Modelling daily rainfall with climatological predictors: Poisson-gamma generalized linear modelling approach-Reference-Cited by-同舟云学术

Modelling daily rainfall with climatological predictors: Poisson-gamma generalized linear modelling approach

Published:2016-06-10 Issue:3 Volume:37 Page:1391-1399
ISSN:0899-8418
Container-title:International Journal of Climatology
language:en
Short-container-title:Int. J. Climatol.

Author:

Yunus Rossita M.¹²,Hasan Masud M.²,Razak Nuradhiathy A.³,Zubairi Yong Z.⁴,Dunn Peter K.⁵

Affiliation:

1. Institute of Mathematical Sciences; University of Malaya; Kuala Lumpur Malaysia

2. National Centre for Groundwater Research and Training, Fenner School of Environment and Society; Australian National University; Canberra Australia

3. Institute of Graduate Studies; University of Malaya; Kuala Lumpur Malaysia

4. Centre for Foundation Studies in Science; University of Malaya; Kuala Lumpur Malaysia

5. School of Health and Sport Sciences; University of the Sunshine Coast; Sippy Downs Australia

Funder

Universiti Malaya

Publisher

Wiley

Subject

Atmospheric Science

Reference41 articles.

1. Forecasting local daily precipitation patterns in a climate change scenario;Abaurrea;Clim. Res.,2005

2. Managing Malaysian water resources development;Azhar;J. Kesihatan Masyarakat,2000

3. On the choice of the temporal aggregation level for statistical downscaling of precipitation;Buishand;J. Clim.,2004

4. Analysis of rainfall variability using generalized linear models: a case study from the west of Ireland;Chandler;Water Resour. Res.,2002

5. Fitting optimum order of Markov chain models for daily rainfall occurrences in Peninsular Malaysia;Deni;Theor. Appl. Climatol.,2009

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The effect of El Niño-Southern Oscillation (ENSO) indices on monthly rainfall distributions in East Malaysia;AIP Conference Proceedings;2024

2. Deep Learning of Extreme Rainfall Patterns Using Enhanced Spatial Random Sampling With Pattern Recognition;Advanced Hydroinformatics;2023-12-15

3. Inferring heavy tails of flood distributions through hydrograph recession analysis;Hydrology and Earth System Sciences;2023-12-14

4. Modelling occurrence and quantity of longitudinal semicontinuous data simultaneously with nonparametric unobserved heterogeneity;Canadian Journal of Statistics;2023-12-09

5. Tweedie models for Malaysia rainfall simulations with seasonal variabilities;Journal of Water and Climate Change;2023-09-28