Articles | Volume 6, issue 4
https://doi.org/10.5194/gmd-6-1137-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-6-1137-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
07 Aug 2013
Model description paper |
| 07 Aug 2013
Atmospheric dissolved iron deposition to the global oceans: effects of oxalate-promoted Fe dissolution, photochemical redox cycling, and dust mineralogy
M. S. Johnson
now at: NASA Ames Research Center, Moffett Field, CA, USA
Marine, Earth, and Atmospheric Science, North Carolina State University, Raleigh, NC, USA
N. Meskhidze
Marine, Earth, and Atmospheric Science, North Carolina State University, Raleigh, NC, USA
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Matthew S. Johnson, Xiong Liu, Peter Zoogman, John Sullivan, Michael J. Newchurch, Shi Kuang, Thierry Leblanc, and Thomas McGee
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Short summary
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Satellites provide vital information for studying the processes controlling ozone formation. Based on the abundance of particular gases in the atmosphere, ozone formation is sensitive to specific human-induced and natural emission sources. However, errors and biases in satellite retrievals hinder this data source’s application for studying ozone formation sensitivity. We conducted a thorough statistical evaluation of two commonly applied satellites for investigating ozone formation sensitivity.
Brendan Byrne, David F. Baker, Sourish Basu, Michael Bertolacci, Kevin W. Bowman, Dustin Carroll, Abhishek Chatterjee, Frédéric Chevallier, Philippe Ciais, Noel Cressie, David Crisp, Sean Crowell, Feng Deng, Zhu Deng, Nicholas M. Deutscher, Manvendra K. Dubey, Sha Feng, Omaira E. García, David W. T. Griffith, Benedikt Herkommer, Lei Hu, Andrew R. Jacobson, Rajesh Janardanan, Sujong Jeong, Matthew S. Johnson, Dylan B. A. Jones, Rigel Kivi, Junjie Liu, Zhiqiang Liu, Shamil Maksyutov, John B. Miller, Scot M. Miller, Isamu Morino, Justus Notholt, Tomohiro Oda, Christopher W. O'Dell, Young-Suk Oh, Hirofumi Ohyama, Prabir K. Patra, Hélène Peiro, Christof Petri, Sajeev Philip, David F. Pollard, Benjamin Poulter, Marine Remaud, Andrew Schuh, Mahesh K. Sha, Kei Shiomi, Kimberly Strong, Colm Sweeney, Yao Té, Hanqin Tian, Voltaire A. Velazco, Mihalis Vrekoussis, Thorsten Warneke, John R. Worden, Debra Wunch, Yuanzhi Yao, Jeongmin Yun, Andrew Zammit-Mangion, and Ning Zeng
Earth Syst. Sci. Data, 15, 963–1004, https://doi.org/10.5194/essd-15-963-2023, https://doi.org/10.5194/essd-15-963-2023, 2023
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Changes in the carbon stocks of terrestrial ecosystems result in emissions and removals of CO2. These can be driven by anthropogenic activities (e.g., deforestation), natural processes (e.g., fires) or in response to rising CO2 (e.g., CO2 fertilization). This paper describes a dataset of CO2 emissions and removals derived from atmospheric CO2 observations. This pilot dataset informs current capabilities and future developments towards top-down monitoring and verification systems.
Amir H. Souri, Matthew S. Johnson, Glenn M. Wolfe, James H. Crawford, Alan Fried, Armin Wisthaler, William H. Brune, Donald R. Blake, Andrew J. Weinheimer, Tijl Verhoelst, Steven Compernolle, Gaia Pinardi, Corinne Vigouroux, Bavo Langerock, Sungyeon Choi, Lok Lamsal, Lei Zhu, Shuai Sun, Ronald C. Cohen, Kyung-Eun Min, Changmin Cho, Sajeev Philip, Xiong Liu, and Kelly Chance
Atmos. Chem. Phys., 23, 1963–1986, https://doi.org/10.5194/acp-23-1963-2023, https://doi.org/10.5194/acp-23-1963-2023, 2023
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We have rigorously characterized different sources of error in satellite-based HCHO / NO2 tropospheric columns, a widely used metric for diagnosing near-surface ozone sensitivity. Specifically, the errors were categorized/quantified into (i) an inherent chemistry error, (ii) the decoupled relationship between columns and the near-surface concentration, (iii) the spatial representativeness error of ground satellite pixels, and (iv) the satellite retrieval errors.
Brendan Byrne, Junjie Liu, Yonghong Yi, Abhishek Chatterjee, Sourish Basu, Rui Cheng, Russell Doughty, Frédéric Chevallier, Kevin W. Bowman, Nicholas C. Parazoo, David Crisp, Xing Li, Jingfeng Xiao, Stephen Sitch, Bertrand Guenet, Feng Deng, Matthew S. Johnson, Sajeev Philip, Patrick C. McGuire, and Charles E. Miller
Biogeosciences, 19, 4779–4799, https://doi.org/10.5194/bg-19-4779-2022, https://doi.org/10.5194/bg-19-4779-2022, 2022
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Plants draw CO2 from the atmosphere during the growing season, while respiration releases CO2 to the atmosphere throughout the year, driving seasonal variations in atmospheric CO2 that can be observed by satellites, such as the Orbiting Carbon Observatory 2 (OCO-2). Using OCO-2 XCO2 data and space-based constraints on plant growth, we show that permafrost-rich northeast Eurasia has a strong seasonal release of CO2 during the autumn, hinting at an unexpectedly large respiration signal from soils.
Meloë S. F. Kacenelenbogen, Qian Tan, Sharon P. Burton, Otto P. Hasekamp, Karl D. Froyd, Yohei Shinozuka, Andreas J. Beyersdorf, Luke Ziemba, Kenneth L. Thornhill, Jack E. Dibb, Taylor Shingler, Armin Sorooshian, Reed W. Espinosa, Vanderlei Martins, Jose L. Jimenez, Pedro Campuzano-Jost, Joshua P. Schwarz, Matthew S. Johnson, Jens Redemann, and Gregory L. Schuster
Atmos. Chem. Phys., 22, 3713–3742, https://doi.org/10.5194/acp-22-3713-2022, https://doi.org/10.5194/acp-22-3713-2022, 2022
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The impact of aerosols on Earth's radiation budget and human health is important and strongly depends on their composition. One desire of our scientific community is to derive the composition of the aerosol from satellite sensors. However, satellites observe aerosol optical properties (and not aerosol composition) based on remote sensing instrumentation. This study assesses how much aerosol optical properties can tell us about aerosol composition.
Hélène Peiro, Sean Crowell, Andrew Schuh, David F. Baker, Chris O'Dell, Andrew R. Jacobson, Frédéric Chevallier, Junjie Liu, Annmarie Eldering, David Crisp, Feng Deng, Brad Weir, Sourish Basu, Matthew S. Johnson, Sajeev Philip, and Ian Baker
Atmos. Chem. Phys., 22, 1097–1130, https://doi.org/10.5194/acp-22-1097-2022, https://doi.org/10.5194/acp-22-1097-2022, 2022
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Satellite CO2 observations are constantly improved. We study an ensemble of different atmospheric models (inversions) from 2015 to 2018 using separate ground-based data or two versions of the OCO-2 satellite. Our study aims to determine if different satellite data corrections can yield different estimates of carbon cycle flux. A difference in the carbon budget between the two versions is found over tropical Africa, which seems to show the impact of corrections applied in satellite data.
Amir H. Souri, Kelly Chance, Kang Sun, Xiong Liu, and Matthew S. Johnson
Atmos. Meas. Tech., 15, 41–59, https://doi.org/10.5194/amt-15-41-2022, https://doi.org/10.5194/amt-15-41-2022, 2022
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The central component of satellite and model validation is pointwise measurements. A point is an element of space, whereas satellite (model) pixels represent an averaged area. These two datasets are inherently different. We leveraged some geostatistical tools to transform discrete points to gridded data with quantified uncertainty, comparable to satellite footprint (and response functions). This in part alleviated some complications concerning point–pixel comparisons.
Jia Su, M. Patrick McCormick, Matthew S. Johnson, John T. Sullivan, Michael J. Newchurch, Timothy A. Berkoff, Shi Kuang, and Guillaume P. Gronoff
Atmos. Meas. Tech., 14, 4069–4082, https://doi.org/10.5194/amt-14-4069-2021, https://doi.org/10.5194/amt-14-4069-2021, 2021
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A new technique using a three-wavelength differential absorption lidar (DIAL) technique based on an optical parametric oscillator (OPO) laser is proposed to obtain more accurate measurements of NO2. The retrieval uncertainties in aerosol extinction using the three-wavelength DIAL technique are reduced to less than 2 % of those when using the two-wavelength DIAL technique. Hampton University (HU) lidar NO2 profiles are compared with simulated data from the WRF-Chem model, and they agree well.
Fernando Chouza, Thierry Leblanc, Mark Brewer, Patrick Wang, Sabino Piazzolla, Gabriele Pfister, Rajesh Kumar, Carl Drews, Simone Tilmes, Louisa Emmons, and Matthew Johnson
Atmos. Chem. Phys., 21, 6129–6153, https://doi.org/10.5194/acp-21-6129-2021, https://doi.org/10.5194/acp-21-6129-2021, 2021
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The tropospheric ozone lidar at the JPL Table Mountain Facility (TMF) was used to investigate the impact of Los Angeles (LA) Basin pollution transport and stratospheric intrusions in the planetary boundary layer on the San Gabriel Mountains. The results of this study indicate a dominant role of the LA Basin pollution on days when high ozone levels were observed at TMF (March–October period).
Sajeev Philip, Matthew S. Johnson, Christopher Potter, Vanessa Genovesse, David F. Baker, Katherine D. Haynes, Daven K. Henze, Junjie Liu, and Benjamin Poulter
Atmos. Chem. Phys., 19, 13267–13287, https://doi.org/10.5194/acp-19-13267-2019, https://doi.org/10.5194/acp-19-13267-2019, 2019
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This research was conducted to quantify the impact of different prior global biosphere models on the estimate of terrestrial CO2 fluxes when assimilating Orbiting Carbon Observatory-2 (OCO-2) satellite observations. To determine the prior model impact, we apply observing system simulation experiments (OSSEs). Even with the substantial spatiotemporal coverage of OCO-2 data, residual differences in posterior CO2 flux estimates remain due to the choice of prior flux mean and uncertainties.
