Articles | Volume 14, issue 6
Geosci. Model Dev., 14, 3215–3249, 2021
https://doi.org/10.5194/gmd-14-3215-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 14, 3215–3249, 2021
https://doi.org/10.5194/gmd-14-3215-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
03 Jun 2021
Development and technical paper
| 03 Jun 2021
Limitations of WRF land surface models for simulating land use and land cover change in Sub-Saharan Africa and development of an improved model (CLM-AF v. 1.0)
Timothy Glotfelty et al.
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Kai-Lan Chang, Owen R. Cooper, J. Jason West, Marc L. Serre, Martin G. Schultz, Meiyun Lin, Virginie Marécal, Béatrice Josse, Makoto Deushi, Kengo Sudo, Junhua Liu, and Christoph A. Keller
Geosci. Model Dev., 12, 955–978, https://doi.org/10.5194/gmd-12-955-2019, https://doi.org/10.5194/gmd-12-955-2019, 2019
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We developed a new method for combining surface ozone observations from thousands of monitoring sites worldwide with the output from multiple atmospheric chemistry models. The result is a global surface ozone distribution with greater accuracy than any single model can achieve. We focused on an ozone metric relevant to human mortality caused by long-term ozone exposure. Our method can be applied to studies that quantify the impacts of ozone on human health and mortality.
Christopher G. Nolte, Tanya L. Spero, Jared H. Bowden, Megan S. Mallard, and Patrick D. Dolwick
Atmos. Chem. Phys., 18, 15471–15489, https://doi.org/10.5194/acp-18-15471-2018, https://doi.org/10.5194/acp-18-15471-2018, 2018
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Changes in air pollution in the United States are simulated under three near-future climate scenarios. Widespread increases in average ozone levels are projected, with the largest increases during summer under the highest warming scenario. Increases are driven by higher temperatures and emissions from vegetation and are magnified at the upper end of the ozone distribution. The increases in ozone have potentially important implications for efforts to protect human health.
Yuqiang Zhang, J. Jason West, Rohit Mathur, Jia Xing, Christian Hogrefe, Shawn J. Roselle, Jesse O. Bash, Jonathan E. Pleim, Chuen-Meei Gan, and David C. Wong
Atmos. Chem. Phys., 18, 15003–15016, https://doi.org/10.5194/acp-18-15003-2018, https://doi.org/10.5194/acp-18-15003-2018, 2018
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Here we use a fine-resolution (36 km) self-consistent 21-year air quality simulation from 1990 to 2010, a health impact function, and annual county-level population and baseline mortality rate estimates to estimate annual mortality burdens from PM2.5 and O3 in the US, and also the contributions to the trends. We found that the PM2.5-related mortality burden has steadily decreased by 53 %, while the O3-related mortality burden has increased by 13 %, with larger inter-annual variabilities.
Ciao-Kai Liang, J. Jason West, Raquel A. Silva, Huisheng Bian, Mian Chin, Yanko Davila, Frank J. Dentener, Louisa Emmons, Johannes Flemming, Gerd Folberth, Daven Henze, Ulas Im, Jan Eiof Jonson, Terry J. Keating, Tom Kucsera, Allen Lenzen, Meiyun Lin, Marianne Tronstad Lund, Xiaohua Pan, Rokjin J. Park, R. Bradley Pierce, Takashi Sekiya, Kengo Sudo, and Toshihiko Takemura
Atmos. Chem. Phys., 18, 10497–10520, https://doi.org/10.5194/acp-18-10497-2018, https://doi.org/10.5194/acp-18-10497-2018, 2018
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Emissions from one continent affect air quality and health elsewhere. Here we quantify the effects of intercontinental PM2.5 and ozone transport on human health using a new multi-model ensemble, evaluating the health effects of emissions from six world regions and three emission source sectors. Emissions from one region have significant health impacts outside of that source region; similarly, foreign emissions contribute significantly to air-pollution-related deaths in several world regions.
Ulas Im, Jørgen Brandt, Camilla Geels, Kaj Mantzius Hansen, Jesper Heile Christensen, Mikael Skou Andersen, Efisio Solazzo, Ioannis Kioutsioukis, Ummugulsum Alyuz, Alessandra Balzarini, Rocio Baro, Roberto Bellasio, Roberto Bianconi, Johannes Bieser, Augustin Colette, Gabriele Curci, Aidan Farrow, Johannes Flemming, Andrea Fraser, Pedro Jimenez-Guerrero, Nutthida Kitwiroon, Ciao-Kai Liang, Uarporn Nopmongcol, Guido Pirovano, Luca Pozzoli, Marje Prank, Rebecca Rose, Ranjeet Sokhi, Paolo Tuccella, Alper Unal, Marta Garcia Vivanco, Jason West, Greg Yarwood, Christian Hogrefe, and Stefano Galmarini
Atmos. Chem. Phys., 18, 5967–5989, https://doi.org/10.5194/acp-18-5967-2018, https://doi.org/10.5194/acp-18-5967-2018, 2018
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The impacts of air pollution on human health and their costs in Europe and the United States for the year 2010 ared modeled by a multi-model ensemble. In Europe, the number of premature deaths is calculated to be 414 000, while in the US it is estimated to be 160 000. Health impacts estimated by individual models can vary up to a factor of 3. Results show that the domestic emissions have the largest impact on premature deaths, compared to foreign sources.
Raquel A. Silva, J. Jason West, Jean-François Lamarque, Drew T. Shindell, William J. Collins, Stig Dalsoren, Greg Faluvegi, Gerd Folberth, Larry W. Horowitz, Tatsuya Nagashima, Vaishali Naik, Steven T. Rumbold, Kengo Sudo, Toshihiko Takemura, Daniel Bergmann, Philip Cameron-Smith, Irene Cionni, Ruth M. Doherty, Veronika Eyring, Beatrice Josse, Ian A. MacKenzie, David Plummer, Mattia Righi, David S. Stevenson, Sarah Strode, Sophie Szopa, and Guang Zengast
Atmos. Chem. Phys., 16, 9847–9862, https://doi.org/10.5194/acp-16-9847-2016, https://doi.org/10.5194/acp-16-9847-2016, 2016
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Using ozone and PM2.5 concentrations from the ACCMIP ensemble of chemistry-climate models for the four Representative Concentration Pathway scenarios (RCPs), together with projections of future population and baseline mortality rates, we quantify the human premature mortality impacts of future ambient air pollution in 2030, 2050 and 2100, relative to 2000 concentrations. We also estimate the global mortality burden of ozone and PM2.5 in 2000 and each future period.
