, 2020.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Dentener, F., Muntean, M., Pouliot, G., Keating, T., Zhang, Q., Kurokawa, J., Wankmüller, R., Denier van der Gon, H., Kuenen, J. J. P., Klimont, Z., Frost, G., Darras, S., Koffi, B., and Li, M.: HTAP_v2.2: a mosaic of regional and global emission grid maps for 2008 and 2010 to study hemispheric transport of air pollution, Atmos. Chem. Phys., 15, 11411–11432, https://doi.org/10.5194/acp-15-11411-2015, 2015.
Jena, C., Ghude, S. D., Kulkarni, R., Debnath, S., Kumar, R., Soni, V. K., Acharja, P., Kulkarni, S. H., Khare, M., Kaginalkar, A. J., Chate, D. M., Ali, K., Nanjundiah, R. S., and Rajeevan, M. N.: Evaluating the sensitivity of fine particulate matter (PM2.5) simulations to chemical mechanism in Delhi, Atmos. Chem. Phys. Discuss. [preprint], https://doi.org/10.5194/acp-2020-673, 2020.
Jena, C., Ghude, S. D., Kumar, R., Debnath, S., Govardhan, G., Soni, V. K., Kulkarni, S. H., Beig, G., Nanjundiah, R. S., and Rajeevan, M.: Performance of high resolution (400 m) PM2.5 forecast over Delhi, Sci. Rep.-UK, 11, 4104, https://www.nature.com/articles/s41598-021-83467-8 (last access: 4 April 2024), 2021.
Jiménez, P. A., Dudhia, J., González-Rouco, J. F., Navarro, J., Montávez, J. P., and García-Bustamante, E.: A revised scheme for the WRF surface layer formulation, Mon. Weather Rev., 140, 898–918, https://doi.org/10.1175/MWR-D-11-00056.1, 2012.
Kaiser, J. W., Heil, A., Andreae, M. O., Benedetti, A., Chubarova, N., Jones, L., Morcrette, J.-J., Razinger, M., Schultz, M. G., Suttie, M., and van der Werf, G. R.: Biomass burning emissions estimated with a global fire assimilation system based on observed fire radiative power, Biogeosciences, 9, 527–554, https://doi.org/10.5194/bg-9-527-2012, 2012.
Kanawade, V. P., Srivastava, A. K., Ram, K., Asmi, E., Vakkari, V., Soni, V. K., Varaprasad, V., and Sarangi, C.: What caused severe air pollution episode of November 2016 in New Delhi?, Atmos. Environ., 222, 117125, https://doi.org/10.1016/j.atmosenv.2019.117125, 2020.
Kulkarni, S. H., Ghude, S. D., Jena, C., Karumuri, R. K., Sinha, B., Sinha, V., Kumar, R., Soni, V. K., and Khare, M.: How Much Does Large-Scale Crop Residue Burning Affect the Air Quality in Delhi?, Environ. Sci. Technol., 54, 4790–4799, https://doi.org/10.1021/ACS.EST.0C00329, 2020.
Kumar, A., Hakkim, H., Sinha, B., and Sinha, V.: Gridded 1 km × 1 km emission inventory for paddy stubble burning emissions over north-west India constrained by measured emission factors of 77 VOCs and district-wise crop yield data, Sci. Total Environ., 789, 148064, https://doi.org/10.1016/j.scitotenv.2021.148064, 2021.
Kumar, P., Gulia, S., Harrison, R. M., and Khare, M.: The influence of odd–even car trial on fine and coarse particles in Delhi, Environ. Pollut., 225, 20–30, https://doi.org/10.1016/j.envpol.2017.03.017, 2017.
Kumar, R., Ghude, S. D., Biswas, M., Jena, C., Alessandrini, S., Debnath, S., Kulkarni, S., Sperati, S., Soni, V. K., Nanjundiah, R. S., and Rajeevan, M.: Enhancing accuracy of air quality and temperature forecasts during paddy crop residue burning season in Delhi via chemical data assimilation, J. Geophys. Res.-Atmos., 125, 1–16, https://doi.org/10.1029/2020JD033019, 2020.
Lalchandani, V., Kumar, V., Tobler, A., M. Thamban, N., Mishra, S., Slowik, J. G., Bhattu, D., Rai, P., Satish, R., Ganguly, D., Tiwari, S., Rastogi, N., Tiwari, S., Močnik, G., Prévôt, A. S. H., and Tripathi, S. N.: Real-time characterization and source apportionment of fine particulate matter in the Delhi megacity area during late winter, Sci. Total Environ., 770, 145324, https://doi.org/10.1016/j.scitotenv.2021.145324, 2021.
