Evidence map›Paper›PMID 34367521›Full record

ArticleGeoscientific model development2021

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.

Xiaoyang Chen, Yang Zhang, Kai Wang, Daniel Tong, Pius Lee, Youhua Tang, Jianping Huang, Patrick C Campbell, Jeff Mcqueen, Havala O T Pye and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Geoscientific model development, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Xiaoyang ChenDepartment of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA.
Yang ZhangDepartment of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA.
Kai WangDepartment of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA.
Daniel TongDepartment of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA 22030, USA.
Pius LeeAir Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD 20740, USA.
Youhua TangCenter for Spatial Information Science and System, George Mason University, Fairfax, VA 22030, USA.
Jianping HuangNational Oceanic and Atmospheric Administration/National Centers for Environmental Prediction/Environmental Modeling Center, College Park, MD 20740, USA.
Patrick C CampbellCenter for Spatial Information Science and System, George Mason University, Fairfax, VA 22030, USA.
Jeff McqueenNational Oceanic and Atmospheric Administration/National Centers for Environmental Prediction/Environmental Modeling Center, College Park, MD 20740, USA.
Havala O T PyeOffice of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Benjamin N MurphyOffice of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
Daiwen KangOffice of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.

Funding

Intramural EPA EPA999999
6 · The paper itself

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

Identifiers

PMID34367521
PMCPMC8340608

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.