On-Line Chemistry Within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

Grell, Georg; Fast, Jerome D.; Gustafson, William I.; Peckham, Steven E.; McKeen, S. A.; Salzmann, Marc; Freitas, Saulo R.

doi:10.1007/978-3-642-13980-2_3

Cited by 10 publications

(7 citation statements)

References 133 publications

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“…Aerosols can affect climate directly through absorption and scattering and indirectly through the modification of cloud formation and evolution. Despite an increasing number of applications of online‐coupled models [e.g., Grell et al , 2005, 2011a; Fast et al , 2006; Zhang et al , 2010a, 2010b, 2012a; Grell and Baklanov , 2011; Forkel et al , 2011; Yu et al , 2011], the feedbacks from aerosols to boundary meteorology and radiation cannot typically be simulated in most current three‐dimensional (3‐D) models that do not couple meteorology and chemistry online. Those feedbacks, however, are important because they can have a profound impact on climate state and sensitivity to anthropogenic influences [e.g., Jacobson , 2002; Chung and Seinfeld , 2005; H. Liao et al , 2009] and future climate changes may be affected by improved air quality [ Brasseur and Roeckner , 2005].…”

Section: Introductionmentioning

confidence: 99%

Development and initial application of the global‐through‐urban weather research and forecasting model with chemistry (GU‐WRF/Chem)

Zhang¹,

Karamchandani²,

Glotfelty³

et al. 2012

J. Geophys. Res.

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[1] A unified model framework with online-coupled meteorology and chemistry and consistent model treatments across spatial scales is required to realistically simulate chemistry-aerosol-cloud-radiation-precipitation-climate interactions. In this work, a global-through-urban WRF/Chem model (i.e., GU-WRF/Chem) has been developed to provide such a unified model framework to simulate these important interactions across a wide range of spatial scales while reducing uncertainties from the use of offline-coupled model systems with inconsistent model treatments. Evaluation against available observations shows that GU-WRF/Chem is capable of reproducing observations with comparable or superior fidelity than existing mesoscale models. The net effect of atmospheric aerosols is to decrease shortwave and longwave radiation, NO 2 photolysis rate, near-surface temperature, wind speed at 10-m, planetary boundary layer height, and precipitation as well as to increase relative humidity at 2-m, aerosol optical depths, column cloud condensation nuclei, cloud optical thickness, and cloud droplet number concentrations at all scales. As expected, such feedbacks also change the abundance and lifetimes of chemical species through changing radiation, atmospheric stability, and the rates of many meteorologically-dependent chemical and microphysical processes. The use of higher resolutions in progressively nested domains from the global to local scale notably improves the model performance of some model predictions (especially for chemical predictions) and also captures spatial variability of aerosol feedbacks that cannot be simulated at a coarser grid resolution. Simulated aerosol, radiation, and cloud properties exhibit small-to-high sensitivity to various nucleation and aerosol activation parameterizations. Representing one of the few unified global-through-urban models, GU-WRF/Chem can be applied to simulate air quality and its interactions with meteorology and climate and to quantify the impact of global change on urban/regional air quality across various spatial scales.Citation: Zhang, Y., P. Karamchandani, T. Glotfelty, D. G. Streets, G. Grell, A. Nenes, F. Yu, and R. Bennartz (2012), Development and initial application of the global-through-urban weather research and forecasting model with chemistry (GU-WRF/Chem),

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Section: Introductionmentioning

confidence: 99%

Development and initial application of the global‐through‐urban weather research and forecasting model with chemistry (GU‐WRF/Chem)

Zhang¹,

Karamchandani²,

Glotfelty³

et al. 2012

J. Geophys. Res.

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“…WRF/Chem v3.4 contains two hard coded gas phase chemical mechanisms: the second generation Regional Acid Deposition Model mechanism (RADM2) (Stockwell et al, 1990), and the Carbon Bond Mechanism version Z (CBM-Z) (Zaveri and Peters, 1999). The kinetic preprocessor (KPP, Salzmann, 2008;Grell et al, 2011b) is also used in WRF-Chem, which allows many additional gas phase chemical mechanisms. The aerosol modules available in WRFV3.4 are the Modal Aerosol Dynamics Model for Europe (MADE) (Ackermann et al, 1998) with the secondary organic aerosol (SOA) model (SORGAM) of Schell et al (2001) (referred to as MADE/SORGAM), and the Model for Simulating Aerosol Interactions and Chemistry (MOSAIC) (Zaveri et al, 2008).…”

Section: Inclusion Of Volcanic Emissions In Wrf-chemmentioning

confidence: 99%

Inclusion of ash and SO<sub>2</sub> emissions from volcanic eruptions in WRF-Chem: development and some applications

et al. 2013

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Abstract. We describe a new functionality within the Weather Research and Forecasting (WRF) model with coupled Chemistry (WRF-Chem) that allows simulating emission, transport, dispersion, transformation and sedimentation of pollutants released during volcanic activities. Emissions from both an explosive eruption case and a relatively calm degassing situation are considered using the most recent volcanic emission databases. A preprocessor tool provides emission fields and additional information needed to establish the initial three-dimensional cloud umbrella/vertical distribution within the transport model grid, as well as the timing and duration of an eruption. From this source condition, the transport, dispersion and sedimentation of the ash cloud can be realistically simulated by WRF-Chem using its own dynamics and physical parameterization as well as data assimilation. Examples of model applications include a comparison of tephra fall deposits from the 1989 eruption of Mount Redoubt (Alaska) and the dispersion of ash from the 2010 Eyjafjallajökull eruption in Iceland. Both model applications show good coincidence between WRF-Chem and observations.

