Articles | Volume 11, issue 6
https://doi.org/10.5194/gmd-11-2333-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-11-2333-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
19 Jun 2018
Model evaluation paper |
| 19 Jun 2018
| 19 Jun 2018
The implementation of NEMS GFS Aerosol Component (NGAC) Version 2.0 for global multispecies forecasting at NOAA/NCEP – Part 2: Evaluation of aerosol optical thickness
Partha Sarathi Bhattacharjee
CORRESPONDING AUTHOR
I. M. Systems Group, INC. at NOAA/NWS National Centers for Environment Prediction, College Park, MD 20740, USA
Jun Wang
NOAA/NWS National Centers for Environment Prediction, College Park, MD 20740, USA
Cheng-Hsuan Lu
University of Albany, State University of New York, Albany, NY 12222, USA
Vijay Tallapragada
NOAA/NWS National Centers for Environment Prediction, College Park, MD 20740, USA
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Jun Wang, Partha S. Bhattacharjee, Vijay Tallapragada, Cheng-Hsuan Lu, Shobha Kondragunta, Arlindo da Silva, Xiaoyang Zhang, Sheng-Po Chen, Shih-Wei Wei, Anton S. Darmenov, Jeff McQueen, Pius Lee, Prabhat Koner, and Andy Harris
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The NEMS GFS Aerosol Component (NGAC) version 2.0 for global multispecies aerosol forecast was developed at NCEP. Additional sea salt, sulfate, organic carbon, and black carbon aerosol species were included. This implementation advanced the global aerosol forecast capability and made a step forward toward developing a global aerosol data assimilation system. The aerosol products from this system have been provided to meet the stakeholder's needs.
Cheng-Hsuan Lu, Arlindo da Silva, Jun Wang, Shrinivas Moorthi, Mian Chin, Peter Colarco, Youhua Tang, Partha S. Bhattacharjee, Shen-Po Chen, Hui-Ya Chuang, Hann-Ming Henry Juang, Jeffery McQueen, and Mark Iredell
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A GEFS-Aerosols simulation was conducted from 1 September 2019 to 30 September 2020 to evaluate the model performance of GEFS-Aerosols. The purpose of this study was to understand how aerosol chemical and physical processes affect ambient aerosol concentrations by placing aerosol wet deposition, dry deposition, reactions, gravitational deposition, and emissions into the aerosol mass balance equation.
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Geosci. Model Dev., 17, 117–141, https://doi.org/10.5194/gmd-17-117-2024, https://doi.org/10.5194/gmd-17-117-2024, 2024
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In numerical models, the turbulent exchanges of heat and momentum at the air–sea interface are not represented explicitly but with parameterisations depending on the surface parameters. A new parameterisation of turbulent fluxes (WASP) has been implemented in the surface model SURFEX v8.1 and validated on four case studies. It combines a close fit to observations including cyclonic winds, a dependency on the wave growth rate, and the possibility of being used in atmosphere–wave coupled models.
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This work highlights upgrades to SASKTRAN, a model that simulates sunlight interacting with the atmosphere to help measure trace gases. The upgrades were verified by detailed comparisons between different numerical methods. A case study was performed using SASKTRAN’s multidimensional capabilities, which found that ignoring horizontal variation in the atmosphere (a common practice in the field) can introduce non-negligible errors where there is snow or high pollution.
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Exposure to air pollution is one of the greatest risks to human health, and it is indoors, where we spend upwards of 90 % of our time, that our exposure is greatest. The INdoor CHEMical model in Python (INCHEM-Py) is a new, community-led box model that tracks the evolution and fate of atmospheric chemical pollutants indoors. We have shown the processes simulated by INCHEM-Py, its ability to model experimental data and how it may be used to develop further understanding of indoor air chemistry.
Willem E. van Caspel, David Simpson, Jan Eiof Jonson, Anna M. K. Benedictow, Yao Ge, Alcide di Sarra, Giandomenico Pace, Massimo Vieno, Hannah L. Walker, and Mathew R. Heal
Geosci. Model Dev., 16, 7433–7459, https://doi.org/10.5194/gmd-16-7433-2023, https://doi.org/10.5194/gmd-16-7433-2023, 2023
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Radiation coming from the sun is essential to atmospheric chemistry, driving the breakup, or photodissociation, of atmospheric molecules. This in turn affects the chemical composition and reactivity of the atmosphere. The representation of photodissociation effects is therefore essential in atmospheric chemistry modeling. One such model is the EMEP MSC-W model, for which a new way of calculating the photodissociation rates is tested and evaluated in this paper.
Jungmin Lee, Walter M. Hannah, and David C. Bader
Geosci. Model Dev., 16, 7275–7287, https://doi.org/10.5194/gmd-16-7275-2023, https://doi.org/10.5194/gmd-16-7275-2023, 2023
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Representing accurate land–atmosphere interaction processes is overlooked in weather and climate models. In this study, we propose three methods to represent land–atmosphere coupling in the Energy Exascale Earth System Model (E3SM) with the Multi-scale Modeling Framework (MMF) approach. In this study, we introduce spatially homogeneous and heterogeneous land–atmosphere interaction processes within the cloud-resolving model domain. Our 5-year simulations reveal only small differences.
Liangke Huang, Shengwei Lan, Ge Zhu, Fade Chen, Junyu Li, and Lilong Liu
Geosci. Model Dev., 16, 7223–7235, https://doi.org/10.5194/gmd-16-7223-2023, https://doi.org/10.5194/gmd-16-7223-2023, 2023
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The existing zenith tropospheric delay (ZTD) models have limitations such as using a single fitting function, neglecting daily cycle variations, and relying on only one resolution grid data point for modeling. This model considers the daily cycle variation and latitude factor of ZTD, using the sliding window algorithm based on ERA5 atmospheric reanalysis data. The ZTD data from 545 radiosonde stations and MERRA-2 atmospheric reanalysis data are used to validate the accuracy of the GGZTD-P model.
Jonathan J. Guerrette, Zhiquan Liu, Chris Snyder, Byoung-Joo Jung, Craig S. Schwartz, Junmei Ban, Steven Vahl, Yali Wu, Ivette Hernández Baños, Yonggang G. Yu, Soyoung Ha, Yannick Trémolet, Thomas Auligné, Clementine Gas, Benjamin Ménétrier, Anna Shlyaeva, Mark Miesch, Stephen Herbener, Emily Liu, Daniel Holdaway, and Benjamin T. Johnson
Geosci. Model Dev., 16, 7123–7142, https://doi.org/10.5194/gmd-16-7123-2023, https://doi.org/10.5194/gmd-16-7123-2023, 2023
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We demonstrate an ensemble of variational data assimilations (EDA) with the Model for Prediction Across Scales and the Joint Effort for Data assimilation Integration (JEDI) software framework. When compared to 20-member ensemble forecasts from operational initial conditions, those from 80-member EDA-generated initial conditions improve flow-dependent error covariances and subsequent 10 d forecasts. These experiments are repeatable for any atmospheric model with a JEDI interface.
