Articles | Volume 11, issue 12
https://doi.org/10.5194/gmd-11-4843-2018
© Author(s) 2018. 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-11-4843-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
04 Dec 2018
Development and technical paper |
| 04 Dec 2018
| 04 Dec 2018
A Lagrangian approach towards extracting signals of urban CO2 emissions from satellite observations of atmospheric column CO2 (XCO2): X-Stochastic Time-Inverted Lagrangian Transport model (“X-STILT v1”)
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, USA
John C. Lin
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, USA
Benjamin Fasoli
Department of Atmospheric Sciences, University of Utah, Salt Lake
City, USA
Tomohiro Oda
Goddard Earth Sciences Technology and Research, Universities Space
Research Association, Columbia, Maryland/Global Modeling and Assimilation
Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Xinxin Ye
Department of Meteorology and Atmospheric Science, Pennsylvania State
University, USA
Thomas Lauvaux
Department of Meteorology and Atmospheric Science, Pennsylvania State
University, USA
Emily G. Yang
Climate and Space Sciences and Engineering, University of Michigan,
Ann Arbor, USA
Eric A. Kort
Climate and Space Sciences and Engineering, University of Michigan,
Ann Arbor, USA
Related authors
Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yuyan Cui, Dien Wu, Alex Turner, and Marc Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2152, https://doi.org/10.5194/egusphere-2024-2152, 2024
Short summary
Short summary
Satellites, such as NASA’s Orbiting Carbon Observatory-2 and -3 (OCO-2/3), retrieve carbon dioxide (CO2) concentrations which provide vital information for estimating surface CO2 emissions. Here we investigate the ability of OCO-2/3 retrievals to constrain CO2 emissions for the state of California for the major emission sectors (i.e., fossil fuels, net ecosystem exchange, wildfire).
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
Short summary
Short summary
To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Kai Wu, Paul I. Palmer, Dien Wu, Denis Jouglet, Liang Feng, and Tom Oda
Atmos. Meas. Tech., 16, 581–602, https://doi.org/10.5194/amt-16-581-2023, https://doi.org/10.5194/amt-16-581-2023, 2023
Short summary
Short summary
We evaluate the theoretical ability of the upcoming MicroCarb satellite to estimate urban CO2 emissions over Paris and London. We explore the relative performance of alternative two-sweep and three-sweep city observing modes and take into account the impacts of cloud cover and urban biological CO2 fluxes. Our results find both the two-sweep and three-sweep observing modes are able to reduce prior flux errors by 20 %–40 % depending on the prevailing wind direction and cloud coverage.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
Short summary
Short summary
Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
Dustin Roten, John C. Lin, Lewis Kunik, Derek Mallia, Dien Wu, Tomohiro Oda, and Eric A. Kort
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-315, https://doi.org/10.5194/acp-2022-315, 2022
Revised manuscript not accepted
Short summary
Short summary
The systems used to monitor carbon dioxide (CO2) emissions from urban areas provides a means to observe and quantify emissions reductions from policy-related reduction efforts. Space-based instruments, such as NASA's Orbiting Carbon Observatory-3 (OCO-3), provides detailed "snapshots" of CO2 emissions from many megacities around the world. This work quantifies the amount of emission "information" contained in these snapshots and uses this information to update previous estimates of urban CO2.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
Short summary
Short summary
A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
Xinxin Ye, Thomas Lauvaux, Eric A. Kort, Tomohiro Oda, Sha Feng, John C. Lin, Emily Yang, and Dien Wu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1022, https://doi.org/10.5194/acp-2017-1022, 2017
Revised manuscript not accepted
Short summary
Short summary
Rapid global urbanization and significant fossil fuel consumption by cities emphasize the necessity of achieving independent and accurate quantification of the carbon emissions from urban areas. In this paper, we assess the potential of using total column CO2 concentration observed from satellite to quantify fossil-fuel carbon emissions from cities. This study could give insights into the capability of satellite observations on monitoring of the emissions on local scale.
John C. Lin, Derek V. Mallia, Dien Wu, and Britton B. Stephens
Atmos. Chem. Phys., 17, 5561–5581, https://doi.org/10.5194/acp-17-5561-2017, https://doi.org/10.5194/acp-17-5561-2017, 2017
Short summary
Short summary
Mountainous areas can potentially serve as regions where the key greenhouse gas, carbon dioxide (CO2), can be absorbed from the atmosphere by vegetation, through photosynthesis. Variations in atmospheric CO2 can be used to understand the amount of biospheric fluxes in general. However, CO2 measured in mountains can be difficult to interpret due to the impact from complex atmospheric flows. We show how mountaintop CO2 data can be interpreted by carrying out a series of atmospheric simulations.
Bianca C. Baier, John B. Miller, Colm Sweeney, Scott Lehman, Chad Wolak, Joshua P. DiGangi, Yonghoon Choi, Kenneth Davis, Sha Feng, and Thomas Lauvaux
EGUsphere, https://doi.org/10.5194/egusphere-2025-821, https://doi.org/10.5194/egusphere-2025-821, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
CO2 radiocarbon content (Δ14CO2) is a unique tracer helps to accurately quantify anthropogenic CO2 emitted into the atmosphere. Δ14CO2 measured in airborne flask samples is used to distinguish fossil versus biogenic CO2 sources. Mid-Atlantic U.S. CO2 variability is found to be driven by the biosphere. Errors in modeled fossil fuel CO2 are evaluated using Δ14CO2 airborne data as an avenue to improving future regional models of atmospheric CO2 transport.
Alexandre Danjou, Grégoire Broquet, Andrew Schuh, François-Marie Bréon, and Thomas Lauvaux
Atmos. Meas. Tech., 18, 533–554, https://doi.org/10.5194/amt-18-533-2025, https://doi.org/10.5194/amt-18-533-2025, 2025
Short summary
Short summary
We study the capacity of XCO2 spaceborne imagery to estimate urban CO2 emissions with synthetic data. We define automatic and standard methods and objective criteria for image selection. The wind variability and urban emission budget guide the emission estimation error. Images with low wind variability and high urban emissions account for 47 % of images and give a bias in the emission estimation of −7 % and a spread of 56 %. Other images give a bias of −31 % and a spread of 99 %.
Félix Langot, Cyril Crevoisier, Thomas Lauvaux, Charbel Abdallah, Jérôme Pernin, Xin Lin, Marielle Saunois, Axel Guedj, Thomas Ponthieu, Anke Roiger, Klaus-Dirk Gottschaldt, and Alina Fiehn
EGUsphere, https://doi.org/10.5194/egusphere-2024-3559, https://doi.org/10.5194/egusphere-2024-3559, 2024
Short summary
Short summary
Our study compares outputs from meteorological and atmospheric composition models to data from the MAGIC2021 campaign that took place in Sweden. Our results highlight performance differences among models, revealing strengths and weaknesses of different modelling techniques. We also found that wetland emission inventories overestimated emissions in regional simulations. This work helps refining methane emission predictions, essential for understanding climate change.
Noémie Taquet, Wolfgang Stremme, María Eugenia González del Castillo, Victor Almanza, Alejandro Bezanilla, Olivier Laurent, Carlos Alberti, Frank Hase, Michel Ramonet, Thomas Lauvaux, Ke Che, and Michel Grutter
Atmos. Chem. Phys., 24, 11823–11848, https://doi.org/10.5194/acp-24-11823-2024, https://doi.org/10.5194/acp-24-11823-2024, 2024
Short summary
Short summary
We characterize the variability in CO and CO2 emissions over Mexico City from long-term time-resolved Fourier transform infrared spectroscopy solar absorption and surface measurements from 2013 to 2021. Using the average intraday CO growth rate from total columns, the average CO / CO2 ratio and TROPOMI data, we estimate the interannual variability in the CO and CO2 anthropogenic emissions of Mexico City, highlighting the effect of an unprecedented drop in activity due to the COVID-19 lockdown.
Rafaela Cruz Alves Alberti, Thomas Lauvaux, Angel Liduvino Vara-Vela, Ricard Segura Barrero, Christoffer Karoff, Maria de Fátima Andrade, Márcia Talita Amorim Marques, Noelia Rojas Benavente, Osvaldo Machado Rodrigues Cabral, Humberto Ribeiro da Rocha, and Rita Yuri Ynoue
EGUsphere, https://doi.org/10.5194/egusphere-2024-3060, https://doi.org/10.5194/egusphere-2024-3060, 2024
Short summary
Short summary
This study addresses uncertainties in atmospheric models by analyzing CO2 dynamics in a complex urban environment characterized by a dense population and tropical vegetation. High-accuracy sensors were deployed, and the WRF-GHG model was utilized to simulate CO2 transport, capturing variations and assessing contributions from both anthropogenic and biogenic sources.
Jinghui Lian, Olivier Laurent, Mali Chariot, Luc Lienhardt, Michel Ramonet, Hervé Utard, Thomas Lauvaux, François-Marie Bréon, Grégoire Broquet, Karina Cucchi, Laurent Millair, and Philippe Ciais
Atmos. Meas. Tech., 17, 5821–5839, https://doi.org/10.5194/amt-17-5821-2024, https://doi.org/10.5194/amt-17-5821-2024, 2024
Short summary
Short summary
We have designed and deployed a mid-cost medium-precision CO2 sensor monitoring network in Paris since July 2020. The data are automatically calibrated by a newly implemented data processing system. The accuracies of the mid-cost instruments vary from 1.0 to 2.4 ppm for hourly afternoon measurements. Our model–data analyses highlight prospects for integrating mid-cost instrument data with high-precision measurements to improve fine-scale CO2 emission quantification in urban areas.
Cynthia D. Nevison, Qing Liang, Paul A. Newman, Britton B. Stephens, Geoff Dutton, Xin Lan, Roisin Commane, Yenny Gonzalez, and Eric Kort
Atmos. Chem. Phys., 24, 10513–10529, https://doi.org/10.5194/acp-24-10513-2024, https://doi.org/10.5194/acp-24-10513-2024, 2024
Short summary
Short summary
This study examines the drivers of interannual variability in tropospheric N2O. New insights are obtained from aircraft data and a chemistry–climate model that explicitly simulates stratospheric N2O. The stratosphere is found to be the dominant driver of N2O variability in the Northern Hemisphere, while both the stratosphere and El Niño cycles are important in the Southern Hemisphere. These results are consistent with known atmospheric dynamics and differences between the hemispheres.
Josselin Doc, Michel Ramonet, François-Marie Bréon, Delphine Combaz, Mali Chariot, Morgan Lopez, Marc Delmotte, Cristelle Cailteau-Fischbach, Guillaume Nief, Nathanaël Laporte, Thomas Lauvaux, and Philippe Ciais
EGUsphere, https://doi.org/10.5194/egusphere-2024-2826, https://doi.org/10.5194/egusphere-2024-2826, 2024
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Description of the network for measuring greenhouse gas concentrations in the Paris region and analysis of eight years of continuous monitoring.
Eleanor J. Derry, Tyler R. Elgiar, Taylor Y. Wilmot, Nicholas W. Hoch, Noah S. Hirshorn, Peter Weiss-Penzias, Christopher F. Lee, John C. Lin, A. Gannet Hallar, Rainer Volkamer, Seth N. Lyman, and Lynne E. Gratz
Atmos. Chem. Phys., 24, 9615–9643, https://doi.org/10.5194/acp-24-9615-2024, https://doi.org/10.5194/acp-24-9615-2024, 2024
Short summary
Short summary
Mercury (Hg) is a globally distributed neurotoxic pollutant. Atmospheric deposition is the main source of Hg in ecosystems. However, measurement biases hinder understanding of the origins and abundance of the more bioavailable oxidized form. We used an improved, calibrated measurement system to study air mass composition and transport of atmospheric Hg at a remote mountaintop site in the central US. Oxidized Hg originated upwind in the low to middle free troposphere under clean, dry conditions.
Matthew S. Johnson, Sofia D. Hamilton, Seongeun Jeong, Yuyan Cui, Dien Wu, Alex Turner, and Marc Fischer
EGUsphere, https://doi.org/10.5194/egusphere-2024-2152, https://doi.org/10.5194/egusphere-2024-2152, 2024
Short summary
Short summary
Satellites, such as NASA’s Orbiting Carbon Observatory-2 and -3 (OCO-2/3), retrieve carbon dioxide (CO2) concentrations which provide vital information for estimating surface CO2 emissions. Here we investigate the ability of OCO-2/3 retrievals to constrain CO2 emissions for the state of California for the major emission sectors (i.e., fossil fuels, net ecosystem exchange, wildfire).
Magdalena Pühl, Anke Roiger, Alina Fiehn, Alan M. Gorchov Negron, Eric A. Kort, Stefan Schwietzke, Ignacio Pisso, Amy Foulds, James Lee, James L. France, Anna E. Jones, Dave Lowry, Rebecca E. Fisher, Langwen Huang, Jacob Shaw, Prudence Bateson, Stephen Andrews, Stuart Young, Pamela Dominutti, Tom Lachlan-Cope, Alexandra Weiss, and Grant Allen
Atmos. Chem. Phys., 24, 1005–1024, https://doi.org/10.5194/acp-24-1005-2024, https://doi.org/10.5194/acp-24-1005-2024, 2024
Short summary
Short summary
In April–May 2019 we carried out an airborne field campaign in the southern North Sea with the aim of studying methane emissions of offshore gas installations. We determined methane emissions from elevated methane measured downstream of the sampled installations. We compare our measured methane emissions with estimated methane emissions from national and global annual inventories. As a result, we find inconsistencies of inventories and large discrepancies between measurements and inventories.
