Identification

Title

Comparison of CAMS and CMAQ analyses of surface-level PM2.5 and O3 over the conterminous United States (CONUS)

Alternative title(s)

d315001

Abstract

In this study, we compare the performance of the analysis time series over the period of August 2020 to December 2021 at EPA AirNow stations for both PM2.5 and O3 from raw Copernicus Atmosphere Monitoring Service (CAMS) reanalyses (CAMS RA Raw), raw CAMS near real-time forecasts (CAMS FC Raw), raw near real-time Community Multi-scale Air Quality (CMAQ) forecasts (CMAQ FC Raw), bias-corrected CAMS forecasts (CAMS FC BC), and bias-corrected CMAQ forecasts (CMAQ FC BC). This 17-month period spans two wildfire seasons, to assess model analysis performance in high-end AQ events. In addition to determining the best-performing gridded product, this process allows us to benchmark the performance of CMAQ forecasts against other global datasets (CAMS reanalysis and forecasts). For both PM2.5 and O3, the bias correction algorithm employed here greatly improved upon the raw model time series, and CMAQ FC BC was the best-performing model analysis time series, having the lowest RMSE, smallest bias error, and largest critical success index at multiple thresholds.

Resource type

dataset

Resource locator

https://rda.ucar.edu/datasets/d315001/

protocol: https

applicationProfile: browser

name: Dataset Description

description: Related Link

function: information

https://rda.ucar.edu/datasets/d315001/dataaccess/

protocol: https

applicationProfile: browser

name: Data Access

description: Related Link

function: download

Unique resource identifier

code

codeSpace

Dataset language

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

climatologyMeteorologyAtmosphere

Keywords

Keyword set

keyword value

dataset

originating controlled vocabulary

title

reference date

date type

revision

effective date

2014-10-16

Keyword set

keyword value

AirNow > EPA AirNow Program

OPERATIONAL MODELS

originating controlled vocabulary

title

reference date

date type

revision

effective date

2024-09-20

Keyword set

keyword value

EARTH SCIENCE > ATMOSPHERE > AIR QUALITY > PARTICULATE MATTER (PM 2.5)

EARTH SCIENCE > ATMOSPHERE > AIR QUALITY > TROPOSPHERIC OZONE

originating controlled vocabulary

title

reference date

date type

revision

effective date

2024-10-04

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

2020-08

End position

2021-12

Dataset reference date

date type

publication

effective date

2024-08-26

Frequency of update

notPlanned

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Creative Commons Attribution 4.0 International License

Limitations on public access

None

Responsible organisations

Responsible party

organisation name

UCAR/NCAR - Research Data Archive

full postal address

National Center for Atmospheric Research

CISL/DECS

P.O. Box 3000

Boulder

80307

U.S.A.

telephone number

(303)-497-1833

facsimile number

303-497-1291

email address

chifan@ucar.edu

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact

organisation name

NCAR Research Data Archive

full postal address

National Center for Atmospheric Research

CISL/DECS

P.O. Box 3000

Boulder

80307

U.S.A.

facsimile number

303-497-1291

email address

rdahelp@ucar.edu

web address

https://rda.ucar.edu/

name: NCAR Research Data Archive

description: The Research Data Archive (RDA), managed by the Data Engineering and Curation Section (DECS) of the Computational and Information Systems Laboratory (CISL) at NCAR, contains a large and diverse collection of meteorological and oceanographic observations, operational and reanalysis model outputs, and remote sensing datasets to support atmospheric and geosciences research, along with ancillary datasets, such as topography/bathymetry, vegetation, and land use.

function: downlaod

responsible party role

pointOfContact

Metadata date

2024-10-08T20:05:03Z

Metadata language