Identification

Title

Exploring bounded nonparametric ensemble filter impacts on sea ice Data Assimilation

Abstract

Standard ensemble Kalman filter algorithms have Gaussian assumptions built into their formulations. Gaussian assumptions make these algorithms susceptible to biased solutions when prior distributions or likelihoods are non-Gaussian. Sea ice poses a unique application for testing ensemble Kalman filter algorithms because sea ice observations are nonnegative and doubly bounded, leading to non-Gaussian distributions. Four different ensemble Kalman filter algorithms are tested in observing system simulation experiments (OSSEs) to evaluate their ability to update different sea ice fields: 1) ensemble adjustment Kalman filter, 2) ensemble Kalman filter with perturbed observations, 3) rank histogram filter (RHF), and 4) bounded RHF. The bounded RHF, an extension of the standard RHF, was recently developed to properly respect bounds (singly and doubly bounded) on distributions in observation space. Compared to the other ensemble Kalman filter algorithms, the bounded RHF pulls the ensemble closer to the true value and respects the bounds. Most notably during winter when sea ice concentration is near its upper bound of one, the bounded RHF provides updates in the observation space that are more uniformly distributed around zero compared to the other algorithms. One common finding among all ensemble Kalman filter algorithms tested is the overdispersive nature of sea ice thickness. This was linked back to the method used to create the initial ensemble spread for our free forecasts in our OSSEs. Improving our ability to assimilate sea ice observations within our coupled Earth system modeling frameworks will help improve future projections of the climate and processes related to the cryosphere.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.net/ark:/85065/d7s186x7

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

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South bounding latitude

Temporal reference

Temporal extent

Begin position

End position

Dataset reference date

date type

publication

effective date

2025-04-01T00:00:00Z

Frequency of update

Quality and validity

Lineage

Conformity

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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