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A spatiodynamic model for assessing frost risk in south‐eastern Australia
Author(s) -
Bakar K. Shuvo,
Kokic Philip,
Jin Huidong
Publication year - 2015
Publication title -
journal of the royal statistical society: series c (applied statistics)
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.205
H-Index - 72
eISSN - 1467-9876
pISSN - 0035-9254
DOI - 10.1111/rssc.12103
Subject(s) - frost (temperature) , environmental science , climatology , climate change , greenhouse gas , grid , climate model , physical geography , sample (material) , meteorology , geography , geology , geodesy , oceanography , chemistry , chromatography
Summary Previous climate research concluded that causal influences which have contributed to changes in frost risk in south‐eastern Australia include greenhouse gas concentration, El‐Niño southern oscillation and other effects. Some of the climatic indices representing these effects have spatiotemporal misalignment and may have a spatially and temporally varying effect on observed data. Other indices are constructed from grid‐referenced physical models, which creates a point‐to‐area problem. To address these issues we use a spatiodynamic model, which comprises a blending of spatially varying and temporally dynamic parameters. For the data that we examine the model proposed performs well in out‐of‐sample validation compared with a spatiotemporal model.