Minjie Zheng, Hongyu Liu, Florian Adolphi, Raimund Muscheler, Zhengyao Lu, Mousong Wu, and Nønne L. Prisle
Geosci. Model Dev., 16, 7037–7057, https://doi.org/10.5194/gmd-16-7037-2023, https://doi.org/10.5194/gmd-16-7037-2023, 2023
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The radionuclides 7Be and 10Be are useful tracers for atmospheric transport studies. Here we use the GEOS-Chem to simulate 7Be and 10Be with different production rates: the default production rate in GEOS-Chem and two from the state-of-the-art beryllium production model. We demonstrate that reduced uncertainties in the production rates can enhance the utility of 7Be and 10Be as tracers for evaluating transport and scavenging processes in global models.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6833–6856, https://doi.org/10.5194/gmd-16-6833-2023, https://doi.org/10.5194/gmd-16-6833-2023, 2023
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In addition to the dominant role of the PBL scheme on the results of the meteorological field, many factors in the model are influenced by large uncertainties. This study focuses on the uncertainties that influence numerical simulation results (including horizontal resolution, vertical resolution, near-surface scheme, initial and boundary conditions, underlying surface update, and update of model version), hoping to provide a reference for scholars conducting research on the model.
Owen K. Hughes and Christiane Jablonowski
Geosci. Model Dev., 16, 6805–6831, https://doi.org/10.5194/gmd-16-6805-2023, https://doi.org/10.5194/gmd-16-6805-2023, 2023
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Atmospheric models benefit from idealized tests that assess their accuracy in a simpler simulation. A new test with artificial mountains is developed for models on a spherical earth. The mountains trigger the development of both planetary-scale and small-scale waves. These can be analyzed in dry or moist environments, with a simple rainfall mechanism. Four atmospheric models are intercompared. This sheds light on the pros and cons of the model design and the impact of mountains on the flow.
Zhongwei Luo, Yan Han, Kun Hua, Yufen Zhang, Jianhui Wu, Xiaohui Bi, Qili Dai, Baoshuang Liu, Yang Chen, Xin Long, and Yinchang Feng
Geosci. Model Dev., 16, 6757–6771, https://doi.org/10.5194/gmd-16-6757-2023, https://doi.org/10.5194/gmd-16-6757-2023, 2023
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This study explores how the variation in the source profiles adopted in chemical transport models (CTMs) impacts the simulated results of chemical components in PM2.5 based on sensitivity analysis. The impact on PM2.5 components cannot be ignored, and its influence can be transmitted and linked between components. The representativeness and timeliness of the source profile should be paid adequate attention in air quality simulation.
Wenxing Jia, Xiaoye Zhang, Hong Wang, Yaqiang Wang, Deying Wang, Junting Zhong, Wenjie Zhang, Lei Zhang, Lifeng Guo, Yadong Lei, Jizhi Wang, Yuanqin Yang, and Yi Lin
Geosci. Model Dev., 16, 6635–6670, https://doi.org/10.5194/gmd-16-6635-2023, https://doi.org/10.5194/gmd-16-6635-2023, 2023
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Most current studies on planetary boundary layer (PBL) parameterization schemes are relatively fragmented and lack systematic in-depth analysis and discussion. In this study, we comprehensively evaluate the performance capability of the PBL scheme in five typical regions of China in different seasons from the mechanism of the scheme and the effects of PBL schemes on the near-surface meteorological parameters, vertical structures of the PBL, PBL height, and turbulent diffusion.
William Rudisill, Alejandro Flores, and Rosemary Carroll
Geosci. Model Dev., 16, 6531–6552, https://doi.org/10.5194/gmd-16-6531-2023, https://doi.org/10.5194/gmd-16-6531-2023, 2023
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It is important to know how well atmospheric models do in mountains, but there are not very many weather stations. We evaluate rain and snow from a model from 1987–2020 in the Upper Colorado River basin against the available data. The model works rather well, but there are still some uncertainties in remote locations. We then use snow maps collected by aircraft, streamflow measurements, and some advanced statistics to help identify how well the model works in ways we could not do before.
Angel Liduvino Vara-Vela, Christoffer Karoff, Noelia Rojas Benavente, and Janaina P. Nascimento
Geosci. Model Dev., 16, 6413–6431, https://doi.org/10.5194/gmd-16-6413-2023, https://doi.org/10.5194/gmd-16-6413-2023, 2023
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A 1-year simulation of atmospheric CH4 over Europe is performed and evaluated against observations based on the TROPOspheric Monitoring Instrument (TROPOMI). A good general model–observation agreement is found, with discrepancies reaching their minimum and maximum values during the summer peak season and winter months, respectively. A huge and under-explored potential for CH4 inverse modeling using improved TROPOMI XCH4 data sets in large-scale applications is identified.
Zhaojun Tang, Zhe Jiang, Jiaqi Chen, Panpan Yang, and Yanan Shen
Geosci. Model Dev., 16, 6377–6392, https://doi.org/10.5194/gmd-16-6377-2023, https://doi.org/10.5194/gmd-16-6377-2023, 2023
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We designed a new framework to facilitate emission inventory updates in the adjoint of GEOS-Chem model. It allows us to support Harmonized Emissions Component (HEMCO) emission inventories conveniently and to easily add more emission inventories following future updates in GEOS-Chem forward simulations. Furthermore, we developed new modules to support MERRA-2 meteorological data; this allows us to perform long-term analysis with consistent meteorological data.
Rui Zhu, Zhaojun Tang, Xiaokang Chen, Xiong Liu, and Zhe Jiang
Geosci. Model Dev., 16, 6337–6354, https://doi.org/10.5194/gmd-16-6337-2023, https://doi.org/10.5194/gmd-16-6337-2023, 2023
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A single ozone (O3) tracer mode was developed in this work to build the capability of the GEOS-Chem model for rapid O3 simulation. It is combined with OMI and surface O3 observations to investigate the changes in tropospheric O3 in China in 2015–2020. The assimilations indicate rapid surface O3 increases that are underestimated by the a priori simulations. We find stronger increases in tropospheric O3 columns over polluted areas and a large discrepancy by assimilating different observations.
