scholarly journals Computational Benefit of GPU Optimization for the Atmospheric Chemistry Modeling

2018 ◽  
Vol 10 (8) ◽  
pp. 1952-1969 ◽  
Author(s):  
Jian Sun ◽  
Joshua S. Fu ◽  
John B. Drake ◽  
Qingzhao Zhu ◽  
Azzam Haidar ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Chemistry Modeling ◽  
Gpu Optimization

scholarly journals Effects of temperature on the heterogeneous oxidation of sulfur dioxide by ozone on calcium carbonate

2011 ◽  
Vol 11 (13) ◽  
pp. 6593-6605 ◽  
Author(s):  
L. Y. Wu ◽  
S. R. Tong ◽  
W. G. Wang ◽  
M. F. Ge
Keyword(s):  
Sulfur Dioxide ◽  
Atmospheric Chemistry ◽  
Ambient Pressure ◽  
Oxidation Reactions ◽  
Heterogeneous Oxidation ◽  
Fourier Transform Spectrometry ◽  
Different Temperatures ◽  
Chemistry Modeling ◽  
Sulfate Formation ◽  
Diffuse Reflectance Infrared

Abstract. The heterogeneous oxidation of sulfur dioxide by ozone on CaCO3 was studied as a function of temperature (230 to 298 K) at ambient pressure. Oxidation reactions were followed in real time using diffuse reflectance infrared Fourier transform spectrometry (DRIFTS) to obtain kinetic and mechanistic data. From the analysis of the spectral features, the formation of sulfate was identified on the surface in the presence of O3 and SO2 at different temperatures from 230 to 298 K. The results showed that the heterogeneous oxidation and the rate of sulfate formation were sensitive to temperature. An interesting stage-transition region was observed at temperatures ranging from 230 to 257 K, but it became ambiguous gradually above 257 K. The reactive uptake coefficients at different temperatures from 230 to 298 K were acquired for the first time, which can be used directly in atmospheric chemistry modeling studies to predict the formation of secondary sulfate aerosol in the troposphere. Furthermore, the rate of sulfate formation had a turning point at about 250 K. The sulfate concentration at 250 K was about twice as large as that at 298 K. The rate of sulfate formation increased with decreasing temperature at temperatures above 250 K, while there is a contrary temperature effect at temperatures below 250 K. The activation energy for heterogeneous oxidation at temperatures from 245 K to 230 K was determined to be 14.63 ± 0.20 kJ mol−1. A mechanism for the temperature dependence was proposed and the atmospheric implications were discussed.

scholarly journals Tailored reduced kinetic mechanisms for atmospheric chemistry modeling

2019 ◽  
Vol 213 ◽  
pp. 675-685 ◽  
Author(s):  
L.M.T. Joelsson ◽  
C. Pichler ◽  
E.J.K. Nilsson
Keyword(s):  
Atmospheric Chemistry ◽  
Kinetic Mechanisms ◽  
Chemistry Modeling

scholarly journals Quantifying uncertainties due to chemistry modeling – evaluation of tropospheric composition simulations in the CAMS model

2019 ◽  
Author(s):  
Vincent Huijnen ◽  
Andrea Pozzer ◽  
Joaquim Arteta ◽  
Guy Brasseur ◽  
Idir Bouarar ◽  
...  
Keyword(s):  
Atmospheric Chemistry ◽  
Model Uncertainty ◽  
Tropospheric Ozone ◽  
Trace Gas ◽  
Chemical Production ◽  
Chemistry Modeling ◽  
Gas Products ◽  
Forecasting System ◽  
Field Campaigns ◽  
Secondary Chemical

Abstract. We report on an evaluation of tropospheric ozone and its precursor gases in three atmospheric chemistry versions as implemented in ECMWF’s Integrated Forecasting System (IFS), referred to as IFS(CB05BASCOE), IFS(MOZART) and IFS(MOCAGE). While the model versions were forced with the same overall meteorology, emissions, transport and deposition schemes, they vary largely in their parameterizations describing atmospheric chemistry, including the organics degradation, heterogeneous chemistry and photolysis, as well as chemical solver. The model results from the three chemistry versions are compared against a range of aircraft field campaigns, ozone sondes and satellite observations, which provides quantification of the overall model uncertainty driven by the chemistry parameterizations. We find that they produce similar patterns and magnitudes for carbon monoxide (CO) and ozone (O3), as well as a range of non-methane hydrocarbons (NMHCs), with averaged differences for O3 (CO) within 10 % (20 %) throughout the troposphere. Most of the divergence in the magnitude of NMHCs can be explained by differences in OH concentrations, which can reach up to 50 % particularly at high latitudes. Also comparatively large discrepancies between model versions exist for NO2, SO2 and HNO3, which are strongly influenced by secondary chemical production and loss. Other, common biases in CO and NMHCs are mainly attributed to uncertainties in their emissions. This configuration of having various chemistry versions within IFS provides a quantification of uncertainties induced by chemistry modeling in the main CAMS global trace gas products beyond those that are constrained by data-assimilation.

