Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China

Abstract Seasonal precipitation changes under the influence of large-scale climate oscillations in the East River basin were studied using daily precipitation data at 29 rain stations during 1959–2010. Seasonal and global models were developed and evaluated for probabilistic precipitation forecastin...

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Published in:International Journal of Disaster Risk Science
Main Authors: Peng Sun, Qiang Zhang, Xihui Gu, Peijun Shi, Vijay P. Singh, Changqing Song, Xiuyu Zhang
Format: Article in Journal/Newspaper
Language:English
Published: SpringerOpen 2018
Subjects:
Online Access:https://doi.org/10.1007/s13753-018-0165-x
https://doaj.org/article/e6bab97def954421896cf2f27e05934c
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spelling ftdoajarticles:oai:doaj.org/article:e6bab97def954421896cf2f27e05934c 2023-05-15T15:08:23+02:00 Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China Peng Sun Qiang Zhang Xihui Gu Peijun Shi Vijay P. Singh Changqing Song Xiuyu Zhang 2018-03-01T00:00:00Z https://doi.org/10.1007/s13753-018-0165-x https://doaj.org/article/e6bab97def954421896cf2f27e05934c EN eng SpringerOpen http://link.springer.com/article/10.1007/s13753-018-0165-x https://doaj.org/toc/2095-0055 https://doaj.org/toc/2192-6395 doi:10.1007/s13753-018-0165-x 2095-0055 2192-6395 https://doaj.org/article/e6bab97def954421896cf2f27e05934c International Journal of Disaster Risk Science, Vol 9, Iss 1, Pp 100-115 (2018) China ENSO regimes GAMLSS model Nonstationarity Probabilistic precipitation forecasting Disasters and engineering TA495 article 2018 ftdoajarticles https://doi.org/10.1007/s13753-018-0165-x 2023-01-08T01:31:47Z Abstract Seasonal precipitation changes under the influence of large-scale climate oscillations in the East River basin were studied using daily precipitation data at 29 rain stations during 1959–2010. Seasonal and global models were developed and evaluated for probabilistic precipitation forecasting. Generalized additive model for location, scale, and shape was used for at-site precipitation forecasting. The results indicate that: (1) winter and spring precipitation processes at most stations are nonstationary, while summer and autumn precipitation processes at few of the stations are stationary. In this sense, nonstationary precipitation processes are dominant across the study region; (2) the magnitude of precipitation is influenced mainly by the Arctic Oscillation, the North Pacific Oscillation, and the Pacific Decadal Oscillation (PDO). The El Niño / Southern Oscillation (ENSO) also has a considerable effect on the variability of precipitation regimes across the East River basin; (3) taking the seasonal precipitation changes of the entire study period as a whole, the climate oscillations influence precipitation magnitude, and this is particularly clear for the PDO and the ENSO. The latter also impacts the dispersion of precipitation changes; and (4) the seasonal model is appropriate for modeling spring precipitation, but the global model performs better for summer, autumn, and winter precipitation. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Pacific International Journal of Disaster Risk Science 9 1 100 115
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic China
ENSO regimes
GAMLSS model
Nonstationarity
Probabilistic precipitation forecasting
Disasters and engineering
TA495
spellingShingle China
ENSO regimes
GAMLSS model
Nonstationarity
Probabilistic precipitation forecasting
Disasters and engineering
TA495
Peng Sun
Qiang Zhang
Xihui Gu
Peijun Shi
Vijay P. Singh
Changqing Song
Xiuyu Zhang
Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
topic_facet China
ENSO regimes
GAMLSS model
Nonstationarity
Probabilistic precipitation forecasting
Disasters and engineering
TA495
description Abstract Seasonal precipitation changes under the influence of large-scale climate oscillations in the East River basin were studied using daily precipitation data at 29 rain stations during 1959–2010. Seasonal and global models were developed and evaluated for probabilistic precipitation forecasting. Generalized additive model for location, scale, and shape was used for at-site precipitation forecasting. The results indicate that: (1) winter and spring precipitation processes at most stations are nonstationary, while summer and autumn precipitation processes at few of the stations are stationary. In this sense, nonstationary precipitation processes are dominant across the study region; (2) the magnitude of precipitation is influenced mainly by the Arctic Oscillation, the North Pacific Oscillation, and the Pacific Decadal Oscillation (PDO). The El Niño / Southern Oscillation (ENSO) also has a considerable effect on the variability of precipitation regimes across the East River basin; (3) taking the seasonal precipitation changes of the entire study period as a whole, the climate oscillations influence precipitation magnitude, and this is particularly clear for the PDO and the ENSO. The latter also impacts the dispersion of precipitation changes; and (4) the seasonal model is appropriate for modeling spring precipitation, but the global model performs better for summer, autumn, and winter precipitation.
format Article in Journal/Newspaper
author Peng Sun
Qiang Zhang
Xihui Gu
Peijun Shi
Vijay P. Singh
Changqing Song
Xiuyu Zhang
author_facet Peng Sun
Qiang Zhang
Xihui Gu
Peijun Shi
Vijay P. Singh
Changqing Song
Xiuyu Zhang
author_sort Peng Sun
title Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
title_short Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
title_full Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
title_fullStr Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
title_full_unstemmed Nonstationarities and At-site Probabilistic Forecasts of Seasonal Precipitation in the East River Basin, China
title_sort nonstationarities and at-site probabilistic forecasts of seasonal precipitation in the east river basin, china
publisher SpringerOpen
publishDate 2018
url https://doi.org/10.1007/s13753-018-0165-x
https://doaj.org/article/e6bab97def954421896cf2f27e05934c
geographic Arctic
Pacific
geographic_facet Arctic
Pacific
genre Arctic
genre_facet Arctic
op_source International Journal of Disaster Risk Science, Vol 9, Iss 1, Pp 100-115 (2018)
op_relation http://link.springer.com/article/10.1007/s13753-018-0165-x
https://doaj.org/toc/2095-0055
https://doaj.org/toc/2192-6395
doi:10.1007/s13753-018-0165-x
2095-0055
2192-6395
https://doaj.org/article/e6bab97def954421896cf2f27e05934c
op_doi https://doi.org/10.1007/s13753-018-0165-x
container_title International Journal of Disaster Risk Science
container_volume 9
container_issue 1
container_start_page 100
op_container_end_page 115
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