Ewa M. Bednarz, Ryan Hossaini, N. Luke Abraham, and Martyn P. Chipperfield
Geosci. Model Dev., 16, 6187–6209, https://doi.org/10.5194/gmd-16-6187-2023, https://doi.org/10.5194/gmd-16-6187-2023, 2023
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Development and performance of the new DEST chemistry scheme of UM–UKCA is described. The scheme extends the standard StratTrop scheme by including important updates to the halogen chemistry, thus allowing process-oriented studies of stratospheric ozone depletion and recovery, including impacts from both controlled long-lived ozone-depleting substances and emerging issues around uncontrolled, very short-lived substances. It will thus aid studies in support of future ozone assessment reports.
Shaohui Zhou, Chloe Yuchao Gao, Zexia Duan, Xingya Xi, and Yubin Li
Geosci. Model Dev., 16, 6247–6266, https://doi.org/10.5194/gmd-16-6247-2023, https://doi.org/10.5194/gmd-16-6247-2023, 2023
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The proposed wind speed correction model (VMD-PCA-RF) demonstrates the highest prediction accuracy and stability in the five southern provinces in nearly a year and at different heights. VMD-PCA-RF evaluation indices for 13 months remain relatively stable: the forecasting accuracy rate FA is above 85 %. In future research, the proposed VMD-PCA-RF algorithm can be extrapolated to the 3 km grid points of the five southern provinces to generate a 3 km grid-corrected wind speed product.
Simone Tilmes, Michael J. Mills, Yunqian Zhu, Charles G. Bardeen, Francis Vitt, Pengfei Yu, David Fillmore, Xiaohong Liu, Brian Toon, and Terry Deshler
Geosci. Model Dev., 16, 6087–6125, https://doi.org/10.5194/gmd-16-6087-2023, https://doi.org/10.5194/gmd-16-6087-2023, 2023
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We implemented an alternative aerosol scheme in the high- and low-top model versions of the Community Earth System Model Version 2 (CESM2) with a more detailed description of tropospheric and stratospheric aerosol size distributions than the existing aerosol model. This development enables the comparison of different aerosol schemes with different complexity in the same model framework. It identifies improvements compared to a range of observations in both the troposphere and stratosphere.
Dien Wu, Joshua L. Laughner, Junjie Liu, Paul I. Palmer, John C. Lin, and Paul O. Wennberg
Geosci. Model Dev., 16, 6161–6185, https://doi.org/10.5194/gmd-16-6161-2023, https://doi.org/10.5194/gmd-16-6161-2023, 2023
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To balance computational expenses and chemical complexity in extracting emission signals from tropospheric NO2 columns, we propose a simplified non-linear Lagrangian chemistry transport model and assess its performance against TROPOMI v2 over power plants and cities. Using this model, we then discuss how NOx chemistry affects the relationship between NOx and CO2 emissions and how studying NO2 columns helps quantify modeled biases in wind directions and prior emissions.
Jiangshan Zhu and Ross Noel Bannister
Geosci. Model Dev., 16, 6067–6085, https://doi.org/10.5194/gmd-16-6067-2023, https://doi.org/10.5194/gmd-16-6067-2023, 2023
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We describe how condensation and evaporation are included in the existing (otherwise dry) simplified ABC model. The new model (Hydro-ABC) includes transport of vapour and condensate within a dynamical core, and it transitions between these two phases via a micro-physics scheme. The model shows the development of an anvil cloud and excitation of atmospheric waves over many frequencies. The covariances that develop between variables are also studied together with indicators of convective motion.
Jiangyong Li, Chunlin Zhang, Wenlong Zhao, Shijie Han, Yu Wang, Hao Wang, and Boguang Wang
Geosci. Model Dev., 16, 6049–6066, https://doi.org/10.5194/gmd-16-6049-2023, https://doi.org/10.5194/gmd-16-6049-2023, 2023
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Photochemical box models, crucial for understanding tropospheric chemistry, face challenges due to slow computational efficiency with large chemical equations. The model introduced in this study, ROMAC, boosts efficiency by up to 96 % using an advanced atmospheric solver and an adaptive optimization algorithm. Moreover, ROMAC exceeds traditional box models in evaluating the impact of physical processes on pollutant concentrations.
Lina Vitali, Kees Cuvelier, Antonio Piersanti, Alexandra Monteiro, Mario Adani, Roberta Amorati, Agnieszka Bartocha, Alessandro D'Ausilio, Paweł Durka, Carla Gama, Giulia Giovannini, Stijn Janssen, Tomasz Przybyła, Michele Stortini, Stijn Vranckx, and Philippe Thunis
Geosci. Model Dev., 16, 6029–6047, https://doi.org/10.5194/gmd-16-6029-2023, https://doi.org/10.5194/gmd-16-6029-2023, 2023
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Air quality forecasting models play a key role in fostering short-term measures aimed at reducing human exposure to air pollution. Together with this role comes the need for a thorough assessment of the model performances to build confidence in models’ capabilities, in particular when model applications support policymaking. In this paper, we propose an evaluation methodology and test it on several domains across Europe, highlighting its strengths and room for improvement.
Wenfu Tang, Louisa K. Emmons, Helen M. Worden, Rajesh Kumar, Cenlin He, Benjamin Gaubert, Zhonghua Zheng, Simone Tilmes, Rebecca R. Buchholz, Sara-Eva Martinez-Alonso, Claire Granier, Antonin Soulie, Kathryn McKain, Bruce C. Daube, Jeff Peischl, Chelsea Thompson, and Pieternel Levelt
Geosci. Model Dev., 16, 6001–6028, https://doi.org/10.5194/gmd-16-6001-2023, https://doi.org/10.5194/gmd-16-6001-2023, 2023
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The new MUSICAv0 model enables the study of atmospheric chemistry across all relevant scales. We develop a MUSICAv0 grid for Africa. We evaluate MUSICAv0 with observations and compare it with a previously used model – WRF-Chem. Overall, the performance of MUSICAv0 is comparable to WRF-Chem. Based on model–satellite discrepancies, we find that future field campaigns in an eastern African region (30°E–45°E, 5°S–5°N) could substantially improve the predictive skill of air quality models.
Shuzhuang Feng, Fei Jiang, Zheng Wu, Hengmao Wang, Wei He, Yang Shen, Lingyu Zhang, Yanhua Zheng, Chenxi Lou, Ziqiang Jiang, and Weimin Ju
Geosci. Model Dev., 16, 5949–5977, https://doi.org/10.5194/gmd-16-5949-2023, https://doi.org/10.5194/gmd-16-5949-2023, 2023
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We document the system development and application of a Regional multi-Air Pollutant Assimilation System (RAPAS v1.0). This system is developed to optimize gridded source emissions of CO, SO2, NOx, primary PM2.5, and coarse PM10 on a regional scale via simultaneously assimilating surface measurements of CO, SO2, NO2, PM2.5, and PM10. A series of sensitivity experiments demonstrates the advantage of the “two-step” inversion strategy and the robustness of the system in estimating the emissions.