Thierry Leblanc, Mark A. Brewer, Patrick S. Wang, Maria Jose Granados-Muñoz, Kevin B. Strawbridge, Michael Travis, Bernard Firanski, John T. Sullivan, Thomas J. McGee, Grant K. Sumnicht, Laurence W. Twigg, Timothy A. Berkoff, William Carrion, Guillaume Gronoff, Ali Aknan, Gao Chen, Raul J. Alvarez, Andrew O. Langford, Christoph J. Senff, Guillaume Kirgis, Matthew S. Johnson, Shi Kuang, and Michael J. Newchurch
Atmos. Meas. Tech., 11, 6137–6162, https://doi.org/10.5194/amt-11-6137-2018, https://doi.org/10.5194/amt-11-6137-2018, 2018
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This article reviews the capability of five ozone lidars from the North American TOLNet lidar network. These ground-based laser remote-sensing instruments typically measure ozone in the troposphere with a precision of 5 % and vertical and time resolutions of 100 m and 10 min, respectively. Understanding ozone variability at high spatiotemporal scales is essential for monitoring air quality, human health, and climate. The article shows that the TOLNet lidars are very well suited for this purpose.
Stelios Myriokefalitakis, Akinori Ito, Maria Kanakidou, Athanasios Nenes, Maarten C. Krol, Natalie M. Mahowald, Rachel A. Scanza, Douglas S. Hamilton, Matthew S. Johnson, Nicholas Meskhidze, Jasper F. Kok, Cecile Guieu, Alex R. Baker, Timothy D. Jickells, Manmohan M. Sarin, Srinivas Bikkina, Rachel Shelley, Andrew Bowie, Morgane M. G. Perron, and Robert A. Duce
Biogeosciences, 15, 6659–6684, https://doi.org/10.5194/bg-15-6659-2018, https://doi.org/10.5194/bg-15-6659-2018, 2018
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The first atmospheric iron (Fe) deposition model intercomparison is presented in this study, as a result of the deliberations of the United Nations Joint Group of Experts on the Scientific Aspects of Marine Environmental Protection (GESAMP; http://www.gesamp.org/) Working Group 38. We conclude that model diversity over remote oceans reflects uncertainty in the Fe content parameterizations of dust aerosols, combustion aerosol emissions and the size distribution of transported aerosol Fe.
Matthew S. Johnson, Xiong Liu, Peter Zoogman, John Sullivan, Michael J. Newchurch, Shi Kuang, Thierry Leblanc, and Thomas McGee
Atmos. Meas. Tech., 11, 3457–3477, https://doi.org/10.5194/amt-11-3457-2018, https://doi.org/10.5194/amt-11-3457-2018, 2018
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This research was conducted to determine the impact of multiple a priori ozone (O3) profile products on Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite retrievals. It was determined that non-climatological model predictions, in particular those from a chemical transport model, when applied as the a priori profile improved the accuracy of TEMPO tropospheric O3 retrievals in comparison to the TB-Clim product that is currently suggested for use in the TEMPO retrieval algorithm.
N. Meskhidze, M. S. Johnson, D. Hurley, and K. Dawson
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-14377-2015, https://doi.org/10.5194/bgd-12-14377-2015, 2015
Revised manuscript not accepted
K. W. Dawson, N. Meskhidze, D. Josset, and S. Gassó
Atmos. Chem. Phys., 15, 3241–3255, https://doi.org/10.5194/acp-15-3241-2015, https://doi.org/10.5194/acp-15-3241-2015, 2015
B. Gantt, M. S. Johnson, M. Crippa, A. S. H. Prévôt, and N. Meskhidze
Geosci. Model Dev., 8, 619–629, https://doi.org/10.5194/gmd-8-619-2015, https://doi.org/10.5194/gmd-8-619-2015, 2015
N. Meskhidze, A. Sabolis, R. Reed, and D. Kamykowski
Biogeosciences, 12, 637–651, https://doi.org/10.5194/bg-12-637-2015, https://doi.org/10.5194/bg-12-637-2015, 2015
E. L. Yates, L. T. Iraci, M. C. Roby, R. B. Pierce, M. S. Johnson, P. J. Reddy, J. M. Tadić, M. Loewenstein, and W. Gore
Atmos. Chem. Phys., 13, 12481–12494, https://doi.org/10.5194/acp-13-12481-2013, https://doi.org/10.5194/acp-13-12481-2013, 2013
B. Gantt and N. Meskhidze
Atmos. Chem. Phys., 13, 3979–3996, https://doi.org/10.5194/acp-13-3979-2013, https://doi.org/10.5194/acp-13-3979-2013, 2013
Related subject area
Atmospheric sciences
Evaluation of dust emission and land surface schemes in predicting a mega Asian dust storm over South Korea using WRF-Chem
Sensitivity studies of a four-dimensional local ensemble transform Kalman filter coupled with WRF-Chem version 3.9.1 for improving particulate matter simulation accuracy
A Bayesian method for predicting background radiation at environmental monitoring stations in local-scale networks
Inclusion of the ECMWF ecRad radiation scheme (v1.5.0) in the MAR (v3.14), regional evaluation for Belgium, and assessment of surface shortwave spectral fluxes at Uccle
Development of a fast radiative transfer model for ground-based microwave radiometers (ARMS-gb v1.0): validation and comparison to RTTOV-gb
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
PALACE v1.0: Paranal Airglow Line And Continuum Emission model
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)
A new set of indicators for model evaluation complementing to FAIRMODE’s MQO
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)
Carbon dioxide plume dispersion simulated at hectometer scale using DALES: model formulation and observational evaluation
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
Atmospheric moisture tracking with WAM2layers v3
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
Ji Won Yoon, Seungyeon Lee, Ebony Lee, and Seon Ki Park
Geosci. Model Dev., 18, 2303–2328, https://doi.org/10.5194/gmd-18-2303-2025, https://doi.org/10.5194/gmd-18-2303-2025, 2025
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This study evaluates the Weather Research and Forecasting Model (WRF) coupled with Chemistry (WRF-Chem) to predict a mega Asian dust storm (ADS) over South Korea on 28–29 March 2021. We assessed combinations of five dust emission and four land surface schemes by analyzing meteorological and air quality variables. The best scheme combination reduced the root mean square error (RMSE) for particulate matter 10 (PM10) by up to 29.6 %, demonstrating the highest performance.
Jianyu Lin, Tie Dai, Lifang Sheng, Weihang Zhang, Shangfei Hai, and Yawen Kong
Geosci. Model Dev., 18, 2231–2248, https://doi.org/10.5194/gmd-18-2231-2025, https://doi.org/10.5194/gmd-18-2231-2025, 2025
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The effectiveness of this assimilation system and its sensitivity to the ensemble member size and length of the assimilation window are investigated. This study advances our understanding of the selection of basic parameters in the four-dimensional local ensemble transform Kalman filter assimilation system and the performance of ensemble simulation in a particulate-matter-polluted environment.
Jens Peter Karolus Wenceslaus Frankemölle, Johan Camps, Pieter De Meutter, and Johan Meyers
Geosci. Model Dev., 18, 1989–2003, https://doi.org/10.5194/gmd-18-1989-2025, https://doi.org/10.5194/gmd-18-1989-2025, 2025
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To detect anomalous radioactivity in the environment, it is paramount that we understand the natural background level. In this work, we propose a statistical model to describe the most likely background level and the associated uncertainty in a network of dose rate detectors. We train, verify, and validate the model using real environmental data. Using the model, we show that we can correctly predict the background level in a subset of the detector network during a known
anomalous event.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Yi-Ning Shi, Jun Yang, Wei Han, Lujie Han, Jiajia Mao, Wanlin Kan, and Fuzhong Weng
Geosci. Model Dev., 18, 1947–1964, https://doi.org/10.5194/gmd-18-1947-2025, https://doi.org/10.5194/gmd-18-1947-2025, 2025
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Direct assimilation of observations from ground-based microwave radiometers (GMRs) holds significant potential for improving forecast accuracy. Radiative transfer models (RTMs) play a crucial role in direct data assimilation. In this study, we introduce a new RTM, the Advanced Radiative Transfer Modeling System – Ground-Based (ARMS-gb), designed to simulate brightness temperatures observed by GMRs along with their Jacobians. Several enhancements have been incorporated to achieve higher accuracy.
R. Phani Murali Krishna, Siddharth Kumar, A. Gopinathan Prajeesh, Peter Bechtold, Nils Wedi, Kumar Roy, Malay Ganai, B. Revanth Reddy, Snehlata Tirkey, Tanmoy Goswami, Radhika Kanase, Sahadat Sarkar, Medha Deshpande, and Parthasarathi Mukhopadhyay
Geosci. Model Dev., 18, 1879–1894, https://doi.org/10.5194/gmd-18-1879-2025, https://doi.org/10.5194/gmd-18-1879-2025, 2025
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The High-Resolution Global Forecast Model (HGFM) is an advanced iteration of the operational Global Forecast System (GFS) model. HGFM can produce forecasts at a spatial scale of ~6 km in tropics. It demonstrates improved accuracy in short- to medium-range weather prediction over the Indian region, with notable success in predicting extreme events. Further, the model will be entrusted to operational forecasting agencies after validation and testing.
Jenna Ritvanen, Seppo Pulkkinen, Dmitri Moisseev, and Daniele Nerini
Geosci. Model Dev., 18, 1851–1878, https://doi.org/10.5194/gmd-18-1851-2025, https://doi.org/10.5194/gmd-18-1851-2025, 2025
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Nowcasting models struggle with the rapid evolution of heavy rain, and common verification methods are unable to describe how accurately the models predict the growth and decay of heavy rain. We propose a framework to assess model performance. In the framework, convective cells are identified and tracked in the forecasts and observations, and the model skill is then evaluated by comparing differences between forecast and observed cells. We demonstrate the framework with four open-source models.
Andrew Geiss and Po-Lun Ma
Geosci. Model Dev., 18, 1809–1827, https://doi.org/10.5194/gmd-18-1809-2025, https://doi.org/10.5194/gmd-18-1809-2025, 2025
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Particles in the Earth's atmosphere strongly impact the planet's energy budget, and atmosphere simulations require accurate representation of their interaction with light. This work introduces two approaches to represent light scattering by small particles. The first is a scattering simulator based on Mie theory implemented in Python. The second is a neural network emulator that is more accurate than existing methods and is fast enough to be used in climate and weather simulations.
