IMHE OpenIR  > Journal of Mountain Science  > Journal of Mountain Science-2016  > Vol13 No.4
Long-range precipitation forecasts using paleoclimate reconstructions in the western United States
Christopher Allen CARRIER; Ajay KALRA; Sajjad AHMAD
Corresponding AuthorSajjad AHMAD
2016-04
Source PublicationJournal of Mountain Science
ISSN1672-6316
Volume13Issue:4Pages:614-632
Subtype期刊论文
AbstractLong-range precipitation forecasts are useful when managing water supplies. Oceanic-atmospheric oscillations have been shown to influence precipitation. Due to a longer cycle of some of the oscillations, a short instrumental record is a limitation in using them for long-range precipitation forecasts. The influence of oscillations over precipitation is observable within paleoclimate reconstructions; however, there have been no attempts to utilize these reconstructions in precipitation forecasting. A data-driven model, KStar, is used for obtaining long-range precipitation forecasts by extending the period of record through the use of reconstructions of oscillations. KStar is a nearest neighbor algorithm with an entropy-based distance function. Oceanic-atmospheric oscillation reconstructions include the El Niño-Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the North Atlantic Oscillation (NAO), and the Atlantic Multi-decadal Oscillation (AMO). Precipitation is forecasted for 20 climate divisions in the western United States. A 10-year moving average is applied to aid in the identification of oscillation phases. A lead time approach is used to simulate a one-year forecast, with a 10-fold cross-validation technique to test the models. Reconstructions are used from 1658-1899, while the observed record is used from 1900-2007. The model is evaluated using mean absolute error (MAE), root mean squared error (RMSE), RMSE-observations standard deviation ratio (RSR), Pearson’s correlation coefficient (R), Nash-Sutcliffe coefficient of efficiency (NSE), and linear error in probability space (LEPS) skill score (SK).The role of individual and coupled oscillations is evaluated by dropping oscillations in the model. The results indicate ‘good’ precipitation estimates using the KStar model. This modeling technique is expected to be useful for long-term water resources planning and management.
KeywordPrecipitation Oscillations Paleoclimate Reconstruction Forecast Kstar
DOI10.1007/s11629-014-3360-2
Indexed BySCI
Language英语
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Cited Times:22[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.imde.ac.cn/handle/131551/15039
CollectionJournal of Mountain Science_Journal of Mountain Science-2016_Vol13 No.4
Recommended Citation
GB/T 7714
Christopher Allen CARRIER,Ajay KALRA,Sajjad AHMAD. Long-range precipitation forecasts using paleoclimate reconstructions in the western United States[J]. Journal of Mountain Science,2016,13(4):614-632.
APA Christopher Allen CARRIER,Ajay KALRA,&Sajjad AHMAD.(2016).Long-range precipitation forecasts using paleoclimate reconstructions in the western United States.Journal of Mountain Science,13(4),614-632.
MLA Christopher Allen CARRIER,et al."Long-range precipitation forecasts using paleoclimate reconstructions in the western United States".Journal of Mountain Science 13.4(2016):614-632.
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