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Showing results 3 to 8 of 8
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Issue Date
Title
Author(s)
2020-08-01
Machine learning-based integration of large-scale climate drivers can improve the forecast of seasonal rainfall probability in Australia
Feng, P
;
Wang, B
;
Liu, DL
;
Ji, F
;
Niu, X
;
Ruan, H
;
Shi, L
;
Yu, Q
2019-10-01
Modelling and evaluating the impacts of climate change on three major crops in south-eastern Australia using regional climate model simulations
Wang, B
;
Liu, DL
;
Evans, JP
;
Ji, F
;
Waters, C
;
Macadam, I
;
Feng, P
;
Beyer, K
2019-01-01
Propagation of climate model biases to biophysical modelling can complicate assessments of climate change impact in agricultural systems
Liu, DL
;
Wang, B
;
Evans, J
;
Ji, F
;
Waters, C
;
Macadam, I
;
Yang, X
;
Beyer, K
2023-11
Structural complexity biases vegetation greenness measures.
Zeng, Y
;
Hao, D
;
Park, T
;
Zhu, P
;
Huete, A
;
Myneni, R
;
Knyazikhin, Y
;
Qi, J
;
Nemani, RR
;
Li, F
;
Huang, J
;
Gao, Y
;
Li, B
;
Ji, F
;
Köhler, P
;
Frankenberg, C
;
Berry, JA
;
Chen, M
2020-07
Using large-scale climate drivers to forecast meteorological drought condition in growing season across the Australian wheatbelt.
Feng, P
;
Wang, B
;
Luo, J-J
;
Liu, DL
;
Waters, C
;
Ji, F
;
Ruan, H
;
Xiao, D
;
Shi, L
;
Yu, Q
2018-11-15
Using multi-model ensembles of CMIP5 global climate models to reproduce observed monthly rainfall and temperature with machine learning methods in Australia
Wang, B
;
Zheng, L
;
Liu, DL
;
Ji, F
;
Clark, A
;
Yu, Q