Apisada Chulakadabba, Maryann Sargent, Thomas Lauvaux, Joshua S. Benmergui, Jonathan E. Franklin, Christopher Chan Miller, Jonas S. Wilzewski, Sébastien Roche, Eamon Conway, Amir H. Souri, Kang Sun, Bingkun Luo, Jacob Hawthrone, Jenna Samra, Bruce C. Daube, Xiong Liu, Kelly Chance, Yang Li, Ritesh Gautam, Mark Omara, Jeff S. Rutherford, Evan D. Sherwin, Adam Brandt, and Steven C. Wofsy
Atmos. Meas. Tech., 16, 5771–5785, https://doi.org/10.5194/amt-16-5771-2023, https://doi.org/10.5194/amt-16-5771-2023, 2023
Short summary
Short summary
We show that MethaneAIR, a precursor to the MethaneSAT satellite, demonstrates accurate point source quantification during controlled release experiments and regional observations in 2021 and 2022. Results from our two independent quantification methods suggest the accuracy of our sensor and algorithms is better than 25 % for sources emitting 200 kg h−1 or more. Insights from these measurements help establish the capabilities of MethaneSAT and MethaneAIR.
Ioannis Cheliotis, Thomas Lauvaux, Jinghui Lian, Theodoros Christoudias, George Georgiou, Alba Badia, Frédéric Chevallier, Pramod Kumar, Yathin Kudupaje, Ruixue Lei, and Philippe Ciais
EGUsphere, https://doi.org/10.5194/egusphere-2023-2487, https://doi.org/10.5194/egusphere-2023-2487, 2023
Preprint withdrawn
Short summary
Short summary
A consistent estimation of CO2 emissions is complicated due to the scarcity of CO2 observations. In this study, we showcase the potential to improve the CO2 emissions estimations from the NO2 concentrations based on the NO2-to-CO2 ratio, which should be constant for a source co-emitting NO2 and CO2, by comparing satellite observations with atmospheric chemistry and transport model simulations for NO2 and CO2. Furthermore, we demonstrate the significance of the chemistry in NO2 simulations.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
Short summary
Short summary
To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Jinghui Lian, Thomas Lauvaux, Hervé Utard, François-Marie Bréon, Grégoire Broquet, Michel Ramonet, Olivier Laurent, Ivonne Albarus, Mali Chariot, Simone Kotthaus, Martial Haeffelin, Olivier Sanchez, Olivier Perrussel, Hugo Anne Denier van der Gon, Stijn Nicolaas Camiel Dellaert, and Philippe Ciais
Atmos. Chem. Phys., 23, 8823–8835, https://doi.org/10.5194/acp-23-8823-2023, https://doi.org/10.5194/acp-23-8823-2023, 2023
Short summary
Short summary
This study quantifies urban CO2 emissions via an atmospheric inversion for the Paris metropolitan area over a 6-year period from 2016 to 2021. Results show a long-term decreasing trend of about 2 % ± 0.6 % per year in the annual CO2 emissions over Paris. We conclude that our current capacity can deliver near-real-time CO2 emission estimates at the city scale in under a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories.
Joffrey Dumont Le Brazidec, Pierre Vanderbecken, Alban Farchi, Marc Bocquet, Jinghui Lian, Grégoire Broquet, Gerrit Kuhlmann, Alexandre Danjou, and Thomas Lauvaux
Geosci. Model Dev., 16, 3997–4016, https://doi.org/10.5194/gmd-16-3997-2023, https://doi.org/10.5194/gmd-16-3997-2023, 2023
Short summary
Short summary
Monitoring of CO2 emissions is key to the development of reduction policies. Local emissions, from cities or power plants, may be estimated from CO2 plumes detected in satellite images. CO2 plumes generally have a weak signal and are partially concealed by highly variable background concentrations and instrument errors, which hampers their detection. To address this problem, we propose and apply deep learning methods to detect the contour of a plume in simulated CO2 satellite images.
Kai Wu, Paul I. Palmer, Dien Wu, Denis Jouglet, Liang Feng, and Tom Oda
Atmos. Meas. Tech., 16, 581–602, https://doi.org/10.5194/amt-16-581-2023, https://doi.org/10.5194/amt-16-581-2023, 2023
Short summary
Short summary
We evaluate the theoretical ability of the upcoming MicroCarb satellite to estimate urban CO2 emissions over Paris and London. We explore the relative performance of alternative two-sweep and three-sweep city observing modes and take into account the impacts of cloud cover and urban biological CO2 fluxes. Our results find both the two-sweep and three-sweep observing modes are able to reduce prior flux errors by 20 %–40 % depending on the prevailing wind direction and cloud coverage.
Dien Wu, Junjie Liu, Paul O. Wennberg, Paul I. Palmer, Robert R. Nelson, Matthäus Kiel, and Annmarie Eldering
Atmos. Chem. Phys., 22, 14547–14570, https://doi.org/10.5194/acp-22-14547-2022, https://doi.org/10.5194/acp-22-14547-2022, 2022
Short summary
Short summary
Prior studies have derived the combustion efficiency for a region/city using observed CO2 and CO. We further zoomed into the urban domain and accounted for factors affecting the calculation of spatially resolved combustion efficiency from two satellites. The intra-city variability in combustion efficiency was linked to heavy industry within Shanghai and LA without relying on emission inventories. Such an approach can be applied when analyzing data from future geostationary satellites.
E. Ouerghi, T. Ehret, C. de Franchis, G. Facciolo, T. Lauvaux, E. Meinhardt, and J.-M. Morel
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2022, 147–154, https://doi.org/10.5194/isprs-annals-V-3-2022-147-2022, https://doi.org/10.5194/isprs-annals-V-3-2022-147-2022, 2022
Dustin Roten, John C. Lin, Lewis Kunik, Derek Mallia, Dien Wu, Tomohiro Oda, and Eric A. Kort
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2022-315, https://doi.org/10.5194/acp-2022-315, 2022
Revised manuscript not accepted
Short summary
Short summary
The systems used to monitor carbon dioxide (CO2) emissions from urban areas provides a means to observe and quantify emissions reductions from policy-related reduction efforts. Space-based instruments, such as NASA's Orbiting Carbon Observatory-3 (OCO-3), provides detailed "snapshots" of CO2 emissions from many megacities around the world. This work quantifies the amount of emission "information" contained in these snapshots and uses this information to update previous estimates of urban CO2.
Zhu Deng, Philippe Ciais, Zitely A. Tzompa-Sosa, Marielle Saunois, Chunjing Qiu, Chang Tan, Taochun Sun, Piyu Ke, Yanan Cui, Katsumasa Tanaka, Xin Lin, Rona L. Thompson, Hanqin Tian, Yuanzhi Yao, Yuanyuan Huang, Ronny Lauerwald, Atul K. Jain, Xiaoming Xu, Ana Bastos, Stephen Sitch, Paul I. Palmer, Thomas Lauvaux, Alexandre d'Aspremont, Clément Giron, Antoine Benoit, Benjamin Poulter, Jinfeng Chang, Ana Maria Roxana Petrescu, Steven J. Davis, Zhu Liu, Giacomo Grassi, Clément Albergel, Francesco N. Tubiello, Lucia Perugini, Wouter Peters, and Frédéric Chevallier
Earth Syst. Sci. Data, 14, 1639–1675, https://doi.org/10.5194/essd-14-1639-2022, https://doi.org/10.5194/essd-14-1639-2022, 2022
Short summary
Short summary
In support of the global stocktake of the Paris Agreement on climate change, we proposed a method for reconciling the results of global atmospheric inversions with data from UNFCCC national greenhouse gas inventories (NGHGIs). Here, based on a new global harmonized database that we compiled from the UNFCCC NGHGIs and a comprehensive framework presented in this study to process the results of inversions, we compared their results of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O).
Jennifer D. Hegarty, Karen E. Cady-Pereira, Vivienne H. Payne, Susan S. Kulawik, John R. Worden, Valentin Kantchev, Helen M. Worden, Kathryn McKain, Jasna V. Pittman, Róisín Commane, Bruce C. Daube Jr., and Eric A. Kort
Atmos. Meas. Tech., 15, 205–223, https://doi.org/10.5194/amt-15-205-2022, https://doi.org/10.5194/amt-15-205-2022, 2022
Short summary
Short summary
Carbon monoxide (CO) is produced by combustion of substances such as fossil fuels and plays an important role in atmospheric pollution and climate. We evaluated estimates of atmospheric CO derived from outgoing radiation measurements of the Atmospheric Infrared Sounder (AIRS) on a satellite orbiting the Earth against CO measurements from aircraft to show that these satellite measurements are reliable for continuous global monitoring of atmospheric CO concentrations.
Eric J. Hintsa, Fred L. Moore, Dale F. Hurst, Geoff S. Dutton, Bradley D. Hall, J. David Nance, Ben R. Miller, Stephen A. Montzka, Laura P. Wolton, Audra McClure-Begley, James W. Elkins, Emrys G. Hall, Allen F. Jordan, Andrew W. Rollins, Troy D. Thornberry, Laurel A. Watts, Chelsea R. Thompson, Jeff Peischl, Ilann Bourgeois, Thomas B. Ryerson, Bruce C. Daube, Yenny Gonzalez Ramos, Roisin Commane, Gregory W. Santoni, Jasna V. Pittman, Steven C. Wofsy, Eric Kort, Glenn S. Diskin, and T. Paul Bui
Atmos. Meas. Tech., 14, 6795–6819, https://doi.org/10.5194/amt-14-6795-2021, https://doi.org/10.5194/amt-14-6795-2021, 2021
Short summary
Short summary
We built UCATS to study atmospheric chemistry and transport. It has measured trace gases including CFCs, N2O, SF6, CH4, CO, and H2 with gas chromatography, as well as ozone and water vapor. UCATS has been part of missions to study the tropical tropopause; transport of air into the stratosphere; greenhouse gases, transport, and chemistry in the troposphere; and ozone chemistry, on both piloted and unmanned aircraft. Its design, capabilities, and some results are shown and described here.
Xinxin Ye, Pargoal Arab, Ravan Ahmadov, Eric James, Georg A. Grell, Bradley Pierce, Aditya Kumar, Paul Makar, Jack Chen, Didier Davignon, Greg R. Carmichael, Gonzalo Ferrada, Jeff McQueen, Jianping Huang, Rajesh Kumar, Louisa Emmons, Farren L. Herron-Thorpe, Mark Parrington, Richard Engelen, Vincent-Henri Peuch, Arlindo da Silva, Amber Soja, Emily Gargulinski, Elizabeth Wiggins, Johnathan W. Hair, Marta Fenn, Taylor Shingler, Shobha Kondragunta, Alexei Lyapustin, Yujie Wang, Brent Holben, David M. Giles, and Pablo E. Saide
Atmos. Chem. Phys., 21, 14427–14469, https://doi.org/10.5194/acp-21-14427-2021, https://doi.org/10.5194/acp-21-14427-2021, 2021
Short summary
Short summary
Wildfire smoke has crucial impacts on air quality, while uncertainties in the numerical forecasts remain significant. We present an evaluation of 12 real-time forecasting systems. Comparison of predicted smoke emissions suggests a large spread in magnitudes, with temporal patterns deviating from satellite detections. The performance for AOD and surface PM2.5 and their discrepancies highlighted the role of accurately represented spatiotemporal emission profiles in improving smoke forecasts.
Pramod Kumar, Grégoire Broquet, Camille Yver-Kwok, Olivier Laurent, Susan Gichuki, Christopher Caldow, Ford Cropley, Thomas Lauvaux, Michel Ramonet, Guillaume Berthe, Frédéric Martin, Olivier Duclaux, Catherine Juery, Caroline Bouchet, and Philippe Ciais
Atmos. Meas. Tech., 14, 5987–6003, https://doi.org/10.5194/amt-14-5987-2021, https://doi.org/10.5194/amt-14-5987-2021, 2021
Short summary
Short summary
This study presents a simple atmospheric inversion modeling framework for the localization and quantification of unknown CH4 and CO2 emissions from point sources based on near-surface mobile concentration measurements and a Gaussian plume dispersion model. It is applied for the estimate of a series of brief controlled releases of CH4 and CO2 with a wide range of rates during the TOTAL TADI-2018 experiment. Results indicate a ~10 %–40 % average error on the estimate of the release rates.
Jinghui Lian, François-Marie Bréon, Grégoire Broquet, Thomas Lauvaux, Bo Zheng, Michel Ramonet, Irène Xueref-Remy, Simone Kotthaus, Martial Haeffelin, and Philippe Ciais
Atmos. Chem. Phys., 21, 10707–10726, https://doi.org/10.5194/acp-21-10707-2021, https://doi.org/10.5194/acp-21-10707-2021, 2021
Short summary
Short summary
Currently there is growing interest in monitoring city-scale CO2 emissions based on atmospheric CO2 measurements, atmospheric transport modeling, and inversion technique. We analyze the various sources of uncertainty that impact the atmospheric CO2 modeling and that may compromise the potential of this method for the monitoring of CO2 emission over Paris. Results suggest selection criteria for the assimilation of CO2 measurements into the inversion system that aims at retrieving city emissions.
Dien Wu, John C. Lin, Henrique F. Duarte, Vineet Yadav, Nicholas C. Parazoo, Tomohiro Oda, and Eric A. Kort
Geosci. Model Dev., 14, 3633–3661, https://doi.org/10.5194/gmd-14-3633-2021, https://doi.org/10.5194/gmd-14-3633-2021, 2021
Short summary
Short summary
A model (SMUrF) is presented that estimates biogenic CO2 fluxes over cities around the globe to separate out biogenic fluxes from anthropogenic emissions. The model leverages satellite-based solar-induced fluorescence data and a machine-learning technique. We evaluate the biogenic fluxes against flux observations and show contrasts between biogenic and anthropogenic fluxes over cities, revealing urban–rural flux gradients, diurnal cycles, and the resulting imprints on atmospheric-column CO2.
E. Ouerghi, T. Ehret, C. de Franchis, G. Facciolo, T. Lauvaux, E. Meinhardt, and J.-M. Morel
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-3-2021, 81–87, https://doi.org/10.5194/isprs-annals-V-3-2021-81-2021, https://doi.org/10.5194/isprs-annals-V-3-2021-81-2021, 2021
Amy Hrdina, Jennifer G. Murphy, Anna Gannet Hallar, John C. Lin, Alexander Moravek, Ryan Bares, Ross C. Petersen, Alessandro Franchin, Ann M. Middlebrook, Lexie Goldberger, Ben H. Lee, Munkh Baasandorj, and Steven S. Brown
Atmos. Chem. Phys., 21, 8111–8126, https://doi.org/10.5194/acp-21-8111-2021, https://doi.org/10.5194/acp-21-8111-2021, 2021
Short summary
Short summary
Wintertime air pollution in the Salt Lake Valley is primarily composed of ammonium nitrate, which is formed when gas-phase ammonia and nitric acid react. The major point in this work is that the chemical composition of snow tells a very different story to what we measured in the atmosphere. With the dust–sea salt cations observed in PM2.5 and particle sizing data, we can estimate how much nitric acid may be lost to dust–sea salt that is not accounted for and how much more PM2.5 this could form.