Qin Wang, Bo Zeng, Gong Chen, and Yaoting Li
Geosci. Model Dev., 18, 1769–1784, https://doi.org/10.5194/gmd-18-1769-2025, https://doi.org/10.5194/gmd-18-1769-2025, 2025
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This study evaluates the performance of four planetary boundary layer (PBL) schemes in near-surface wind fields over the Sichuan Basin, China. Using 112 sensitivity experiments with the Weather Research and Forecasting (WRF) model and focusing on 28 wind events, it is found that wind direction was less sensitive to the PBL schemes. The quasi-normal scale elimination (QNSE) scheme captured temporal variations best, while the Mellor–Yamada–Janjić (MYJ) scheme had the least error in wind speed.
Tai-Long He, Nikhil Dadheech, Tammy M. Thompson, and Alexander J. Turner
Geosci. Model Dev., 18, 1661–1671, https://doi.org/10.5194/gmd-18-1661-2025, https://doi.org/10.5194/gmd-18-1661-2025, 2025
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It is computationally expensive to infer greenhouse gas (GHG) emissions using atmospheric observations. This is partly due to the detailed model used to represent atmospheric transport. We demonstrate how a machine learning (ML) model can be used to simulate high-resolution atmospheric transport. This type of ML model will help estimate GHG emissions using dense observations, which are becoming increasingly common with the proliferation of urban monitoring networks and geostationary satellites.
Wei Li, Beiming Tang, Patrick C. Campbell, Youhua Tang, Barry Baker, Zachary Moon, Daniel Tong, Jianping Huang, Kai Wang, Ivanka Stajner, and Raffaele Montuoro
Geosci. Model Dev., 18, 1635–1660, https://doi.org/10.5194/gmd-18-1635-2025, https://doi.org/10.5194/gmd-18-1635-2025, 2025
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The study describes the updates of NOAA's current UFS-AQMv7 air quality forecast model by incorporating the latest scientific and structural changes in CMAQv5.4. An evaluation during the summer of 2023 shows that the updated model overall improves the simulation of MDA8 O3 by reducing the bias by 8%–12% in the contiguous US. PM2.5 predictions have mixed results due to wildfire, highlighting the need for future refinements.
Yanwei Zhu, Aitor Atencia, Markus Dabernig, and Yong Wang
Geosci. Model Dev., 18, 1545–1559, https://doi.org/10.5194/gmd-18-1545-2025, https://doi.org/10.5194/gmd-18-1545-2025, 2025
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Most works have delved into convective weather nowcasting, and only a few works have discussed the nowcasting uncertainty for variables at the surface level. Hence, we proposed a method to estimate uncertainty. Generating appropriate noises associated with the characteristic of the error in analysis can simulate the uncertainty of nowcasting. This method can contribute to the estimation of near–surface analysis uncertainty in both nowcasting applications and ensemble nowcasting development.
Joël Thanwerdas, Antoine Berchet, Lionel Constantin, Aki Tsuruta, Michael Steiner, Friedemann Reum, Stephan Henne, and Dominik Brunner
Geosci. Model Dev., 18, 1505–1544, https://doi.org/10.5194/gmd-18-1505-2025, https://doi.org/10.5194/gmd-18-1505-2025, 2025
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The Community Inversion Framework (CIF) brings together methods for estimating greenhouse gas fluxes from atmospheric observations. The initial ensemble method implemented in CIF was found to be incomplete and could hardly be compared to other ensemble methods employed in the inversion community. In this paper, we present and evaluate a new implementation of the ensemble mode, building upon the initial developments.
Astrid Kerkweg, Timo Kirfel, Duong H. Do, Sabine Griessbach, Patrick Jöckel, and Domenico Taraborrelli
Geosci. Model Dev., 18, 1265–1286, https://doi.org/10.5194/gmd-18-1265-2025, https://doi.org/10.5194/gmd-18-1265-2025, 2025
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Normally, the Modular Earth Submodel System (MESSy) is linked to complete dynamic models to create chemical climate models. However, the modular concept of MESSy and the newly developed DWARF component presented here make it possible to create simplified models that contain only one or a few process descriptions. This is very useful for technical optimisation, such as porting to GPUs, and can be used to create less complex models, such as a chemical box model.
Edward C. Chan, Ilona J. Jäkel, Basit Khan, Martijn Schaap, Timothy M. Butler, Renate Forkel, and Sabine Banzhaf
Geosci. Model Dev., 18, 1119–1139, https://doi.org/10.5194/gmd-18-1119-2025, https://doi.org/10.5194/gmd-18-1119-2025, 2025
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An enhanced emission module has been developed for the PALM model system, improving flexibility and scalability of emission source representation across different sectors. A model for parametrized domestic emissions has also been included, for which an idealized model run is conducted for particulate matter (PM10). The results show that, in addition to individual sources and diurnal variations in energy consumption, vertical transport and urban topology play a role in concentration distribution.
Gregor Ehrensperger, Thorsten Simon, Georg J. Mayr, and Tobias Hell
Geosci. Model Dev., 18, 1141–1153, https://doi.org/10.5194/gmd-18-1141-2025, https://doi.org/10.5194/gmd-18-1141-2025, 2025
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As lightning is a brief and localized event, it is not explicitly resolved in atmospheric models. Instead, expert-based auxiliary descriptions are used to assess it. This study explores how AI can improve our understanding of lightning without relying on traditional expert knowledge. We reveal that AI independently identified the key factors known to experts as essential for lightning in the Alps region. This shows how knowledge discovery could be sped up in areas with limited expert knowledge.
David Patoulias, Kalliopi Florou, and Spyros N. Pandis
Geosci. Model Dev., 18, 1103–1118, https://doi.org/10.5194/gmd-18-1103-2025, https://doi.org/10.5194/gmd-18-1103-2025, 2025
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The effect of the assumed atmospheric nucleation mechanism on particle number concentrations and size distribution was investigated. Two quite different mechanisms involving sulfuric acid and ammonia or a biogenic organic vapor gave quite similar results which were consistent with measurements at 26 measurement stations across Europe. The number of larger particles that serve as cloud condensation nuclei showed little sensitivity to the assumed nucleation mechanism.
Tim Radke, Susanne Fuchs, Christian Wilms, Iuliia Polkova, and Marc Rautenhaus
Geosci. Model Dev., 18, 1017–1039, https://doi.org/10.5194/gmd-18-1017-2025, https://doi.org/10.5194/gmd-18-1017-2025, 2025
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In our study, we built upon previous work to investigate the patterns artificial intelligence (AI) learns to detect atmospheric features like tropical cyclones (TCs) and atmospheric rivers (ARs). As primary objective, we adopt a method to explain the AI used and investigate the plausibility of learned patterns. We find that plausible patterns are learned for both TCs and ARs. Hence, the chosen method is very useful for gaining confidence in the AI-based detection of atmospheric features.
Stefan Noll, Carsten Schmidt, Patrick Hannawald, Wolfgang Kausch, and Stefan Kimeswenger
EGUsphere, https://doi.org/10.5194/egusphere-2024-3512, https://doi.org/10.5194/egusphere-2024-3512, 2025
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Non-thermal emission from chemical reactions in the Earth's middle und upper atmosphere strongly contributes to the brightness of the night sky below about 2.3 µm. The new Paranal Airglow Line and Continuum Emission model calculates the emission spectrum and its variability with an unprecedented accuracy. Relying on a large spectroscopic data set from astronomical spectrographs and theoretical molecular/atomic data, it is valuable for airglow research and astronomical observatories.
Felipe Cifuentes, Henk Eskes, Enrico Dammers, Charlotte Bryan, and Folkert Boersma
Geosci. Model Dev., 18, 621–649, https://doi.org/10.5194/gmd-18-621-2025, https://doi.org/10.5194/gmd-18-621-2025, 2025
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We tested the capability of the flux divergence approach (FDA) to reproduce known NOx emissions using synthetic NO2 satellite column retrievals from high-resolution model simulations. The FDA accurately reproduced NOx emissions when column observations were limited to the boundary layer and when the variability of the NO2 lifetime, the NOx : NO2 ratio, and NO2 profile shapes were correctly modeled. This introduces strong model dependency, reducing the simplicity of the original FDA formulation.
Stefano Ubbiali, Christian Kühnlein, Christoph Schär, Linda Schlemmer, Thomas C. Schulthess, Michael Staneker, and Heini Wernli
Geosci. Model Dev., 18, 529–546, https://doi.org/10.5194/gmd-18-529-2025, https://doi.org/10.5194/gmd-18-529-2025, 2025
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We explore a high-level programming model for porting numerical weather prediction (NWP) model codes to graphics processing units (GPUs). We present a Python rewrite with the domain-specific library GT4Py (GridTools for Python) of two renowned cloud microphysics schemes and the associated tangent-linear and adjoint algorithms. We find excellent portability, competitive GPU performance, robust execution on diverse computing architectures, and enhanced code maintainability and user productivity.
Pieter Rijsdijk, Henk Eskes, Arlene Dingemans, K. Folkert Boersma, Takashi Sekiya, Kazuyuki Miyazaki, and Sander Houweling
Geosci. Model Dev., 18, 483–509, https://doi.org/10.5194/gmd-18-483-2025, https://doi.org/10.5194/gmd-18-483-2025, 2025
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Clustering high-resolution satellite observations into superobservations improves model validation and data assimilation applications. In our paper, we derive quantitative uncertainties for satellite NO2 column observations based on knowledge of the retrievals, including a detailed analysis of spatial error correlations and representativity errors. The superobservations and uncertainty estimates are tested in a global chemical data assimilation system and are found to improve the forecasts.
Dario Di Santo, Cenlin He, Fei Chen, and Lorenzo Giovannini
Geosci. Model Dev., 18, 433–459, https://doi.org/10.5194/gmd-18-433-2025, https://doi.org/10.5194/gmd-18-433-2025, 2025
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This paper presents the Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool (ML-AMPSIT), a computationally efficient tool that uses machine learning algorithms for sensitivity analysis in atmospheric models. It is tested with the Weather Research and Forecasting (WRF) model coupled with the Noah-Multiparameterization (Noah-MP) land surface model to investigate sea breeze circulation sensitivity to vegetation-related parameters.
Robert Schoetter, Robin James Hogan, Cyril Caliot, and Valéry Masson
Geosci. Model Dev., 18, 405–431, https://doi.org/10.5194/gmd-18-405-2025, https://doi.org/10.5194/gmd-18-405-2025, 2025
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Radiation is relevant to the atmospheric impact on people and infrastructure in cities as it can influence the urban heat island, building energy consumption, and human thermal comfort. A new urban radiation model, assuming a more realistic form of urban morphology, is coupled to the urban climate model Town Energy Balance (TEB). The new TEB is evaluated with a reference radiation model for a variety of urban morphologies, and an improvement in the simulated radiative observables is found.
