澳门贵宾会,澳门贵宾会最新网站,vip登录

Welcome to Faculty of Mathematics and Statistics

Bayesian spatio-temporal models for frost risk analysis and projection
Author: Release time:2019-04-10 Number of clicks:

Title: Bayesian spatio-temporal models for frost risk analysis and projection

Speaker: Huidong Jin

Affiliation: Commonwealth Scientific and Industrial Research Organisation.The University of Sydney

Time: 2019-04-18 09:00-10:30

Venue: Room 201 Lecture Hall

Abstract:

Previous climate research concluded that causal influences which have contributed to changes in frost risk in south‐eastern Australia include greenhouse gas concentration, El‐Ni?o 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 climate models, which creates a point‐to‐area problem. To address these issues we propose 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. These models are later used to project how frost frequency changes in 2048, which provide evidences to form climate adaption strategies for winter crops.



Copyright ? 2013 isg. hubu.edu.cn All Rights Reserved.    

Address: No. 368, Friendship Avenue, Wuchang District, Wuhan, Hubei. Zip code: 430062

Email:stxy@hubu.edu.cn phone: 027-88662127