Li, R., Tao, M., Zhang, M., Chen, L., Wang, L., Wang, Y., He, X., Wei, L., Mei, X., and Wang, J.: Application potential of satellite thermal anomaly products in updating industrial emission inventory, Geophys. Res. Lett., 48, 1–7, https://doi.org/10.1029/2021GL092997, 2021.
Liu, T., Mickley, L. J., Singh, S., Jain, M., Defries, R. S., and Marlier, M. E.: Crop residue burning practices across north India inferred from household survey data: Bridging gaps in satellite observations, Atmos. Environ., 8, 100091, https://doi.org/10.1016/j.aeaoa.2020.100091, 2020.
Liu, Y., Hu, C., Zhan, W., Sun, C., Murch, B., and Ma, L.: Identifying industrial heat sources using time-series of the VIIRS Night fire product with an object-oriented approach, Remote Sens. Environ., 204, 347–365, https://doi.org/10.1016/j.rse.2017.10.019, 2018.
Liu, Z., Liu, Q., Lin, H.-C., Schwartz, C. S., Lee, Y.-H., and Wang, T.: Three-dimensional variational assimilation of MODIS aerosol optical depth: Implementation and application to a dust storm over East Asia, J. Geophys. Res., 116, 1–19, https://doi.org/10.1029/2011JD016159, 2011.
Meng, X., Zhang, K., Pang, K., and Xiang, X.: Characterization of spatio-temporal distribution of vehicle emissions using web-based real-time traffic data, Sci. Total Environ., 709, 136227, https://doi.org/10.1016/j.scitotenv.2019.136227, 2020.
Meteosim: World Most Polluted Cities – Meteosim (WWW Document), Meteosim, https://www.meteosim.com/en/world-most-polluted-citie/ (last access: 5 April 2024), 2019.
Mlawer, E. J., Taubman, S. J., Brown, P. D., Iacono, M. J., and Clough, S. A.: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave, J. Geophys. Res.-Atmos., 102, 16663–16682, https://doi.org/10.1029/97JD00237, 1997.
Molina, M. J. and Molina, L. T.: Megacities and atmospheric pollution, J. Air Waste Manage., 54, 644–680, https://doi.org/10.1080/10473289.2004.10470936, 2004.
Mukherjee, T., Vinoj, V., Midya, S. K., Puppala, S. P., and Adhikary, B.: Numerical simulations of different sectoral contributions to post-monsoon pollution over Delhi, Heliyon, 6, e03548, https://doi.org/10.1016/j.heliyon.2020.e03548, 2020.
Mukhopadhyay, P., Prasad, V. S., Krishna, R., Deshpande, M., Ganai, M., Tirkey, S., Sarkar, S., Goswami, T., Johny, C. J., Roy, K., Mahakur, M., Durai V. R., and Rajeevan, M.: Performance of a very high-resolution global forecast system model (GFS T1534) at 12.5 km over the Indian region during the 2016–2017 monsoon seasons, J. Earth Syst. Sci., 128, 1–18, https://doi.org/10.1007/s12040-019-1186-6, 2019.
Nair, M., Bherwani, H., Kumar, S., Gulia, S., Goyal, S., and Kumar, R.: Assessment of contribution of agricultural residue burning on air quality of Delhi using remote sensing and modelling tools, Atmos. Environ., 230, 117504, https://doi.org/10.1016/j.atmosenv.2020.117504, 2020.
Nakanishi, M. and Niino, H.: An Improved Mellor–Yamada Level-3 Model: Its Numerical Stability and Application to a Regional Prediction of Advection Fog, Bound. Lay. Meteorol., 119, 397–407, https://doi.org/10.1007/s10546-005-9030-8, 2006.
Niu, G. Y., Yang, Z. L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., and Tewari, M.: The community Noah land surface model with multi parameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res.-Atmos., 116, 1–19, https://doi.org/10.1029/2010JD015140, 2011.
Parde, A. N., Dhangar, N. G., Nivdange, S., Ghude, S. D., Pithani, P., Jena, C., Lal, D. M., and Gopalakrishnan, V.: The analysis of pre-monsoon dust storm over Delhi using ground-based observations, Nat. Hazards, 112, 829–844, https://doi.org/10.1007/s11069-022-05207-z, 2022.
Parkhi, N., Chate, D., Ghude, S. D., Peshin, S., Mahajan, A., Srinivas, R., Surendran, D., Ali, K., Singh, S., Trimbake, H., and Beig, G.: Large inter annual variation in air quality during the annual festival “Diwali” in an Indian megacity, J. Environ. Sci., 43, 265–272, https://doi.org/10.1016/j.jes.2015.08.015, 2016.
