Identification

Title

Particle filter data assimilation for ubiquitous unstable trajectories of two-dimensional three-state cellular automata

Abstract

Estimating the states of error-growing (sensitive to initial state) cellular automata (CA) based on noisy imperfect data is challenging due to the discreteness of the dynamical system. This paper proposes particle filter (PF)–based data assimilation (DA) for three-state error-growing CA and demonstrates that the PF-based DA can predict the present and future state even with noisy and sparse observations. The error-growing CA used in the present study comprised a competitive system of land , grass , and sheep . To the best of the authors’ knowledge, this is the first application of DA to such CA. The performance of DA for different observation sets was evaluated in terms of observational error, density, and frequency, and a series of sensitivity tests of the internal parameters in the DA was conducted. The inflation and localization parameters were tuned according to the sensitivity tests.

Resource type

document

Resource locator

Unique resource identifier

code

https://n2t.net/ark:/85065/d7sx6jjn

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

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Temporal reference

Temporal extent

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Dataset reference date

date type

publication

effective date

2024-12-01T00:00:00Z

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Use constraints

<span style="font-family:Arial;font-size:10pt;font-style:normal;" data-sheets-root="1">Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</span>

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