Yuqiang Zhang, Jared H. Bowden, Zachariah Adelman, Vaishali Naik, Larry W. Horowitz, Steven J. Smith, and J. Jason West
Atmos. Chem. Phys., 16, 9533–9548, https://doi.org/10.5194/acp-16-9533-2016, https://doi.org/10.5194/acp-16-9533-2016, 2016
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Reducing greenhouse gas (GHG) emissions can also improve air quality. We estimate the co-benefits of global GHG mitigation for US air quality in 2050 at fine resolution by downscaling from a previous global study. Foreign GHG mitigation under RCP4.5 contributes more to the US O3 reduction (76 % of the total) than domestic mitigation and contributes 26 % of the PM2.5 reduction. Therefore, the US gains significantly greater air quality co-benefits by coordinating GHG controls internationally.
Y. Gao, A. Ghilardi, J. F. Mas, J. Paneque-Galvez, and M. Skutsch
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 9–13, https://doi.org/10.5194/isprs-archives-XLI-B2-9-2016, https://doi.org/10.5194/isprs-archives-XLI-B2-9-2016, 2016
M. C. Woody, J. J. West, S. H. Jathar, A. L. Robinson, and S. Arunachalam
Atmos. Chem. Phys., 15, 6929–6942, https://doi.org/10.5194/acp-15-6929-2015, https://doi.org/10.5194/acp-15-6929-2015, 2015
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Utilizing an aircraft-specific parameterization based on smog chamber data in a regional AQM, contributions of non-traditional secondary organic aerosols (NTSOA) from aircraft emissions of semi-volatile and intermediate volatility organic compounds were assessed. NTSOA, a previously unaccounted component of PM2.5 in most AQMs, contributed up to 7.4% of aviation-attributable PM2.5 at the airport and rose to 17.9% downwind, suggesting its significance in aviation-attributed PM2.5 at all scales.
M. M. Fry, M. D. Schwarzkopf, Z. Adelman, and J. J. West
Atmos. Chem. Phys., 14, 523–535, https://doi.org/10.5194/acp-14-523-2014, https://doi.org/10.5194/acp-14-523-2014, 2014
J. Rissman, S. Arunachalam, M. Woody, J. J. West, T. BenDor, and F. S. Binkowski
Atmos. Chem. Phys., 13, 9285–9302, https://doi.org/10.5194/acp-13-9285-2013, https://doi.org/10.5194/acp-13-9285-2013, 2013
M. M. Fry, M. D. Schwarzkopf, Z. Adelman, V. Naik, W. J. Collins, and J. J. West
Atmos. Chem. Phys., 13, 5381–5399, https://doi.org/10.5194/acp-13-5381-2013, https://doi.org/10.5194/acp-13-5381-2013, 2013
W. J. Collins, M. M. Fry, H. Yu, J. S. Fuglestvedt, D. T. Shindell, and J. J. West
Atmos. Chem. Phys., 13, 2471–2485, https://doi.org/10.5194/acp-13-2471-2013, https://doi.org/10.5194/acp-13-2471-2013, 2013
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Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1
Coupling a weather model directly to GNSS orbit determination – case studies with OpenIFS
Implementation of an ensemble Kalman filter in the Community Multiscale Air Quality model (CMAQ model v5.1) for data assimilation of ground-level PM2.5
Massive-Parallel Trajectory Calculations version 2.2 (MPTRAC-2.2): Lagrangian transport simulations on graphics processing units (GPUs)
Bedymo: a combined quasi-geostrophic and primitive equation model in σ coordinates
Simulation of organics in the atmosphere: evaluation of EMACv2.54 with the Mainz Organic Mechanism (MOM) coupled to the ORACLE (v1.0) submodel
An update on the 4D-LETKF data assimilation system for the whole neutral atmosphere
Determining the sensitive parameters of the Weather Research and Forecasting (WRF) model for the simulation of tropical cyclones in the Bay of Bengal using global sensitivity analysis and machine learning
A unified framework to estimate the origins of atmospheric moisture and heat using Lagrangian models
Implementation of aerosol data assimilation in WRFDA (v4.0.3) for WRF-Chem (v3.9.1) using the RACM/MADE-VBS scheme
Representing low-intensity fire sensible heat output in a mesoscale atmospheric model with a canopy submodel: a case study with ARPS-CANOPY (version 5.2.12)
A machine-learning-guided adaptive algorithm to reduce the computational cost of integrating kinetics in global atmospheric chemistry models: application to GEOS-Chem versions 12.0.0 and 12.9.1
Deep-learning spatial principles from deterministic chemical transport models for chemical reanalysis: an application in China for PM2.5
Model development in practice: a comprehensive update to the boundary layer schemes in HARMONIE-AROME cycle 40
A parameterization of long-continuing-current (LCC) lightning in the lightning submodel LNOX (version 3.0) of the Modular Earth Submodel System (MESSy, version 2.54)
Air Control Toolbox (ACT_v1.0): a flexible surrogate model to explore mitigation scenarios in air quality forecasts
The Aerosol Module in the Community Radiative Transfer Model (v2.2 and v2.3): accounting for aerosol transmittance effects on the radiance observation operator
The Flexible Modelling Framework for the Met Office Unified Model (Flex-UM, using UM 12.0 release)
Integration-based extraction and visualization of jet stream cores
Particle-filter-based volcanic ash emission inversion applied to a hypothetical sub-Plinian Eyjafjallajökull eruption using the Ensemble for Stochastic Integration of Atmospheric Simulations (ESIAS-chem) version 1.0
Evaluating the assimilation of S5P/TROPOMI near real-time SO2 columns and layer height data into the CAMS integrated forecasting system (CY47R1), based on a case study of the 2019 Raikoke eruption
Improvement of stomatal resistance and photosynthesis mechanism of Noah-MP-WDDM (v1.42) in simulation of NO2 dry deposition velocity in forests
Representation of the autoconversion from cloud to rain using a weighted ensemble approach: a case study using WRF v4.1.3
EuLerian Identification of ascending AirStreams (ELIAS 2.0) in numerical weather prediction and climate models – Part 1: Development of deep learning model
