Identification

Title

A novel ensemble design for probabilistic predictions of fine particulate matter over the contiguous United States (CONUS)

Abstract

This study examines the benefit of using a dynamical ensemble for 48 hr deterministic and probabilistic predictions of near-surface fine particulate matter (PM2.5) over the contiguous United States (CONUS). Our ensemble design captures three key sources of uncertainties in PM(2.5)modeling including meteorology, emissions, and secondary organic aerosol (SOA) formation. Twenty-four ensemble members were simulated using the Community Multiscale Air Quality (CMAQ) model during January, April, July, and October 2016. The raw ensemble mean performed better than most of the ensemble members but underestimated the observed PM(2.5)over the CONUS with the largest underestimation over the western CONUS owing to negative PM(2.5)bias in nearly all the members. To improve the ensemble performance, we calibrated the raw ensemble using model output statistics (MOS) and variance deficit methods. The calibrated ensemble captured the diurnal and day-to-day variability in observed PM(2.5)very well and exhibited almost zero mean bias. The mean bias in the calibrated ensemble was reduced by 90-100% in the western CONUS and by 40-100% in other parts of the CONUS, compared to the raw ensemble in all months. The corresponding reduction in root-mean-square error (RMSE) was 13-40%. The calibrated ensemble also showed 30% improvement in the RMSE and spread matching compared to the raw ensemble. We have also shown that a nine-member ensemble based on combinations of three meteorological and three anthropogenic emission scenarios can be used as a smaller subset of the full ensemble when sufficient computational resources are not available in the operational setting.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.org/ark:/85065/d72j6g44

codeSpace

Dataset language

eng

Spatial reference system

code identifying the spatial reference system

Classification of spatial data and services

Topic category

geoscientificInformation

Keywords

Keyword set

keyword value

Text

originating controlled vocabulary

title

Resource Type

reference date

date type

publication

effective date

2016-01-01T00:00:00Z

Geographic location

West bounding longitude

East bounding longitude

North bounding latitude

South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2020-08-27T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

Data format

name of format

version of format

Constraints related to access and use

Constraint set

Use constraints

Limitations on public access

None

Responsible organisations

Responsible party

contact position

OpenSky Support

organisation name

UCAR/NCAR - Library

full postal address

PO Box 3000

Boulder

80307-3000

email address

opensky@ucar.edu

web address

http://opensky.ucar.edu/

name: homepage

responsible party role

pointOfContact

Metadata on metadata

Metadata point of contact