Identification

Title

Localizing the impact of satellite radiance observations using a global group ensemble filter

Abstract

Assimilation of satellite radiances has been proven to have positive impacts on the forecast skill, especially for regions with sparse conventional observations. Localization is an essential component to effectively assimilate satellite radiances in ensemble Kalman filters with affordable ensemble sizes. However, localizing the impact of radiance observations is not straightforward, since their location and separation from grid point model variables are not well defined. A global group filter (GGF) is applied here to provide a theoretical estimate of vertical localization functions for radiance observations being assimilated for global numerical weather prediction. As an extension of the hierarchical ensemble filter, the GGF uses groups of climatological ensembles to provide an estimated localization function that reduces the erroneous increments due to ensemble correlation sampling error. Results from an idealized simulation with known background error covariances show that the GGF localization function is superior to the optimal Gaspari and Cohn (GC) localization function. When the GGF is applied to the AMSU-A radiances, it can provide different localization functions for different channels, which indicates the complexity and large computational cost of tuning the localization scales for radiance observations. The GC, GGF, and fitted GGF (FGGF) localization functions are compared using experiments with the NCEP GFS and the NOAA operational EnKF. Verifications relative to the conventional observations, AMSU-A radiances, and the ECMWF analyses show that the GGF and FGGF have smaller errors than GC except in the tropics, and the advantages of the GGF and FGGF persist through 120 h forecast lead time.

Resource type

document

Resource locator

Unique resource identifier

code

http://n2t.net/ark:/85065/d7vh5qgx

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

2016-06-01T00:00:00Z

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