David R. Lyon, Benjamin Hmiel, Ritesh Gautam, Mark Omara, Katherine A. Roberts, Zachary R. Barkley, Kenneth J. Davis, Natasha L. Miles, Vanessa C. Monteiro, Scott J. Richardson, Stephen Conley, Mackenzie L. Smith, Daniel J. Jacob, Lu Shen, Daniel J. Varon, Aijun Deng, Xander Rudelis, Nikhil Sharma, Kyle T. Story, Adam R. Brandt, Mary Kang, Eric A. Kort, Anthony J. Marchese, and Steven P. Hamburg
Atmos. Chem. Phys., 21, 6605–6626, https://doi.org/10.5194/acp-21-6605-2021, https://doi.org/10.5194/acp-21-6605-2021, 2021
Short summary
Short summary
The Permian Basin (USA) is the world’s largest oil field. We use tower- and aircraft-based approaches to measure how methane emissions in the Permian Basin changed throughout 2020. In early 2020, 3.3 % of the region’s gas was emitted; then in spring 2020, the loss rate temporarily dropped to 1.9 % as oil price crashed. We find this short-term reduction to be a result of reduced well development, less gas flaring, and fewer abnormal events despite minimal reductions in oil and gas production.
Xueying Yu, Dylan B. Millet, Kelley C. Wells, Daven K. Henze, Hansen Cao, Timothy J. Griffis, Eric A. Kort, Genevieve Plant, Malte J. Deventer, Randall K. Kolka, D. Tyler Roman, Kenneth J. Davis, Ankur R. Desai, Bianca C. Baier, Kathryn McKain, Alan C. Czarnetzki, and A. Anthony Bloom
Atmos. Chem. Phys., 21, 951–971, https://doi.org/10.5194/acp-21-951-2021, https://doi.org/10.5194/acp-21-951-2021, 2021
Short summary
Short summary
Methane concentrations have doubled since 1750. The US Upper Midwest is a key region contributing to such trends, but sources are poorly understood. We collected and analyzed aircraft data to resolve spatial and timing biases in wetland and livestock emission estimates and uncover errors in inventory treatment of manure management. We highlight the importance of intensive agriculture for the regional and US methane budgets and the potential for methane mitigation through improved management.
Pengfei Han, Ning Zeng, Tom Oda, Xiaohui Lin, Monica Crippa, Dabo Guan, Greet Janssens-Maenhout, Xiaolin Ma, Zhu Liu, Yuli Shan, Shu Tao, Haikun Wang, Rong Wang, Lin Wu, Xiao Yun, Qiang Zhang, Fang Zhao, and Bo Zheng
Atmos. Chem. Phys., 20, 11371–11385, https://doi.org/10.5194/acp-20-11371-2020, https://doi.org/10.5194/acp-20-11371-2020, 2020
Short summary
Short summary
An accurate estimation of China’s fossil-fuel CO2 emissions (FFCO2) is significant for quantification of carbon budget and emissions reductions towards the Paris Agreement goals. Here we assessed 9 global and regional inventories. Our findings highlight the significance of using locally measured coal emission factors. We call on the enhancement of physical measurements for validation and provide comprehensive information for inventory, monitoring, modeling, assimilation, and reducing emissions.
Nikolay V. Balashov, Kenneth J. Davis, Natasha L. Miles, Thomas Lauvaux, Scott J. Richardson, Zachary R. Barkley, and Timothy A. Bonin
Atmos. Chem. Phys., 20, 4545–4559, https://doi.org/10.5194/acp-20-4545-2020, https://doi.org/10.5194/acp-20-4545-2020, 2020
Short summary
Short summary
An accurate independent verification methodology to estimate methane (a powerful greenhouse gas) emissions is essential for the effective implementation of policies that aim to reduce the impacts of climate change. In this paper, four uncertainties that complicate the independent estimation of urban methane emissions are identified: the definition of urban domain, background heterogeneity, emissions temporal variability, and missing sources. Ways to improve emission estimates are suggested.
Xiaohua Pan, Charles Ichoku, Mian Chin, Huisheng Bian, Anton Darmenov, Peter Colarco, Luke Ellison, Tom Kucsera, Arlindo da Silva, Jun Wang, Tomohiro Oda, and Ge Cui
Atmos. Chem. Phys., 20, 969–994, https://doi.org/10.5194/acp-20-969-2020, https://doi.org/10.5194/acp-20-969-2020, 2020
Short summary
Short summary
The differences between these six BB emission datasets are large. Our study found that (1) most current biomass burning (BB) aerosol emission datasets derived from satellite observations lead to the underestimation of aerosol optical depth (AOD) in this model in the biomass-burning-dominated regions and (2) it is important to accurately estimate both the magnitudes and spatial patterns of regional BB emissions in order for a model using these emissions to reproduce observed AOD levels.
Alexander Moravek, Jennifer G. Murphy, Amy Hrdina, John C. Lin, Christopher Pennell, Alessandro Franchin, Ann M. Middlebrook, Dorothy L. Fibiger, Caroline C. Womack, Erin E. McDuffie, Randal Martin, Kori Moore, Munkhbayar Baasandorj, and Steven S. Brown
Atmos. Chem. Phys., 19, 15691–15709, https://doi.org/10.5194/acp-19-15691-2019, https://doi.org/10.5194/acp-19-15691-2019, 2019
Short summary
Short summary
Ammonium nitrate is a major component of fine particulate matter of wintertime air pollution in the Great Salt Lake Region (UT, USA). We investigate the sources of ammonia in the region by using aircraft observations and comparing them to modelled ammonia mixing ratios based on emission inventory estimates. The results suggest that ammonia emissions are underestimated, specifically in regions with high agricultural activity, while ammonia in Salt Lake City is mainly of local origin.
Elizabeth Asher, Rebecca S. Hornbrook, Britton B. Stephens, Doug Kinnison, Eric J. Morgan, Ralph F. Keeling, Elliot L. Atlas, Sue M. Schauffler, Simone Tilmes, Eric A. Kort, Martin S. Hoecker-Martínez, Matt C. Long, Jean-François Lamarque, Alfonso Saiz-Lopez, Kathryn McKain, Colm Sweeney, Alan J. Hills, and Eric C. Apel
Atmos. Chem. Phys., 19, 14071–14090, https://doi.org/10.5194/acp-19-14071-2019, https://doi.org/10.5194/acp-19-14071-2019, 2019
Short summary
Short summary
Halogenated organic trace gases, which are a source of reactive halogens to the atmosphere, exert a disproportionately large influence on atmospheric chemistry and climate. This paper reports novel aircraft observations of halogenated compounds over the Southern Ocean in summer and evaluates hypothesized regional sources and emissions of these trace gases through their relationships to additional aircraft observations.
Thomas Lauvaux, Liza I. Díaz-Isaac, Marc Bocquet, and Nicolas Bousserez
Atmos. Chem. Phys., 19, 12007–12024, https://doi.org/10.5194/acp-19-12007-2019, https://doi.org/10.5194/acp-19-12007-2019, 2019
Short summary
Short summary
A small-size ensemble of mesoscale simulations has been filtered to characterize the spatial structures of transport errors in atmospheric CO2 mixing ratios. The extracted error structures in in situ and column CO2 show similar length scales compared to other meteorological variables, including seasonality, which could be used as proxies in regional inversion systems.
Ryan Bares, Logan Mitchell, Ben Fasoli, David R. Bowling, Douglas Catharine, Maria Garcia, Byron Eng, Jim Ehleringer, and John C. Lin
Earth Syst. Sci. Data, 11, 1291–1308, https://doi.org/10.5194/essd-11-1291-2019, https://doi.org/10.5194/essd-11-1291-2019, 2019
Short summary
Short summary
We overview two near-surface trace gas measurement networks with the aim of describing procedures, locations, and data structure with sufficient detail to serve as an in-depth method reference. Additionally, we developed a novel method for quantifying measurement uncertainty produced by these networks providing insight into appropriate applications of the data and differences in data collection methods. This uncertainty metric is broadly applicable to many trace gas and air quality datasets.
Sean Crowell, David Baker, Andrew Schuh, Sourish Basu, Andrew R. Jacobson, Frederic Chevallier, Junjie Liu, Feng Deng, Liang Feng, Kathryn McKain, Abhishek Chatterjee, John B. Miller, Britton B. Stephens, Annmarie Eldering, David Crisp, David Schimel, Ray Nassar, Christopher W. O'Dell, Tomohiro Oda, Colm Sweeney, Paul I. Palmer, and Dylan B. A. Jones
Atmos. Chem. Phys., 19, 9797–9831, https://doi.org/10.5194/acp-19-9797-2019, https://doi.org/10.5194/acp-19-9797-2019, 2019
Short summary
Short summary
Space-based retrievals of carbon dioxide offer the potential to provide dense data in regions that are sparsely observed by the surface network. We find that flux estimates that are informed by the Orbiting Carbon Observatory-2 (OCO-2) show different character from that inferred using surface measurements in tropical land regions, particularly in Africa, with a much larger total emission and larger amplitude seasonal cycle.
Yilong Wang, Philippe Ciais, Grégoire Broquet, François-Marie Bréon, Tomohiro Oda, Franck Lespinas, Yasjka Meijer, Armin Loescher, Greet Janssens-Maenhout, Bo Zheng, Haoran Xu, Shu Tao, Kevin R. Gurney, Geoffrey Roest, Diego Santaren, and Yongxian Su
Earth Syst. Sci. Data, 11, 687–703, https://doi.org/10.5194/essd-11-687-2019, https://doi.org/10.5194/essd-11-687-2019, 2019
Short summary
Short summary
We address the question of the global characterization of fossil fuel CO2 emission hotspots that may cause coherent XCO2 plumes in space-borne CO2 images, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. For space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 hotspots are identified, covering 72 % of the global emissions. These hotspots define the targets for the purpose of monitoring fossil fuel CO2 emissions from space.
Liza I. Díaz-Isaac, Thomas Lauvaux, Marc Bocquet, and Kenneth J. Davis
Atmos. Chem. Phys., 19, 5695–5718, https://doi.org/10.5194/acp-19-5695-2019, https://doi.org/10.5194/acp-19-5695-2019, 2019
Short summary
Short summary
We demonstrate that transport model errors, one of the main contributors to the uncertainty in regional CO2 inversions, can be represented by a small-size ensemble carefully calibrated with meteorological data. Our results also confirm transport model errors represent a significant fraction of the model–data mismatch in CO2 mole fractions and hence in regional inverse CO2 fluxes.
Anna Karion, Thomas Lauvaux, Israel Lopez Coto, Colm Sweeney, Kimberly Mueller, Sharon Gourdji, Wayne Angevine, Zachary Barkley, Aijun Deng, Arlyn Andrews, Ariel Stein, and James Whetstone
Atmos. Chem. Phys., 19, 2561–2576, https://doi.org/10.5194/acp-19-2561-2019, https://doi.org/10.5194/acp-19-2561-2019, 2019
Short summary
Short summary
In this study, we use atmospheric methane concentration observations collected during an airborne campaign to compare different model-based emissions estimates from the Barnett Shale oil and natural gas production basin in Texas, USA. We find that the tracer dispersion model has a significant impact on the results because the models differ in their simulation of vertical dispersion. Additional work is needed to evaluate and improve vertical mixing in the tracer dispersion models.
Martha P. Butler, Thomas Lauvaux, Sha Feng, Junjie Liu, Kevin W. Bowman, and Kenneth J. Davis
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-342, https://doi.org/10.5194/gmd-2018-342, 2019
Revised manuscript not accepted
Short summary
Short summary
This paper describes a mass-conserving framework for computing time-varying lateral boundary conditions from global model carbon dioxide concentrations for introduction into the WRF-Chem regional model. The goal is to create a laboratory environment in which carbon dioxide transport uncertainties may be explored separately from inversion-derived flux uncertainties. The software is currently available on GitHub at https://github.com/psu-inversion/WRF_Boundary_Coupling.
Benjamin Gaubert, Britton B. Stephens, Sourish Basu, Frédéric Chevallier, Feng Deng, Eric A. Kort, Prabir K. Patra, Wouter Peters, Christian Rödenbeck, Tazu Saeki, David Schimel, Ingrid Van der Laan-Luijkx, Steven Wofsy, and Yi Yin
Biogeosciences, 16, 117–134, https://doi.org/10.5194/bg-16-117-2019, https://doi.org/10.5194/bg-16-117-2019, 2019
Short summary
Short summary
We have compared global carbon budgets calculated from numerical inverse models and CO2 observations, and evaluated how these systems reproduce vertical gradients in atmospheric CO2 from aircraft measurements. We found that available models have converged on near-neutral tropical total fluxes for several decades, implying consistent sinks in intact tropical forests, and that assumed fossil fuel emissions and predicted atmospheric growth rates are now the dominant axes of disagreement.
David Carlson and Tomohiro Oda
Earth Syst. Sci. Data, 10, 2275–2278, https://doi.org/10.5194/essd-10-2275-2018, https://doi.org/10.5194/essd-10-2275-2018, 2018
Jacob K. Hedelius, Junjie Liu, Tomohiro Oda, Shamil Maksyutov, Coleen M. Roehl, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Jianming Liang, Kevin R. Gurney, Debra Wunch, and Paul O. Wennberg
Atmos. Chem. Phys., 18, 16271–16291, https://doi.org/10.5194/acp-18-16271-2018, https://doi.org/10.5194/acp-18-16271-2018, 2018
Short summary
Short summary
Human activities can cause concentrated emissions of greenhouse gases and other pollutants from cities. There is ongoing effort to convert new satellite observations of pollutants into fluxes for many cities. Here we present a method for determining the flux of three species (CO2, CH4, and CO) from the greater LA area using satellite (CO2 only) and ground-based (all three species) observations. We run tests to estimate uncertainty and find the direct net CO2 flux is 104 ± 26 Tg CO2 yr−1.
