Identification

Title

Seasonal prediction potential for springtime dustiness in the United States

Abstract

Most dust forecast models focus on short, subseasonal lead times, that is, 3 to 6 days, and the skill of seasonal prediction is not clear. In this study we examine the potential of seasonal dust prediction in the United States using an observation-constrained regression model and key variables predicted by a seasonal prediction model developed at National Oceanic and Atmospheric Administration Geophysical Fluid Dynamics Laboratory, the Forecast-Oriented Low Ocean Resolution (FLOR) model. Our method shows skillful predictions of spring dustiness 3 to 6 months in advance. It is found that the regression model explains about 71% of the variances of dust event frequency over the Great Plains and 63% over the southwestern United States in March-May from 2004 to 2016 using predictors from FLOR initialized on 1 December. Variations in springtime dustiness are dominated by springtime climatic factors rather than wintertime factors. Findings here will help development of a seasonal dust prediction system and hazard prevention.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7ms3wvr

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

2019-08-16T00:00:00Z

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

Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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

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 date

2023-08-18T18:24:16.457215

Metadata language

eng; USA