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“…All of these models are capable of resolving meso-scale features, but nonetheless are of regional to continental coverage and computationally viable for operational forecasting application. The selected models are: (a) The European Center for Medium range Weather Forecast meteorology model (ECMWF) coupled with CHIMERE [1,2]; (b) The Stanford Gas-Aerosol-TranspOrt-Radiation chemistry model (GATOR)-coupled with the General-Circulation-Mesoscale-and-Ocean-Model (GCMOM) [3][4][5]; (c) The Canadian Global Environmental Multi-scale meteorology model (GEM) coupled with the Modelling Air quality and CHemistry in 15 km horizontal grid resolution (MACH15) [6]; (d) The Weather Research and Forecasting (WRF)-Advanced Research WRF (ARW) dynamic core meteorology model coupled with Chemistry (Chem) model [7,8]; and (e) the WRF-Non-hydrostatic Meso-scale Model (NMM) dynamic core meteorology model [9] coupled with the Community Multi-scale Air Quality model (CMAQ) [10,11].…”

Section: Introductionmentioning

confidence: 99%

“…There are many science module upgrades throughout its decade of service [6] the WRF-Chem model was built by Grell et al [19] as a fully online meteorological and tropo-spheric chemistry model. It has since added many state-of-science upgrades [8]; and the WRF-NMM-CMAQ model was a successor of the National Center for Environmental Prediction (NCEP) ETA-CMAQ model that provided incrementally enlarging geographical coverage for the U.S. between 2004 until 2006. WRF-NNM-CMAQ replaced ETA-CMAQ since 2007 [9,10].…”

Section: Introductionmentioning

confidence: 99%

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

Lee

Ngan

2011

Atmosphere

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A consensus among many Air Quality (AQ) modelers is that planetary boundary layer processes are the most influential processes for surface concentrations of air pollutants. Due to the many uncertainties intrinsically embedded in the parameterization of these processes, parameter optimization is often employed to determine an optimal set or range of values of the sensitive parameters. In this review study, we focus on the two of the most important physical processes: turbulent mixing and dry deposition. An emphasis was put on surveying AQ models that have been proven to resolve meso-scale features and cover a large geographical area, such as large regional, continental, or trans-continental boundary extents. Five AQ models were selected. Four of the models were run in real-time operational forecasting settings for continental scale AQ. The models use various forms of level 2.5 closure algorithms to calculate turbulent mixing. Tuning and parameter optimization has been used to tailor these algorithms to better suit their AQ models which are typically comprised of a coupled chemistry and meteorology model. Longer forecasts and long lead-times are inevitably under increasing demand for these models. Land Surface Models that have the capability for soil moisture and temperature data assimilation will have an advantage to constrain the key variables that govern the partitioning of surface sensible and latent heat fluxes and thus attain the potential to perform better in longer forecasts than those models that do not have this capability. Dry deposition velocity is a OPEN ACCESSAtmosphere 2011, 2 465 very significant model parameter that governs a major surface exchange activity. An exploratory study has been conducted to see the upper bound of roughness length in the similarity equation for aerodynamic resistance.

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On-Line Chemistry Within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

Cited by 10 publications

References 133 publications

Development and initial application of the global‐through‐urban weather research and forecasting model with chemistry (GU‐WRF/Chem)

Development and initial application of the global‐through‐urban weather research and forecasting model with chemistry (GU‐WRF/Chem)

Inclusion of ash and SO<sub>2</sub> emissions from volcanic eruptions in WRF-Chem: development and some applications

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

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On-Line Chemistry Within WRF: Description and Evaluation of a State-of-the-Art Multiscale Air Quality and Weather Prediction Model

Cited by 10 publications

References 133 publications

Development and initial application of the global‐through‐urban weather research and forecasting model with chemistry (GU‐WRF/Chem)

Development and initial application of the global‐through‐urban weather research and forecasting model with chemistry (GU‐WRF/Chem)

Inclusion of ash and SO&lt;sub&gt;2&lt;/sub&gt; emissions from volcanic eruptions in WRF-Chem: development and some applications

Coupling of Important Physical Processes in the Planetary Boundary Layer between Meteorological and Chemistry Models for Regional to Continental Scale Air Quality Forecasting: An Overview

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Inclusion of ash and SO<sub>2</sub> emissions from volcanic eruptions in WRF-Chem: development and some applications