Alexander Gvakharia, Eric A. Kort, Mackenzie L. Smith, and Stephen Conley
Atmos. Meas. Tech., 11, 6059–6074, https://doi.org/10.5194/amt-11-6059-2018, https://doi.org/10.5194/amt-11-6059-2018, 2018
Short summary
Short summary
We present a new flight system to measure the atmospheric trace gases N2O, CO2, CO, and H2O. We use a novel calibration technique to correct altitude-dependent artifacts that have hindered similar instruments. In-flight null-tests and comparison with other flight-proven instruments provide validation. This high-precision, high-accuracy system provides opportunities for airborne studies to improve our understanding of N2O emission processes.
Liza I. Díaz-Isaac, Thomas Lauvaux, and Kenneth J. Davis
Atmos. Chem. Phys., 18, 14813–14835, https://doi.org/10.5194/acp-18-14813-2018, https://doi.org/10.5194/acp-18-14813-2018, 2018
Short summary
Short summary
Atmospheric inversions rely on the accurate representation of the atmospheric dynamics in order to produce reliable surface fluxes. In this work, we evaluate the sensitivity of a state-of-the-art mesoscale atmospheric model to the different physics parameterizations and forcing. We conclude that no model configuration is optimal across an entire region. Therefore, we recommend an ensemble approach or the assimilation of meteorological observations in future inversion studies.
Benjamin Fasoli, John C. Lin, David R. Bowling, Logan Mitchell, and Daniel Mendoza
Geosci. Model Dev., 11, 2813–2824, https://doi.org/10.5194/gmd-11-2813-2018, https://doi.org/10.5194/gmd-11-2813-2018, 2018
Short summary
Short summary
The Stochastic Time-Inverted Lagrangian Transport (STILT) model is used to determine the area upstream that influences the air arriving at a given location. We introduce a new framework that makes the STILT model faster and easier to deploy and improves results. We also show how the model can be applied to spatially complex measurement strategies using trace gas observations collected onboard a Salt Lake City, Utah, USA, light-rail train.
Richard P. Fiorella, Ryan Bares, John C. Lin, James R. Ehleringer, and Gabriel J. Bowen
Atmos. Chem. Phys., 18, 8529–8547, https://doi.org/10.5194/acp-18-8529-2018, https://doi.org/10.5194/acp-18-8529-2018, 2018
Short summary
Short summary
Fossil fuel combustion produces water; where fossil fuel combustion is concentrated in urban areas, this humidity source may represent ~ 10 % of total humidity. In turn, this water vapor addition may alter urban meteorology, though the contribution of combustion vapor is difficult to measure. Using stable water isotopes, we estimate that up to 16 % of urban humidity may arise from combustion when the atmosphere is stable during winter, and develop recommendations for application in other cities.
Natasha L. Miles, Douglas K. Martins, Scott J. Richardson, Christopher W. Rella, Caleb Arata, Thomas Lauvaux, Kenneth J. Davis, Zachary R. Barkley, Kathryn McKain, and Colm Sweeney
Atmos. Meas. Tech., 11, 1273–1295, https://doi.org/10.5194/amt-11-1273-2018, https://doi.org/10.5194/amt-11-1273-2018, 2018
Short summary
Short summary
Analyzers measuring methane and methane isotopic ratio were deployed at four towers in the Marcellus Shale natural gas extraction region of Pennsylvania. The methane isotopic ratio is helpful for differentiating emissions from natural gas activities from other sources (e.g., landfills). We describe the analyzer calibration. The signals observed in the study region were generally small, but the instrumental performance demonstrated here could be used in regions with stronger enhancements.
Tomohiro Oda, Shamil Maksyutov, and Robert J. Andres
Earth Syst. Sci. Data, 10, 87–107, https://doi.org/10.5194/essd-10-87-2018, https://doi.org/10.5194/essd-10-87-2018, 2018
Short summary
Short summary
The Open-source Data Inventory for Anthropogenic CO2 (ODIAC) is a 1 x 1 km global high-resolution fossil fuel CO2 emissions data product. ODIAC first introduced the combined use of point source profiles and nighttime light satellite data to create high-resolution emissions spatial distributions and it has been intensively used in the carbon cycle research community. This manuscript describes the 2016 version of ODIAC data, the modeling approach, and future data production and model developments.
Xinxin Ye, Thomas Lauvaux, Eric A. Kort, Tomohiro Oda, Sha Feng, John C. Lin, Emily Yang, and Dien Wu
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2017-1022, https://doi.org/10.5194/acp-2017-1022, 2017
Revised manuscript not accepted
Short summary
Short summary
Rapid global urbanization and significant fossil fuel consumption by cities emphasize the necessity of achieving independent and accurate quantification of the carbon emissions from urban areas. In this paper, we assess the potential of using total column CO2 concentration observed from satellite to quantify fossil-fuel carbon emissions from cities. This study could give insights into the capability of satellite observations on monitoring of the emissions on local scale.
Zachary R. Barkley, Thomas Lauvaux, Kenneth J. Davis, Aijun Deng, Natasha L. Miles, Scott J. Richardson, Yanni Cao, Colm Sweeney, Anna Karion, MacKenzie Smith, Eric A. Kort, Stefan Schwietzke, Thomas Murphy, Guido Cervone, Douglas Martins, and Joannes D. Maasakkers
Atmos. Chem. Phys., 17, 13941–13966, https://doi.org/10.5194/acp-17-13941-2017, https://doi.org/10.5194/acp-17-13941-2017, 2017
Short summary
Short summary
This study quantifies methane emissions from natural gas production in north-eastern Pennsylvania. Methane observations from 10 flights in spring 2015 are compared to model-projected values, and methane emissions from natural gas are adjusted within the model to create the best match between the two data sets. This study find methane emissions from natural gas production to be low and may be indicative of characteristics of the basin that make sources from north-eastern Pennsylvania unique.
Andrew K. Thorpe, Christian Frankenberg, David R. Thompson, Riley M. Duren, Andrew D. Aubrey, Brian D. Bue, Robert O. Green, Konstantin Gerilowski, Thomas Krings, Jakob Borchardt, Eric A. Kort, Colm Sweeney, Stephen Conley, Dar A. Roberts, and Philip E. Dennison
Atmos. Meas. Tech., 10, 3833–3850, https://doi.org/10.5194/amt-10-3833-2017, https://doi.org/10.5194/amt-10-3833-2017, 2017
Short summary
Short summary
At local scales emissions of methane (CH4) and carbon dioxide (CO2) are highly uncertain. The AVIRIS-NG imaging spectrometer maps large regions and generates high-spatial-resolution CH4 and CO2 concentration maps from anthropogenic and natural sources. Examples include CH4 from a processing plant, tank, pipeline leak, seep, mine vent shafts, and CO2 from power plants. This demonstrates a greenhouse gas monitoring capability that targets the two dominant anthropogenic climate-forcing agents.
Henrique F. Duarte, Brett M. Raczka, Daniel M. Ricciuto, John C. Lin, Charles D. Koven, Peter E. Thornton, David R. Bowling, Chun-Ta Lai, Kenneth J. Bible, and James R. Ehleringer
Biogeosciences, 14, 4315–4340, https://doi.org/10.5194/bg-14-4315-2017, https://doi.org/10.5194/bg-14-4315-2017, 2017
Short summary
Short summary
We evaluate the Community Land Model (CLM4.5) against observations at an old-growth coniferous forest site that is subjected to water stress each summer. We found that, after calibration, CLM was able to reasonably simulate the observed fluxes of energy and carbon, carbon stocks, carbon isotope ratios, and ecosystem response to water stress. This study demonstrates that carbon isotopes can expose structural weaknesses in CLM and provide a key constraint that may guide future model development.
Yanni Cao, Guido Cervone, Zachary Barkley, Thomas Lauvaux, Aijun Deng, and Alan Taylor
Geosci. Model Dev., 10, 3425–3440, https://doi.org/10.5194/gmd-10-3425-2017, https://doi.org/10.5194/gmd-10-3425-2017, 2017
Short summary
Short summary
This research investigates the role and importance of reprojecting geographic information system layers used by weather numerical models as input by performing sensitivity studies of greenhouse gas transport and dispersion in northeastern Pennsylvania. To bridge the gap between geographic information system data and atmospheric models, this study presents an innovative approach by creating R code to automatically generate model input from geographic data and analyze the model output.
Stephen Conley, Ian Faloona, Shobhit Mehrotra, Maxime Suard, Donald H. Lenschow, Colm Sweeney, Scott Herndon, Stefan Schwietzke, Gabrielle Pétron, Justin Pifer, Eric A. Kort, and Russell Schnell
Atmos. Meas. Tech., 10, 3345–3358, https://doi.org/10.5194/amt-10-3345-2017, https://doi.org/10.5194/amt-10-3345-2017, 2017
Short summary
Short summary
This paper describes a new method of quantifying surface trace gas emissions (e.g. methane) from small aircraft (e.g. Mooney, Cessna) in about 30 min. This technique greatly enhances our ability to rapidly respond in the event of catastrophic failures such as Aliso Canyon and Deep Water Horizon.
Camille Viatte, Thomas Lauvaux, Jacob K. Hedelius, Harrison Parker, Jia Chen, Taylor Jones, Jonathan E. Franklin, Aijun J. Deng, Brian Gaudet, Kristal Verhulst, Riley Duren, Debra Wunch, Coleen Roehl, Manvendra K. Dubey, Steve Wofsy, and Paul O. Wennberg
Atmos. Chem. Phys., 17, 7509–7528, https://doi.org/10.5194/acp-17-7509-2017, https://doi.org/10.5194/acp-17-7509-2017, 2017
Short summary
Short summary
This study estimates methane emissions at local scale in dairy farms using four new mobile ground-based remote sensing spectrometers (EM27/SUN) and isotopic in situ measurements. Our top-down estimates are in the low end of previous studies. Inverse modeling from a comprehensive high-resolution model simulations (WRF-LES) is used to assess the geographical distribution of the emissions. Both the model and the measurements indicate a mixture of anthropogenic and biogenic emissions.
John C. Lin, Derek V. Mallia, Dien Wu, and Britton B. Stephens
Atmos. Chem. Phys., 17, 5561–5581, https://doi.org/10.5194/acp-17-5561-2017, https://doi.org/10.5194/acp-17-5561-2017, 2017
Short summary
Short summary
Mountainous areas can potentially serve as regions where the key greenhouse gas, carbon dioxide (CO2), can be absorbed from the atmosphere by vegetation, through photosynthesis. Variations in atmospheric CO2 can be used to understand the amount of biospheric fluxes in general. However, CO2 measured in mountains can be difficult to interpret due to the impact from complex atmospheric flows. We show how mountaintop CO2 data can be interpreted by carrying out a series of atmospheric simulations.
A. Anthony Bloom, Thomas Lauvaux, John Worden, Vineet Yadav, Riley Duren, Stanley P. Sander, and David S. Schimel
Atmos. Chem. Phys., 16, 15199–15218, https://doi.org/10.5194/acp-16-15199-2016, https://doi.org/10.5194/acp-16-15199-2016, 2016
Short summary
Short summary
Understanding terrestrial carbon processes is a major challenge in climate science. We define the satellite system required to understand greenhouse gas biogeochemistry: our study is focused on Amazon wetland CH4 emissions. We find that future geostationary satellites will provide the CH4 measurements required to understand wetland CH4 processes. Low-earth orbit satellites will be unable to resolve wetland CH4 processes due to a low number of cloud-free CH4 measurements over the Amazon basin.
Clare K. Wong, Thomas J. Pongetti, Tom Oda, Preeti Rao, Kevin R. Gurney, Sally Newman, Riley M. Duren, Charles E. Miller, Yuk L. Yung, and Stanley P. Sander
Atmos. Chem. Phys., 16, 13121–13130, https://doi.org/10.5194/acp-16-13121-2016, https://doi.org/10.5194/acp-16-13121-2016, 2016
Short summary
Short summary
Methane is the second most important greenhouse gas and a target of new emissions regulations in the United States. Despite its importance, its emissions are poorly understood. In this study, we used a remote sensing instrument located on Mount Wilson to estimate the monthly and annual methane emissions from Los Angeles. Derived methane emissions from Los Angeles showed consistent peaks in late summer/early fall and winter during the study period from 2011 to 2015.
Brett Raczka, Henrique F. Duarte, Charles D. Koven, Daniel Ricciuto, Peter E. Thornton, John C. Lin, and David R. Bowling
Biogeosciences, 13, 5183–5204, https://doi.org/10.5194/bg-13-5183-2016, https://doi.org/10.5194/bg-13-5183-2016, 2016
Short summary
Short summary
We use carbon isotopes of CO2 to improve the performance of a land surface model, a component with earth system climate models. We found that isotope observations can provide important information related to the exchange of carbon and water from vegetation driven by environmental stress from low atmospheric moisture and nitrogen limitation. It follows that isotopes have a unique potential to improve model performance and provide insight into land surface model development.
Makoto Inoue, Isamu Morino, Osamu Uchino, Takahiro Nakatsuru, Yukio Yoshida, Tatsuya Yokota, Debra Wunch, Paul O. Wennberg, Coleen M. Roehl, David W. T. Griffith, Voltaire A. Velazco, Nicholas M. Deutscher, Thorsten Warneke, Justus Notholt, John Robinson, Vanessa Sherlock, Frank Hase, Thomas Blumenstock, Markus Rettinger, Ralf Sussmann, Esko Kyrö, Rigel Kivi, Kei Shiomi, Shuji Kawakami, Martine De Mazière, Sabrina G. Arnold, Dietrich G. Feist, Erica A. Barrow, James Barney, Manvendra Dubey, Matthias Schneider, Laura T. Iraci, James R. Podolske, Patrick W. Hillyard, Toshinobu Machida, Yousuke Sawa, Kazuhiro Tsuboi, Hidekazu Matsueda, Colm Sweeney, Pieter P. Tans, Arlyn E. Andrews, Sebastien C. Biraud, Yukio Fukuyama, Jasna V. Pittman, Eric A. Kort, and Tomoaki Tanaka
Atmos. Meas. Tech., 9, 3491–3512, https://doi.org/10.5194/amt-9-3491-2016, https://doi.org/10.5194/amt-9-3491-2016, 2016
Short summary
Short summary
In this study, we correct the biases of GOSAT XCO2 and XCH4 using TCCON data. To evaluate the effectiveness of our correction method, uncorrected/corrected GOSAT data are compared to independent XCO2 and XCH4 data derived from aircraft measurements. Consequently, we suggest that this method is effective for reducing the biases of the GOSAT data. We consider that our work provides GOSAT data users with valuable information and contributes to the further development of studies on greenhouse gases.