Pawar, P. V., Ghude, S. D., Govardhan, G., Acharja, P., Kulkarni, R., Kumar, R., Sinha, B., Sinha, V., Jena, C., Gunwani, P., Adhya, T. K., Nemitz, E., and Sutton, M. A.: Chloride (HCl / Cl−) dominates inorganic aerosol formation from ammonia in the Indo-Gangetic Plain during winter: modeling and comparison with observations, Atmos. Chem. Phys., 23, 41–59, https://doi.org/10.5194/acp-23-41-2023, 2023.
Rai, P., Furger, M., el Haddad, I., Kumar, V., Wang, L., Singh, A., Dixit, K., Bhattu, D., Petit, J. E., Ganguly, D., Rastogi, N., Baltensperger, U., Tripathi, S. N., Slowik, J. G., and Prévôt, A. S. H.: Real-time measurement and source apportionment of elements in Delhi's atmosphere, Sci. Total Environ., 742, 140332, https://doi.org/10.1016/j.scitotenv.2020.140332, 2020.
Riahi, K., Van Vuuren, D. P., Kriegler, E., Edmonds, J., O'neill, B. C., Fujimori, S., Bauer, N., Calvin, K., Dellink, R., Fricko, O., and Lutz, W.: The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview, Global Environ. Chang., 42, 153–168, https://doi.org/10.1016/j.gloenvcha.2016.05.009, 2017.
Roebber, P. J.: Visualizing multiple measures of forecast quality, Weather Forecast, 24, 601–608, https://doi.org/10.1175/2008WAF2222159.1, 2009.
Roozitalab, B., Carmichael, G. R., and Guttikunda, S. K.: Improving regional air quality predictions in the Indo-Gangetic Plain – case study of an intensive pollution episode in November 2017, Atmos. Chem. Phys., 21, 2837–2860, https://doi.org/10.5194/acp-21-2837-2021, 2021.
Sahu, S. K., Mangaraj, P., and Beig, G.: Decadal growth in emission load of major air pollutants in Delhi, Earth Syst. Sci. Data, 15, 3183–3202, https://doi.org/10.5194/essd-15-3183-2023, 2023.
Saini, P. and Sharma, M.: Cause and Age-specific premature mortality attributable to PM2.5 Exposure: An analysis for Million-Plus Indian cities, Sci. Total Environ., 710, 135230, https://doi.org/10.1016/j.scitotenv.2019.135230, 2020.
Saxena, P., Srivastava, A., Verma, S., Singh, L., and Sonwani, S.: Analysis of atmospheric pollutants during fireworks festival “`Diwali” at a residential site Delhi in India, in: Energy, Environment, and Sustainability, Springer, 91–105, https://doi.org/10.1007/978-981-15-0540-9_4, 2020.
Schroeder, W., Oliva, P., Giglio, L., and Csiszar, I. A.: The New VIIRS 375 m active fire detection data product: algorithm description and initial assessment, Remote Sens Environ., 143, 85–96, https://doi.org/10.1016/j.rse.2013.12.008, 2014.
Sengupta, A., Govardhan, G., Debnath, S., Yadav, P., Kulkarni, S. H., Parde, A. N., Lonkar, P., Dhangar, N., Gunwani, P., Wagh, S., Nivdange, S., Jena, C., Kumar, R., and Ghude, S. D.: Probing into the wintertime meteorology and particulate matter (PM2.5 and PM10) forecast over Delhi, Atmos. Pollut. Res., 13, 101426, https://doi.org/10.1016/j.apr.2022.101426, 2022.
Sharma, S. K. and Mandal, T. K.: Chemical composition of fine mode particulate matter (PM2.5) in an urban area of Delhi, India and its source apportionment, Urban Climate, 21, 106–122, https://doi.org/10.1016/j.uclim.2017.05.009, 2017.
Sharma, S. K., Sharma, A., Saxena, M., Choudhary, N., Masiwal, R., Mandal, T. K., and Sharma, C.: Chemical characterization and source apportionment of aerosol at an urban area of Central Delhi, India, Atmos. Pollut. Res., 7, 110–121, https://doi.org/10.1016/j.apr.2015.08.002, 2016.
Shivani, Gadi, R., Sharma, S. K., and Mandal, T. K.: Seasonal variation, source apportionment and source attributed health risk of fine carbonaceous aerosols over National Capital Region, India, Chemosphere, 237, 124500, https://doi.org/10.1016/j.chemosphere.2019.124500, 2019.
