Bayesian Multi-Scale Spatio-Temporal Modeling of Precipitation in the Indus Watershed-Reference-Cited by-同舟云学术

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Bayesian Multi-Scale Spatio-Temporal Modeling of Precipitation in the Indus Watershed

Published:2019-08-14 Issue: Volume:7 Page:
ISSN:2296-6463
Container-title:Frontiers in Earth Science
language:
Short-container-title:Front. Earth Sci.

Author:

Christensen Michael F.,Heaton Matthew J.,Rupper Summer,Reese C. Shane,Christensen William F.

Funder

National Aeronautics and Space Administration

Publisher

Frontiers Media SA

Subject

General Earth and Planetary Sciences

Reference38 articles.

1. Gaussian predictive process models for large spatial data sets;Banerjee;J. R. Stat. Soc. Ser. B (Stat. Methodol.),2008

2. Can climate trends be calculated from reanalysis data;Bengtsson;J. Geophys. Res.,2004

3. Brief communication: glaciers in the Hunza catchment (Karakoram) have been nearly in balance since the 1970s;Bolch;Cryosphere,2017

4. Explaining the gibbs sampler;Casella;Am. Stat.,1992

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1. Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System;Earth System Dynamics;2023-02-08

2. Distributional Validation of Precipitation Data Products with Spatially Varying Mixture Models;Journal of Agricultural, Biological and Environmental Statistics;2022-09-24

3. Grand Challenges of Hydrologic Modeling for Food-Energy-Water Nexus Security in High Mountain Asia;Frontiers in Water;2021-10-05

4. Precipitation response to aerosol–radiation and aerosol–cloud interactions in regional climate simulations over Europe;Atmospheric Chemistry and Physics;2021-01-14

5. Precipitation Trends over the Indus Basin;Climate;2019-09-26

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