Matches in SemOpenAlex for { <https://semopenalex.org/work/W4313405513> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W4313405513 abstract "Abstract. Statistical post-processing techniques are widely used to reduce systematic biases and quantify forecast uncertainty in numerical weather prediction (NWP). In this study, we propose a method to correct the raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information such as topography and meteorological factors. Particularly, we first use the self-organizing map (SOM) model to classify large-scale circulation patterns for each season, then build the convolutional neural network (CNN) model to extract spatial information (e.g., elevation, specific humidity, and mean sea level pressure) and long short-term memory network (LSTM) model to extract time series (e.g., t, t-1, t-2), and finally correct local precipitation for each circulation pattern separately. Furthermore, the proposed method (SOM-CNN-LSTM) is compared with other benchmark methods (i.e., CNN, LSTM, and CNN-LSTM) in the Huaihe River basin with a lead time of 15 days from 2007 to 2021. The results show that the proposed SOM-CNN-LSTM post-processing method outperforms other benchmark methods for all lead times and each season with the largest correlation coefficient improvement (32.30 %) and root mean square error reduction (26.58 %). Moreover, the proposed method can effectively capture the westward and northward movement of the western Pacific subtropical high (WPSH), which impacts the basin's summer rain. The results illustrate that incorporating large-scale circulation patterns with local spatiotemporal information is a feasible and effective post-processing method to improve forecasting skills, which would benefit hydrological forecasts and other applications." @default.
- W4313405513 created "2023-01-06" @default.
- W4313405513 creator A5001262405 @default.
- W4313405513 creator A5004992306 @default.
- W4313405513 creator A5042241049 @default.
- W4313405513 creator A5050493451 @default.
- W4313405513 creator A5061108304 @default.
- W4313405513 creator A5083617730 @default.
- W4313405513 date "2023-01-02" @default.
- W4313405513 modified "2023-10-17" @default.
- W4313405513 title "Statistical post-processing of precipitation forecasts using circulation classifications and spatiotemporal deep neural networks" @default.
- W4313405513 doi "https://doi.org/10.5194/hess-2022-432" @default.
- W4313405513 hasPublicationYear "2023" @default.
- W4313405513 type Work @default.
- W4313405513 citedByCount "1" @default.
- W4313405513 countsByYear W43134055132023 @default.
- W4313405513 crossrefType "posted-content" @default.
- W4313405513 hasAuthorship W4313405513A5001262405 @default.
- W4313405513 hasAuthorship W4313405513A5004992306 @default.
- W4313405513 hasAuthorship W4313405513A5042241049 @default.
- W4313405513 hasAuthorship W4313405513A5050493451 @default.
- W4313405513 hasAuthorship W4313405513A5061108304 @default.
- W4313405513 hasAuthorship W4313405513A5083617730 @default.
- W4313405513 hasBestOaLocation W43134055131 @default.
- W4313405513 hasConcept C105795698 @default.
- W4313405513 hasConcept C107054158 @default.
- W4313405513 hasConcept C127313418 @default.
- W4313405513 hasConcept C139945424 @default.
- W4313405513 hasConcept C140178040 @default.
- W4313405513 hasConcept C153294291 @default.
- W4313405513 hasConcept C154945302 @default.
- W4313405513 hasConcept C160945548 @default.
- W4313405513 hasConcept C170061395 @default.
- W4313405513 hasConcept C185798385 @default.
- W4313405513 hasConcept C205649164 @default.
- W4313405513 hasConcept C2778755073 @default.
- W4313405513 hasConcept C33923547 @default.
- W4313405513 hasConcept C41008148 @default.
- W4313405513 hasConcept C49204034 @default.
- W4313405513 hasConcept C50644808 @default.
- W4313405513 hasConcept C58640448 @default.
- W4313405513 hasConcept C81363708 @default.
- W4313405513 hasConceptScore W4313405513C105795698 @default.
- W4313405513 hasConceptScore W4313405513C107054158 @default.
- W4313405513 hasConceptScore W4313405513C127313418 @default.
- W4313405513 hasConceptScore W4313405513C139945424 @default.
- W4313405513 hasConceptScore W4313405513C140178040 @default.
- W4313405513 hasConceptScore W4313405513C153294291 @default.
- W4313405513 hasConceptScore W4313405513C154945302 @default.
- W4313405513 hasConceptScore W4313405513C160945548 @default.
- W4313405513 hasConceptScore W4313405513C170061395 @default.
- W4313405513 hasConceptScore W4313405513C185798385 @default.
- W4313405513 hasConceptScore W4313405513C205649164 @default.
- W4313405513 hasConceptScore W4313405513C2778755073 @default.
- W4313405513 hasConceptScore W4313405513C33923547 @default.
- W4313405513 hasConceptScore W4313405513C41008148 @default.
- W4313405513 hasConceptScore W4313405513C49204034 @default.
- W4313405513 hasConceptScore W4313405513C50644808 @default.
- W4313405513 hasConceptScore W4313405513C58640448 @default.
- W4313405513 hasConceptScore W4313405513C81363708 @default.
- W4313405513 hasFunder F4320321001 @default.
- W4313405513 hasLocation W43134055131 @default.
- W4313405513 hasLocation W43134055132 @default.
- W4313405513 hasOpenAccess W4313405513 @default.
- W4313405513 hasPrimaryLocation W43134055131 @default.
- W4313405513 hasRelatedWork W154791109 @default.
- W4313405513 hasRelatedWork W1980430798 @default.
- W4313405513 hasRelatedWork W2058959951 @default.
- W4313405513 hasRelatedWork W2069225437 @default.
- W4313405513 hasRelatedWork W2132065513 @default.
- W4313405513 hasRelatedWork W2197498248 @default.
- W4313405513 hasRelatedWork W3091981235 @default.
- W4313405513 hasRelatedWork W4308071692 @default.
- W4313405513 hasRelatedWork W4386183259 @default.
- W4313405513 hasRelatedWork W2157312879 @default.
- W4313405513 isParatext "false" @default.
- W4313405513 isRetracted "false" @default.
- W4313405513 workType "article" @default.