Singh, D. P., Gadi, R., Mandal, T. K., Dixit, C. K., Singh, K., Saud, T., Singh, N., and Gupta, P. K.: Study of temporal variation in ambient air quality during Diwali festival in India, Environ. Monit. Assess., 169, 1–13, https://doi.org/10.1007/s10661-009-1145-9, 2010.
Sud, S. and Iyengar, S.: A Conceptual Review of the Odd-Even Policy on Delhi's Urban Environment, Artha Journal of Social Sciences, 15, 87–116, https://doi.org/10.12724/ajss.39.6, 2016.
TERI and ARAI: Source apportionment of PM2.5 and PM10 concentrations of Delhi NCR for identification of major sources, TERI and ARAI, https://www.teriin.org/sites/default/files/2018-08/Report_SA_AQM-Delhi-NCR_0.pdf (last access: 26 December 2022), 2018.
Tiwari, S., Bisht, D. S., Srivastava, A. K., Pipal, A. S., Taneja, A., Srivastava, M. K., and Attri, S. D.: Variability in atmospheric particulates and meteorological effects on their mass concentrations over Delhi, India, Atmos. Res., 145, 45–56, https://doi.org/10.1016/j.atmosres.2014.03.027, 2014.
Tiwari, S., Thomas, A., Rao, P., Chate, D. M., Soni, V. K., Singh, S., Ghude, S. D., Singh, D., and Hopke, P. K.: Pollution concentrations in Delhi India during winter 2015–16: A case study of an odd-even vehicle strategy, Atmos. Pollut. Res., 9, 1137–1145, https://doi.org/10.1016/j.apr.2018.04.008, 2018.
Tobler, A., Bhattu, D., Canonaco, F., Lalchandani, V., Shukla, A., Thamban, N. M., Mishra, S., Srivastava, A. K., Bisht, D. S., Tiwari, S., Singh, S., Močnik, G., Baltensperger, U., Tripathi, S. N., Slowik, J. G., and Prévôt, A. S. H.: Chemical characterization of PM2.5 and source apportionment of organic aerosol in New Delhi, India, Sci. Total Environ., 745, 1–12, https://doi.org/10.1016/j.scitotenv.2020.140924, 2020.
Vadrevu, K. P., Lasko, K., Giglio, L., and Justice, C.: Vegetation fires, absorbing aerosols and smoke plume characteristics in diverse biomass burning regions of Asia, Environ. Res. Lett., 10, 105003, https://doi.org/10.1088/1748-9326/10/10/105003, 2015.
Wiedinmyer, C., Akagi, S. K., Yokelson, R. J., Emmons, L. K., Al-Saadi, J. A., Orlando, J. J., and Soja, A. J.: The Fire INventory from NCAR (FINN): a high resolution global model to estimate the emissions from open burning, Geosci. Model Dev., 4, 625–641, https://doi.org/10.5194/gmd-4-625-2011, 2011.
Yadav, A., Behera, S. N., Nagar, P. K., and Sharma, M.: Spatio-seasonal concentrations, source apportionment and assessment of associated human health risks of PM2.5-bound polycyclic aromatic hydrocarbons in delhi, india, Aerosol Air Qual. Res., 20, 2805–2825, https://doi.org/10.4209/aaqr.2020.04.0182, 2020.
Yadav, S., Tripathi, S. N., and Rupakheti, M.: Current status of source apportionment of ambient aerosols in India, Atmos. Environ., 274, 118987, https://doi.org/10.1016/j.atmosenv.2022.118987, 2022.
Zhang, P., Yuan, C., Sun, Q., Liu, A., You, S., Li, X., Zhang, Y., Jiao, X., Sun, D., Sun, M., Liu, M., and Lun, F.: Satellite-based detection and characterization of industrial heat sources in China, Environ. Sci. Technol., 53, 11031–11042, https://doi.org/10.1021/acs.est.9b02643, 2019.
Zhang, X., Han, L., Wei, H., Tan, X., Zhou, W., Li, W., and Qian, Y.: Linking urbanization and air quality together: A review and a perspective on the future sustainable urban development, J. Clean. Prod., 346, 130988, https://doi.org/10.1016/j.jclepro.2022.130988, 2022.
Short summary
A newly developed air quality forecasting framework, Decision Support System (DSS), for air quality management in Delhi, India, provides source attribution with numerous emission reduction scenarios besides forecasts. DSS shows that during post-monsoon and winter seasons, Delhi and its neighboring districts contribute to 30 %–40 % each to pollution in Delhi. On average, a 40 % reduction in the emissions in Delhi and the surrounding districts would result in a 24 % reduction in Delhi's pollution.
A newly developed air quality forecasting framework, Decision Support System (DSS), for air...