WRF-GC: online two-way coupling of WRF and GEOS-Chem for regional atmospheric chemistry modeling

2020 ◽  
Author(s):  
Xu Feng ◽  
Haipeng Lin ◽  
Tzung-May Fu
Keyword(s):  
Atmospheric Chemistry ◽  
Transport Model ◽  
Surface Ozone ◽  
Eastern China ◽  
Cloud Microphysics ◽  
Chemical Transport Model ◽  
Meteorological Model ◽  
Ozone Concentrations ◽  
Chemistry Modeling ◽  
Nested Grid

<p>We developed the two-way version of the WRF-GC model, which is an online coupling of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the GEOS-Chem chemical transport model, for regional air quality and atmospheric chemistry modeling. WRF-GC allows the two parent models to be updated independently, such that WRF-GC can stay state-of-the-science. The meteorological fields and chemical variables are transferred between the two models in the coupler to simulate the feedback of gases and aerosols to meteorological processes via interactions with radiation and cloud microphysics. We used the WRF-GC model to simulate surface PM<sub>2.5</sub> concentrations over China during January 22 to 27, 2015 and compared the results to the outcomes from classic GEOS-Chem nested-grid simulations as well as the surface observations. For PM<sub>2.5</sub> simulations, both models were able to reproduce the spatiotemporal variations, but the WRF-GC (r = 0.68, bias = 29%) performing better than GEOS-Chem (r = 0.72, bias = 55%) especially over Eastern China. For ozone simulations, we found that including aerosol-chemistry-cloud-radiation interactions reduced the mean bias of simulated surface ozone concentrations from 34% to 29% compared to observed afternoon ozone concentrations. WRF-GC is computationally efficient, with the physical and chemical variables managed in distributed memory. At similar resolutions, WRF-GC simulations were three times faster than the classic GEOS-Chem nested-grid simulations, due to the more efficient transport algorithm and the MPI-based parallelization provided by the WRF software framework. We envision WRF-GC to become a powerful tool for advancing science, serving the public, and informing policy-making.</p>

scholarly journals WRF-GC (v1.0): online coupling of WRF (v3.9.1.1) and GEOS-Chem (v12.2.1) for regional atmospheric chemistry modeling – Part 1: Description of the one-way model

2020 ◽  
Vol 13 (7) ◽  
pp. 3241-3265 ◽  
Author(s):  
Haipeng Lin ◽  
Xu Feng ◽  
Tzung-May Fu ◽  
Heng Tian ◽  
Yaping Ma ◽  
...  
Keyword(s):  
Open Source ◽  
Atmospheric Chemistry ◽  
Message Passing ◽  
Message Passing Interface ◽  
Eastern China ◽  
State Variables ◽  
Meteorological Model ◽  
Chemistry Modeling ◽  
Meteorological Observations ◽  
Upper Level

Abstract. We developed the WRF-GC model, an online coupling of the Weather Research and Forecasting (WRF) mesoscale meteorological model and the GEOS-Chem atmospheric chemistry model, for regional atmospheric chemistry and air quality modeling. WRF and GEOS-Chem are both open-source community models. WRF-GC offers regional modellers access to the latest GEOS-Chem chemical module, which is state of the science, well documented, traceable, benchmarked, actively developed by a large international user base, and centrally managed by a dedicated support team. At the same time, WRF-GC enables GEOS-Chem users to perform high-resolution forecasts and hindcasts for any region and time of interest. WRF-GC uses unmodified copies of WRF and GEOS-Chem from their respective sources; the coupling structure allows future versions of either one of the two parent models to be integrated into WRF-GC with relative ease. Within WRF-GC, the physical and chemical state variables are managed in distributed memory and translated between WRF and GEOS-Chem by the WRF-GC coupler at runtime. We used the WRF-GC model to simulate surface PM2.5 concentrations over China during 22 to 27 January 2015 and compared the results to surface observations and the outcomes from a GEOS-Chem Classic nested-China simulation. Both models were able to reproduce the observed spatiotemporal variations of regional PM2.5, but the WRF-GC model (r=0.68, bias =29 %) reproduced the observed daily PM2.5 concentrations over eastern China better than the GEOS-Chem Classic model did (r=0.72, bias =55 %). This was because the WRF-GC simulation, nudged with surface and upper-level meteorological observations, was able to better represent the pollution meteorology during the study period. The WRF-GC model is parallelized across computational cores and scales well on massively parallel architectures. In our tests where the two models were similarly configured, the WRF-GC simulation was 3 times more efficient than the GEOS-Chem Classic nested-grid simulation due to the efficient transport algorithm and the Message Passing Interface (MPI)-based parallelization provided by the WRF software framework. WRF-GC v1.0 supports one-way coupling only, using WRF-simulated meteorological fields to drive GEOS-Chem with no chemical feedbacks. The development of two-way coupling capabilities, i.e., the ability to simulate radiative and microphysical feedbacks of chemistry to meteorology, is under way. The WRF-GC model is open source and freely available from http://wrf.geos-chem.org (last access: 10 July 2020).

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