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A new exponentially decaying error correlation model for assimilating OCO-2 column-average CO2 data using a length scale computed from airborne lidar measurements
Numerically consistent budgets of potential temperature, momentum, and moisture in Cartesian coordinates: application to the WRF model
An aerosol classification scheme for global simulations using the K-means machine learning method
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Downscaling of air pollutants in Europe using uEMEP_v6
WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America
Evaluation of the COSMO model (v5.1) in polarimetric radar space – impact of uncertainties in model microphysics, retrievals and forward operators
Development of aerosol optical properties for improving the MESSy photolysis module in the GEM-MACH v2.4 air quality model and application for calculating photolysis rates in a biomass burning plume
The sensitivity of simulated aerosol climatic impact to domain size using regional model (WRF-Chem v3.6)
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Reduced-complexity air quality intervention modeling over China: the development of InMAPv1.6.1-China and a comparison with CMAQv5.2
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On the application and grid-size sensitivity of the urban dispersion model CAIRDIO for the simulation of a real city and realistic meteorology
Black carbon modeling in urban areas: investigating the influence of resuspension and non-exhaust emissions in streets using the Street-in-Grid model for inert particles (SinG-inert)
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Santos J. González-Rojí, Martina Messmer, Christoph C. Raible, and Thomas F. Stocker
Geosci. Model Dev., 15, 2859–2879, https://doi.org/10.5194/gmd-15-2859-2022, https://doi.org/10.5194/gmd-15-2859-2022, 2022
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Different configurations of physics parameterizations of a regional climate model are tested over southern Peru at fine resolution. The most challenging regions compared to observational data are the slopes of the Andes. Model configurations for Europe and East Africa are not perfectly suitable for southern Peru. The experiment with the Stony Brook University microphysics scheme and the Grell–Freitas cumulus parameterization provides the most accurate results over Madre de Dios.
Angel Navarro Trastoy, Sebastian Strasser, Lauri Tuppi, Maksym Vasiuta, Markku Poutanen, Torsten Mayer-Gürr, and Heikki Järvinen
Geosci. Model Dev., 15, 2763–2771, https://doi.org/10.5194/gmd-15-2763-2022, https://doi.org/10.5194/gmd-15-2763-2022, 2022
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Production of satellite products relies on information from different centers. By coupling a weather model and an orbit determination solver we eliminate the dependence on one of the centers. The coupling has proven to be possible in the first stage, where no formatting has been applied to any of the models involved. This opens a window for further development and improvement to a coupling that has proven to be as good as the predecessor model.
Soon-Young Park, Uzzal Kumar Dash, Jinhyeok Yu, Keiya Yumimoto, Itsushi Uno, and Chul Han Song
Geosci. Model Dev., 15, 2773–2790, https://doi.org/10.5194/gmd-15-2773-2022, https://doi.org/10.5194/gmd-15-2773-2022, 2022
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An EnKF was applied to CMAQ for assimilating ground PM2.5 observations from China and South Korea. The EnKF performed better than that without assimilation and even superior to 3D-Var. The reduced MBs in 24 h predictions were 48 % and 27 % by improving ICs and BCs, respectively.
Lars Hoffmann, Paul F. Baumeister, Zhongyin Cai, Jan Clemens, Sabine Griessbach, Gebhard Günther, Yi Heng, Mingzhao Liu, Kaveh Haghighi Mood, Olaf Stein, Nicole Thomas, Bärbel Vogel, Xue Wu, and Ling Zou
Geosci. Model Dev., 15, 2731–2762, https://doi.org/10.5194/gmd-15-2731-2022, https://doi.org/10.5194/gmd-15-2731-2022, 2022
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We describe the new version (2.2) of the Lagrangian transport model MPTRAC, which has been ported for application on GPUs. The model was verified by comparing kinematic trajectories and synthetic tracer simulations for the free troposphere and stratosphere from GPUs and CPUs. Benchmarking showed a speed-up of a factor of 16 of GPU-enabled simulations compared to CPU-only runs, indicating the great potential of applying GPUs for Lagrangian transport simulations on upcoming HPC systems.
Clemens Spensberger, Trond Thorsteinsson, and Thomas Spengler
Geosci. Model Dev., 15, 2711–2729, https://doi.org/10.5194/gmd-15-2711-2022, https://doi.org/10.5194/gmd-15-2711-2022, 2022
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In order to understand the atmosphere, we rely on a hierarchy of models ranging from very simple to very complex. Comparing different steps in this hierarchy usually entails comparing different models. Here we combine two such steps that are commonly used in one modelling framework. This makes comparisons both much easier and much more direct.
Andrea Pozzer, Simon F. Reifenberg, Vinod Kumar, Bruno Franco, Matthias Kohl, Domenico Taraborrelli, Sergey Gromov, Sebastian Ehrhart, Patrick Jöckel, Rolf Sander, Veronica Fall, Simon Rosanka, Vlassis Karydis, Dimitris Akritidis, Tamara Emmerichs, Monica Crippa, Diego Guizzardi, Johannes W. Kaiser, Lieven Clarisse, Astrid Kiendler-Scharr, Holger Tost, and Alexandra Tsimpidi
Geosci. Model Dev., 15, 2673–2710, https://doi.org/10.5194/gmd-15-2673-2022, https://doi.org/10.5194/gmd-15-2673-2022, 2022
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A newly developed setup of the chemistry general circulation model EMAC (ECHAM5/MESSy for Atmospheric Chemistry) is evaluated here. A comprehensive organic degradation mechanism is used and coupled with a volatility base model.