Zebediah Engberg, Roger Teoh, Tristan Abbott, Thomas Dean, Marc E. J. Stettler, and Marc L. Shapiro
Geosci. Model Dev., 18, 253–286, https://doi.org/10.5194/gmd-18-253-2025, https://doi.org/10.5194/gmd-18-253-2025, 2025
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Contrails forming in some atmospheric conditions may persist and become strongly warming cirrus, while in other conditions may be neutral or cooling. We develop a contrail forecast model to predict contrail climate forcing for any arbitrary point in space and time and explore integration into flight planning and air traffic management. This approach enables contrail interventions to target high-probability high-climate-impact regions and reduce unintended consequences of contrail management.
Nils Eingrüber, Alina Domm, Wolfgang Korres, and Karl Schneider
Geosci. Model Dev., 18, 141–160, https://doi.org/10.5194/gmd-18-141-2025, https://doi.org/10.5194/gmd-18-141-2025, 2025
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Climate change adaptation measures like unsealings can reduce urban heat stress. As grass grid pavers have never been parameterized for microclimate model simulations with ENVI-met, a new parameterization was developed based on field measurements. To analyse the cooling potential, scenario analyses were performed for a densely developed area in Cologne. Statistically significant average cooling effects of up to −11.1 K were found for surface temperature and up to −2.9 K for 1 m air temperature.
Xuan Wang, Lei Bi, Hong Wang, Yaqiang Wang, Wei Han, Xueshun Shen, and Xiaoye Zhang
Geosci. Model Dev., 18, 117–139, https://doi.org/10.5194/gmd-18-117-2025, https://doi.org/10.5194/gmd-18-117-2025, 2025
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The Artificial-Intelligence-based Nonspherical Aerosol Optical Scheme (AI-NAOS) was developed to improve the estimation of the aerosol direct radiation effect and was coupled online with a chemical weather model. The AI-NAOS scheme considers black carbon as fractal aggregates and soil dust as super-spheroids, encapsulated with hygroscopic aerosols. Real-case simulations emphasize the necessity of accurately representing nonspherical and inhomogeneous aerosols in chemical weather models.
Lukas Pfitzenmaier, Pavlos Kollias, Nils Risse, Imke Schirmacher, Bernat Puigdomenech Treserras, and Katia Lamer
Geosci. Model Dev., 18, 101–115, https://doi.org/10.5194/gmd-18-101-2025, https://doi.org/10.5194/gmd-18-101-2025, 2025
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The Python tool Orbital-Radar transfers suborbital radar data (ground-based, airborne, and forward-simulated numerical weather prediction model) into synthetic spaceborne cloud profiling radar data, mimicking platform-specific instrument characteristics, e.g. EarthCARE or CloudSat. The tool's novelty lies in simulating characteristic errors and instrument noise. Thus, existing data sets are transferred into synthetic observations and can be used for satellite calibration–validation studies.
Mark Buehner, Jean-Francois Caron, Ervig Lapalme, Alain Caya, Ping Du, Yves Rochon, Sergey Skachko, Maziar Bani Shahabadi, Sylvain Heilliette, Martin Deshaies-Jacques, Weiguang Chang, and Michael Sitwell
Geosci. Model Dev., 18, 1–18, https://doi.org/10.5194/gmd-18-1-2025, https://doi.org/10.5194/gmd-18-1-2025, 2025
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The Modular and Integrated Data Assimilation System (MIDAS) software is described. The flexible design of MIDAS enables both deterministic and ensemble prediction applications for the atmosphere and several other Earth system components. It is currently used for all main operational weather prediction systems in Canada and also for sea ice and sea surface temperature analysis. The use of MIDAS for multiple Earth system components will facilitate future research on coupled data assimilation.
Alexander de Meij, Cornelis Cuvelier, Philippe Thunis, and Enrico Pisoni
EGUsphere, https://doi.org/10.5194/egusphere-2024-3690, https://doi.org/10.5194/egusphere-2024-3690, 2025
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We assess the relevance and utility indicators developed within FAIRMODE by evaluating 9 CAMS models in calculated air pollutant values. For NO2, the results highlight difficulties at traffic stations. For PM2.5 and PM10 the bias and Winter-Summer gradients reveal issues. O3 evaluation shows that e.g. seasonal gradients are useful. Overall, the indicators provide valuable insights into model limitations, yet there is a need to reconsider the strictness of some indicators for certain pollutants.
Zichen Wu, Xueshun Chen, Zifa Wang, Huansheng Chen, Zhe Wang, Qing Mu, Lin Wu, Wending Wang, Xiao Tang, Jie Li, Ying Li, Qizhong Wu, Yang Wang, Zhiyin Zou, and Zijian Jiang
Geosci. Model Dev., 17, 8885–8907, https://doi.org/10.5194/gmd-17-8885-2024, https://doi.org/10.5194/gmd-17-8885-2024, 2024
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We developed a model to simulate polycyclic aromatic hydrocarbons (PAHs) from global to regional scales. The model can reproduce PAH distribution well. The concentration of BaP (indicator species for PAHs) could exceed the target values of 1 ng m-3 over some areas (e.g., in central Europe, India, and eastern China). The change in BaP is lower than that in PM2.5 from 2013 to 2018. China still faces significant potential health risks posed by BaP although the Action Plan has been implemented.
Marie Taufour, Jean-Pierre Pinty, Christelle Barthe, Benoît Vié, and Chien Wang
Geosci. Model Dev., 17, 8773–8798, https://doi.org/10.5194/gmd-17-8773-2024, https://doi.org/10.5194/gmd-17-8773-2024, 2024
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We have developed a complete two-moment version of the LIMA (Liquid Ice Multiple Aerosols) microphysics scheme. We have focused on collection processes, where the hydrometeor number transfer is often estimated in proportion to the mass transfer. The impact of these parameterizations on a convective system and the prospects for more realistic estimates of secondary parameters (reflectivity, hydrometeor size) are shown in a first test on an idealized case.
Yuya Takane, Yukihiro Kikegawa, Ko Nakajima, and Hiroyuki Kusaka
Geosci. Model Dev., 17, 8639–8664, https://doi.org/10.5194/gmd-17-8639-2024, https://doi.org/10.5194/gmd-17-8639-2024, 2024
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A new parameterisation for dynamic anthropogenic heat and electricity consumption is described. The model reproduced the temporal variation in and spatial distributions of electricity consumption and temperature well in summer and winter. The partial air conditioning was the most critical factor, significantly affecting the value of anthropogenic heat emission.
Arseniy Karagodin-Doyennel, Fredrik Jansson, Bart van Stratum, Hugo Denier van der Gon, Jordi Vilà-Guerau de Arellano, and Sander Houweling
EGUsphere, https://doi.org/10.5194/egusphere-2024-3721, https://doi.org/10.5194/egusphere-2024-3721, 2024
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We introduce a new simulation platform based on the Dutch Large-Eddy Simulation (DALES) to simulate carbon dioxide (CO2) emissions and their dispersion in the turbulent environments with hectometer resolution. This model incorporates both anthropogenic emission inventory and ecosystem exchanges. Simulation results for the main urban area in the Netherlands demonstrate a strong potential of DALES to enhance CO2 emission modeling, which is important for refining their reduction strategies.
Hongyi Li, Ting Yang, Lars Nerger, Dawei Zhang, Di Zhang, Guigang Tang, Haibo Wang, Yele Sun, Pingqing Fu, Hang Su, and Zifa Wang
Geosci. Model Dev., 17, 8495–8519, https://doi.org/10.5194/gmd-17-8495-2024, https://doi.org/10.5194/gmd-17-8495-2024, 2024
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To accurately characterize the spatiotemporal distribution of particulate matter <2.5 µm chemical components, we developed the Nested Air Quality Prediction Model System with the Parallel Data Assimilation Framework (NAQPMS-PDAF) v2.0 for chemical components with non-Gaussian and nonlinear properties. NAQPMS-PDAF v2.0 has better computing efficiency, excels when used with a small ensemble size, and can significantly improve the simulation performance of chemical components.
T. Nash Skipper, Christian Hogrefe, Barron H. Henderson, Rohit Mathur, Kristen M. Foley, and Armistead G. Russell
Geosci. Model Dev., 17, 8373–8397, https://doi.org/10.5194/gmd-17-8373-2024, https://doi.org/10.5194/gmd-17-8373-2024, 2024
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Chemical transport model simulations are combined with ozone observations to estimate the bias in ozone attributable to US anthropogenic sources and individual sources of US background ozone: natural sources, non-US anthropogenic sources, and stratospheric ozone. Results indicate a positive bias correlated with US anthropogenic emissions during summer in the eastern US and a negative bias correlated with stratospheric ozone during spring.
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024, https://doi.org/10.5194/gmd-17-8267-2024, 2024
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Model evaluations against ground observations are usually unfair. The former simulates mean status over coarse grids and the latter the surrounding atmosphere. To solve this, we proposed the new land-use-based representative (LUBR) operator that considers intra-grid variance. The LUBR operator is validated to provide insights that align with satellite measurements. The results highlight the importance of considering fine-scale urban–rural differences when comparing models and observation.
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024, https://doi.org/10.5194/gmd-17-8223-2024, 2024
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The ensemble Kalman filter (EnKF) improves dust storm forecasts but faces challenges with position errors. The valid time shifting EnKF (VTS-EnKF) addresses this by adjusting for position errors, enhancing accuracy in forecasting dust storms, as proven in tests on 2021 events, even with smaller ensembles and time intervals.
