A comparative study of two-way and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous US: performance evaluation and impacts of chemistry–meteorology feedbacks on air quality
<p>The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more realistically represent the atmosphere by accounting for complex chemistry–meteorology feedbacks. In this study, we present a comparative analysis of two-way...
Guardado en:
| Autores principales: | , , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Copernicus Publications
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/d2aa28c0c53e44919a95d7d7ed138053 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | <p>The two-way coupled Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model has been developed to more
realistically represent the atmosphere by accounting for complex
chemistry–meteorology feedbacks. In this study, we present a comparative
analysis of two-way (with consideration of both aerosol direct and indirect
effects) and offline coupled WRF v3.4 and CMAQ v5.0.2 over the contiguous
US. Long-term (5 years from 2008 to 2012) simulations using WRF-CMAQ with both
offline and two-way coupling modes are carried out with anthropogenic
emissions based on multiple years of the U.S. National Emission Inventory
and chemical initial and boundary conditions derived from an advanced Earth
system model (i.e., a modified version of the Community Earth System
Model/Community Atmospheric Model). The comprehensive model evaluations show that both two-way WRF-CMAQ and WRF-only simulations perform well for major
meteorological variables such as temperature at 2 m, relative humidity at 2 m, wind speed at 10 m, precipitation (except for against the National Climatic Data Center data), and shortwave and longwave radiation. Both two-way and offline CMAQ also show good performance for ozone (<span class="inline-formula">O<sub>3</sub></span>) and fine particulate matter (PM<span class="inline-formula"><sub>2.5</sub></span>). Due to the consideration of aerosol
direct and indirect effects, two-way WRF-CMAQ shows improved performance
over offline coupled WRF and CMAQ in terms of spatiotemporal distributions
and statistics, especially for radiation, cloud forcing, <span class="inline-formula">O<sub>3</sub></span>, sulfate, nitrate, ammonium, elemental carbon, tropospheric <span class="inline-formula">O<sub>3</sub></span> residual, and column nitrogen dioxide (<span class="inline-formula">NO<sub>2</sub></span>). For example, the mean biases have been reduced by more than 10 W m<span class="inline-formula"><sup>−2</sup></span> for shortwave radiation and cloud radiative forcing and by more than 2 ppb for max 8 h
<span class="inline-formula">O<sub>3</sub></span>. However, relatively large biases still exist for cloud predictions,
some PM<span class="inline-formula"><sub>2.5</sub></span> species, and PM<span class="inline-formula"><sub>10</sub></span> that warrant follow-up studies to
better understand those issues. The impacts of chemistry–meteorological
feedbacks are found to play important roles in affecting regional air
quality in the US by reducing domain-average concentrations of carbon
monoxide (CO), <span class="inline-formula">O<sub>3</sub></span>, nitrogen oxide (<span class="inline-formula">NO<sub><i>x</i></sub></span>), volatile organic
compounds (VOCs), and PM<span class="inline-formula"><sub>2.5</sub></span> by 3.1 % (up to 27.8 %), 4.2 % (up to
16.2 %), 6.6 % (up to 50.9 %), 5.8 % (up to 46.6 %), and 8.6 %
(up to 49.1 %), respectively, mainly due to reduced radiation,
temperature, and wind speed. The overall performance of the two-way coupled
WRF-CMAQ model achieved in this work is generally good or satisfactory and
the improved performance for two-way coupled WRF-CMAQ should be considered
along with other factors in developing future model applications to inform
policy making.</p> |
|---|