The results show that the model reproduces most of the tracers and aerosols satisfactorily but shows discrepancies for oxygenated organic gases. It is also shown that this model configuration can be used for further research in atmospheric chemistry.
Dai Koshin, Kaoru Sato, Masashi Kohma, and Shingo Watanabe
Geosci. Model Dev., 15, 2293–2307, https://doi.org/10.5194/gmd-15-2293-2022, https://doi.org/10.5194/gmd-15-2293-2022, 2022
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The 4D ensemble Kalman filter data assimilation system for the whole neutral atmosphere has been updated. The update includes the introduction of a filter to reduce the generation of spurious waves, change in the order of horizontal diffusion of the forecast model to reproduce more realistic tidal amplitudes, and use of additional satellite observations. As a result, the analysis performance has been greatly improved, even for disturbances with periods of less than 1 d.
Harish Baki, Sandeep Chinta, C Balaji, and Balaji Srinivasan
Geosci. Model Dev., 15, 2133–2155, https://doi.org/10.5194/gmd-15-2133-2022, https://doi.org/10.5194/gmd-15-2133-2022, 2022
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WRF model accuracy relies on numerous aspects, and the model parameters are one of them. By calibrating the model parameters, we can improve the model forecast. However, there exist hundreds of parameters, and calibrating all of them is unimaginably expensive. Thus, there is a need to identify the sensitive parameters that influence the model output variables to reduce the parameter dimensionality. This study addresses the different methods and outcomes of parameter sensitivity analysis.
Jessica Keune, Dominik L. Schumacher, and Diego G. Miralles
Geosci. Model Dev., 15, 1875–1898, https://doi.org/10.5194/gmd-15-1875-2022, https://doi.org/10.5194/gmd-15-1875-2022, 2022
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Air transports moisture and heat, shaping the weather we experience. When and where was this air moistened and warmed by the surface? To address this question, atmospheric models trace the history of air parcels in space and time. However, their uncertainties remain unexplored, which hinders their utility and application. Here, we present a framework that sheds light on these uncertainties. Our approach sets a new standard in the assessment of atmospheric moisture and heat trajectories.
Soyoung Ha
Geosci. Model Dev., 15, 1769–1788, https://doi.org/10.5194/gmd-15-1769-2022, https://doi.org/10.5194/gmd-15-1769-2022, 2022
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In an effort to improve air quality forecasting, the WRFDA 3D-Var system is newly extended for the assimilation of surface PM2.5 and PM10 using the RACM/MADE-VBS chemistry in the WRF-Chem model. Through a case study during the Korea–United States Air Quality (KORUS-AQ) period, it is demonstrated that the analysis can lead to improving the prediction of surface PM concentrations up to 26 % for 24 h, diminishing most bias errors.
Michael T. Kiefer, Warren E. Heilman, Shiyuan Zhong, Joseph J. Charney, Xindi Bian, Nicholas S. Skowronski, Kenneth L. Clark, Michael R. Gallagher, John L. Hom, and Matthew Patterson
Geosci. Model Dev., 15, 1713–1734, https://doi.org/10.5194/gmd-15-1713-2022, https://doi.org/10.5194/gmd-15-1713-2022, 2022
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We examine methods used to represent wildland fire sensible heat release in atmospheric models. A set of simulations are evaluated using observations from a low-intensity prescribed fire in the New Jersey Pine Barrens. The comparison is motivated by the need for guidance regarding the representation of low-intensity fire sensible heating in atmospheric models. Such fires are prevalent during prescribed fire operations and can impact the health and safety of fire personnel and the public.
Lu Shen, Daniel J. Jacob, Mauricio Santillana, Kelvin Bates, Jiawei Zhuang, and Wei Chen
Geosci. Model Dev., 15, 1677–1687, https://doi.org/10.5194/gmd-15-1677-2022, https://doi.org/10.5194/gmd-15-1677-2022, 2022
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The high computational cost of chemical integration is a long-standing limitation in global atmospheric chemistry models. Here we present an adaptive and efficient algorithm that can reduce the computational time of atmospheric chemistry by 50 % and maintain the error below 2 % for important species, inspired by machine learning clustering techniques and traditional asymptotic analysis ideas.
Baolei Lyu, Ran Huang, Xinlu Wang, Weiguo Wang, and Yongtao Hu
Geosci. Model Dev., 15, 1583–1594, https://doi.org/10.5194/gmd-15-1583-2022, https://doi.org/10.5194/gmd-15-1583-2022, 2022
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Data fusion is used to estimate spatially completed and smooth reanalysis fields from multiple data sources of observations and model simulations. We developed a well-designed deep-learning model framework to embed spatial correlation principles of atmospheric physics and chemical models. The deep-learning model has very high accuracy to predict reanalysis data fields from isolated observation data points. It is also feasible for operational applications due to computational efficiency.
Wim C. de Rooy, Pier Siebesma, Peter Baas, Geert Lenderink, Stephan R. de Roode, Hylke de Vries, Erik van Meijgaard, Jan Fokke Meirink, Sander Tijm, and Bram van 't Veen
Geosci. Model Dev., 15, 1513–1543, https://doi.org/10.5194/gmd-15-1513-2022, https://doi.org/10.5194/gmd-15-1513-2022, 2022
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This paper describes a comprehensive model update to the boundary layer schemes. Because the involved parameterisations are all built on widely applied frameworks, the here-described modifications are applicable to many NWP and climate models. The model update contains substantial modifications to the cloud, turbulence, and convection schemes and leads to a substantial improvement of several aspects of the model, especially low cloud forecasts.