Mike Bush, David L. A. Flack, Huw W. Lewis, Sylvia I. Bohnenstengel, Chris J. Short, Charmaine Franklin, Adrian P. Lock, Martin Best, Paul Field, Anne McCabe, Kwinten Van Weverberg, Segolene Berthou, Ian Boutle, Jennifer K. Brooke, Seb Cole, Shaun Cooper, Gareth Dow, John Edwards, Anke Finnenkoetter, Kalli Furtado, Kate Halladay, Kirsty Hanley, Margaret A. Hendry, Adrian Hill, Aravindakshan Jayakumar, Richard W. Jones, Humphrey Lean, Joshua C. K. Lee, Andy Malcolm, Marion Mittermaier, Saji Mohandas, Stuart Moore, Cyril Morcrette, Rachel North, Aurore Porson, Susan Rennie, Nigel Roberts, Belinda Roux, Claudio Sanchez, Chun-Hsu Su, Simon Tucker, Simon Vosper, David Walters, James Warner, Stuart Webster, Mark Weeks, Jonathan Wilkinson, Michael Whitall, Keith D. Williams, and Hugh Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-201, https://doi.org/10.5194/gmd-2024-201, 2024
Revised manuscript accepted for GMD
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RAL configurations define settings for the Unified Model atmosphere and Joint UK Land Environment Simulator. The third version of the Regional Atmosphere and Land (RAL3) science configuration for kilometre and sub-km scale modelling represents a major advance compared to previous versions (RAL2) by delivering a common science definition for applications in tropical and mid-latitude regions. RAL3 has more realistic precipitation distributions and improved representation of clouds and visibility.
Peter Kalverla, Imme Benedict, Chris Weijenborg, and Ruud J. van der Ent
EGUsphere, https://doi.org/10.5194/egusphere-2024-3401, https://doi.org/10.5194/egusphere-2024-3401, 2024
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We introduce a new version of WAM2layers, a computer program that tracks how the weather brings water from one place to another. It uses data from weather and climate models, whose resolution is steadily increasing. Processing the latest data became a challenge, and the updates presented here ensure that WAM2layers runs smoothly again. We also made it easier to use the program and to understand its source code. This makes it more transparent and reliable, and easier to maintain.
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024, https://doi.org/10.5194/gmd-17-8093-2024, 2024
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Inadequate representation of surface–atmosphere interaction processes is a major source of uncertainty in numerical weather prediction models. Here, an effort has been made to improve the Weather Research and Forecasting (WRF) model version 4.2.2 by introducing a unique theoretical framework under convective conditions. In addition, to enhance the potential applicability of the WRF modeling system, various commonly used similarity functions under convective conditions have also been installed.
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024, https://doi.org/10.5194/gmd-17-8069-2024, 2024
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Supercooled liquid clouds (liquid clouds colder than 0°C) are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We compare a single-column version of a weather model to observations with two different cloud schemes and find that both the dynamical environment and atmospheric aerosols are important for reproducing observations.
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024, https://doi.org/10.5194/gmd-17-7995-2024, 2024
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This study updates the CESM's aerosol schemes, focusing on dust, marine aerosol emissions, and secondary organic aerosol (SOA) . Dust emission modifications make deflation areas more continuous, improving results in North America and the sub-Arctic. Humidity correction to sea-salt emissions has a minor effect. Introducing marine organic aerosol emissions, coupled with ocean biogeochemical processes, and adding aqueous reactions for SOA formation advance the CESM's aerosol modelling results.
Lucas A. McMichael, Michael J. Schmidt, Robert Wood, Peter N. Blossey, and Lekha Patel
Geosci. Model Dev., 17, 7867–7888, https://doi.org/10.5194/gmd-17-7867-2024, https://doi.org/10.5194/gmd-17-7867-2024, 2024
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Marine cloud brightening (MCB) is a climate intervention technique to potentially cool the climate. Climate models used to gauge regional climate impacts associated with MCB often assume large areas of the ocean are uniformly perturbed. However, a more realistic representation of MCB application would require information about how an injected particle plume spreads. This work aims to develop such a plume-spreading model.
Leonardo Olivetti and Gabriele Messori
Geosci. Model Dev., 17, 7915–7962, https://doi.org/10.5194/gmd-17-7915-2024, https://doi.org/10.5194/gmd-17-7915-2024, 2024
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Data-driven models are becoming a viable alternative to physics-based models for weather forecasting up to 15 d into the future. However, it is unclear whether they are as reliable as physics-based models when forecasting weather extremes. We evaluate their performance in forecasting near-surface cold, hot, and windy extremes globally. We find that data-driven models can compete with physics-based models and that the choice of the best model mainly depends on the region and type of extreme.
David C. Wong, Jeff Willison, Jonathan E. Pleim, Golam Sarwar, James Beidler, Russ Bullock, Jerold A. Herwehe, Rob Gilliam, Daiwen Kang, Christian Hogrefe, George Pouliot, and Hosein Foroutan
Geosci. Model Dev., 17, 7855–7866, https://doi.org/10.5194/gmd-17-7855-2024, https://doi.org/10.5194/gmd-17-7855-2024, 2024
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This work describe how we linked the meteorological Model for Prediction Across Scales – Atmosphere (MPAS-A) with the Community Multiscale Air Quality (CMAQ) air quality model to form a coupled modelling system. This could be used to study air quality or climate and air quality interaction at a global scale. This new model scales well in high-performance computing environments and performs well with respect to ground surface networks in terms of ozone and PM2.5.
Markus Kunze, Christoph Zülicke, Tarique Adnan Siddiqui, Claudia Christine Stephan, Yosuke Yamazaki, Claudia Stolle, Sebastian Borchert, and Hauke Schmidt
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-191, https://doi.org/10.5194/gmd-2024-191, 2024
Revised manuscript accepted for GMD
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We present the Icosahedral Nonhydrostatic (ICON) general circulation model with upper atmosphere extension with the physics package for numerical weather prediction (UA-ICON(NWP)). The parameters for the gravity wave parameterizations were optimized, and realistic modelling of the thermal and dynamic state of the mesopause regions was achieved. UA-ICON(NWP) now shows a realistic frequency of major sudden stratospheric warmings and well-represented solar tides in temperature.
Giulio Mandorli and Claudia J. Stubenrauch
Geosci. Model Dev., 17, 7795–7813, https://doi.org/10.5194/gmd-17-7795-2024, https://doi.org/10.5194/gmd-17-7795-2024, 2024
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In recent years, several studies focused their attention on the disposition of convection. Lots of methods, called indices, have been developed to quantify the amount of convection clustering. These indices are evaluated in this study by defining criteria that must be satisfied and then evaluating the indices against these standards. None of the indices meet all criteria, with some only partially meeting them.
Wonbae Bang, Jacob Carlin, Kwonil Kim, Alexander Ryzhkov, Guosheng Liu, and Gyuwon Lee
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-179, https://doi.org/10.5194/gmd-2024-179, 2024
Revised manuscript accepted for GMD
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Microphysics model-based diagnosis such as the spectral bin model (SBM) recently has been attempted to diagnose winter precipitation types. In this study, the accuracy of SBM-based precipitation type diagnosis is compared with other traditional methods. SBM have relatively higher accuracy about snow and wetsnow events whereas lower accuracy about rain event. When microphysics scheme in the SBM was optimized for the corresponding region, accuracy about rain events was improved.
Kerry Anderson, Jack Chen, Peter Englefield, Debora Griffin, Paul A. Makar, and Dan Thompson
Geosci. Model Dev., 17, 7713–7749, https://doi.org/10.5194/gmd-17-7713-2024, https://doi.org/10.5194/gmd-17-7713-2024, 2024
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The Global Forest Fire Emissions Prediction System (GFFEPS) is a model that predicts smoke and carbon emissions from wildland fires. The model calculates emissions from the ground up based on satellite-detected fires, modelled weather and fire characteristics. Unlike other global models, GFFEPS uses daily weather conditions to capture changing burning conditions on a day-to-day basis. GFFEPS produced lower carbon emissions due to the changing weather not captured by the other models.
Cited articles
Alexander, B., Savarino, J., Lee, C. C. W., Park, R. J., Jacob, D. J., Thiemens, M. H., Li, Q. B., and Yantosca, R. M.: Sulfate formation in seasalt aerosols: Constraints from oxygen isotopes, J. Geophys. Res., 110, D10307, https://doi.org/10.1029/2004JD005659, 2005.
Arimoto, R., Balssam, W., and Schloesslin, C.: Visible spectroscopy of aerosol particles collected on filters: Iron-oxide minerals, Atmos. Environ., 36, 89–96, 2002.
Aumont, O., Maier-Reimer, E., Blain, S., and Monfray, P.: An ecosystem model of the global ocean including Fe, Si, P colimitations, Global Biogeochem. Cy., 17, 1060, https://doi.org/10.1029/2001GB001745, 2003.
Balmer, M. E. and Sulzberger, B.: Atrazine degradation in irradiated iron/oxalate systems: Effects of pH and oxalate, Environ. Sci. Technol., 33, 2418–2424, 1999.
Barbeau, K.: Photochemistry of organic Fe(III) complexing ligands in oceanic systems, Photochem. Photobiol., 82, 1505–1516, 2006.
Benkelberg, H. J. and Warneck, P.: Photodecomposition of iron(III) hydroxo and sulfato complexes in aqueous solutions: Wavelength dependence of pH and SO4- quantum yields, J. Phys. Chem., 99, 5214–5221, 1995.
Bey, I., Jacob, D. J., Yantosca, R. M., Logan, J. A., Field, B., Fiore, A. M., Li, Q., Liu, H., Mickley, L. J., and Schultz, M.: Global modeling of tropospheric chemistry with assimilated meteorology: Model description and evaluation, J. Geophys. Res., 106, 23073–23095, 2001.
Bielski, B. H. J., Cabelli, D. E., Arudi, R. L., and Ross, A. B.: Reactivity of HO2/O2 radicals in aqueous solution, J. Phys. Chem. Ref. Data, 14, 1041–1100, 1985.
Boyd, P. W., Watson, A. J., Law, C. S., Abraham, E. R., Trull, T., Murdoch, R., Bakker, D. C. E., Bowie, A. R., Buesseler, K. O., Chang, H., Charette, M., Croot, P., Downing, K., Frew, R., Gall, M., Hadfield, M., Hall, J., Harvey, M., Jameson, G., LaRoche, J., Liddicoat, M., Ling, R., Maldonado, M. T., McKay, R. M., Nodder, S., Pickmere, S., Pridmore, R., Rintoul, S., Safi, K., Sutton, P., Strzepek, R., Tanneberger, K., Turner, S., Waite, A., and Zeldis, J.: A mesoscale phytoplankton bloom in the polar Southern Ocean stimulated by iron fertilization, Nature, 407, 695–702, 2000.
