A statistical prediction model for summer extreme precipitation days over the northern central China

2020 ◽  
Vol 40 (9) ◽  
pp. 4189-4202
Author(s):  
Tingting Han ◽  
Shangfeng Li ◽  
Xin Hao ◽  
Xinyi Guo
Keyword(s):  
Prediction Model ◽  
Extreme Precipitation ◽  
Central China ◽  
Statistical Prediction ◽  
Statistical Prediction Model

Management Forecasts and Statistical Prediction Model Forecasts in Corporate Budgeting

1991 ◽  
Vol 29 (2) ◽  
pp. 371 ◽  
Author(s):  
Kenton B. Walker ◽  
Lawrence A. McClelland
Keyword(s):  
Prediction Model ◽  
Statistical Prediction ◽  
Management Forecasts ◽  
Statistical Prediction Model

scholarly journals Development of a Dynamics-Based Statistical Prediction Model for the Changma Onset

2015 ◽  
Vol 28 (17) ◽  
pp. 6647-6666 ◽  
Author(s):  
Hae-li Park ◽  
Kyong-Hwan Seo ◽  
Jun-Hyeok Son
Keyword(s):  
Prediction Model ◽  
North Atlantic ◽  
Korean Peninsula ◽  
Statistical Prediction ◽  
Central Pacific ◽  
Anticyclonic Anomaly ◽  
The North ◽  
The North Atlantic ◽  
Statistical Prediction Model ◽  
The North Pacific

Abstract The timing of the changma onset has high impacts on the Korean Peninsula, yet its seasonal prediction remains a great challenge because the changma undergoes various influences from the tropics, subtropics, and midlatitudes. In this study, a dynamics-based statistical prediction model for the changma onset is proposed. This model utilizes three predictors of slowly varying sea surface temperature anomalies (SSTAs) over the northern tropical central Pacific, the North Atlantic, and the North Pacific occurring in the preceding spring season. SSTAs associated with each predictor persist until June and have an effect on the changma onset by inducing an anticyclonic anomaly to the southeast of the Korean Peninsula earlier than the climatological changma onset date. The persisting negative SSTAs over the northern tropical central Pacific and accompanying anomalous trade winds induce enhanced convection over the far-western tropical Pacific; in turn, these induce a cyclonic anomaly over the South China Sea and an anticyclonic anomaly southeast of the Korean Peninsula. The diabatic heating and cooling tendency related to the North Atlantic dipolar SSTAs induces downstream Rossby wave propagation in the upper troposphere, developing a barotropic anticyclonic anomaly to the south of the Korean Peninsula. A westerly wind anomaly at around 45°N resulting from the developing positive SSTAs over the North Pacific directly reduces the strength of the Okhotsk high and gives rise to an anticyclonic anomaly southeast of the Korean Peninsula. With the dynamics-based statistical prediction model, it is demonstrated that the changma onset has considerable predictability of r = 0.73 for the period from 1982 to 2014.

scholarly journals The Development of Ensemble Statistical Prediction Model for Changma Precipitation

Atmosphere ◽  
2014 ◽  
Vol 24 (4) ◽  
pp. 533-540
Author(s):  
Jin-Yong Kim ◽  
Kyong-Hwan Seo
Keyword(s):  
Prediction Model ◽  
Statistical Prediction ◽  
Statistical Prediction Model
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