Francisco J. Pérez-Invernón, Heidi Huntrieser, Patrick Jöckel, and Francisco J. Gordillo-Vázquez
Geosci. Model Dev., 15, 1545–1565, https://doi.org/10.5194/gmd-15-1545-2022, https://doi.org/10.5194/gmd-15-1545-2022, 2022
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This study reports the first parameterization of long-continuing-current lightning in a climate model. Long-continuing-current lightning is proposed to be the main precursor of lightning-ignited wildfires and sprites, a type of transient luminous event taking place in the mesosphere. This parameterization can significantly contribute to improving the implementation of wildfires in climate models.
Augustin Colette, Laurence Rouïl, Frédérik Meleux, Vincent Lemaire, and Blandine Raux
Geosci. Model Dev., 15, 1441–1465, https://doi.org/10.5194/gmd-15-1441-2022, https://doi.org/10.5194/gmd-15-1441-2022, 2022
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We introduce the first toolbox that allows exploration of the benefits of air pollution mitigation scenarios in the every-day air quality forecasts through a web interface. The toolbox relies on the joint use of chemistry-transport models (CTMs) and surrogate modelling techniques.
Cheng-Hsuan Lu, Quanhua Liu, Shih-Wei Wei, Benjamin T. Johnson, Cheng Dang, Patrick G. Stegmann, Dustin Grogan, Guoqing Ge, Ming Hu, and Michael Lueken
Geosci. Model Dev., 15, 1317–1329, https://doi.org/10.5194/gmd-15-1317-2022, https://doi.org/10.5194/gmd-15-1317-2022, 2022
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This article is a technical note on the aerosol absorption and scattering calculations of the Community Radiative Transfer Model (CRTM) v2.2 and v2.3. It also provides guidance for prospective users of the CRTM aerosol option and Gridpoint Statistical Interpolation (GSI) aerosol-aware radiance assimilation. Scientific aspects of aerosol-affected BT in atmospheric data assimilation are also briefly discussed.
Penelope Maher and Paul Earnshaw
Geosci. Model Dev., 15, 1177–1194, https://doi.org/10.5194/gmd-15-1177-2022, https://doi.org/10.5194/gmd-15-1177-2022, 2022
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Climate models do a pretty good job. But they are far from perfect. Fixing these imperfections is really hard because the models are complicated. One way to make progress is to create simpler models: think impressionism rather than realism in the art world. We changed the Met Office model to be intentionally simple and it still does a pretty good job. This will help to identify sources of model imperfections, develop new methods and improve our understanding of how the climate works.
Lukas Bösiger, Michael Sprenger, Maxi Boettcher, Hanna Joos, and Tobias Günther
Geosci. Model Dev., 15, 1079–1096, https://doi.org/10.5194/gmd-15-1079-2022, https://doi.org/10.5194/gmd-15-1079-2022, 2022
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Jet streams are coherent air flows that interact with atmospheric structures such as warm conveyor belts (WCBs) and the tropopause. Individually, these structures have a significant impact on the weather evolution. A first step towards a deeper understanding of the meteorological processes is to extract jet stream core lines, for which we develop a novel feature extraction algorithm. Based on the line geometry, we automatically detect and visualize potential interactions between WCBs and jets.
Philipp Franke, Anne Caroline Lange, and Hendrik Elbern
Geosci. Model Dev., 15, 1037–1060, https://doi.org/10.5194/gmd-15-1037-2022, https://doi.org/10.5194/gmd-15-1037-2022, 2022
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The paper proposes an ensemble-based analysis framework (ESIAS-chem) for time- and altitude-resolved volcanic ash emission fluxes and their uncertainty. The core of the algorithm is an ensemble Nelder–Mead optimization algorithm accompanied by a particle filter update. The performed notional experiments demonstrate the high accuracy of ESIAS-chem in analyzing the vertically resolved volcanic ash in the atmosphere. Further, the system is in general able to estimate the emission fluxes properly.
Antje Inness, Melanie Ades, Dimitris Balis, Dmitry Efremenko, Johannes Flemming, Pascal Hedelt, Maria-Elissavet Koukouli, Diego Loyola, and Roberto Ribas
Geosci. Model Dev., 15, 971–994, https://doi.org/10.5194/gmd-15-971-2022, https://doi.org/10.5194/gmd-15-971-2022, 2022
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This paper describes the way that the Copernicus Atmosphere Monitoring Service (CAMS) produces forecasts of volcanic SO2. These forecasts are provided routinely every day. They are created by blending SO2 data from satellite instruments (TROPOMI and GOME-2) with the CAMS model. We show that the quality of the CAMS SO2 forecasts can be improved if additional information about the height of volcanic plumes is provided in the satellite data.
Ming Chang, Jiachen Cao, Qi Zhang, Weihua Chen, Guotong Wu, Liping Wu, Weiwen Wang, and Xuemei Wang
Geosci. Model Dev., 15, 787–801, https://doi.org/10.5194/gmd-15-787-2022, https://doi.org/10.5194/gmd-15-787-2022, 2022
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Despite the importance of nitrogen deposition, its simulation is still insufficiently represented in current atmospheric chemistry models. In this study, the improvement of the canopy stomatal resistance mechanism and the nitrogen-limiting schemes in Noah-MP-WDDM v1.42 give new options for simulating nitrogen dry deposition velocity. This study finds that the combined BN-23 mechanism agrees better with the observed NO2 dry deposition velocity, with the mean bias reduced by 50.1 %.
Jinfang Yin, Xudong Liang, Hong Wang, and Haile Xue
Geosci. Model Dev., 15, 771–786, https://doi.org/10.5194/gmd-15-771-2022, https://doi.org/10.5194/gmd-15-771-2022, 2022
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An ensemble (EN) approach was designed to improve autoconversion (ATC) from cloud water to rainwater in cloud microphysics schemes. One unique feature of the EN approach is that the ATC rate is a mean value based on the calculations from several widely used ATC schemes. The ensemble approach proposed herein appears to help improve the representation of cloud and precipitation processes in weather and climate models.
