Identification

Title

A dynamic blending scheme to mitigate largeâ€�scale bias in regional models

Abstract

Several blending methods have been developed in dynamic downscaling and rapid cycled data assimilation. Blending the large-scale part of the global model (GM) analysis or forecast has led to improvement in regional model (RM) simulations. However, in previous studies the blended waveband of the GM has generally been determined using a fixed, arbitrarily chosen cutoff wave number. Here we introduce a new dynamic blending (DB) scheme with a dynamic cutoff wave number computed according to the spectral characteristics of GM forecast quality and the spectral distribution of errors in the RM. The DB scheme is described and applied to eight-day summertime and seven-day wintertime cycled Weather Research and Forecasting Model forecasts over a regional domain in the continental United States. The scheme can determine a cutoff wave number with significant temporal variations. The temporal variation results from the error growth property of the RM and has a clear diurnal oscillation, suggesting that fewer (more) GM waves should be introduced into the RM at noon (night). The cutoff wave number difference between the two periods indicates seasonal variation of the cutoff wave number with larger day-to-day change in winter. Comparison among no blending experiment, two fixed wave number blending experiments, and two DB experiments with and without vertically varying cutoff wave number suggests that the DB scheme with vertically averaged but temporally varying cutoff wave number results in less model bias and less disturbance to the RM dynamic balance. By reducing the forecast background error, the DB scheme can potentially provide improved first guess for a rapid-update-cycle weather forecast system.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7dn488t

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

2020-03-01T00:00:00Z

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