Application and Evaluation of High-Resolution WRF-CMAQ with Simple Urban Parameterization

Pleim, Jonathan; Gilliam, Robert C.; Appel, Wyat; Godowitch, James M.; Wong, David C.; Pouliot, George; Ran, Limei

doi:10.1007/978-3-319-04379-1_80

Cited by 4 publications

(6 citation statements)

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“…The simulation is performed during a summer period from 1 July to 20 August 2012 for which the first 3 weeks are considered as spin-up. The model parameter setup is based on the COSMO-CLM model configurations of Brisson et al (2016b, a) and Prein et al (2015), employing convection-resolving climate simulations. The domain covers an area of 175 × 175 grid cells centred over Brussels with a horizontal grid spacing of 2.8 km resolution.…”

Section: Model Setupmentioning

confidence: 99%

“…During the past 3 decades, a vast amount of urban landsurface schemes have been developed. They enable the convection-permitting atmospheric models to resolve the heterogeneity of cities with applications for heat stress assessment and the development of urban climate adaptation and mitigation strategies (Prein et al, 2015). Even though their purpose of representing urban physics in land-surface schemes of atmospheric models is the same, intercomparison studies (Karsisto et al, 2016;Trusilova et al, 2016;Best and Grimmond, 2015;Grimmond et al, 2011) demonstrate that they differ in terms of modelling strategy, complexity, input parameters and applicability: on the one hand, the bulk schemes (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…An example here is the use of morphological data from CityGML (Gröger and Plümer, 2012) in urban climate modelling . Despite those initiatives, expansion and updates of urban canopy information remain challenging (Seto et al, 2011) at the convection-permitting scales, not to mention the prognoses from future land-use change scenarios (Prein et al, 2015). Consequently, the spatial detail, accuracy, coverage and variety in those urban canopy parameters data sets are limited, which is also clear from the substantial differences between the data sets (Schneider et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

“…2.4. The COSMO(-CLM) model without an urban land-surface scheme has already been evaluated extensively for numerical weather prediction at the convection-permitting scale (Baldauf et al, 2011) and regional climate modelling applications (Brisson et al, 2016b, a;Bucchignani et al, 2016;Prein et al, 2015;Thiery et al, 2015;Vanden Broucke et al, 2015;Fosser et al, 2014;Ban et al, 2014;Feldhoff et al, 2014;Dosio et al, 2014;Kotlarski et al, 2014;Lange et al, 2014;Van Weverberg et al, 2014;Panitz et al, 2013;Berg et al, 2012;Keuler et al, 2012, and references herein). Therefore, the evaluation (Sect.…”

Section: Introductionmentioning

confidence: 99%

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The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

et al. 2016

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Abstract. This paper presents the Semi-empirical URban canopY parametrization (SURY) v1.0, which bridges the gap between bulk urban land-surface schemes and explicit-canyon schemes. Based on detailed observational studies, modelling experiments and available parameter inventories, it offers a robust translation of urban canopy parameters – containing the three-dimensional information – into bulk parameters. As a result, it brings canopy-dependent urban physics to existing bulk urban land-surface schemes of atmospheric models. At the same time, SURY preserves a low computational cost of bulk schemes for efficient numerical weather prediction and climate modelling at the convection-permitting scales. It offers versatility and consistency for employing both urban canopy parameters from bottom-up inventories and bulk parameters from top-down estimates. SURY is tested for Belgium at 2.8 km resolution with the COSMO-CLM model (v5.0_clm6) that is extended with the bulk urban land-surface scheme TERRA_URB (v2.0). The model reproduces very well the urban heat islands observed from in situ urban-climate observations, satellite imagery and tower observations, which is in contrast to the original COSMO-CLM model without an urban land-surface scheme. As an application of SURY, the sensitivity of atmospheric modelling with the COSMO-CLM model is addressed for the urban canopy parameter ranges from the local climate zones of http://WUDAPT.org. City-scale effects are found in modelling the land-surface temperatures, air temperatures and associated urban heat islands. Recommendations are formulated for more precise urban atmospheric modelling at the convection-permitting scales. It is concluded that urban canopy parametrizations including SURY, combined with the deployment of the WUDAPT urban database platform and advancements in atmospheric modelling systems, are essential.