Boyd, P. W., Jickells, T., Law, C. S., Blain, S., Boyle, E. A., Buesseler, K. O., Coale, K. H., Cullen, J. J., de Baar, H. J. W., Follows, M., Harvey, M., Lancelot, C., Levasseur, M., Owens, N. P. J., Pollard, R., Rivkin, R. B., Sarmiento, J., Schoemann, V., Smetacek, V., Takeda, S., Tsuda, A., Turner, S., and Watson, A. J.: Mesoscale iron enrichment experiments 1993–2005: Synthesis and future directions, Science, 315, 612–617, 2007.
Brandt, C. and van Eldik, R.: Transition metal-catalyzed oxidation of sulfur(IV) oxides, Atmospheric-relevant processes and mechanisms, Chem. Rev., 95, 119–190, 1995.
Bromley, L. A.: Thermodynamic properties of strong electrolytes in aqueous solution, AIChE J., 19, 313–320, 1973.
Cheah, S.-F., Kraemer, S. M., Cervini-Silva, J., and Sposito, G.: Steady-state dissolution kinetics of goethite in the presence of desferrioxamine B and oxalate ligands: implications for the microbial acquisition of iron, Chemical Geology, 198, 63–75, 2003.
Chen, Y.: Sources and fate of atmospheric nutrients over the remote oceans and their role on controlling marine diazotrophic microorganisms, 1-224, University of Maryland Center for Environmental Science, 2004.
Chen, Y. and Siefert, R. L.: Determination of various types of labile atmospheric iron over remote oceans, J. Geophys. Res., 108, 4774, https://doi.org/10.1029/2003JD003515, 2003.
Chen, Y. and Siefert, R. L.: Seasonal and spatial distributions and dry deposition fluxes of atmospheric total and labile iron over the tropical and subtropical North Atlantic Ocean, J. Geophys. Res., 109, D09305, https://doi.org/10.1029/2003JD003958, 2004.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B., Duncan, B., Martin, R., Logan, J., Higurashi, A., and Nakajima, T.: Tropospheric aerosol optical thickness from the GOCART model and comparisons with satellite and sunphotometer measurements, J. Atmos. Sci., 59, 461–483, 2002.
Coale, K. H., Johnson, K. S., Fitzwater, S. E., Gordon, R. M., Tanner, S., Chavez, F. P., Ferioli, L., Sakamoto, C., Rogers, P., Millero, F., Steinberg, P., Nightingale, P., Cooper, D., Cochlan, W. P., Landry, M. R., Constantinou, J., Rollwagen, G., Trasvina, A., and Kudela, R.: A massive phytoplankton bloom induced by an ecosystem-scale iron fertilization experiment in the equatorial Pacific Ocean, Nature, 383, 495–501, https://doi.org/10.1038/383495a0, 1996.
Cornell R. M. and Schindler, P. W.: Photochemical dissolution of goethite in acid/oxalate solution, Clays Clay Miner., 35, 347–352, 1987.
Cornell, R. M. and Schwertmann, U.: The iron oxides, structure, properties, reactions, occurrence and uses, John Wiley, Hoboken, NJ, 573 pp., 1996.
Cornell, R. M., Posner, A. M., and Quirk, J. P.: Kinetics and mechanisms of the acid dissolution of Goethite (α-FeOOH), J. Inorg. Nucl. Chem., 38, 563–567, 1976.
Cwiertny, D. M., Hunter, G. J., Pettibone, J. M., Scherer, M. M., and Grassian, V. H.: Surface chemistry and dissolution of α-FeOOH nanorods and microrods: Environmental implications of size-dependent interactions with oxalate, J. Phys. Chem., 113, 2175–2186, 2009.
Dedik, A. N. and Hoffmann P.: Chemical characterization of iron in atmospheric aerosols, Atmos. Environ., 26, 2545–2548, 1992.
Deguillaume, L., Leriche, M., Desboeufs, K., Mailhot, G., George, C., and Chaumerliac, N.: Transition metals in atmospheric liquid phases: Sources, reactivity, and sensitivity parameters, Chem. Rev., 105, 3388–3431, 2005.
Dos Santos Afonso, M., Morando, P. J., Blesa, M. A., Banwart, S., and Stumm, W.: The reductive dissolution of iron oxides by ascorbate, J. Colloid Interface Sci., 138, 74–82, 1990.
Duce, R. A. and Tindale, N. W.: Atmospheric transport of iron and its deposition in the ocean, Limnol. Oceanogr., 36, 1715–1726, 1991.
Duckworth, O. W. and Martin, S. T.: Surface complexation and dissolution of hematite by C1-C6 dicarboxylic acids at pH = 5, Geochim. Cosmochim. Acta, 65, 4289–4301, 2001.
Epstein, I. R., Kustin, K., and Simoyi, R. H.: Nitrous acid decomposition catalyzed by an iron(II) complex: Tris(3,4,7,8-tetramethyl-1,10-phenanthroline)iron(II)1, J. Am. Chem. Soc., 104, 712–717, 1982.
Fairlie, T. D., Jacobs, D. J., and Rokjin, R. J.: The impact of transpacific transport of mineral dust in the United States, Atmos. Environ., 41, 1251–1266, 2007.
Falkowski, P. G.: Evolution of the nitrogen cycle and its influence on the biological sequestration of CO2 in the ocean, Nature, 387, 272–275, 1997.
Faust, B. C. and Zepp, R. G.: Photochemistry of aqueous iron(III)-polycarboxylate complexes: Roles in the chemistry of atmospheric and surface waters, Environ. Sci. Technol., 27, 2517–2522, 1993.
Fischer, R. B. and Peters, D. G.: Chemical equilibrium, Saunders Limited, 1970.
Fu, H., Cwiertny, D. M., Carmichael, G. R., Scherer, M. M., and Grassian, V. H.: Photoreductive dissolution of Fe-containing mineral dust particles in acidic media, J. Geophys. Res., 115, D11304, https://doi.org/10.1029/2009JD012702, 2010.
Fu, T.-M., Jacob, D. J., Wittrock, F., Burrows, J. P., Vrekoussis, M., and Henze, D. K.: Global budgets of atmospheric glyoxal and methylglyoxal, and implications for formation of secondary organic aerosols, J. Geophys. Res., 113, D15303, https://doi.org/10.1029/2007JD009505, 2008.
Fung, I. Y., Meyn, S. K., Tegen, I., Doney, S. C., John, J. G., and Bishop, J. K. B.: Iron supply and demand in the upper ocean, Global Biogeochem. Cy., 14, 281–291, 2000.
Furukawa, T. and Takahashi, Y.: Oxalate metal complexes in aerosol particles: implications for the hygroscopicity of oxalate-containing particles, Atmos. Chem. Phys., 11, 4289–4301, https://doi.org/10.5194/acp-11-4289-2011, 2011.
Getoff, N., Schwoerer, F., Markovic, V. M., and Sehested, K.: Pulse radiolysis of oxalic acid and oxalates, J. Phys. Chem., 75, 749–755, 1971.
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O., and Lin, S.-J.: Sources and distributions of dust aerosols simulated with the GOCART model, J. Geophys. Res., 106, 20255–20273, 2001.
Gregg, W., Ginoux, P., Schopf, P. S., and Casey, N. W.: Phytoplankton and iron: Validation of a global three-dimensional ocean biogeochemical model, Deep Sea Res. Part II, 50, 3143–3169, 2003.
Heald, C. L., Jacob, D. J., Park, R. J., Alexander, B., Fairlie, T. D., Yantosca, R. M., and Chu, D. A.: Transpacific transport of Asian anthropogenic aerosols and its impact on surface air quality in the United States, J. Geophys. Res., 111, D14310, https://doi.org/10.1029/2005JD006847, 2006.
Hoffmann, P., Dedik, A. N., Ensling, J., Weinbruch, S., Weber, S., Sinner, T., Gutlich, P., and Ornter, H. M.: Speciation of iron in atmospheric aerosol samples, J. Aerosol Sci., 27, 325–337, 1996.
Huneeus, N., Schulz, M., Balkanski, Y., Griesfeller, J., Prospero, J., Kinne, S., Bauer, S., Boucher, O., Chin, M., Dentener, F., Diehl, T., Easter, R., Fillmore, D., Ghan, S., Ginoux, P., Grini, A., Horowitz, L., Koch, D., Krol, M. C., Landing, W., Liu, X., Mahowald, N., Miller, R., Morcrette, J.-J., Myhre, G., Penner, J., Perlwitz, J., Stier, P., Takemura, T., and Zender, C. S.: Global dust model intercomparison in AeroCom phase I, Atmos. Chem. Phys., 11, 7781–7816, https://doi.org/10.5194/acp-11-7781-2011, 2011.
Ito, A.: Contrasting the effect of iron mobilization on soluble iron deposition to the ocean in the Northern and Southern Hemispheres, J. Meteorol. Soc. Jpn., 90A, 167–188, 2012.
Ito, A. and Feng, Y.: Role of dust alkalinity in acid mobilization of iron, Atmos. Chem. Phys., 10, 9237–9250, https://doi.org/10.5194/acp-10-9237-2010, 2010.
Jacobsen, F., Holcman, J., and Sehested, K.: Reactions of the ferryl ion with some compounds found in cloud water, Int. J. Chem. Kinet., 30, 215–224, 1998.
Jacobson, M. Z.: Computation of global photochemistry with SMVGEARII, Atmos. Environ., 29, 2541–2546, 1995.
Jacobson, M. Z.: Improvement of SMVGEARII on vector and scalar machines through absolute error tolerance control, Atmos. Environ., 32, 791–796, 1998.
Jacobson, M. Z. and Turco, R. P.: SMVGEAR: A sparse-matrix, vectorized gear code for atmospheric models, Atmos. Environ., 2, 273–284, 1994.
Jayson, G. G., Parson, B. J., and Swallow, A. J.: Oxidation of ferrous ions by perhydroxyl radicals, J. Chem. Soc. Faraday Trans., 69, 236–242, 1973.
Jickells, T. D., An, Z. S., Andersen, K. K., Baker, A. R., Bergametti, G., Brooks, N., Cao, J. J., Boyd, P. W., Duce, R. A., Hunter, K. A., Kawahata, H., Kubilay, N., LaRoche, J., Liss, P. S., Mahowald, N., Prospero, J. M., Ridgwell, A. J., Tegen, I., and Torres, R.: Global iron connections between desert dust, ocean biogeochemistry, and climate, Science, 308, 67–71, 2005.
Johansen, A. M., Siefert, R. L., and Hoffmann, M. R.: Chemical composition of aerosols collected over the tropical North Atlantic Ocean, J. Geophys. Res., 105, 15277–15312, 2000.
