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Multi-site statistical downscaling of precipitation using generalized hierarchical linear models: a case study of the imperilled Lake Urmia basin

Abbasian, M. S ; Sharif University of Technology | 2020

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  1. Type of Document: Article
  2. DOI: 10.1080/02626667.2020.1810255
  3. Publisher: Taylor and Francis Ltd , 2020
  4. Abstract:
  5. A downscaling model capable of explaining the temporal and spatial variability of regional hydroclimatic variables is essential for reliable climate change studies and impact assessments. This study proposes a novel statistical approach based on generalized hierarchical linear model (GHLM) to downscale precipitation from the outputs of general circulation models (GCMs) at multiple sites. GHLM partitions the total variance of precipitation into within- and between-site variability allowing for transferring information between sites to develop a regional downscaling model. The methodology is demonstrated by downscaling precipitation using the outputs of eight GCMs in Lake Urmia basin in northwestern Iran. Multi-model ensemble simulations are merged and bias-corrected using Bayesian model averaging and equidistant quantile mapping, respectively. The results of this study show projected declining trends in precipitation resulting in approximately 11.2% and 15.3% decrease during 2060–2080 compared to the historical period of 1985–2005 considering representative concentration pathways (RCPs) 4.5 and 8.5, respectively. © 2020 IAHS
  6. Keywords:
  7. Bayesian model averaging ; Climate change impact ; Downscaling ; Hierarchical linear model ; Lake Urmia ; Precipitation ; Bayesian networks ; Climate change ; Lakes ; General circulation model ; Hierarchical linear modeling ; Hierarchical linear models ; Hydroclimatic variables ; Regional downscaling ; Statistical downscaling ; Temporal and spatial variability ; Climate models ; Bayesian analysis ; Concentration (composition) ; Hierarchical system ; Numerical model ; Precipitation (climatology) ; Spatial variation ; Temporal variation ; Iran
  8. Source: Hydrological Sciences Journal ; Volume 65, Issue 14 , 2020 , Pages 2466-2481
  9. URL: https://www.tandfonline.com/doi/abs/10.1080/02626667.2020.1810255