Megan A. Stretton, William Morrison, Robin J. Hogan, and Sue Grimmond
Geosci. Model Dev., 16, 5931–5947, https://doi.org/10.5194/gmd-16-5931-2023, https://doi.org/10.5194/gmd-16-5931-2023, 2023
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Cities' materials and forms impact radiative fluxes. We evaluate the SPARTACUS-Urban multi-layer approach to modelling longwave radiation, describing realistic 3D geometry statistically using the explicit DART (Discrete Anisotropic Radiative Transfer) model. The temperature configurations used are derived from thermal camera observations. SPARTACUS-Urban accurately predicts longwave fluxes, with a low computational time (cf. DART), but has larger errors with sunlit/shaded surface temperatures.
Daehyeon Han, Jungho Im, Yeji Shin, and Juhyun Lee
Geosci. Model Dev., 16, 5895–5914, https://doi.org/10.5194/gmd-16-5895-2023, https://doi.org/10.5194/gmd-16-5895-2023, 2023
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To identify the key factors affecting quantitative precipitation nowcasting (QPN) using deep learning (DL), we carried out a comprehensive evaluation and analysis. We compared four key factors: DL model, length of the input sequence, loss function, and ensemble approach. Generally, U-Net outperformed ConvLSTM. Loss function and ensemble showed potential for improving performance when they synergized well. The length of the input sequence did not significantly affect the results.
Fabien Margairaz, Balwinder Singh, Jeremy A. Gibbs, Loren Atwood, Eric R. Pardyjak, and Rob Stoll
Geosci. Model Dev., 16, 5729–5754, https://doi.org/10.5194/gmd-16-5729-2023, https://doi.org/10.5194/gmd-16-5729-2023, 2023
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The Quick Environmental Simulation (QES) tool is a low-computational-cost fast-response framework. It provides high-resolution wind and concentration information to study complex problems, such as spore or smoke transport, urban pollution, and air quality. This paper presents the particle dispersion model and its validation against analytical solutions and wind-tunnel data for a mock-urban setting. In all cases, the model provides accurate results with competitive computational performance.
Tao Wang, Hang Liu, Jie Li, Shuai Wang, Youngseob Kim, Yele Sun, Wenyi Yang, Huiyun Du, Zhe Wang, and Zifa Wang
Geosci. Model Dev., 16, 5585–5599, https://doi.org/10.5194/gmd-16-5585-2023, https://doi.org/10.5194/gmd-16-5585-2023, 2023
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This paper developed a two-way coupled module in a new version of a regional urban–street network model, IAQMS-street v2.0, in which the mass flux from streets to background is considered. Test cases are defined to evaluate the performance of IAQMS-street v2.0 in Beijing by comparing it with that simulated by IAQMS-street v1.0 and a regional model. The contribution of local emissions and the influence of on-road vehicle control measures on air quality are evaluated by using IAQMS-street v2.0.
Denis E. Sergeev, Nathan J. Mayne, Thomas Bendall, Ian A. Boutle, Alex Brown, Iva Kavčič, James Kent, Krisztian Kohary, James Manners, Thomas Melvin, Enrico Olivier, Lokesh K. Ragta, Ben Shipway, Jon Wakelin, Nigel Wood, and Mohamed Zerroukat
Geosci. Model Dev., 16, 5601–5626, https://doi.org/10.5194/gmd-16-5601-2023, https://doi.org/10.5194/gmd-16-5601-2023, 2023
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Three-dimensional climate models are one of the best tools we have to study planetary atmospheres. Here, we apply LFRic-Atmosphere, a new model developed by the Met Office, to seven different scenarios for terrestrial planetary climates, including four for the exoplanet TRAPPIST-1e, a primary target for future observations. LFRic-Atmosphere reproduces these scenarios within the spread of the existing models across a range of key climatic variables, justifying its use in future exoplanet studies.
Roland Eichinger, Sebastian Rhode, Hella Garny, Peter Preusse, Petr Pisoft, Aleš Kuchař, Patrick Jöckel, Astrid Kerkweg, and Bastian Kern
Geosci. Model Dev., 16, 5561–5583, https://doi.org/10.5194/gmd-16-5561-2023, https://doi.org/10.5194/gmd-16-5561-2023, 2023
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The columnar approach of gravity wave (GW) schemes results in dynamical model biases, but parallel decomposition makes horizontal GW propagation computationally unfeasible. In the global model EMAC, we approximate it by GW redistribution at one altitude using tailor-made redistribution maps generated with a ray tracer. More spread-out GW drag helps reconcile the model with observations and close the 60°S GW gap. Polar vortex dynamics are improved, enhancing climate model credibility.
Sanam N. Vardag and Robert Maiwald
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-192, https://doi.org/10.5194/gmd-2023-192, 2023
Revised manuscript accepted for GMD
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We use the atmospheric transport model GRAMM/GRAL in an inversion to estimate urban CO2 emissions on neighbourhood scale. We analyse the effect of varying number, precision and location of CO2 sensors for CO2 flux estimation. We further test the inclusion of co-emitted species and correlation into the inversion. The study showcases the general usefulness of GRAMM/GRAL in measurement network design.
François Roberge, Alejandro Di Luca, René Laprise, Philippe Lucas-Picher, and Julie Thériault
EGUsphere, https://doi.org/10.5194/egusphere-2023-1512, https://doi.org/10.5194/egusphere-2023-1512, 2023
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Our study addresses a challenge in dynamical downscaling using regional climate models, focusing on the lack of small-scale features near the boundaries. We introduce a method to identify this “spatial spin-up” in precipitation simulations. Results show spin-up distances up to 300 km, varying by season and driving variables. Double nesting with comprehensive variables (e.g. microphysical variables) offers advantages. Findings will help optimizing simulations for better climate projections.
Xueying Liu, Yuxuan Wang, Shailaja Wasti, Wei Li, Ehsan Soleimanian, James Flynn, Travis Griggs, Sergio Alvarez, John T. Sullivan, Maurice Roots, Laurence Twigg, Guillaume Gronoff, Timothy Berkoff, Paul Walter, Mark Estes, Johnathan W. Hair, Taylor Shingler, Amy Jo Scarino, Marta Fenn, and Laura Judd
Geosci. Model Dev., 16, 5493–5514, https://doi.org/10.5194/gmd-16-5493-2023, https://doi.org/10.5194/gmd-16-5493-2023, 2023
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With a comprehensive suite of ground-based and airborne remote sensing measurements during the 2021 TRacking Aerosol Convection ExpeRiment – Air Quality (TRACER-AQ) campaign in Houston, this study evaluates the simulation of the planetary boundary layer (PBL) height and the ozone vertical profile by a high-resolution (1.33 km) 3-D photochemical model Weather Research and Forecasting-driven GEOS-Chem (WRF-GC).