Johnson, M. S., Meskhidze, N., Solmon, F., Gassó, S., Chuang, P. Y., Gaiero, D. M., Yantosca, R. M., Wu, S., Wang, Y., and Carouge, C.: Modeling dust and soluble iron deposition to the South Atlantic Ocean, J. Geophys. Res., 115, D15202, https://doi.org/10.1029/2009JD013311, 2010.
Johnson, M. S., Meskhidze, N., Kiliyanpilakkil, V. P., and Gassó, S.: Understanding the transport of Patagonian dust and its influence on marine biological activity in the South Atlantic Ocean, Atmos. Chem. Phys., 11, 2487–2502, https://doi.org/10.5194/acp-11-2487-2011, 2011.
Johnson, M. S., Meskhidze, N., and Kiliyanpilakkil, V. P.: A global comparison of GEOS-Chem-predicted and remotely-sensed mineral dust aerosol optical depth and extinction profiles, J. Adv. Model. Earth Syst., 4, M07001, https://doi.org/10.1029/2011MS000109, 2012.
Journet, E., Desboeufs, K. V., Caquineau, S., and Colin, J.-L.: Mineralogy as a critical factor of dust iron solubility, Geophys. Res. Lett., 35, L07805, https://doi.org/10.1029/2007GL031589, 2008.
Kawamura, K. and Ikushima, K.: Seasonal changes in the distribution of dicarboxylic acids in the urban atmosphere, Environ. Sci. Technol., 27, 2227–2235, 1993.
Kawamura, K., Kasukabe, H., and Barrie, L. A.: Source and reaction pathways of dicarboxylic acids, ketoacids and dicarbonyls in arctic aerosols at polar sunrise, Atmos. Environ., 30, 1709–1722, https://doi.org/10.1016/1352-2310(95)00395-9, 1996.
Kawamura, K., Imai, Y., and Barrie, L. A.: Photochemical production and loss of organic acids in high Arctic aerosols during long range transport and polar sunrise ozone depletion events, Atmos. Environ., 39, 599–614, https://doi.org/10.1016/j.atmosenv.2004.10.020, 2005.
Kieber, R. J., Skrabal, S. A., Smith, B. J., and Willey, J. D.: Organic complexation of Fe(II) and its impact on the redox cycling of iron in rain, Environ. Sci. Technol., 39, 1576–1583, 2005.
Kleindienst, T. E., Smith, D. F., Li, W., Edney, E. O., Driscoll, D. J., Speer, R. E., and Weathers, W. S.: Secondary organic aerosol formation from the oxidation of aromatic hydrocarbons in the presence of dry submicron ammonium sulfate aerosol, Atmos. Environ., 33, 3669–3681, 1999.
Kraemer, S. M., Butler, A., Borer, P. M., and Cervini-Silva, J.: Siderophores and the dissolution of iron-bearing minerals in marine systems, in: Reviews in Mineralogy and Geochemistry, edited by: Banfield, J. F., Cervini-Silva, J., and Nealson, K. M., Mineralogical Society of America, Washington, DC, 53–84, 2005.
Kremer, M. L.: The Fenton reaction, Dependence of the rate on pH, J. Phys. Chem. A, 107, 1734–1741, 2003.
Kusik, C. L. and Meissner, H. P.: Electrolyte activity coefficients in inorganic processing, AIChE Symp. Ser., 173, 14–20, 1978.
Legrand, M., Preunkert, S., Oliveira, T., Pio, C., Hammer, S., Gelencser, A., Kasper-Giebl, A., and Laj, P.: Origin of C2-C5 dicarboxylic acids in the European atmosphere inferred from year round aerosol study conducted at a west-east transect, J. Geophys. Res., 112, D23S07, https://doi.org/10.1029/2006JD008019, 2007.
Liu, H., Jacob, D. J., Bey, I., and Yantosca, R. M.: Constraints from 210Pb and 7Be on wet deposition and transport in a global three-dimensional chemical tracer model driven by assimilated meteorological fields, J. Geophys. Res., 106, 12109–12128, 2001.
Logager, T., Holcman, J., Sehested, K., and Pedersen, T.: Oxidation of ferrous ions by ozone in acidic solution, Inorg. Chem., 31, 3523–3529, 1992.
Luo, C. and Gao, Y.: Aeolian iron mobilisation by dust-acid interactions and their implications for soluble iron deposition to the ocean: a test involving potential anthropogenic organic acidic species, Environ. Chem., 7, 153–161, https://doi.org/10.1071/EN09116, 2010.
Luo, C., Mahowald, N. M., Meskhidze, N., Chen, Y., Siefert, R. L., Baker, A. R., and Johansen, A. M.: Estimation of iron solubility from observations and a global aerosol model, J. Geophys. Res., 110, D23307, https://doi.org/10.1029/2005JD006059, 2005.
Luo, C., Mahowald, N., Bond, T., Chuang, P. Y., Artaxo, P., Siefert, R., Chen, Y., and Schauer, J.: Combustion iron distribution and deposition, Global Biogeochem. Cy., 22, GB1012, https://doi.org/10.1029/2007GB002964, 2008.
Mahowald, N. M., Engelstaedter, S., Luo, C., Sealy, A., Artaxo, P., Benitez-Nelson, C., Bonnet, S., Chen, Y., Chuang, P. Y., Cohen, D. D., Dulac, F., Herut, B., Johansen, A. M., Kubilay, N., Losno, R., Maenhaut, W., Paytan, A., Prospero, J. A., Shank, L. M., and Siefert, R. L.: Atmospheric iron deposition: Global distribution, variability, and human perturbations, Annu. Rev. Mar. Sci., 1, 245–278, 2009.
Mao, J., Fan, S., Jacob, D. J., and Travis, K. R.: Radical loss in the atmosphere from Cu-Fe redox coupling in aerosols, Atmos. Chem. Phys., 13, 509–519, https://doi.org/10.5194/acp-13-509-2013, 2013.
Martin, J. H.: Glacial-interglacial CO2 change: The Iron Hypothesis, Paleoceanography, 5, 1–13 1990.
Martin, J. H. and Fitzwater, S. E.: Iron-deficiency limits phytoplankton growth in the northeast pacific subarctic, Nature, 331, 341–343, 1988.
Meskhidze, N., Chameides, W. L., Nenes, A., and Chen, G.: Iron mobilization in mineral dust: Can anthropogenic SO2 emissions affect ocean productivity?, Geophys. Res. Lett., 30, 2085, https://doi.org/10.1029/2003GL018035, 2003.
Meskhidze, N., Chameides, W. L., and Nenes, A.: Dust and pollution: A recipe for enhanced ocean fertilization?, J. Geophys. Res., 110, D03301, https://doi.org/10.1029/2004JD005082, 2005.
Meyerstein, D.: Trivalent copper: I: a pulse radiolytic study of the properties of the aquocomplex, Inorg. Chem., 10, 638–641, 1971.
Millero, F. J., Sotolongo, S., and Izaguirre, M.: The kinetics of oxidation of Fe(II) in seawater, Geochim. Cosmochim. Acta, 51, 793–801, 1987.
Mills, M. M., Ridame, C., Davey, M., La Roche, J., and Geider, R. J.: Iron and phosphorus co-limit nitrogen fixation in the eastern tropical north Atlantic, Nature, 429, 292–294, 2004.
Moore, J. K., Doney, S. C., and Lindsay, K.: Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model, Global Biogeochem. Cy., 18, GB4028, https://doi.org/10.1029/2004GB002220, 2004.
Myriokefalitakis, S., Vrekoussis, M., Tsigaridis, K., Wittrock, F., Richter, A., Brühl, C., Volkamer, R., Burrows, J. P., and Kanakidou, M.: The influence of natural and anthropogenic secondary sources on the glyoxal global distribution, Atmos. Chem. Phys., 8, 4965–4981, https://doi.org/10.5194/acp-8-4965-2008, 2008.
Myriokefalitakis, S., Tsigaridis, K., Mihalopoulos, N., Sciare, J., Nenes, A., Kawamura, K., Segers, A., and Kanakidou, M.: In-cloud oxalate formation in the global troposphere: a 3-D modeling study, Atmos. Chem. Phys., 11, 5761–5782, https://doi.org/10.5194/acp-11-5761-2011, 2011.
Nenes, A., Pandis, S. N., and Pilinis, C.: ISORROPIA: A new thermodynamic equilibrium model for multiphase multicomponent inorganic aerosols, Aquat. Geochem., 4, 123–152, 1998.
Nickovic, S., Vukovic, A., Vujadinovic, M., Djurdjevic, V., and Pejanovic, G.: Technical Note: High-resolution mineralogical database of dust-productive soils for atmospheric dust modeling, Atmos. Chem. Phys., 12, 845–855, https://doi.org/10.5194/acp-12-845-2012, 2012.
Nickovic, S., Vukovic, A., and Vujadinovic, M.: Atmospheric processing of iron carried by mineral dust, Atmos. Chem. Phys. Discuss., 13, 2695–2723, https://doi.org/10.5194/acpd-13-2695-2013, 2013.
Okin, G. S., Baker, A. R., Tegen, I., Mahowald, N. M., Dentener, F. J., Duce, R. A., Galloway, J. N., Hunter, K., Kanakidou, M., Kubilay, N., Prospero, J. M., Sarin, M., Surapipith, V., Uematsu, M., and Zhu, T.: Impacts of atmospheric nutrient deposition on marine productivity: Roles of nitrogen, phosphorus, and iron, Global Biogeochem. Cy., 25, GB2022, https://doi.org/10.1029/2010GB003858, 2011.
Olsen, J., Prather, M., Berntsen, T., Carmichael, G., Chatfield, R., Connell, P., Derwent, R., Horowitz, L., Jin, S., Kanakidou, M., Kasibhatla, P., Kotamarthi, R., Kuhn, M., Law, K., Penner, J., Perliski, L., Sillman, S., Stordal, F., Thompson, A., and Wild, O.: Results from the Intergovernmental Panel on Climate Change photochemical model intercomparison (PhotoComp), J. Geophys. Res., 102, 5979–5991, 1997.
Paris, R., Desboeufs, K. V., and Journet, E.: Variability of dust iron solubility in atmospheric waters: Investigation of the role of oxalate organic complexation, Atmos. Environ., 45, 6510–6517, 2011.
Park, R. J., Jacob, D. J., Field, B. D., Yantosca, R. M., and Chin, M.: Natural and transboundary pollution influences on sulfate nitrate-ammonium aerosols in the United States: Implications for policy, J. Geophys. Res., 109, D15204, https://doi.org/10.1029/2003JD004473, 2004.