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Section: Model Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

et al. 2016

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“…During the non-O 3 season, the biases in predicting MDA8 O 3 for regions 4 and 6 are small and consistent with good daytime predictions. However, O 3 is still overpredicted during the nighttime in these regions, associated with the collapse of the boundary layer and difficulty in simulating its time and magnitude ( Hu et al, 2013 ; Cuchiara et al, 2014 ; Pleim et al, 2016 ).…”

Section: Evaluation Of Model Forecast Skillsmentioning

confidence: 99%

Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States

et al. 2021

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Abstract. As a candidate for the next-generation National Air Quality Forecast Capability (NAQFC), the meteorological forecast from the Global Forecast System with the new Finite Volume Cube-Sphere dynamical core (GFS–FV3) will be applied to drive the chemical evolution of gases and particles described by the Community Multiscale Air Quality modeling system. CMAQv5.0.2, a historical version of CMAQ, has been coupled with the North American Mesoscale Forecast System (NAM) model in the current operational NAQFC. An experimental version of the NAQFC based on the offline-coupled GFS–FV3 version 15 with CMAQv5.0.2 modeling system (GFSv15–CMAQv5.0.2) has been developed by the National Oceanic and Atmospheric Administration (NOAA) to provide real-time air quality forecasts over the contiguous United States (CONUS) since 2018. In this work, comprehensive region-specific, time-specific, and categorical evaluations are conducted for meteorological and chemical forecasts from the offline-coupled GFSv15–CMAQv5.0.2 for the year 2019. The forecast system shows good overall performance in forecasting meteorological variables with the annual mean biases of −0.2 ∘C for temperature at 2 m, 0.4 % for relative humidity at 2 m, and 0.4 m s−1 for wind speed at 10 m compared to the METeorological Aerodrome Reports (METAR) dataset. Larger biases occur in seasonal and monthly mean forecasts, particularly in spring. Although the monthly accumulated precipitation forecasts show generally consistent spatial distributions with those from the remote-sensing and ensemble datasets, moderate-to-large biases exist in hourly precipitation forecasts compared to the Clean Air Status and Trends Network (CASTNET) and METAR. While the forecast system performs well in forecasting ozone (O3) throughout the year and fine particles with a diameter of 2.5 µm or less (PM2.5) for warm months (May–September), it significantly overpredicts annual mean concentrations of PM2.5. This is due mainly to the high predicted concentrations of fine fugitive and coarse-mode particle components. Underpredictions in the southeastern US and California during summer are attributed to missing sources and mechanisms of secondary organic aerosol formation from biogenic volatile organic compounds (VOCs) and semivolatile or intermediate-volatility organic compounds. This work demonstrates the ability of FV3-based GFS in driving the air quality forecasting. It identifies possible underlying causes for systematic region- and time-specific model biases, which will provide a scientific basis for further development of the next-generation NAQFC.

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Intraurban NO₂ hotspot detection across multiple air quality products

Montgomery,

Daepp,

Abdin

et al. 2023

Environ. Res. Lett.

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High-resolution air quality data products have the potential to help quantify inequitable environmental exposures over space and across time by enabling the identification of hotspots, or areas that consistently experience elevated pollution levels relative to their surroundings. However, when different high-resolution data products identify different hotspots, the spatial sparsity of “gold-standard” regulatory observations leaves researchers, regulators, and concerned citizens without a means to differentiate signal from noise. This study compares NO2 hotspots detected within the city of Chicago, IL, USA using three distinct high-resolution (1.3 km) air quality products: (1) an interpolated product from Microsoft Research’s Project Eclipse – a dense network of over 100 low-cost sensors; (2) a two-way coupled WRF-CMAQ simulation; and (3) a down-sampled product using TropOMI satellite instrument observations. We use the Getis-Ord Gi * statistic to identify hotspots of NO2 and stratify results into high-, medium-, and low-agreement hotspots, including one consensus hotspot detected in all three datasets. Interrogating medium- and low-agreement hotspots offers insights into dataset discrepancies, such as sensor placement and model physics considerations, data retrieval caveats, and the potential for missing emission inventories. When treated as complements rather than substitutes, our work demonstrates that novel air quality products can enable researchers to address discrepancies in data products and can help regulators evaluate confidence in policy-relevant insights.

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Application and Evaluation of High-Resolution WRF-CMAQ with Simple Urban Parameterization

Cited by 4 publications

References 4 publications

The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States

Intraurban NO₂ hotspot detection across multiple air quality products

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Application and Evaluation of High-Resolution WRF-CMAQ with Simple Urban Parameterization

Cited by 4 publications

References 4 publications

The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer

Evaluation of the offline-coupled GFSv15–FV3–CMAQv5.0.2 in support of the next-generation National Air Quality Forecast Capability over the contiguous United States

Intraurban NO2 hotspot detection across multiple air quality products

Contact Info

Product

Resources

About

Intraurban NO₂ hotspot detection across multiple air quality products