Tao Zheng, Sha Feng, Jeffrey Steward, Xiaoxu Tian, David Baker, and Martin Baxter
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-169, https://doi.org/10.5194/gmd-2023-169, 2023
Revised manuscript accepted for GMD
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The tangent linear and adjoint models have been successfully implemented in the MPAS-CO2 system, a milestone that has undergone rigorous accuracy testing. This development lays the groundwork for a global carbon flux data assimilation system, which offers the flexibility of high-resolution focus on specific areas while maintaining a coarser resolution elsewhere. This approach significantly reduces computational costs, thus perfectly suited for future CO2 geo-stationery and imager satellites.
Salvatore Larosa, Domenico Cimini, Donatello Gallucci, Saverio Teodosio Nilo, and Filomena Romano
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-171, https://doi.org/10.5194/gmd-2023-171, 2023
Revised manuscript accepted for GMD
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PyRTlib is an attractive educational software because it provides a flexible and user friendly tool to broadly simulate how electromagnetic radiation travels through the atmosphere as it interacts with atmospheric constituents (such as gases, aerosols and hydrometeors). PyRTlib is a so called Radiative Transfer model which are commonly used to simulate and understand remote sensing observations from ground-based, airborne or satellite instruments.
Stijn Van Leuven, Pieter De Meutter, Johan Camps, Piet Termonia, and Andy Delcloo
Geosci. Model Dev., 16, 5323–5338, https://doi.org/10.5194/gmd-16-5323-2023, https://doi.org/10.5194/gmd-16-5323-2023, 2023
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Precipitation collects airborne particles and deposits these on the ground. This process is called wet deposition and greatly determines how airborne radioactive particles (released routinely or accidentally) contaminate the surface. In this work we present a new method to improve the calculation of wet deposition in computer models. We apply this method to the existing model FLEXPART by simulating the Fukushima nuclear accident (2011) and show that it improves the simulation of wet deposition.
Thibaud Sarica, Alice Maison, Yelva Roustan, Matthias Ketzel, Steen Solvang Jensen, Youngseob Kim, Christophe Chaillou, and Karine Sartelet
Geosci. Model Dev., 16, 5281–5303, https://doi.org/10.5194/gmd-16-5281-2023, https://doi.org/10.5194/gmd-16-5281-2023, 2023
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A new version of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) is developed to represent heterogeneities of concentrations in streets. The street volume is discretized vertically and horizontally to limit the artificial dilution of emissions and concentrations. This new version is applied to street networks in Copenhagen and Paris. The comparisons to observations are improved, with higher concentrations of pollutants emitted by traffic at the bottom of the street.
Cited articles
Ben-Ami, Y., Koren, I., and Altaratz, O.: Patterns of North African dust
transport over the Atlantic: winter vs. summer, based on CALIPSO first year
data, Atmos. Chem. Phys., 9, 7867–7875, https://doi.org/10.5194/acp-9-7867-2009, 2009.
Benedetti, A., Morcrette, J.-J., Boucher, O., Dethof, A., Engelen, R. J.,
Fisher, M., Flentje, H., Huneeus, N., Jones, L., Kaiser, J. W., Kinne, S.,
Mangold, A., Razinger, M., Simmons, A. J., and Suttieet, M.: Aerosol analysis
and forecast in the European Centre for Medium Range Forecasts Integrated
Forecast System: 2. Data assimilation, J. Geophys. Res., 114, D13205,
https://doi.org/10.1029/2008JD011115, 2009.
Bhawar, R. L., Lee, W.-S., and Rahul, P. R. C.: Aerosol types and radiative
forcing estimates over East Asia, Atmos. Environ., 141, 532–541, 2016.
Campbell, J. R., Tackett, J. L., Reid, J. S., Zhang, J., Curtis, C. A., Hyer,
E. J., Sessions, W. R., Westphal, D. L., Prospero, J. M., Welton, E. J.,
Omar, A. H., Vaughan, M. A., and Winker, D. M.: Evaluating nighttime CALIOP
0.532 µm aerosol optical depth and extinction coefficient
retrievals, Atmos. Meas. Tech., 5, 2143–2160, https://doi.org/10.5194/amt-5-2143-2012,
2012.
Cesnulyte, V., Lindfors, A. V., Pitkänen, M. R. A., Lehtinen, K. E. J.,
Morcrette, J.-J., and Arola, A.: Comparing ECMWF AOD with AERONET
observations at visible and UV wavelengths, Atmos. Chem. Phys., 14, 593–608,
https://doi.org/10.5194/acp-14-593-2014, 2014.
Chin, M., Ginoux, P., Kinne, S., Torres, O., Holben, B. N., Duncan, B. N.,
Martin, R. V., Logan, J. A., Higurashi, A., and Nakajima, T.: Tropospheric
aerosol optical thickness from the GOCART model and comparisons with
satellite and sunphotometer measurements, J. Atmos. Sci., 59, 461–483, 2002.
Chin, M., Diehl, T., Ginoux, P., and Malm, W.: Intercontinental transport of
pollution and dust aerosols: implications for regional air quality, Atmos.
Chem. Phys., 7, 5501–5517, https://doi.org/10.5194/acp-7-5501-2007, 2007.
Ciren, P., Liu, H., Kondragunta, S., and Laszlo, I.: Adapting MODIS Dust Mask
Algorithm toSuomi NPP VIIRS for Air Quality Applications, AGU Fall Meeting
Abstracts, San Francisco, 11–16 December 2012.
Colarco, P., da Silva, A., Chin, M., and Diehl, T.: Online simulations of
global aerosol distributions in the NASA GEOS-4 model and comparisons to
satellite and ground-based aerosol optical depth, J. Geophys. Res., 115,
D14207, https://doi.org/10.1029/2009JD012820, 2010.
Darmenov, A. and Da Sila, A. M.: The Quick Fire Emissions Dataset (QFED) –
Documentation of versions 2.1, 2.2 and 2.4, NASA Technical Report Series on
Global Modeling and Data Assimilation, NASA/TM-2015-104606, Vol. 18, 211 pp.,
available at: http://gmao.gsfc.nasa.gov/pubs/tm/ (last access: November
2017), 2015.
Eck, T. F., Holben, B. N., Reid, J. S., Dubovik, O., Smirnov, A., O'Neill, N.
T., Slutsker, I., and Kinne, S.: The wavelength dependence of the optical
depth of biomass burning, urban and desert dust aerosols, J. Geophys. Res.,
104, 31333–31350, 1999.