Pehkonen, S. O., Siefert, R., Erel, Y., Webb, S., and Hoffmann, M. R.: Photoreduction of iron oxyhydroxides in the presence of important atmospheric organic compounds, Environ. Sci. Technol., 27, 2056–2062, 1993.
Peterson, T. D., Whitney, F. A., and Harrison, P. J.: Macronutrient dynamics in an anticyclonic mesoscale eddy in the Gulf of Alaska, Deep-Sea Res. II, 52, 909–932, 2005.
Pikaev, A. K., Sibirskaya, G. K., Shirshov, E. M., Glazunov, P. Y., and Spitsyn, V. I.: Pulsed radiolysis of concentrated aqueous solutions of nitric acid, Dokl. Phys. Chem., Proc. Acad. Sci. USSR, 215, 328–331, 1974.
Prospero, J. M., Ginoux, P., Torres, O., and Nicholson, S. E.: Environmental characterization of global sources of atmospheric soil dust identified with the Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) absorbing aerosol product, Rev. Geophys., 40, 1002, https://doi.org/10.1029/2000RG000095, 2002.
Raabe, G.: Eine laserphotolytische studie zur kinetik der reaktionen des NO3- radikals in wäßriger lösung, Cuvillier, Göttingen, Germany, 1996.
Raiswell, R. and Canfield, D. E.: The iron biogeochemical cycle past and present, Geochem. Perspect., 1, 1–220, 2012.
Rinaldi, M., Decesari, S., Carbone, C., Finessi, E., Fuzzi, S., Ceburnis, D., O'Dowd, C. D., Sciare, J., Burrows, J. P., Vrekoussis, M., Ervens, B., Tsigaridis, K., and Facchini, M. C.: Evidence of a natural marine source of oxalic acid and a possible link to glyoxal, J. Geophys. Res., 116, D16204, https://doi.org/10.1029/2011JD015659, 2011.
Roy, E. G., Wells, M. L., and King, D. W.: Persistence of iron(II) in surface waters of the western subarctic Pacific, Limnol. Oceanogr., 53, 89–98, 2008.
Rubin, M., Berman-Frank, I., and Shaked, Y.: Dust and mineral iron utilization by the marine diazotroph Trichodesmium, Nat. Geosci., 4, 529–534, 2011.
Rush, J. D. and Bielski, B. H. J.: Pulse radiolytic studies of the reactions of HO2/O2 with Fe(II)/Fe(III) ions, The reactivity of HO2/O2 with ferric ions and its implication on the occurrence of the Haber-Weiss reaction, J. Phys. Chem., 89, 5062–5066, https://doi.org/10.1021/j100269a035, 1985.
Samson, S. D. and Eggleston, C. M.: Nonsteady-state dissolution of goethite and hematite in response to pH jumps: the role of adsorbed Fe(III), Water-Rock Interactions, Ore Deposits, and Environmental Geochemistry, edited by: Hellman, R. and Wood, S. A., 2002.
Santana-Casiano, J. M., Gonzalez-Davila, M., and Millero, F. J.: Oxidation of nanomolar levels of Fe(II) with oxygen in natural waters, Environ. Sci. Technol., 39, 2073–2079, 2005.
Sciare, J., Favez, O., Sarda-Esteve, R., Oikonomou, K., Cachier, H., and Kazan, V.: Long-term observations of carbonaceous aerosols in the Austral Ocean atmosphere: Evidence of a biogenic marine organic source, J. Geophys. Res., 114, D15302, https://doi.org/10.1029/2009JD011998, 2009.
Schwertmann, U.: Solubility and dissolution of iron oxides, Plant Soil, 130, 1–25, 1991.
Sedlak, D. L. and Hoigné, J.: The role of copper and oxalate in the redox cycling of iron in atmospheric waters, Atmos. Environ., 27A, 2173–2185, 1993.
Sedwick, P. N., Sholkovitz, E. R., and Church, T. M.: Impact of anthropogenic combustion emissions on the fractional solubility of aerosol iron: Evidence from the Sargasso Sea, Geochem. Geophys. Geosyst., 8, Q10Q06, https://doi.org/10.1029/2007GC001586, 2007.
Seinfeld, J. H. and Pandis, S. N.: Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley, New York, 1998.
Shi, Z., Krom, M. D., Jickells, T. D., Bonneville, S., Carslaw, K. S., Mihalopoulos, N., Baker, A. R., and Benning, L. G.: Impacts on iron solubility in the mineral dust by processes in the source region and the atmosphere: A review, Aeolian Research, 5, 21–42, 2012.
Sholkovitz, E. R., Sedwick, P. N., Church, T. M., Baker, A. R., and Powell, C. F.: Fractional solubility of aerosol iron: Synthesis of a global-scale data set, Geochim. Cosmochim. Acta, 89, 173–189, 2012.
Sidhu, P. S., Gilkes, R. J., Cornell, R. M., Posner, A. M., and Quirk, J. P.: Dissolution of iron oxides and oxyhydroxides in hydrochloric and perchloric acids, Clays Clay Minerals, 29, 269–276, 1981.
Siefert, R. L., Johansen, A. M., Hoffmann, M. R., and Pehkonen, S. O.: Measurements of trace metal (Fe, Cu, Mn, Cr) oxidation states in fog and stratus clouds, J. Air Waste Manage., 48, 128–143, 1998.
Sinreich, R., Coburn, S., Dix, B., and Volkamer, R.: Ship-based detection of glyoxal over the remote tropical Pacific Ocean, Atmos. Chem. Phys., 10, 11359–11371, https://doi.org/10.5194/acp-10-11359-2010, 2010.
Solmon, F., Chuang, P. Y., Meskhidze, N., and Chen, Y.: Acidic processing of mineral dust iron by anthropogenic compounds over the north Pacific Ocean, J. Geophys. Res., 114, D02305, https://doi.org/10.1029/2008JD010417, 2009.
Spokes, L. J., Jickells, T. D., and Lim, B.: Solubilization of aerosol trace metals by cloud processing: A laboratory study, Geochim. Cosmochim. Acta, 58, 3281–3287, 1994.
Stumm, W. and Morgan, J. J. (Eds.): Aquatic Chemistry: An Introduction Emphasizing Chemical Equilibria in Natural Waters, John Wiley, Hoboken, N. J., 780 pp., 1981.
Stumm, W., Furrer, G., Wieland, E., and Zinder, B.: The effects of complex-forming ligands on the dissolution of oxides and aluminosilicates, in: The Chemistry of Weathering, edited by: Drever, J. I., Dordrecht, D. Reidel Publishing Co, 55–74, 1985.
Sullivan, R. C., Moore, M. J. K., Petters, M. D., Kreidenweis, S. M., Roberts, G. C., and Prather, K. A.: Effect of chemical mixing state on the hygroscopicity and cloud nucleation properties of calcium mineral dust particles, Atmos. Chem. Phys., 9, 3303–3316, https://doi.org/10.5194/acp-9-3303-2009, 2009.
Suter, D., Banwart, S., and Stumm, W.: Dissolution of hydrous iron(III) oxides by reductive mechanisms, Langmuir, 7, 809–813, 1991.
Taylor, S. R. and McLennan, S. M.: The Continental Crust: its Composition and Evolution, Blackwell Scientific, Oxford, England, 1985.
Trapp, J. M., Millero, F. J., and Prospero, J. M.: Trends in the solubility of iron in dust-dominated aerosols in the equatorial Atlantic trade winds: Importance of iron speciation and sources, Geochem. Geophys. Geosyst., 11, Q03014, https://doi.org/10.1029/2009GC002651, 2010.
Volkamer, R., Coburn, S. C., Dix, B. K., and Sinreich, R.: The Eastern Pacific Ocean is a source for short lived atmospheric gases: glyoxal and iodine oxide, CLIVAR Exchanges, 15, 30–33, 2010.
Waite, T. D., Torikov, A., and Smith, J. D.: Photoassisted dissolution of colloidal iron oxides by thiol containing compounds. I. Dissolution of hematite (α-Fe203), J. Colloid Interface Sci., 112, 412–420, 1986.
Wiederhold, J. G., Kraemer, S. M., Teutsch, N., Borer, P. M., Halliday, A. N., and Kretzschmar, R.: Iron isotope fractionation during proton-promoted, ligand-controlled, and reductive dissolution of goethite, Environ. Sci. Technol., 40, 3787–3793, https://doi.org/10.1021/es052228y, 2006.
Wild, O., Zhu, Q., and Prather, M. J.: Fast-J: Accurate simulation of in- and below-cloud photolysis in global chemical models, J. Atmos. Chem., 37, 245–282, 2000.
Xu, N. and Gao, Y.: Characterization of hematite dissolution affected by oxalate coating, kinetics and pH, Appl. Geochem., 23, 783–793, 2008.
Yu, J., Huang, X., Xu, J., and Hu, M.: When aerosol sulfate goes up, so does oxalate: implication for the formation mechanisms of oxalate, Environ. Sci. Technol., 39, 128–133, 2005.
Zender, C. S., Newman, D., and Torres, O.: Spatial heterogeneity in aeolian erodibility: Uniform, topographic, geomorphic, and hydrologic hypotheses, J. Geophys. Res., 108, https://doi.org/10.1029/2002JD003039, 2003.
Zhang, L., Gong, S. L., Padro, J., and Barrie, L.: A size-segregated particle dry deposition scheme for an atmospheric aerosol module, Atmos. Environ., 35, 549–560, 2001.
Zhu, X. R., Prospero, J. M., and Millero, F. J.: Diel variability of soluble Fe(II) and soluble total Fe in North African dust in the trade winds at Barbados, J. Geophys. Res., 102, 21297–21305, 1997.
Zhuang, G., Yi, Z., Duce, R. A., and Brown, P. R.: Link between iron and sulphur cycles suggested by detection of Fe(II) in remote marine aerosols, Nature, 355, 537–539, 1992.
Ziajka, J., Beer, F., and Warneck, P.: Iron-catalysed oxidation of bisulphite aqueous solution: Evidence for a free radical chain mechanism, Atmos. Environ., 28, 2549–2552, 1994.
Zuo, Y. and Holgné, J.: Formation of hydrogen peroxide and depletion of oxalic acid in atmospheric water by photolysis of iron(III)-oxalato complexes, Environ. Sci. Technol., 26, 1014–1022, 1992.