Sha Feng, Thomas Lauvaux, Sally Newman, Preeti Rao, Ravan Ahmadov, Aijun Deng, Liza I. Díaz-Isaac, Riley M. Duren, Marc L. Fischer, Christoph Gerbig, Kevin R. Gurney, Jianhua Huang, Seongeun Jeong, Zhijin Li, Charles E. Miller, Darragh O'Keeffe, Risa Patarasuk, Stanley P. Sander, Yang Song, Kam W. Wong, and Yuk L. Yung
Atmos. Chem. Phys., 16, 9019–9045, https://doi.org/10.5194/acp-16-9019-2016, https://doi.org/10.5194/acp-16-9019-2016, 2016
Short summary
Short summary
We developed a high-resolution land–atmosphere modelling system for urban CO2 emissions over the LA Basin. We evaluated various model configurations, FFCO2 products, and the impact of the model resolution. FFCO2 emissions outpace the atmospheric model resolution to represent the CO2 concentration variability across the basin. A novel forward model approach is presented to evaluate the surface measurement network, reinforcing the importance of using high-resolution emission products.
Christian Frankenberg, Susan S. Kulawik, Steven C. Wofsy, Frédéric Chevallier, Bruce Daube, Eric A. Kort, Christopher O'Dell, Edward T. Olsen, and Gregory Osterman
Atmos. Chem. Phys., 16, 7867–7878, https://doi.org/10.5194/acp-16-7867-2016, https://doi.org/10.5194/acp-16-7867-2016, 2016
Short summary
Short summary
We use observations from the HIAPER Pole-to-Pole Observations (HIPPO) flights from January 2009 through September 2011 to validate CO2 measurements from satellites (GOSAT, TES, AIRS) and atmospheric inversion models (CarbonTracker CT2013B, MACC v13r1).
Anna Karion, Colm Sweeney, John B. Miller, Arlyn E. Andrews, Roisin Commane, Steven Dinardo, John M. Henderson, Jacob Lindaas, John C. Lin, Kristina A. Luus, Tim Newberger, Pieter Tans, Steven C. Wofsy, Sonja Wolter, and Charles E. Miller
Atmos. Chem. Phys., 16, 5383–5398, https://doi.org/10.5194/acp-16-5383-2016, https://doi.org/10.5194/acp-16-5383-2016, 2016
Short summary
Short summary
Northern high-latitude carbon sources and sinks, including those resulting from degrading permafrost, are thought to be sensitive to the rapidly warming climate. Here we use carbon dioxide and methane measurements from a tower near Fairbanks AK to investigate regional Alaskan fluxes of CO2 and CH4 for 2012–2014.
F. Deng, D. B. A. Jones, T. W. Walker, M. Keller, K. W. Bowman, D. K. Henze, R. Nassar, E. A. Kort, S. C. Wofsy, K. A. Walker, A. E. Bourassa, and D. A. Degenstein
Atmos. Chem. Phys., 15, 11773–11788, https://doi.org/10.5194/acp-15-11773-2015, https://doi.org/10.5194/acp-15-11773-2015, 2015
Short summary
Short summary
The upper troposphere and lower stratosphere (UTLS) is characterized by strong gradients in the distribution of long-lived tracers, which are sensitive to discrepancies in transport in models. We found that our model overestimates CO2 in the polar UTLS through comparison of modeled CO2 with aircraft observations. We then corrected the modeled CO2 and quantified the impact of the correction on the flux estimates using an atmospheric model together with atmospheric CO2 measured from a satellite.
K. C. Wells, D. B. Millet, N. Bousserez, D. K. Henze, S. Chaliyakunnel, T. J. Griffis, Y. Luan, E. J. Dlugokencky, R. G. Prinn, S. O'Doherty, R. F. Weiss, G. S. Dutton, J. W. Elkins, P. B. Krummel, R. Langenfelds, L. P. Steele, E. A. Kort, S. C. Wofsy, and T. Umezawa
Geosci. Model Dev., 8, 3179–3198, https://doi.org/10.5194/gmd-8-3179-2015, https://doi.org/10.5194/gmd-8-3179-2015, 2015
Short summary
Short summary
This paper introduces a new inversion framework for N2O using GEOS-Chem and its adjoint, which we employed in a series of observing system simulation experiments to evaluate the source and sink constraints provided by surface and aircraft-based N2O measurements. We also applied a new approach for estimating a posteriori uncertainty for high-dimensional inversions, and used it to quantify the spatial and temporal resolution of N2O emission constraints achieved with the current observing network.
C. Viatte, K. Strong, J. Hannigan, E. Nussbaumer, L. K. Emmons, S. Conway, C. Paton-Walsh, J. Hartley, J. Benmergui, and J. Lin
Atmos. Chem. Phys., 15, 2227–2246, https://doi.org/10.5194/acp-15-2227-2015, https://doi.org/10.5194/acp-15-2227-2015, 2015
Short summary
Short summary
Seven tropospheric species (CO, HCN, C2H6, C2H2, CH3OH, HCOOH, and H2CO) released by biomass burning events transported to the high Arctic were monitored with two sets of FTIR measurements, located at Eureka (Nunavut, Canada) and Thule (Greenland), from 2008 to 2012. We compared these data sets with the MOZART-4 chemical transport model to help improve its simulations in the Arctic. Emission factors of these biomass burning products were derived and compared to the literature.
K. W. Wong, D. Fu, T. J. Pongetti, S. Newman, E. A. Kort, R. Duren, Y.-K. Hsu, C. E. Miller, Y. L. Yung, and S. P. Sander
Atmos. Chem. Phys., 15, 241–252, https://doi.org/10.5194/acp-15-241-2015, https://doi.org/10.5194/acp-15-241-2015, 2015
M. Inoue, I. Morino, O. Uchino, Y. Miyamoto, T. Saeki, Y. Yoshida, T. Yokota, C. Sweeney, P. P. Tans, S. C. Biraud, T. Machida, J. V. Pittman, E. A. Kort, T. Tanaka, S. Kawakami, Y. Sawa, K. Tsuboi, and H. Matsueda
Atmos. Meas. Tech., 7, 2987–3005, https://doi.org/10.5194/amt-7-2987-2014, https://doi.org/10.5194/amt-7-2987-2014, 2014
M. O. L. Cambaliza, P. B. Shepson, D. R. Caulton, B. Stirm, D. Samarov, K. R. Gurney, J. Turnbull, K. J. Davis, A. Possolo, A. Karion, C. Sweeney, B. Moser, A. Hendricks, T. Lauvaux, K. Mays, J. Whetstone, J. Huang, I. Razlivanov, N. L. Miles, and S. J. Richardson
Atmos. Chem. Phys., 14, 9029–9050, https://doi.org/10.5194/acp-14-9029-2014, https://doi.org/10.5194/acp-14-9029-2014, 2014
D. Wen, L. Zhang, J. C. Lin, R. Vet, and M. D. Moran
Geosci. Model Dev., 7, 1037–1050, https://doi.org/10.5194/gmd-7-1037-2014, https://doi.org/10.5194/gmd-7-1037-2014, 2014
K. A. Luus, Y. Gel, J. C. Lin, R. E. J. Kelly, and C. R. Duguay
Biogeosciences, 10, 7575–7597, https://doi.org/10.5194/bg-10-7575-2013, https://doi.org/10.5194/bg-10-7575-2013, 2013
J. Worden, K. Wecht, C. Frankenberg, M. Alvarado, K. Bowman, E. Kort, S. Kulawik, M. Lee, V. Payne, and H. Worden
Atmos. Chem. Phys., 13, 3679–3692, https://doi.org/10.5194/acp-13-3679-2013, https://doi.org/10.5194/acp-13-3679-2013, 2013
D. Wen, J. C. Lin, L. Zhang, R. Vet, and M. D. Moran
Geosci. Model Dev., 6, 327–344, https://doi.org/10.5194/gmd-6-327-2013, https://doi.org/10.5194/gmd-6-327-2013, 2013
Related subject area
Atmospheric sciences
Indian Institute of Tropical Meteorology (IITM) High-Resolution Global Forecast Model version 1: an attempt to resolve monsoon prediction deadlock
Cell-tracking-based framework for assessing nowcasting model skill in reproducing growth and decay of convective rainfall
NeuralMie (v1.0): an aerosol optics emulator
Simulation performance of planetary boundary layer schemes in WRF v4.3.1 for near-surface wind over the western Sichuan Basin: a single-site assessment
FootNet v1.0: development of a machine learning emulator of atmospheric transport
Updates and evaluation of NOAA's online-coupled air quality model version 7 (AQMv7) within the Unified Forecast System
Quantifying the analysis uncertainty for nowcasting application
Improving the ensemble square root filter (EnSRF) in the Community Inversion Framework: a case study with ICON-ART 2024.01
The MESSy DWARF (based on MESSy v2.55.2)
An enhanced emission module for the PALM model system 23.10 with application for PM10 emission from urban domestic heating
Identifying lightning processes in ERA5 soundings with deep learning
Sensitivity of predicted ultrafine particle size distributions in Europe to different nucleation rate parameterizations using PMCAMx-UF v2.2
Explaining neural networks for detection of tropical cyclones and atmospheric rivers in gridded atmospheric simulation data
Accurate space-based NOx emission estimates with the flux divergence approach require fine-scale model information on local oxidation chemistry and profile shapes
Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes
Quantifying uncertainties in satellite NO2 superobservations for data assimilation and model evaluation
ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool
Coupling the urban canopy model TEB (SURFEXv9.0) with the radiation model SPARTACUS-Urbanv0.6.1 for more realistic urban radiative exchange calculation
Forecasting contrail climate forcing for flight planning and air traffic management applications: the CocipGrid model in pycontrails 0.51.0
Simulation of the heat mitigation potential of unsealing measures in cities by parameterizing grass grid pavers for urban microclimate modelling with ENVI-met (V5)
AI-NAOS: an AI-based nonspherical aerosol optical scheme for the chemical weather model GRAPES_Meso5.1/CUACE
Orbital-Radar v1.0.0: a tool to transform suborbital radar observations to synthetic EarthCARE cloud radar data
The Modular and Integrated Data Assimilation System at Environment and Climate Change Canada (MIDAS v3.9.1)
Modeling of polycyclic aromatic hydrocarbons (PAHs) from global to regional scales: model development (IAP-AACM_PAH v1.0) and investigation of health risks in 2013 and 2018 in China
LIMA (v2.0): A full two-moment cloud microphysical scheme for the mesoscale non-hydrostatic model Meso-NH v5-6
SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2)
NAQPMS-PDAF v2.0: a novel hybrid nonlinear data assimilation system for improved simulation of PM2.5 chemical components
Source-specific bias correction of US background and anthropogenic ozone modeled in CMAQ
Observational operator for fair model evaluation with ground NO2 measurements
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
The third Met Office Unified Model-JULES Regional Atmosphere and Land Configuration, RAL3
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Exploring ship track spreading rates with a physics-informed Langevin particle parameterization
Do data-driven models beat numerical models in forecasting weather extremes? A comparison of IFS HRES, Pangu-Weather, and GraphCast
Development of the MPAS-CMAQ coupled system (V1.0) for multiscale global air quality modeling
UA-ICON with NWP physics package (version: ua-icon-2.1): mean state and variability of the middle atmosphere
Assessment of object-based indices to identify convective organization
Diagnosis of winter precipitation types using Spectral Bin Model (SBM): Comparison of five methods using ICE-POP 2018 field experiment data
The Global Forest Fire Emissions Prediction System version 1.0
Sensitivity Studies of Four‐Dimensional Local Ensemble Transform Kalman Filter Coupled With WRF-Chem Version 3.9.1 for Improving Particulate Matter Simulation Accuracy
Development of A Fast Radiative Transfer Model for Ground-based Microwave Radiometers (ARMS-gb v1.0): Validation and Comparison to RTTOV-gb
NEIVAv1.0: Next-generation Emissions InVentory expansion of Akagi et al. (2011) version 1.0
FLEXPART version 11: improved accuracy, efficiency, and flexibility
Low-level jets in the North and Baltic Seas: Mesoscale Model Sensitivity and Climatology
Challenges of high-fidelity air quality modeling in urban environments – PALM sensitivity study during stable conditions
Knowledge-inspired fusion strategies for the inference of PM2.5 values with a Neural Network
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
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
EGUsphere, https://doi.org/10.5194/egusphere-2024-3321, https://doi.org/10.5194/egusphere-2024-3321, 2024
Short summary
Short summary
The effectiveness of assimilation system and its sensitivity to ensemble member size and length of assimilation window have been investigated. This study advances our understanding about the selection of basic parameters in the four-dimension local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate matter polluted environment.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
EGUsphere, https://doi.org/10.5194/egusphere-2024-2884, https://doi.org/10.5194/egusphere-2024-2884, 2024
Short summary
Short summary
Assimilating Ground-based microwave radiometers' observations into numerical weather prediction models holds significant promise for enhancing forecast accuracy. Radiative transfer models (RTM) are crucial for direct data assimilation. We propose a new RTM capable of simulating brightness temperatures observed by GMRs and their Jacobians. Several improvements are introduced to achieve higher accuracy.The RTM align with RTTOV-gb well and can achieve smaller STD in water vapor absorption channels.