Julian F. Quinting and Christian M. Grams
Geosci. Model Dev., 15, 715–730, https://doi.org/10.5194/gmd-15-715-2022, https://doi.org/10.5194/gmd-15-715-2022, 2022
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Physical processes in weather systems importantly affect the midlatitude large-scale circulation. This study introduces an artificial-intelligence-based framework which allows the identification of an important weather system – the so-called warm conveyor belt (WCB) – at comparably low computational costs and from data at low spatial and temporal resolution. The framework thus newly enables the systematic investigation of WCBs in large data sets such as climate model projections.
Julian F. Quinting, Christian M. Grams, Annika Oertel, and Moritz Pickl
Geosci. Model Dev., 15, 731–744, https://doi.org/10.5194/gmd-15-731-2022, https://doi.org/10.5194/gmd-15-731-2022, 2022
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This study applies novel artificial-intelligence-based models that allow the identification of one specific weather system which affects the midlatitude circulation. We show that the models yield similar results as their trajectory-based counterpart, which requires data at higher spatiotemporal resolution and is computationally more expensive. Overall, we aim to show how deep learning methods can be used efficiently to support process understanding of biases in weather prediction models.
David F. Baker, Emily Bell, Kenneth J. Davis, Joel F. Campbell, Bing Lin, and Jeremy Dobler
Geosci. Model Dev., 15, 649–668, https://doi.org/10.5194/gmd-15-649-2022, https://doi.org/10.5194/gmd-15-649-2022, 2022
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The OCO-2 satellite measures many closely spaced column-averaged CO2 values around its orbit. To give these data proper weight in flux inversions, their error correlations must be accounted for. Here we lay out a 1-D error model with correlations that die out exponentially along-track to do so. A correlation length scale of ∼20 km is derived from column CO2 measurements from an airborne lidar flown underneath OCO-2 for use in this model. The model's performance is compared to previous ones.
Matthias Göbel, Stefano Serafin, and Mathias W. Rotach
Geosci. Model Dev., 15, 669–681, https://doi.org/10.5194/gmd-15-669-2022, https://doi.org/10.5194/gmd-15-669-2022, 2022
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We present WRFlux, an open-source software that allows numerically consistent, time-averaged budget evaluation of prognostic variables for the numerical weather prediction model WRF as well as the transformation of the budget equations from the terrain-following grid of the model to the Cartesian coordinate system. We demonstrate the performance and a possible application of WRFlux and illustrate the detrimental effects of approximations that are inconsistent with the model numerics.
Jingmin Li, Johannes Hendricks, Mattia Righi, and Christof G. Beer
Geosci. Model Dev., 15, 509–533, https://doi.org/10.5194/gmd-15-509-2022, https://doi.org/10.5194/gmd-15-509-2022, 2022
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The growing complexity of global aerosol models results in a large number of parameters that describe the aerosol number, size, and composition. This makes the analysis, evaluation, and interpretation of the model results a challenge. To overcome this difficulty, we apply a machine learning classification method to identify clusters of specific aerosol types in global aerosol simulations. Our results demonstrate the spatial distributions and characteristics of these identified aerosol clusters.
Camilo Fernando Rodríguez Genó and Léster Alfonso
Geosci. Model Dev., 15, 493–507, https://doi.org/10.5194/gmd-15-493-2022, https://doi.org/10.5194/gmd-15-493-2022, 2022
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The representation of the collision–coalescence process in models of different scales has been a great source of uncertainty for many years. The aim of this paper is to show that machine learning techniques can be a useful tool in order to incorporate this process by emulating the explicit treatment of microphysics. Our results show that the machine learning parameterization mimics the evolution of actual droplet size distributions very well.
Li Zhang, Georg A. Grell, Stuart A. McKeen, Ravan Ahmadov, Karl D. Froyd, and Daniel Murphy
Geosci. Model Dev., 15, 467–491, https://doi.org/10.5194/gmd-15-467-2022, https://doi.org/10.5194/gmd-15-467-2022, 2022
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Applying the chemistry package from WRF-Chem into the Flow-following finite-volume Icosahedra Model, we essentially make it possible to explore the importance of different levels of complexity in gas and aerosol chemistry, as well as in physics parameterizations, for the interaction processes in global modeling systems. The model performance validated by the Atmospheric Tomography Mission aircraft measurements in summer 2016 shows good performance in capturing the aerosol and gas-phase tracers.
Qing Mu, Bruce Rolstad Denby, Eivind Grøtting Wærsted, and Hilde Fagerli
Geosci. Model Dev., 15, 449–465, https://doi.org/10.5194/gmd-15-449-2022, https://doi.org/10.5194/gmd-15-449-2022, 2022
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Our study has achieved air quality modelling down to 100 m for all of Europe. This solves the current problem that street-level air quality modelling is usually limited to individual cities. With publicly available downscaling proxy data, even regions without their own high-resolution proxy data can obtain air quality maps at 100 m. The work is of significance for air quality mitigation strategies and human health exposure studies.
Almudena García-García, Francisco José Cuesta-Valero, Hugo Beltrami, J. Fidel González-Rouco, and Elena García-Bustamante
Geosci. Model Dev., 15, 413–428, https://doi.org/10.5194/gmd-15-413-2022, https://doi.org/10.5194/gmd-15-413-2022, 2022
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We study the sensitivity of a regional climate model to resolution and soil scheme changes. Our results show that the use of finer resolutions mainly affects precipitation outputs, particularly in summer due to changes in convective processes. Finer resolutions are associated with larger biases compared with observations. Changing the land surface model scheme affects the simulation of near-surface temperatures, yielding the lowest biases in mean temperature with the most complex soil scheme.
Prabhakar Shrestha, Jana Mendrok, Velibor Pejcic, Silke Trömel, Ulrich Blahak, and Jacob T. Carlin
Geosci. Model Dev., 15, 291–313, https://doi.org/10.5194/gmd-15-291-2022, https://doi.org/10.5194/gmd-15-291-2022, 2022
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The article focuses on the exploitation of radar polarimetry for model evaluation of stratiform precipitation. The model exhibited a low bias in simulated polarimetric moments at lower levels above the melting layer where snow was found to dominate. This necessitates further research into the missing microphysical processes in these lower levels (e.g. fragmentation due to ice–ice collisions) and use of more reliable snow-scattering models in the forward operator to draw valid conclusions.