Eskes, H., Huijnen, V., Arola, A., Benedictow, A., Blechschmidt, A.-M.,
Botek, E., Boucher, O., Bouarar, I., Chabrillat, S., Cuevas, E., Engelen, R.,
Flentje, H., Gaudel, A., Griesfeller, J., Jones, L., Kapsomenakis, J.,
Katragkou, E., Kinne, S., Langerock, B., Razinger, M., Richter, A., Schultz,
M., Schulz, M., Sudarchikova, N., Thouret, V., Vrekoussis, M., Wagner, A.,
and Zerefos, C.: Validation of reactive gases and aerosols in the MACC global
analysis and forecast system, Geosci. Model Dev., 8, 3523–3543,
https://doi.org/10.5194/gmd-8-3523-2015, 2015.
Field, R. D., van der Werf, G. R., Fanin, T., Fetzer, E. J., Fuller, R.,
Jethva, H., Levy, R., Livesey, N. J., Luo, M., Torres, O., and Worden, H. M.:
Indonesian fire activity and smoke pollution in 2015 show persistent
nonlinear sensitivity to El-Nino induced drought, P. Natl. Acad. Sci. USA,
113, 9204–9209, 2016.
Fordham, D. A., Wigley, T. M., Watts, M. J., and Brook, B. W.: Strengthening
forecasts of climate change impacts with multi-model ensemble averaged
projections using MAGICC/SCENGEN 5.3, Ecography, 35, 4–8, 2012.
Forster, P., Ramaswamy, V., Artaxo, P., Berntsen, T., Betts, R., Fahey, D.
W., Haywood, J., Lean, J., Lowe, D. C., Myhre, G., Nganga, J., Prinn, R.,
Raga, G., Schultz, M., and Van Dorland, R.: Changes in Atmospheric
Constituents and in Radiative Forcing, in: Climate Change 2007: The Physical
Science Basis. Contribution of Working Group I to the Fourth Assessment
Report of the Intergovernmental Panel on Climate Change, edited by: Solomon,
S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K. B., Tignor, M.,
and Miller, H. L., Cambridge University Press, Cambridge, United Kingdom and
New York, NY, USA, 2007.
Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs,
L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K.,
Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da
Silva, A. M., Gu, W., Kim, G., Koster, R., Lucchesi, D. Merkova, J. E.,
Nielsen, G. Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S.
D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for
Research and Applications, Version 2 (MERRA-2), J. Climate, 30, 5419–5454,
https://doi.org/10.1175/JCLI-D-16-0758.1, 2017.
Generoso, S., Bréon, F.-M., Balkanski, Y., Boucher, O., and Schulz, M.:
Improving the seasonal cycle and interannual variations of biomass burning
aerosol sources, Atmos. Chem. Phys., 3, 1211–1222,
https://doi.org/10.5194/acp-3-1211-2003, 2003.
Ghan, S. J., Liu, X., Easter, R. C., Zaveri, R., Rasch, P. J., Yoon, J., and
Eaton, B.: Toward a minimal representation of aerosols in climate models:
Comparative decomposition of aerosol direct, semidirect and indirect
radiative forcing, J. Climate, 25, 6461–6476, 2012.
Ginoux, P., Chin, M., Tegen, I., Prospero, J. M., Holben, B., Dubovik, O.,
and Lin, S.-J.: Sources and global distributions of dust aerosols simulated
with the GOCART model, J. Geophys. Res., 106, 20255–20273, 2001.
Hansen, J., Sato, M., and Ruedy, R.: Radiative forcing and climate response,
J. Geophys. Res., 102, 6831–6864, https://doi.org/10.1029/96JD03436, 1997.
Haywood, J. and Boucher, O.: Estimates of the direct and indirect radiative
forcing due to tropospheric aerosols: A review, Rev. Geophys., 38, 513–543,
https://doi.org/10.1029/1999RG000078, 2000.
Haywood, J. M., Allan, R. P., Culverwell, I., Slingo, T., Milton, S.,
Edwards, J., and Clerbaux, N.: Can desert dust explain the outgoing longwave
radiation anomaly over the Sahara during July 2003?, J. Geophys. Res., 110,
D05105, https://doi.org/10.1029/2004JD005232, 2005.
Holben, B. N., Eck, T. F., Slutsker, I., Tanré, D., Buis, J. P., Setzer,
A., Vermote, E., Reagan, J. A., Kaufman, Y. J., Nakajima, T., Lavenu, F.,
Jankowiak, I., and Smirnov, A.: AERONET – A Federated instrument network and
data archive for aerosol characterization, Remote Sens. Environ., 66, 1–16,
1998.
Hsu, N. C., Jeong, M.-J., Bettenhausen, C., Sayer, A. M., Hansell, R.,
Seftor, C. S., Huang, J., and Tsay, S.-C.: Enhanced Deep Blue aerosol
retrieval algorithm: The second generation, J. Geophys. Res.-Atmos., 118,
9296–9315, https://doi.org/10.1002/jgrd.50712, 2013.
Jackson, J., Liu, H., Laszlo, I., Kondragunta, S., Remer, L. A., Huang, J.,
and Huang, H.-C.: Suomi-NPP VIIRS Aerosol Algorithms and Data Products, J.
Geophys. Res., 118, 12673–12689, https://doi.org/10.1002/2013jd020449, 2013.
Karyampudi, V.: Validation of the Saharan dust plume conceptual model using
Lidar, Meteosat, and ECMWF Data, B. Am. Meteorol. Soc., 80, 1045–1075, 1999.
Kaufman, Y. J., Koren, I., Remer, L. A., Tanré, D., Ginoux, P., and Fan,
S.: Dust transport and deposition observed from the Terra-Moderate Resolution
Imaging Spectroradiometer (MODIS) spacecraft ovet the Atlantic Ocean,
J. Geophs. Res., 110, D10S12, https://doi.org/10.1029/2003JD004436, 2005.
Kedia, S., Ramachandran, S., Holben, B. N., and Tripathi, S. N.:
Quantification of aerosol type, and sources of aerosols over the
Indo-Gangetic Plain, Atmos. Environ., 98, 607–619, 2014.
Kroll, J. H. and Seinfeld, J. H.: Chemistry of secondary organic aerosol:
formation and evolution of low-volatility organics in the atmosphere, Atmos.
Environ., 42, 3293–3624, 2008.
Laszlo, I. and Liu, H.: EPS Aerosol Optical Depth (AOD) Algorithm Theoretical
Basis Document, VIIRS ATBD, JPSS internal note, available at:
https://www.star.nesdis.noaa.gov/jpss/documents/ATBD/ATBD_EPS_Aerosol_AOD_v3.0.1.pdf
(last access: March 2018), 2016.
Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia,
F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and
ocean, Atmos. Meas. Tech., 6, 2989–3034, https://doi.org/10.5194/amt-6-2989-2013,
2013.
Lee, P., McQueen, J., Stajner, I., Huang, J., Pan, L., Tong, D., Kim, H.,
Tang, Y., Kondragunta, S., Ruminski, M., Lu, S., Rogers, E., Saylor, R.,
Shafran, P., Huang, H., Gorline, J., Upadhayay, S., and Artz, R.: NAQFC
developmental forecast guidance for Fine particulate matter (PM2.5),
Weather Forecast., 32, 407–421, 2017.
Liu, H., Remer, L. A., Huang, J., Huang, H.-C., Kondragunta, S., Laszlo, I.,
Oo, M., and Jackson, J. M.: Preliminary Evaluation of Suomi-NPP VIIRS Aerosol
Optical Thickness, J. Geophys. Res., 119, 3942–3962,
https://doi.org/10.1002/2013jd020360, 2013.
Lohmann, U. and Feichter, J.: Global indirect aerosol effects: a review,
Atmos. Chem. Phys., 5, 715–737, https://doi.org/10.5194/acp-5-715-2005, 2005.
Lu, C.-H., da Silva, A., Wang, J., Moorthi, S., Chin, M., Colarco, P., Tang,
Y., Bhattacharjee, P. S., Chen, S.-P., Chuang, H.-Y., Juang, H.-M. H.,
McQueen, J., and Iredell, M.: The implementation of NEMS GFS Aerosol
Component (NGAC) Version 1.0 for global dust forecasting at NOAA/NCEP,
Geosci. Model Dev., 9, 1905–1919, https://doi.org/10.5194/gmd-9-1905-2016, 2016.
Lu, C.-H., Wei, S.-W., Zhang, X., Kondragunta, S., Chen, S.-P., Zhao, Q.,
Wang, J., Bhattacharjee, P., and McQueen, J. T.: The utilization of satellite
observations for improving Global aerosol forecasting, Asia Oceania Geosc.
Soc. Conference, Singapore, 11 August 2017.
Lynch, P., Reid, J. S., Westphal, D. L., Zhang, J., Hogan, T. F., Hyer, E.
J., Curtis, C. A., Hegg, D. A., Shi, Y., Campbell, J. R., Rubin, J. I.,
Sessions, W. R., Turk, F. J., and Walker, A. L.: An 11-year global gridded
aerosol optical thickness reanalysis (v1.0) for atmospheric and climate
sciences, Geosci. Model Dev., 9, 1489–1522, https://doi.org/10.5194/gmd-9-1489-2016,
2016.
Mallet, M., Dubovik, O., Nabat, P., Dulac, F., Kahn, R., Sciare, J., Paronis,
D., and Léon, J. F.: Absorption properties of Mediterranean aerosols
obtained from multi-year ground-based remote sensing observations, Atmos.
Chem. Phys., 13, 9195–9210, https://doi.org/10.5194/acp-13-9195-2013, 2013.
Mangold, A., De Backer, H., De Paepe, B., Dewitte, S., Chiapello, I.,
Derimian, Y., Kacenelenbogen, M., Léon, J.-F., Huneeus, N., Schulz, M.,
Ceburnis, D., O'Dowd, C., Flentje, H., Kinne, S., Benedetti, A., Morcrette,
J.-J., and Boucher, O.: Aerosol analysis and forecast in the European Centre
for Medium Range Weather Forecasts Integrated Forecast System: 3. Evaluation
by means of case studies, J. Geophys. Res., 116, D03302,
https://doi.org/10.1029/2010JD014864, 2011.
Menon, S., Hansen, J., Nazarenko, L., and Luo, Y.: Climate effects of black
carbon aerosols in China and India, Science, 297, 2250–2253,
https://doi.org/10.1126/science.1075159, 2002.
Meehl, G. A., Covey, C., Delworth, T., Latif, M., McAvaney, B., Mitchell, J.
F., Stouffer, R. J., and Taylor, K. E.: The WCRP CMIP3 multimodel dataset –
A new era in climate change research, B. Am. Meteorol. Soc, 88, 1383–1394,
2007.
Morcrette, J.-J., Boucher, O., Jones, L., Salmond, D., Bechtold, P.,
Beljaars, A., Benedetti, A., Bonet, A., Kaiser, J. W., Razinger, M., Schulz,
M., Serrar, S., Simmons, A. J., Sofiev, M., Suttie, M., Tompkins, A. M., and
Untch, A.: Aerosol analysis and forecast in the European centre for
medium-range weather forecasts integrated forecast system: forward modeling,
J. Geophys. Res., 114, D06206, https://doi.org/10.1029/2008JD011235, 2009.
Mulcahy, J. P., Walters, D. N., Bellouin, N., and Milton, S. F.: Impacts of
increasing the aerosol complexity in the Met Office global numerical weather
prediction model, Atmos. Chem. Phys., 14, 4749–4778,
https://doi.org/10.5194/acp-14-4749-2014, 2014.
Ramanathan, V., Crutzen, P. J., Lelieveld, J., Mitra, A. P., Althausen, D.,
Andersons, J., Andreae, M. O., Cantrell, W., Cass, G. R., Chung, C. E.,
Clarke, A. D., Coakley, J. A., Collins, W. D., Conant, W. C., Dulac, F.,
Heintzenberg, J., Heymsfield, A. J., Holben, B., Howell, S., Hudson, J.,
Jayaraman, A., Kiehl, J. T., Krishnamurti, T. N., Lubin, D., McFarquhar, G.,
Novakov, T., Ogren, J. A., Podgorny, I. A., Prather, K., Priestley, K.,
Prospero, J. M., Quinn, P. K., Rajeev, K., Rasch, P., Rupert, S., Sadourny,
R., Satheesh, S. K., Shaw, G. E., Sheridan, P., and Valero, F. P. J.: Indian
Ocean Experiment: An integrated analysis of the climate forcing and effects
of the great Indo-Asian haze, J. Geophys. Res., 106, 28371–28398,
https://doi.org/10.1029/2001JD900133, 2001.
Rappold, A. G., Stone, S. L., Cascio, W. E., Neas, L. M., Kilaru, V. J.,
Carraway, M. S., Szykman, J. J., Ising, A., Cleve, W. E., Meredith, J. T.,
Vaughan-Batten, H., Deyneka, L., and Devlin, R. B.: Peat bog wildfire smoke
exposure in rural North Carolina is associated with cardiopulmonary emergency
department visits assessed through syndromic surveillance, Environ. Health
Persp., 119, 1415–1420, 2011.