Samiha Binte Shahid, Forrest G. Lacey, Christine Wiedinmyer, Robert J. Yokelson, and Kelley C. Barsanti
Geosci. Model Dev., 17, 7679–7711, https://doi.org/10.5194/gmd-17-7679-2024, https://doi.org/10.5194/gmd-17-7679-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
Computer models are essential for improving our understanding of how gases and particles move in the atmosphere. We present an update of the atmospheric transport model FLEXPART. FLEXPART 11 is more accurate due to a reduced number of interpolations and a new scheme for wet deposition. It can simulate non-spherical aerosols and includes linear chemical reactions. It is parallelised using OpenMP and includes new user options. A new user manual details how to use FLEXPART 11.
Bjarke Tobias Eisensøe Olsen, Andrea Noemi Hahmann, Nicolás González Alonso-de-Linaje, Mark Žagar, and Martin Dörenkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-3123, https://doi.org/10.5194/egusphere-2024-3123, 2024
Short summary
Short summary
Low-level jets (LLJs) are strong winds in the lower atmosphere, important for wind energy as turbines get taller. This study compares a weather model (WRF) with real data across five North and Baltic Sea sites. Adjusting the model improved accuracy over the widely-used ERA5. In key offshore regions, LLJs occur 10–15 % of the time and significantly boost wind power, especially in spring and summer, contributing up to 30 % of total capacity in some areas.
Jaroslav Resler, Petra Bauerová, Michal Belda, Martin Bureš, Kryštof Eben, Vladimír Fuka, Jan Geletič, Radek Jareš, Jan Karel, Josef Keder, Pavel Krč, William Patiño, Jelena Radović, Hynek Řezníček, Matthias Sühring, Adriana Šindelářová, and Ondřej Vlček
Geosci. Model Dev., 17, 7513–7537, https://doi.org/10.5194/gmd-17-7513-2024, https://doi.org/10.5194/gmd-17-7513-2024, 2024
Short summary
Short summary
Detailed modeling of urban air quality in stable conditions is a challenge. We show the unprecedented sensitivity of a large eddy simulation (LES) model to meteorological boundary conditions and model parameters in an urban environment under stable conditions. We demonstrate the crucial role of boundary conditions for the comparability of results with observations. The study reveals a strong sensitivity of the results to model parameters and model numerical instabilities during such conditions.
Matthieu Dabrowski, José Mennesson, Jérôme Riedi, Chaabane Djeraba, and Pierre Nabat
EGUsphere, https://doi.org/10.5194/egusphere-2024-2676, https://doi.org/10.5194/egusphere-2024-2676, 2024
Short summary
Short summary
This work focuses on the prediction of aerosol concentration values at ground level, which are a strong indicator of air quality, using Artificial Neural Networks. A study of different variables and their efficiency as inputs for these models is also proposed, and reveals that the best results are obtained when using all of them. Comparison of networks architectures and information fusion methods allows the extraction of knowledge on the most efficient methods in the context of this study.
Jorge E. Pachón, Mariel A. Opazo, Pablo Lichtig, Nicolas Huneeus, Idir Bouarar, Guy Brasseur, Cathy W. Y. Li, Johannes Flemming, Laurent Menut, Camilo Menares, Laura Gallardo, Michael Gauss, Mikhail Sofiev, Rostislav Kouznetsov, Julia Palamarchuk, Andreas Uppstu, Laura Dawidowski, Nestor Y. Rojas, María de Fátima Andrade, Mario E. Gavidia-Calderón, Alejandro H. Delgado Peralta, and Daniel Schuch
Geosci. Model Dev., 17, 7467–7512, https://doi.org/10.5194/gmd-17-7467-2024, https://doi.org/10.5194/gmd-17-7467-2024, 2024
Short summary
Short summary
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
Short summary
Short summary
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.
Cited articles
Andres, R. J., Gregg, J. S., Losey, L., Marland, G. and Boden, T. A.:
Monthly, global emissions of carbon dioxide from fossil fuel consumption,
Tellus, Ser. B Chem. Phys. Meteorol., 63, 309–327,
https://doi.org/10.1111/j.1600-0889.2011.00530.x, 2011.
Andres, R. J., Boden, T. A., and Higdon, D.: A new evaluation of the
uncertainty associated with CDIAC estimates of fossil fuel carbon dioxide
emission, Tellus B, 66, 23616, https://doi.org/10.3402/tellusb.v66.23616, 2014.
Andres, R. J., Boden, T. A., and Higdon, D. M.: Gridded uncertainty in fossil
fuel carbon dioxide emission maps, a CDIAC example, Atmos. Chem. Phys., 16,
14979–14995, https://doi.org/10.5194/acp-16-14979-2016, 2016.
Asefi-Najafabad, S., Rayner, P. J., Gurney, K. R., Mcrobert, A., Song, Y.,
Coltin, K., Huang, J., Elvidge, C. and Baugh, K.: A multiyear, global gridded
fossil fuel emission data product: Evaluation and analysis of results, J.
Geophys. Res.-Atmos., 119, 10213–10231, https://doi.org/10.1002/2013JD021296, 2014.
Basu, S., Guerlet, S., Butz, A., Houweling, S., Hasekamp, O., Aben, I.,
Krummel, P., Steele, P., Langenfelds, R., Torn, M., Biraud, S., Stephens, B.,
Andrews, A., and Worthy, D.: Global CO2 fluxes estimated from GOSAT
retrievals of total column CO2, Atmos. Chem. Phys., 13, 8695–8717,
https://doi.org/10.5194/acp-13-8695-2013, 2013.
Brasseur, G. P. and Jacob, D. J.: Modeling of Atmospheric Chemistry,
Cambridge University Press, Cambridge, 2017.
Boden, T. A., Marland, G., and Andres, R. J.: Global, Regional, and National
Fossil-Fuel CO2 Emissions, Carbon Dioxide Information Analysis
Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge,
Tenn., USA, https://doi.org/10.3334/CDIAC/00001_V2017, 2017.
Boesch, H., Baker, D., Connor, B., Crisp, D., and Miller, C.: Global
characterization of CO2 column retrievals from shortwave-infrared
satellite observations of the Orbiting Carbon Observatory-2 mission, Remote
Sens., 3, 270–304, https://doi.org/10.3390/rs3020270, 2011.
BP: Statistical Review of World Energy, available at:
http://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.html
(last access: 6 June 2017), 2017.
Cambaliza, M. O. L., Shepson, P. B., Caulton, D. R., Stirm, B., Samarov, D.,
Gurney, K. R., Turnbull, J., Davis, K. J., Possolo, A., Karion, A., Sweeney,
C., Moser, B., Hendricks, A., Lauvaux, T., Mays, K., Whetstone, J., Huang,
J., Razlivanov, I., Miles, N. L., and Richardson, S. J.: Assessment of
uncertainties of an aircraft-based mass balance approach for quantifying
urban greenhouse gas emissions, Atmos. Chem. Phys., 14, 9029–9050,
https://doi.org/10.5194/acp-14-9029-2014, 2014.
Ciais, P., Sabine, C., Govindasamy, B., Bopp, L., Brovkin, V., Canadell, J.,
Chhabra, A., DeFries, R., Galloway, J., Heimann, M., Jones, C., Le
Quéré, C., Myneni, R., Piao, S., and Thornton, P.: Chapter 6: Carbon
and Other Biogeochemical Cycles, in: Climate Change 2013 The Physical
Science Basis, Cambridge University Press, Cambridge, 2013.
Crisp, D., Fisher, B. M., O'Dell, C., Frankenberg, C., Basilio, R.,
Bösch, H., Brown, L. R., Castano, R., Connor, B., Deutscher, N. M.,
Eldering, A., Griffith, D., Gunson, M., Kuze, A., Mandrake, L., McDuffie, J.,
Messerschmidt, J., Miller, C. E., Morino, I., Natraj, V., Notholt, J.,
O'Brien, D. M., Oyafuso, F., Polonsky, I., Robinson, J., Salawitch, R.,
Sherlock, V., Smyth, M., Suto, H., Taylor, T. E., Thompson, D. R., Wennberg,
P. O., Wunch, D., and Yung, Y. L.: The ACOS CO2 retrieval algorithm
– Part II: Global XCO2 data characterization, Atmos. Meas. Tech.,
5, 687–707, https://doi.org/10.5194/amt-5-687-2012, 2012.
Cui, Y. Y., Brioude, J., Angevine, W. M., Peischl, J., McKeen, S. A., Kim, S.
W., Neuman, J. A., Henze, D. K., Bousserez, N., Fischer, M. L., Jeong, S.,
Michelsen, H. A., Bambha, R. P., Liu, Z., Santoni, G. W., Daube, B. C., Kort,
E. A., Frost, G. J., Ryerson, T. B., Wofsy, S. C., and Trainer, M.: Top-down
estimate of methane emissions in California using a mesoscale inverse
modeling technique: The San Joaquin Valley, J. Geophys. Res.-Atmos., 122,
3686–3699, https://doi.org/10.1002/2016JD026398, 2017.
Deng, A., Lauvaux, T., Davis, K. J., Gaudet, B. J., Miles, N., Richardson, S.
J., Wu, K., Sarmiento, D. P., Hardesty, R. M., Bonin, T. A., Brewer, W. A.,
and Gurney, K. R.: Toward reduced transport errors in a high resolution urban
CO2 inversion system, Elem. Sci. Anth., 5, 20, https://doi.org/10.1525/elementa.133,
2017.
Dlugokencky, E. and Tans, P.: Trends in atmospheric carbon dioxide, National
Oceanic & Atmospheric Administration, Earth System Research Laboratory
(NOAA/ESRL), available at:
http://www.esrl.noaa.gov/gmd/ccgg/trends (last access: 27 July 2017), 2015.
Duren, R. M. and Miller, C. E.: Measuring the carbon emissions of megacities,
Nat. Clim. Chang., 2, 560–562, https://doi.org/10.1038/nclimate1629, 2012.
Efron, B. and Tibshirani, R.: Bootstrap methods for standard errors,
confidence intervals, and other measures of statistical accuracy, Stat. Sci.,
1, 54–75, 1986.
Eldering, A., Bennett, M., and Basilio, R.: The OCO-3 Mission: overview of
science objectives and status, in: EGU General Assembly Conference Abstracts,
18, 5189, 2016.
Ellis, E. C. and Ramankutty, N.: Putting people in the map: anthropogenic
biomes of the world, Front. Ecol. Environ., 6, 439–447, 2008.
Fasoli, B., Lin, J. C., Bowling, D. R., Mitchell, L., and Mendoza, D.:
Simulating atmospheric tracer concentrations for spatially distributed
receptors: updates to the Stochastic Time-Inverted Lagrangian Transport
model's R interface (STILT-R version 2), Geosci. Model Dev., 11, 2813–2824,
https://doi.org/10.5194/gmd-11-2813-2018, 2018.
Feng, S., Lauvaux, T., Newman, S., Rao, P., Ahmadov, R., Deng, A.,
Díaz-Isaac, L. I., Duren, R. M., Fischer, M. L., Gerbig, C., Gurney, K.
R., Huang, J., Jeong, S., Li, Z., Miller, C. E., O'Keeffe, D., Patarasuk, R.,
Sander, S. P., Song, Y., Wong, K. W., and Yung, Y. L.: Los Angeles megacity:
a high-resolution land-atmosphere modelling system for urban CO2
emissions, Atmos. Chem. Phys., 16, 9019–9045,
https://doi.org/10.5194/acp-16-9019-2016, 2016.
Fischer, M. L., Parazoo, N., Brophy, K., Cui, X., Jeong, S., Liu, J.,
Keeling, R., Taylor, T. E., Gurney, K., Oda, T., and Graven, H.: Simulating
estimation of California fossil fuel and biosphere carbon dioxide exchanges
combining in situ tower and satellite column observations, J. Geophys.
Res.-Atmos., 122, 3653–3671, https://doi.org/10.1002/2016JD025617, 2017.
Fisher, J. B., Sikka, M., Huntzinger, D. N., Schwalm, C., and Liu, J.:
Technical note: 3-hourly temporal downscaling of monthly global terrestrial
biosphere model net ecosystem exchange, Biogeosciences, 13, 4271–4277,
https://doi.org/10.5194/bg-13-4271-2016, 2016.
Gately, C. K. and Hutyra, L. R.: Large Uncertainties in Urban-Scale Carbon
Emissions, J. Geophys. Res.-Atmos., 122, 242–260,
https://doi.org/10.1002/2017JD027359, 2017.
Gerbig, C., Lin, J. C., Wofsy, S. C., Daube, B. C., Andrews, A. E., Stephens,
B. B., Bakwin, P. S., and Grainger, C. A.: Toward constraining regional-scale
fluxes of CO2 with atmospheric observations over a continent: 2.
Analysis of COBRA data using a receptor-oriented framework, J. Geophys.
Res.-Atmos., 108, 4757, https://doi.org/10.1029/2003JD003770, 2003.
Gerbig, C., Lin, J. C., Munger, J. W., and Wofsy, S. C.: What can tracer
observations in the continental boundary layer tell us about
surface-atmosphere fluxes?, Atmos. Chem. Phys., 6, 539–554,
https://doi.org/10.5194/acp-6-539-2006, 2006.
Gerbig, C., Körner, S., and Lin, J. C.: Vertical mixing in atmospheric
tracer transport models: error characterization and propagation, Atmos. Chem.
Phys., 8, 591–602, https://doi.org/10.5194/acp-8-591-2008, 2008.
Göckede, M., Turner, D. P., Michalak, A. M., Vickers, D., and Law, B. E.:
Sensitivity of a subregional scale atmospheric inverse CO2 modeling
framework to boundary conditions, J. Geophys. Res.-Atmos., 115, 2010.
Hakkarainen, J., Ialongo, I., and Tamminen, J.: Direct space-based
observations of anthropogenic CO2 emission areas from OCO-2,
Geophys. Res. Lett., 43, 11400–11406, https://doi.org/10.1002/2016GL070885, 2016.
Henderson, J. M., Eluszkiewicz, J., Mountain, M. E., Nehrkorn, T., Chang, R.