Mahtab Majdzadeh, Craig A. Stroud, Christopher Sioris, Paul A. Makar, Ayodeji Akingunola, Chris McLinden, Xiaoyi Zhao, Michael D. Moran, Ihab Abboud, and Jack Chen
Geosci. Model Dev., 15, 219–249, https://doi.org/10.5194/gmd-15-219-2022, https://doi.org/10.5194/gmd-15-219-2022, 2022
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A new lookup table for aerosol optical properties based on a Mie scattering code was calculated and adopted within an improved version of the photolysis module in the GEM-MACH in-line chemical transport model. The modified version of the photolysis module makes use of online interactive aerosol feedback and applies core-shell parameterizations to the black carbon absorption efficiency based on Bond et al. (2006) to the size bins with black carbon mass fraction of less than 40 %.
Xiaodong Wang, Chun Zhao, Mingyue Xu, Qiuyan Du, Jianqiu Zheng, Yun Bi, Shengfu Lin, and Yali Luo
Geosci. Model Dev., 15, 199–218, https://doi.org/10.5194/gmd-15-199-2022, https://doi.org/10.5194/gmd-15-199-2022, 2022
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Regional models are widely used to investigate aerosol climatic impacts. However, there are few studies examining the sensitivities of modeling results to regional domain size. In this study, the regional model is used to study the aerosol impacts on the East Asian summer monsoon system and focus on the modeling sensitivities to domain size. This study highlights the important impacts of domain size on regional modeling results of aerosol climatic impacts, which may not be limited to East Asia.
Haibo Wang, Ting Yang, Zifa Wang, Jianjun Li, Wenxuan Chai, Guigang Tang, Lei Kong, and Xueshun Chen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-374, https://doi.org/10.5194/gmd-2021-374, 2022
Revised manuscript accepted for GMD
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In this paper, we develop an online data coupled assimilation system NAQPMS-PDAF with the Eulerian atmospheric chemistry-transport model. NAQPMS-PDAF allows efficient use of large computational resources. The application and performance of the system are investigated by assimilating one month of vertical aerosol observations. The results show that NAQPMS-PDAF can significantly improve the performance of aerosol vertical structure simulation and reduce the uncertainty to a large extent.
Andrew Zammit-Mangion, Michael Bertolacci, Jenny Fisher, Ann Stavert, Matthew Rigby, Yi Cao, and Noel Cressie
Geosci. Model Dev., 15, 45–73, https://doi.org/10.5194/gmd-15-45-2022, https://doi.org/10.5194/gmd-15-45-2022, 2022
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We present a framework for estimating the sources and sinks (flux) of carbon dioxide from satellite data. The framework is statistical and yields measures of uncertainty alongside all estimates of flux and other parameters in the underlying model. It also allows us to generate other insights, such as the size of errors and biases in the data. The primary aim of this research was to develop a fully statistical flux inversion framework for use by atmospheric scientists.
Xiaotian Xu, Xu Feng, Haipeng Lin, Peng Zhang, Shaojian Huang, Zhengcheng Song, Yiming Peng, Tzung-May Fu, and Yanxu Zhang
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-404, https://doi.org/10.5194/gmd-2021-404, 2022
Revised manuscript accepted for GMD
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High mercury wet deposition in the southeastern US has been a problem for many years. Here we employed a newly developed high-resolution WRF-GC mode with capability of mercury simulation to study this problem. In this research, we conclude that it is the deep convection caused enhanced mercury wet deposition in the southeastern United States.
Galina Wind, Arlindo M. da Silva, Kerry G. Meyer, Steven Platnick, and Peter M. Norris
Geosci. Model Dev., 15, 1–14, https://doi.org/10.5194/gmd-15-1-2022, https://doi.org/10.5194/gmd-15-1-2022, 2022
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This is the third paper in series about the Multi-sensor Cloud and Aerosol Retrieval Simulator (MCARS). In this paper we use MCARS to create a set of constraints that might be used to assimilate a new above-cloud aerosol retrieval product developed for the MODIS instrument into a general circulation model. We executed the above-cloud aerosol retrieval over a series of synthetic MODIS granules and found the product to be of excellent quality.
Xueying Yu, Dylan B. Millet, and Daven K. Henze
Geosci. Model Dev., 14, 7775–7793, https://doi.org/10.5194/gmd-14-7775-2021, https://doi.org/10.5194/gmd-14-7775-2021, 2021
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We conduct observing system simulation experiments to test how well inverse analyses of high-resolution satellite data from sensors such as TROPOMI can quantify methane emissions. Inversions can improve monthly flux estimates at 25 km even with a spatially biased prior or model transport errors, but results are strongly degraded when both are present. We further evaluate a set of alternate formalisms to overcome limitations of the widely used scale factor approach that arise for missing sources.
Ruili Wu, Christopher W. Tessum, Yang Zhang, Chaopeng Hong, Yixuan Zheng, Xinyin Qin, Shigan Liu, and Qiang Zhang
Geosci. Model Dev., 14, 7621–7638, https://doi.org/10.5194/gmd-14-7621-2021, https://doi.org/10.5194/gmd-14-7621-2021, 2021
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Reduced-complexity air quality models are less computationally intensive and easier to use. We developed a reduced-complexity air quality Intervention Model for Air Pollution over China (InMAP-China) to rapidly predict the air quality and estimate the health impacts of emission sources in China. We believe that this work will be of great interest to a broad audience, including environmentalists in China and scientists in relevant fields at both national and local institutes.
Patrick Obin Sturm and Anthony S. Wexler
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-402, https://doi.org/10.5194/gmd-2021-402, 2021
Revised manuscript accepted for GMD
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Large air quality and climate models require vast amounts of computational power. Machine learning tools like neural networks can be used to make these models more efficient, with the downside that their results might not make physical sense or be easy to interpret. This work develops a physically interpretable neural network that obeys scientific laws like conservation of mass, and models atmospheric composition more accurately than a traditional neural network.