Reid, J., Benedetti, A., Colarco, P. R., and Hansen, J. A.: International
operational aerosol observability work-shop, B. Am. Meteorol. Soc., 92,
ES21–ES24, https://doi.org/10.1175/2010BAMS3183.1, 2011.
Sayer, A. M., Hsu, N. C., Bettenhausen, C., and Jeong, M.-J.: Validation and
uncertainty estimates for MODIS Collection 6 “Deep Blue” aerosol data,
J. Geophys. Res.-Atmos., 118, 7864–7872, https://doi.org/10.1002/jgrd.50600, 2013.
Sayer, A. M., L. A. Munchak, N. C. Hsu, R. C. Levy, C. Bettenhausen, and
M.-J. Jeong: MODIS Collection 6 aerosol products: Comparison between Aqua's
e-Deep blue, dark target and “merged” data sets and usage recommendations,
J. Geophys. Res.-Atmos., 119, 13965–989, 2014.
Sekiyama, T. T., Tanaka, T. Y., Shimizu, A., and Miyoshi, T.: Data
assimilation of CALIPSO aerosol observations, Atmos. Chem. Phys., 10, 39–49,
https://doi.org/10.5194/acp-10-39-2010, 2010.
Sessions, W. R., Reid, J. S., Benedetti, A., Colarco, P. R., da Silva, A.,
Lu, S., Sekiyama, T., Tanaka, T. Y., Baldasano, J. M., Basart, S., Brooks, M.
E., Eck, T. F., Iredell, M., Hansen, J. A., Jorba, O. C., Juang, H.-M. H.,
Lynch, P., Morcrette, J.-J., Moorthi, S., Mulcahy, J., Pradhan, Y., Razinger,
M., Sampson, C. B., Wang, J., and Westphal, D. L.: Development towards a
global operational aerosol consensus: basic climatological characteristics of
the International Cooperative for Aerosol Prediction Multi-Model Ensemble
(ICAP-MME), Atmos. Chem. Phys., 15, 335–362, https://doi.org/10.5194/acp-15-335-2015,
2015.
Shalaby, A., Rappenglueck, B., and Eltahir, E. A. B.: The climatology of dust
aerosol over the arabian peninsula, Atmos. Chem. Phys. Discuss., 15,
1523–1571, https://doi.org/10.5194/acpd-15-1523-2015, 2015.
Smirnov, A., Holben, B. N., Eck, T. F., Dubovik, O., and Slutsker, I.: Cloud
Screening and quality control algorithms for the AERONET database, Remote
Sens. Environ., 73, 337–349, 2000.
Takemura, T., Okamoto, H., Maruyama, Y., Numaguti, A., Higurashi, A., and
Nakajima, T.: Global three-dimensional simulation of aerosol optical
thickness distribution of various origins, J. Geophys. Res., 105,
17853–17873, 2000.
Tanaka, T. Y., Orito, K., Sekiyama, T. T., Shibata, K., Chiba, M., and
Tanaka, H.: MASINGAR, a global tropospheric aerosol chemical transport model
coupled with MRI/JMA98 GCM: model description, Pap. Meteorol. Geophys., 53,
119–138, 2003.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, J. Geophys. Res., 106, 7183–7192, https://doi.org/10.1029/2000JD900719, 2001.
Wang, J., Bhattacharjee, P. S., Tallapragada, V., Lu, C.-H., Kondragunta, S.,
da Silva, A., Zhang, X., Chen, S.-P., Wei, S.-W., Darmenov, A. S., McQueen,
J., Lee, P., Koner, P., and Harris, A.: The implementation of NEMS GFS
Aerosol Component (NGAC) Version 2.0 for global multispecies forecasting at
NOAA/NCEP – Part 1: Model descriptions, Geosci. Model Dev., 11, 2315–2332,
https://doi.org/10.5194/gmd-11-2315-2018, 2018.
Wei, S.-W., Zhao, Q., Chen, S. P., Wang, J., Bhattacharjee, P. S.,
Kondragunta, S., McQueen, J.., and Lu, S.: Improving NCEP global aerosol
forecasts by data assimilation of VIIRS aerosol products, Fifth AMS Symposium
on the Joint Center for Satellite Data Assimilation, Seattle, WA, USA, 23–26
January 2017, American Meteorological Society, 2017.
Westphal, D. L., Curtis, C. A., Liu, M., and Walker, A. L.: Operational
aerosol and dust storm forecasting, in: WMO/GEO expert meeting on an
international sand and dust storm warning system, IOP conference series:
Earth and Environmental Science, 7, 012007,
https://doi.org/10.1088/1755-1307/7/1/012007, 2009.
Yoo, H., Li, Z., Hou, Y.-T., Lord, S., Weng, F., and Barker, H. W.: Diagnosis
and testing of low-level cloud parameterizations for the NCEP/GFS model using
satellite and ground-based measurements, Clim. Dynam., 41, 1595–1613, 2013.
Yu, H., Chin, M., Yuan, T., Bian, H., Remer, L. A., Prospero, J. M., Omar,
A., Winker, D., Yang, Y., Zhang, Y., Zhang, Z., and Zhao, C.: The fertilizing
role of African dust in the Amazon rainforest: A first multiyear assessment
based on data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
Observations, Geophys. Res. Lett., 42, 1984–1991,
https://doi.org/10.1002/2015GL063040, 2015.
Zhang, J., Reid, J. S., Westphal, D. L., Baker, N. L., and Hyer, E. J.: A
system for operational aerosol optical depth data assimilation over global
oceans, J. Geophys. Res., 113, D10208, https://doi.org/10.1029/2007JD009065, 2008.
Zhang, X., Kondragunta, S., Ram, J., Schmidt, C., and Huang, H.-C.:
Near-real-time global biomass burning emissions product from geostationary
satellite constellation, J. Geophys. Res., 117, D14201,
https://doi.org/10.1029/2012JD017459, 2012.
Zhao, T. X., Stowe, L. L., Smirnov, A., Crosby, D., Sapper, J., and McClain,
C. R.: Development of a global validation package for satellite oceanic
aerosol optical thickness retrieval based on AERONET observations and its
application to NOAA/NESDIS operational aerosol retrievals, J. Atmos. Sci.,
59, 294–312, 2002.
Short summary
National Center for Environmental Prediction (NCEP) at NOAA recently upgraded their operational global aerosol forecast model from dust-only in version 1 to five species (dust, sea salt, black and organic carbon) of aerosols in version 2. In this work, we have validated the newly implemented aerosol model (NGACv2) which forecast at every 3 h up to 5 days against ground and satellite observations and other available model simulations.
National Center for Environmental Prediction (NCEP) at NOAA recently upgraded their operational...