Y.-W., Karion, A., Miller, J. B., Sweeney, C., Steiner, N., Wofsy, S. C., and
Miller, C. E.: Atmospheric transport simulations in support of the Carbon in
Arctic Reservoirs Vulnerability Experiment (CARVE), Atmos. Chem. Phys., 15,
4093–4116, https://doi.org/10.5194/acp-15-4093-2015, 2015.
Heymann, J., Reuter, M., Buchwitz, M., Schneising, O., Bovensmann, H.,
Burrows, J. P., Massart, S., Kaiser, J. W., and Crisp, D.: CO2
emission of Indonesian fires in 2015 estimated from satellite-derived
atmospheric CO2 concentrations, Geophys. Res. Lett., 44,
1537–1544, https://doi.org/10.1002/2016GL072042, 2017.
Hogue, S., Marland, E., Andres, R. J., Marland, G., and Woodard, D.:
Uncertainty in gridded CO2 emissions estimates, Earths Future, 4,
225–239, https://doi.org/10.1002/2015EF000343, 2016.
Houweling, S., Breon, F.-M., Aben, I., Rödenbeck, C., Gloor, M., Heimann, M.,
and Ciais, P.: Inverse modeling of CO2 sources and sinks using satellite
data: a synthetic inter-comparison of measurement techniques and their
performance as a function of space and time, Atmos. Chem. Phys., 4, 523–538,
https://doi.org/10.5194/acp-4-523-2004, 2004.
Huntzinger, D. N., Schwalm, C., Michalak, A. M., Schaefer, K., King, A. W.,
Wei, Y., Jacobson, A., Liu, S., Cook, R. B., Post, W. M., Berthier, G.,
Hayes, D., Huang, M., Ito, A., Lei, H., Lu, C., Mao, J., Peng, C. H., Peng,
S., Poulter, B., Riccuito, D., Shi, X., Tian, H., Wang, W., Zeng, N., Zhao,
F., and Zhu, Q.: The North American Carbon Program Multi-Scale Synthesis and
Terrestrial Model Intercomparison Project – Part 1: Overview and
experimental design, Geosci. Model Dev., 6, 2121–2133,
https://doi.org/10.5194/gmd-6-2121-2013, 2013.
Janardanan, R., Maksyutov, S., Oda, T., Saito, M., Kaiser, J. W., Ganshin,
A., Stohl, A., Matsunaga, T., Yoshida, Y., and Yokota, T.: Comparing GOSAT
observations of localized CO2 enhancements by large emitters with
inventory-based estimates, Geophys. Res. Lett., 43, 3486–3493,
https://doi.org/10.1002/2016GL067843, 2016.
Janssens-Maenhout, G., Crippa, M., Guizzardi, D., Muntean, M., Schaaf, E.,
Dentener, F., Bergamaschi, P., Pagliari, V., Olivier, J. G. J., Peters, J. A.
H. W., van Aardenne, J. A., Monni, S., Doering, U., and Petrescu, A. M. R.:
EDGAR v4.3.2 Global Atlas of the three major Greenhouse Gas Emissions for the
period 1970–2012, Earth Syst. Sci. Data Discuss.,
https://doi.org/10.5194/essd-2017-79, 2017.
Jeong, S., Hsu, Y. K., Andrews, A. E., Bianco, L., Vaca, P., Wilczak, J. M.,
and Fischer, M. L.: A multitower measurement network estimate of California's
methane emissions, J. Geophys. Res.-Atmos., 118, 11339–11351,
https://doi.org/10.1002/jgrd.50854, 2013.
Kim, S. Y., Millet, D. B., Hu, L., Mohr, M. J., Griffis, T. J., Wen, D., Lin,
J. C., Miller, S. M., and Longo, M.: Constraints on carbon monoxide emissions
based on tall tower measurements in the US Upper Midwest, Environ. Sci.
Technol., 47, 8316–8324, 2013.
Kort, E. A., Eluszkiewicz, J., Stephens, B. B., Miller, J. B., Gerbig, C.,
Nehrkorn, T., Daube, B. C., Kaplan, J. O., Houweling, S., and Wofsy, S. C.:
Emissions of CH4 and N2O over the United States and
Canada based on a receptor-oriented modeling framework and COBRA-NA
atmospheric observations, Geophys. Res. Lett., 35, L18808,
https://doi.org/10.1029/2008GL034031, 2008.
Kort, E. A., Frankenberg, C., Miller, C. E., and Oda, T.: Space-based
observations of megacity carbon dioxide, Geophys. Res. Lett., 39, 1–5,
https://doi.org/10.1029/2012GL052738, 2012.
Kort, E. A., Angevine, W. M., Duren, R., and Miller, C. E.: Surface
observations for monitoring urban fossil fuel CO2 emissions:
Minimum site location requirements for the Los Angeles megacity, J. Geophys.
Res.-Atmos., 118, 1–8, https://doi.org/10.1002/jgrd.50135, 2013.
Lauvaux, T., Pannekoucke, O., Sarrat, C., Chevallier, F., Ciais, P., Noilhan,
J., and Rayner, P. J.: Structure of the transport uncertainty in mesoscale
inversions of CO2 sources and sinks using ensemble model
simulations, Biogeosciences, 6, 1089–1102,
https://doi.org/10.5194/bg-6-1089-2009, 2009.
Lauvaux, T. and Davis, K. J.: Planetary boundary layer errors in mesoscale
inversions of column-integrated CO2 measurements, J. Geophys.
Res.-Atmos., 119, 490–508, 2014.
Lauvaux, T., Miles, N. L., Richardson, S. J., Deng, A., Stauffer, D. R.,
Davis, K. J., Jacobson, G., Rella, C., Calonder, G. P., and DeCola, P. L.:
Urban emissions of CO2 from Davos, Switzerland: The first real-time
monitoring system using an atmospheric inversion technique, J. Appl.
Meteorol. Climatol., 52, 2654–2668, 2013.
Lauvaux, T., Miles, N. L., Deng, A., Richardson, S. J., Cambaliza, M. O.,
Davis, K. J., Gaudet, B., Gurney, K. R., Huang, J., O'Keefe, D., Song, Y.,
Karion, A., Oda, T., Patarasuk, R., Razlivanov, I., Sarmiento, D., Shepson,
P., Sweeney, C., Turnbull, J., and Wu, K.: High-resolution atmospheric
inversion of urban CO2 emissions during the dormant season of the
Indianapolis Flux Experiment (INFLUX), J. Geophys. Res.-Atmos., 121,
5213–5236, https://doi.org/10.1002/2015JD024473, 2016.
Levin, I., Kromer, B., Schmidt, M., and Sartorius, H.: A novel approach for
independent budgeting of fossil fuel CO2 over Europe by
14CO2 observations, Geophys. Res. Lett., 30, 2194,
https://doi.org/10.1029/2003GL018477, 2003.
Lin, J. C. and Gerbig, C.: Accounting for the effect of transport errors on
tracer inversions, Geophys. Res. Lett., 32, L01802,
https://doi.org/10.1029/2004GL021127, 2005.
Lin, J. C., Gerbig, C., Wofsy, S. C., Andrews, A. E., Daube, B. C., Davis, K.
J., and Grainger, C. A.: A near-field tool for simulating the upstream
influence of atmospheric observations: The Stochastic Time-Inverted
Lagrangian Transport (STILT) model, J. Geophys. Res.-Atmos., 108, 4493,
https://doi.org/10.1029/2002JD003161, 2003.
Lin, J. C., Gerbig, C., Daube, B. C., Wofsy, S. C., Andrews, A. E., Vay, S.
A., and Anderson, B. E.: An empirical analysis of the spatial variability of
atmospheric CO2: Implications for inverse analyses and space-borne
sensors, Geophys. Res. Lett., 31, 1–5, https://doi.org/10.1029/2004GL020957, 2004.
Lin, J. C., Gerbig, C., Wofsy, S. C., Daube, B. C., Matross, D. M., Chow, V.
Y., Gottlieb, E., Andrews, A. E., Pathmathevan, M., and Munger, J. W.: What
have we learned from intensive atmospheric sampling field programmes of
CO2?, Tellus B, 58, 331–343, https://doi.org/10.1111/j.1600-0889.2006.00202.x,
2006.
Lin, J. C., Mallia, D. V., Wu, D., and Stephens, B. B.: How can mountaintop
CO2 observations be used to constrain regional carbon fluxes?, Atmos. Chem.
Phys., 17, 5561–5581, https://doi.org/10.5194/acp-17-5561-2017, 2017.
Liu, Y., Yang, D., and Cai, Z.: A retrieval algorithm for TanSat
XCO2 observation: Retrieval experiments using GOSAT data, Chin.
Sci. Bull., 58, 1520–1523, https://doi.org/10.1007/s11434-013-5680-y, 2013.
Luus, K. A., Commane, R., Parazoo, N. C., Benmergui, J., Euskirchen, E. S.,
Frankenberg, C., Joiner, J., Lindaas, J., Miller, C. E., Oechel, W. C., Zona,
D., Wofsy, S., and Lin, J. C.: Tundra photosynthesis captured by
satellite-observed solar-induced chlorophyll fluorescence, Geophys. Res.
Lett., 44, 1564–1573, https://doi.org/10.1002/2016GL070842, 2017.
Macatangay, R., Warneke, T., Gerbig, C., Körner, S., Ahmadov, R.,
Heimann, M., and Notholt, J.: A framework for comparing remotely sensed and
in-situ CO2 concentrations, Atmos. Chem. Phys., 8, 2555–2568,
https://doi.org/10.5194/acp-8-2555-2008, 2008.
Mallia, D. V, Lin, J. C., Urbanski, S., Ehleringer, J., and Nehrkorn, T.:
Impacts of upwind wildfire emissions on CO, CO2, and
PM2.5 concentrations in Salt Lake City, Utah, J. Geophys.
Res.-Atmos., 120, 147–166, 2015.
Mallia, D. V., Kochanski, A., Wu, D., Pennell, C., Oswald, W., and Lin, J.
C.: Wind-blown dust modeling using a backward-Lagrangian particle dispersion
model, J. Appl. Meteorol. Climatol., 56, 2845–2867,
https://doi.org/10.1175/JAMC-D-16-0351.1, 2017.
Mandrake, L., Frankenberg, C., O'Dell, C. W., Osterman, G., Wennberg, P., and
Wunch, D.: Semi-autonomous sounding selection for OCO-2, Atmos. Meas. Tech.,
6, 2851–2864, https://doi.org/10.5194/amt-6-2851-2013, 2013.
Marland, G.: Uncertainties in accounting for CO2 from fossil fuels,
J. Ind. Ecol., 12, 136–139, https://doi.org/10.1111/j.1530-9290.2008.00014.x, 2008.
Mitchell, L., Lin, J. C., Bowling, D. R., Pataki, D. E., Strong, C., Schauer,
A. J., Bares, R., Bush, S., Stephens, B. B., Mendoza, D., Mallia, D. V,
Holland, L., Gurney, K. R., and Ehleringer, J. R.: Long-term urban carbon
dioxide observations reveal spatial and temporal dynamics related to urban
characteristics and growth, P. Natl. Acad. Sci. USA, 115, 2912–2917,
https://doi.org/10.1073/pnas.1702393115, 2018.
Nassar, R., Napier-Linton, L., Gurney, K. R., Andres, R. J., Oda, T., Vogel,
F. R., and Deng, F.: Improving the temporal and spatial distribution of
CO2 emissions from global fossil fuel emission data sets, J.
Geophys. Res.-Atmos., 118, 917–933, https://doi.org/10.1029/2012JD018196, 2013.
Nassar, R., Hill, T. G., McLinden, C. A., Wunch, D., Jones, D. B. A., and
Crisp, D.: Quantifying CO2 emissions from individual power plants
from space, Geophys. Res. Lett., 44, 10045–10053,
https://doi.org/10.1002/2017GL074702, 2017.
OCO-2 Science Team/Michael Gunson, Annmarie Eldering: OCO-2 Level 2
bias-corrected solar-induced fluorescence and other select fields from the
IMAP-DOAS algorithm aggregated as daily files, Retrospective processing V7r,
Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services
Center (GES DISC), updated data available at: https://doi.org/10.5067/XR7ZWYSKP7D0,
2015.
O'Dell, C. W., Connor, B., Bösch, H., O'Brien, D., Frankenberg, C.,
Castano, R., Christi, M., Eldering, D., Fisher, B., Gunson, M., McDuffie, J.,
Miller, C. E., Natraj, V., Oyafuso, F., Polonsky, I., Smyth, M., Taylor, T.,
Toon, G. C., Wennberg, P. O., and Wunch, D.: The ACOS CO2 retrieval
algorithm – Part 1: Description and validation against synthetic
observations, Atmos. Meas. Tech., 5, 99–121,
https://doi.org/10.5194/amt-5-99-2012, 2012.
Oda, T. and Maksyutov, S.: A very high-resolution (1 km×1 km) global fossil fuel CO2 emission inventory derived
using a point source database and satellite observations of nighttime lights,
Atmos. Chem. Phys., 11, 543–556, https://doi.org/10.5194/acp-11-543-2011,
2011.
Oda, T. and Maksyutov, S.: ODIAC Fossil Fuel CO2 Emissions Dataset
(Version name: ODIAC2017), Center for Global Environmental Research, National
Institute for Environmental Studies, https://doi.org/10.17595/20170411.001 (last access: 18 October 2017), 2015.
Oda, T., Ott, L., Topylko, P., Halushchak, M., Bun, R., Lesiv, M., Danylo,
O., and Horabik-Pyzel, J.: Uncertainty associated with fossil fuel carbon
dioxide (CO2) gridded emission datasets, 2015.
Oda, T., Maksyutov, S., and Andres, R. J.: The Open-source Data Inventory for
Anthropogenic CO2, version 2016 (ODIAC2016): a global monthly
fossil fuel CO2 gridded emissions data product for tracer transport
simulations and surface flux inversions, Earth Syst. Sci. Data, 10, 87–107,
https://doi.org/10.5194/essd-10-87-2018, 2018.
Olsen, S. C. and Randerson, J. T.: Differences between surface and column
atmospheric CO2 and implications for carbon cycle research, J.
