Downscaling climate variability associated with quasi-periodic climate signals: A new statistical approach using MSSA-Reference-Cited by-同舟云学术

Downscaling climate variability associated with quasi-periodic climate signals: A new statistical approach using MSSA

Published:2011-02 Issue:1-2 Volume:398 Page:65-75
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Cañón Julio,Domínguez Francina,Valdés Juan B.

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference32 articles.

1. Monte Carlo SSA: detecting irregular oscillations in the presence of colored noise;Allen;J. Climate,1996

2. Precipitation in the Colorado River Basin and its low frequency associations with PDO and ENSO signals;Cañón;J. Hydrol.,2007

3. ENSO and hydrologic extremes in the Western United States;Cayan;J. Climate,1999

4. A statistical-topographic model for mapping climatological precipitation over mountainous terrain;Daly;J. Appl. Meteorol.,1994

5. Daly, C., Gibson, W., Doggett, M., Smith, J., 2005. The Near Real Time Monthly High Resolution Precipitation Climate Data set for the Conterminous United States. Spatial Climate Analysis Service at Oregon State University. .

Cited by 12 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. Statistical downscaling of precipitation in northwestern Iran using a hybrid model of discrete wavelet transform, artificial neural networks, and quantile mapping;Theoretical and Applied Climatology;2024-05-25

2. Diagnosing the Temperature Sensitivity of Ecosystem Respiration in Northern High‐Latitude Regions;Journal of Geophysical Research: Biogeosciences;2021-04

3. Influence of bias correction of meteorological and streamflow forecast on hydrological prediction in India;Journal of Hydrometeorology;2021-01-25

4. Forecasting structural strains from long-term monitoring data of a traditional Tibetan building;Structural Control and Health Monitoring;2018-11-29

5. Downscaling of Climate Information;Climate Modelling;2018