Qian Ye, Jie Li, Xueshun Chen, Huansheng Chen, Wenyi Yang, Huiyun Du, Xiaole Pan, Xiao Tang, Wei Wang, Lili Zhu, Jianjun Li, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 14, 7573–7604, https://doi.org/10.5194/gmd-14-7573-2021, https://doi.org/10.5194/gmd-14-7573-2021, 2021
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We developed a global tropospheric atmospheric chemistry source–receptor model. This model can quantify the contributions of multiple air pollutants from various source regions in one simulation without introducing the nonlinear error of atmospheric chemistry. The S-R relationships of PM2.5 and O3 from a global high-resolution (0.5° × 0.5°) simulation were given and compared with previous studies. This model will be useful for creating a link between the scientific community and policymakers.
Alan J. Geer, Peter Bauer, Katrin Lonitz, Vasileios Barlakas, Patrick Eriksson, Jana Mendrok, Amy Doherty, James Hocking, and Philippe Chambon
Geosci. Model Dev., 14, 7497–7526, https://doi.org/10.5194/gmd-14-7497-2021, https://doi.org/10.5194/gmd-14-7497-2021, 2021
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Satellite observations of radiation from the earth can have strong sensitivity to cloud and precipitation in the atmosphere, with applications in weather forecasting and the development of models. Computing the radiation received at the satellite sensor using radiative transfer theory requires a simulation of the optical properties of a volume containing a large number of cloud and precipitation particles. This article describes the physics used to generate these
bulkoptical properties.
Yalda Fatahi, Rostislav Kouznetsov, and Mikhail Sofiev
Geosci. Model Dev., 14, 7459–7475, https://doi.org/10.5194/gmd-14-7459-2021, https://doi.org/10.5194/gmd-14-7459-2021, 2021
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Incorporating information on public holidays into anthropogenic sector emissions results in substantial short-term improvement of the chemistry transport model SILAM scores. The largest impact was found for NOx, which is controlled by the changes in the traffic intensity. Certain improvements were also found for other species, but the signal was weaker than that for NOx.
Mohammad Reza Heidari, Zhaoyang Song, Enrico Degregori, Jörg Behrens, and Hendryk Bockelmann
Geosci. Model Dev., 14, 7439–7457, https://doi.org/10.5194/gmd-14-7439-2021, https://doi.org/10.5194/gmd-14-7439-2021, 2021
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To improve our understanding of climate system dynamics and their variability, the numerical atmospheric model ECHAM6 is used to simulate a complete glacial cycle over the past 120 000 years. However, performing such simulations takes a long time even on state-of-the-art supercomputers. To accelerate the model simulation, we propose calculating radiative transfer processes in parallel with adiabatic processes in the atmosphere, which reduces the simulation time by nearly half.
Kai Wang, Yang Zhang, Shaocai Yu, David C. Wong, Jonathan Pleim, Rohit Mathur, James T. Kelly, and Michelle Bell
Geosci. Model Dev., 14, 7189–7221, https://doi.org/10.5194/gmd-14-7189-2021, https://doi.org/10.5194/gmd-14-7189-2021, 2021
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The two-way coupled WRF-CMAQ model accounting for complex chemistry–meteorology feedbacks has been applied to the long-term predictions of regional meteorology and air quality over the US. The model results show superior performance and importance of chemistry–meteorology feedbacks when compared to the offline coupled WRF and CMAQ simulations, which suggests that feedbacks should be considered along with other factors in developing future model applications to inform policy making.
Michael Weger, Bernd Heinold, Alfred Wiedensohler, and Maik Merkel
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-358, https://doi.org/10.5194/gmd-2021-358, 2021
Revised manuscript accepted for GMD
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Numerical models are an important tool to assess the air quality in cities, as they can provide near-continouos data in time and space. In this paper, air-pollution for an entire city is simulated at a high spatial resolution of 40 m. At this spatial scale, the effects of buildings on the atmosphere, like channeling or blocking of the air flow, are directly represented by diffuse obstacles in the used model CAIRDIO. For model validation, measurements from air-monitoring sites are used.
Lya Lugon, Jérémy Vigneron, Christophe Debert, Olivier Chrétien, and Karine Sartelet
Geosci. Model Dev., 14, 7001–7019, https://doi.org/10.5194/gmd-14-7001-2021, https://doi.org/10.5194/gmd-14-7001-2021, 2021
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The multiscale Street-in-Grid model is used to simulate black carbon (BC) concentrations in streets. To respect street-surface mass balance, particle resuspension is estimated with a new approach based on deposited mass. The contribution of resuspension is low, but non-exhaust emissions from tyre wear may largely contribute to BC concentrations. The impact of the two-way dynamic coupling between scales on BC concentrations varies depending on the street geometry and traffic emission intensity.
Yao Ge, Mathew R. Heal, David S. Stevenson, Peter Wind, and Massimo Vieno
Geosci. Model Dev., 14, 7021–7046, https://doi.org/10.5194/gmd-14-7021-2021, https://doi.org/10.5194/gmd-14-7021-2021, 2021
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This study reports the first evaluation of the global EMEP MSC-W ACTM driven by WRF meteorology, with a focus on surface concentrations and wet deposition of reactive N and S species. The model–measurement comparison is conducted both spatially and temporally, covering 10 monitoring networks worldwide. The statistics from the comprehensive evaluations presented in this study support the application of this model framework for global analysis of the budgets and fluxes of reactive N and SIA.
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Short summary
Land use and land cover change is a major contributor to climate change in Africa. Here we document deficiencies in how a weather model represents the land surface of Africa and how we modify a common land surface model to overcome these deficiencies. Our tests reveal that the default weather model does not accurately predict and transition the properties of different African biomes and growing cycles. This paper demonstrates that our modified model addresses these limitations.
Land use and land cover change is a major contributor to climate change in Africa. Here we...