Geophys. Res., 109, D02301, https://doi.org/10.1029/2003JD003968, 2004.
Pacala, S. W., Breidenich, C., Brewer, P. G., Fung, I., Gunson, M. R.,
Heddle, G., Marland, G., Paustian, K., Prather, M., Randerson, J. T., Tans,
P., and Wofsy, S. C.: Verifying Greenhouse Gas Emissions: Methods to Support
International Climate Agreements, Tech. rep., Committee on Methods for
Estimating Greenhouse Gas Emissions, Washington, DC, 2010.
Palmer, P. I.: Quantifying sources and sinks of trace gases using space-borne
measurements: current and future science, Philos. T. R. Soc. A, 366,
4509–4528, https://doi.org/10.1098/rsta.2008.0176, 2008.
Patra, P. K., Crisp, D., Kaiser, J. W., Wunch, D., Saeki, T., Ichii, K.,
Sekiya, T., Wennberg, P. O., Feist, D. G., Pollard, D. F., Griffith, D. W.
T., Velazco, V. A., De Maziere, M., Sha, M. K., Roehl, C., Chatterjee, A.,
and Ishijima, K.: The Orbiting Carbon Observatory (OCO-2) tracks 2–3
peta-gram increase in carbon release to the atmosphere during the 2014–2016
El Niño, Sci. Rep., 7, 13567, https://doi.org/10.1038/s41598-017-13459-0, 2017.
Peters, W., Jacobson, A. R., Sweeney, C., Andrews, A. E., Conway, T. J.,
Masarie, K., Miller, J. B., Bruhwiler, L. M. P., Petron, G., Hirsch, A. I.,
Worthy, D. E. J., van der Werf, G. R., Randerson, J. T., Wennberg, P. O.,
Krol, M. C., and Tans, P. P.: An atmospheric perspective on North American
carbon dioxide exchange: CarbonTracker, P. Natl. Acad. Sci. USA, 104,
18925–18930, https://doi.org/10.1073/pnas.0708986104, 2007.
Peylin, P., Houweling, S., Krol, M. C., Karstens, U., Rödenbeck, C.,
Geels, C., Vermeulen, A., Badawy, B., Aulagnier, C., Pregger, T., Delage, F.,
Pieterse, G., Ciais, P., and Heimann, M.: Importance of fossil fuel emission
uncertainties over Europe for CO2 modeling: model intercomparison, Atmos.
Chem. Phys., 11, 6607–6622, https://doi.org/10.5194/acp-11-6607-2011, 2011.
Rayner, P. J. and O'Brien, D. M.: The utility of remotely sensed
CO2 concentration data in surface source inversions, Geophys. Res.
Lett., 28, 175–178, https://doi.org/10.1029/2000GL011912, 2001.
Rayner, P. J., Raupach, M. R., Paget, M., Peylin, P., and Koffi, E.: A new
global gridded data set of CO2 emissions from fossil fuel
combustion: Methodology and evaluation, J. Geophys. Res., 115, D19306,
https://doi.org/10.1029/2009JD013439, 2010.
Reuter, M., Buchwitz, M., Hilker, M., Heymann, J., Schneising, O., Pillai,
D., Bovensmann, H., Burrows, J. P., Bösch, H., Parker, R., Butz, A.,
Hasekamp, O., O'Dell, C. W., Yoshida, Y., Gerbig, C., Nehrkorn, T.,
Deutscher, N. M., Warneke, T., Notholt, J., Hase, F., Kivi, R., Sussmann, R.,
Machida, T., Matsueda, H., and Sawa, Y.: Satellite-inferred European carbon
sink larger than expected, Atmos. Chem. Phys., 14, 13739–13753,
https://doi.org/10.5194/acp-14-13739-2014, 2014.
Rodgers, C. D.: Inverse methods for atmospheric sounding: theory and
practice, World scientific, Singapore, 2000.
Rolph, G., Stein, A., and Stunder, B.: Real-time Environmental Applications
and Display sYstem: READY, Environ. Model. Softw., 95, 210–228,
https://doi.org/10.1016/j.envsoft.2017.06.025, 2017.
Rosenzweig, C., Solecki, W., Hammer, S. A., and Mehrotra, S.: Cities lead the
way in climate-change action, Nature, 467, 909–911, https://doi.org/10.1038/467909a,
2010.
Schneising, O., Heymann, J., Buchwitz, M., Reuter, M., Bovensmann, H., and
Burrows, J. P.: Anthropogenic carbon dioxide source areas observed from
space: assessment of regional enhancements and trends, Atmos. Chem. Phys.,
13, 2445–2454, https://doi.org/10.5194/acp-13-2445-2013, 2013.
Seibert, P. and Frank, A.: Source-receptor matrix calculation with a
Lagrangian particle dispersion model in backward mode, Atmos. Chem. Phys., 4,
51–63, https://doi.org/10.5194/acp-4-51-2004, 2004.
Shiga, Y. P., Michalak, A. M., Gourdji, S. M., Mueller, K. L., and Yadav, V.:
Detecting fossil fuel emissions patterns from subcontinental regions using
North American in situ CO2 measurements, Geophys. Res. Lett., 41,
4381–4388, https://doi.org/10.1002/2014GL059684, 2014.
Shiga, Y. P., Tadić, J. M., Qiu, X., Yadav, V., Andrews, A. E., Berry, J.
A., and Michalak, A. M.: Atmospheric CO2 Observations Reveal Strong
Correlation Between Regional Net Biospheric Carbon Uptake and Solar-Induced
Chlorophyll Fluorescence, Geophys. Res. Lett., 45, 1122–1132,
https://doi.org/10.1002/2017GL076630, 2018.
Silva, S. and Arellano, A.: Characterizing Regional-Scale Combustion Using
Satellite Retrievals of CO, NO2 and CO2, Remote Sens., 9,
744, https://doi.org/10.3390/rs9070744, 2017.
Silva, S. J., Arellano, A. F., and Worden, H. M.: Toward anthropogenic
combustion emission constraints from space-based analysis of urban
CO2∕CO sensitivity, Geophys. Res. Lett., 40, 4971–4976,
https://doi.org/10.1002/grl.50954, 2013.
Skamarock, W. C. and Klemp, J. B.: A time-split nonhydrostatic atmospheric
model for weather research and forecasting applications, J. Comput. Phys.,
227, 3465–3485, 2008.
Stein, A. F., Draxler, R. R., Rolph, G. D., Stunder, B. J. B., Cohen, M. D.,
and Ngan, F.: Noaa's hysplit atmospheric transport and dispersion modeling
system, B. Am. Meteorol. Soc., 96, 2059–2077, https://doi.org/10.1175/BAMS-D-14-00110.1,
2015.
Stephens, B. B., Gurney, K. R., Tans, P. P., Sweeney, C., Peters, W.,
Bruhwiler, L., Ciais, P., Ramonet, M., Bousquet, P., Nakazawa, T., Aoki, S.,
Machida, T., Inoue, G., Vinnichenko, N., Lloyd, J., Jordan, A., Heimann, M.,
Shibistova, O., Langenfelds, R. L., Steele, L. P., Francey, R. J., and
Denning, A. S.: Weak Northern and Strong Tropical Land Carbon Uptake from
Vertical Profiles of Atmospheric CO2, Science, 316, 1732–1736,
https://doi.org/10.1126/science.1137004, 2007.
Stohl, A., Forster, C., Frank, A., Seibert, P., and Wotawa, G.: Technical
note: The Lagrangian particle dispersion model FLEXPART version 6.2, Atmos.
Chem. Phys., 5, 2461–2474, https://doi.org/10.5194/acp-5-2461-2005, 2005.
Sun, Y., Frankenberg, C., Wood, J. D., Schimel, D. S., Jung, M., Guanter, L.,
Drewry, D. T., Verma, M., Porcar-Castell, A., Griffis, T. J., Gu, L., Magney,
T. S., Kohler, P., Evans, B., and Yuen, K.: OCO-2 advances photosynthesis
observation from space via solar-induced chlorophyll fluorescence, Science,
358, eaam5747, https://doi.org/10.1126/science.aam5747, 2017.
Sweeney, C., Karion, A., Wolter, S, Newberger, T, Guenther, D, Higgs, J. A.,
Andrews, A. E., Lang, P. M., Neff, D., Dlugokencky, E., and Miller, J. B.:
Seasonal climatology of CO2 across North America from aircraft
measurements in the NOAA/ESRL Global Greenhouse Gas Reference Network, J.
Geophys. Res.-Atmos., 120, 5155–5190, 2015.
Tollefson, J.: Carbon-sensing satellite system faces high hurdles, Nature,
533, 446–447, 2016.
UNFCCC: National Inventory Submissions 2017, United Nations Framework
Convention on Climate Change, available
at: http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/9492.php,
last access: June 2017.
Venables, W. N. and Ripley, B. D.: Random and mixed effects, in: Modern
applied statistics with S, Springer, New York, NY, 271–300, 2002.
Verhulst, K. R., Karion, A., Kim, J., Salameh, P. K., Keeling, R. F., Newman,
S., Miller, J., Sloop, C., Pongetti, T., Rao, P., Wong, C., Hopkins, F. M.,
Yadav, V., Weiss, R. F., Duren, R. M., and Miller, C. E.: Carbon dioxide and
methane measurements from the Los Angeles Megacity Carbon Project – Part 1:
calibration, urban enhancements, and uncertainty estimates, Atmos. Chem.
Phys., 17, 8313–8341, https://doi.org/10.5194/acp-17-8313-2017, 2017.
Wheeler, D. and Ummel, K.: Calculating CARMA: Global Estimation of
CO2 Emissions from the Power Sector, Work. Pap., 145, 37, available
at:
https://www.cgdev.org/publication/calculating-carma-global-estimation-co2-emissions-power-sector-working-paper-145 (last acess: 18 October 2017),
2008.
Wong, K. W., Fu, D., Pongetti, T. J., Newman, S., Kort, E. A., Duren, R.,
Hsu, Y.-K., Miller, C. E., Yung, Y. L., and Sander, S. P.: Mapping
CH4: CO2 ratios in Los Angeles with CLARS-FTS from Mount
Wilson, California, Atmos. Chem. Phys., 15, 241–252,
https://doi.org/10.5194/acp-15-241-2015, 2015.
Worden, J. R., Doran, G., Kulawik, S., Eldering, A., Crisp, D., Frankenberg,
C., O'Dell, C., and Bowman, K.: Evaluation and attribution of OCO-2
XCO2 uncertainties, Atmos. Meas. Tech., 10, 2759–2771,
https://doi.org/10.5194/amt-10-2759-2017, 2017.
Wu, D., Lin, J., and Fasoli, B.: X-Stochastic Time-Inverted Lagrangian
Transport model (“X-STILT” v1), available at: https://doi.org/10.5281/zenodo.1241514,
2018.
Wunch, D., Wennberg, P. O., Toon, G. C., Keppel-Aleks, G., and Yavin, Y. G.:
Emissions of greenhouse gases from a North American megacity, Geophys. Res.
Lett., 36, 1–5, https://doi.org/10.1029/2009GL039825, 2009.
Wunch, D., Wennberg, P. O., Toon, G. C., Connor, B. J., Fisher, B., Osterman,
G. B., Frankenberg, C., Mandrake, L., O'Dell, C., Ahonen, P., Biraud, S. C.,
Castano, R., Cressie, N., Crisp, D., Deutscher, N. M., Eldering, A., Fisher,
M. L., Griffith, D. W. T., Gunson, M., Heikkinen, P., Keppel-Aleks, G.,
Kyrö, E., Lindenmaier, R., Macatangay, R., Mendonca, J., Messerschmidt,
J., Miller, C. E., Morino, I., Notholt, J., Oyafuso, F. A., Rettinger, M.,
Robinson, J., Roehl, C. M., Salawitch, R. J., Sherlock, V., Strong, K.,
Sussmann, R., Tanaka, T., Thompson, D. R., Uchino, O., Warneke, T., and
Wofsy, S. C.: A method for evaluating bias in global measurements of
CO2 total columns from space, Atmos. Chem. Phys., 11, 12317–12337,
https://doi.org/10.5194/acp-11-12317-2011, 2011.
World Urbanization Prospects: The 2014 Revision (WUP 2014), United Nations,
Department of Economic and Social Affairs, Population Division, CD-ROM
Edition, 2014.
Ye, X., Lauvaux, T., Kort, E. A., Oda, T., Feng, S., Lin, J. C., Yang, E.,
and Wu, D.: Constraining fossil fuel CO2 emissions from urban area
using OCO-2 observations of total column CO2, Atmos. Chem. Phys.
Discuss., https://doi.org/10.5194/acp-2017-1022, in review, 2017.
Yokota, T., Yoshida, Y., Eguchi, N., Ota, Y., Tanaka, T., Watanabe, H., and
Maksyutov, S.: Global Concentrations of CO2 and CH4
Retrieved from GOSAT: First Preliminary Results, Sola, 5, 160–163,
https://doi.org/10.2151/sola.2009-041, 2009.
Zhao, C., Andrews, A. E., Bianco, L., Eluszkiewicz, J., Hirsch, A.,
MacDonald, C., Nehrkorn, T., and Fischer, M. L.: Atmospheric inverse
estimates of methane emissions from Central California, J. Geophys.
Res.-Atmos., 114, 1–13, https://doi.org/10.1029/2008JD011671, 2009.
Zuromski, L. M., Bowling, D. R., Köhler, P., Frankenberg, C., Goulden, M.
L., Blanken, P. D., and Lin, J. C.: Solar-Induced Fluorescence Detects
Interannual Variation in Gross Primary Production of Coniferous Forests in
the Western United States, Geophys. Res. Lett., 45, 7184–7193,
https://doi.org/10.1029/2018GL077906, 2018.
Short summary
Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and atmospheric transport models. However, uncertainties due to model configurations, atmospheric transport, and defined background values can potentially impact the derived urban signals. In this paper, we present a modified Lagrangian model framework that extracts urban CO2 signals from satellite observations and determines potential error impacts.
Urban CO2 enhancement signals can be derived using satellite column CO2 concentrations and...
