scholarly journals A New Approach to Forecasting Typhoon Frequency over the Western North Pacific

2009 ◽  
Vol 24 (4) ◽  
pp. 974-986 ◽  
Author(s):  
Ke Fan ◽  
Huijun Wang
Keyword(s):  
Prediction Model ◽  
North Pacific ◽  
Western North Pacific ◽  
Cross Validation ◽  
Forecast Model ◽  
Multilinear Regression ◽  
New Approach ◽  
Validation Test ◽  
Operational Forecasting ◽  
Close Fit

Abstract This paper presents a new approach for forecasting the typhoon frequency of the western North Pacific (WNP). The year-to-year increase or decrease in typhoon frequency is first forecasted to yield a net typhoon frequency prediction. Five key predictors for the year-to-year increment in the number of typhoons in the WNP have been identified, and a forecast model is established using a multilinear regression method based on data taken from 1965 to 2001. Using the forecast model, a hindcast of the typhoon frequency of the WNP during 2002–07 is made. The model exhibited a reasonably close fit for the period 1965–2007, including the larger anomalies in 1997 and 1998. It also accounted for the smaller variability of the typhoon frequency of the WNP during the validation period 2002–07 with an average root-mean-square error (RMSE) of 1.3 (2.85) during 2002–07 (1965–2001). The cross-validation test of the prediction model shows that the new approach and the prediction model demonstrate better prediction skill when compared to the models established based on typhoon frequency rather than the typhoon frequency increment. Thus, this new approach has the potential to improve the operational forecasting skill for typhoon frequency in the WNP.

scholarly journals A Prediction Model for Atlantic Named Storm Frequency Using a Year-by-Year Increment Approach

2010 ◽  
Vol 25 (6) ◽  
pp. 1842-1851 ◽  
Author(s):  
Ke Fan
Keyword(s):  
Prediction Model ◽  
Forecast Model ◽  
Absolute Error ◽  
Good Prediction ◽  
Multilinear Regression ◽  
Incremental Approach ◽  
Percentage Improvement ◽  
Operational Forecasting ◽  
Hurricane Season ◽  
Storm Frequency

Abstract This paper presents a year-by-year incremental approach to forecasting the Atlantic named storm frequency (ATSF) for the hurricane season (1 June–30 November). The year-by-year increase or decrease in the ATSF is first forecasted to yield a net ATSF prediction. Six key predictors for the year-by-year increment in the number of Atlantic named tropical storms have been identified that are available before 1 May. The forecast model for the year-by-year increment of the ATSF is first established using a multilinear regression method based on data taken from the years 1965–99, and the forecast model of the ATSF is then derived. The prediction model for the ATSF shows good prediction skill. Compared to the climatological average mean absolute error (MAE) of 4.1, the percentage improvement in the MAE is 29% for the hindcast period of 2004–09 and 46% for the cross-validation test from 1985 to 2009 (26 yr). This work demonstrates that the year-by-year incremental approach has the potential to improve the operational forecasting skill for the ATSF.

scholarly journals Attribution of Decadal Variability in Tropical Cyclone Passage Frequency over the Western North Pacific: A New Approach Emphasizing the Genesis Location of Cyclones

2013 ◽  
Vol 26 (3) ◽  
pp. 973-987 ◽  
Author(s):  
Satoru Yokoi ◽  
Yukari N. Takayabu
Keyword(s):  
Tropical Cyclone ◽  
Time Scales ◽  
North Pacific ◽  
Western North Pacific ◽  
Decadal Variability ◽  
The Philippines ◽  
Ocean Basin ◽  
New Approach ◽  
Equal Degree ◽  
Analysis Application

Abstract Variability in tropical cyclone (TC) activity is a matter of direct concern for affected populations. On interannual and longer time scales, variability in TC passage frequency can be associated with total TC frequency over the concerned ocean basin [basinwide frequency (BF)], the spatial distribution of TC genesis in the basin [genesis distribution (GD)], and the preferable track (PT) that can be considered as a function of genesis locations. To facilitate investigation of mechanisms responsible for the variability, the authors propose an approach of decomposing anomalies in the passage frequency into contributions of variability in BF, GD, and PT, which is named the Integration of Statistics on TC Activity by Genesis Location (ISTAGL) analysis. Application of this approach to TC best track data in the western North Pacific (WNP) basin reveals that overall distribution of the passage frequency trends over the 1961–2010 period is mainly due to the PT trends. On decadal time scales, passage frequency variability in midlatitudes is primarily due to PT variability, while the BF and GD also play roles in the subtropics. The authors further discuss decadal variability over the East China Sea in detail. The authors demonstrate that northward shift of the PT for TCs generated around the Philippines Sea and westward shift for TCs generated in the eastern part of the WNP contribute the variability with almost equal degree. The relationships between these PT shifts and anomalies in environmental circulation fields are also discussed.

Online Prediction Control Model of CO2 Concentration for Pleurotus eryngii in the Sporocarp Period Based on Matlab and LabVIEW

2017 ◽  
Vol 868 ◽  
pp. 45-50
Author(s):  
Xiao Qing Tian ◽  
Kang Zhang ◽  
Nan Bai ◽  
Xue Jun Zhu
Keyword(s):  
Prediction Model ◽  
Fuzzy Controller ◽  
Forecast Model ◽  
Pleurotus Eryngii ◽  
Time Varying ◽  
Prediction System ◽  
New Approach ◽  
Cultivation Process ◽  
Prediction Control ◽  
Favorable Conditions

In the industrialized cultivation process of fungi, CO2 concentration control system is a nonlinear, time-delay and time-varying system, which is difficult to establish a precise mathematical model. Considering the situation, CO2 concentration prediction model that based on neural network was built, and a fuzzy controller was proposed further based on the prediction model. Finally, matlab/labview based online forecast model was finished, and it is verified that the prediction system has higher prediction accuracy with robust character. It also provides a new approach to control key environmental factors under more favorable conditions for mushroom growth.

scholarly journals Dynamical-Statistical Hybrid Seasonal Prediction of Tropical Cyclone Track Density Over Western North Pacific

2021 ◽  
Author(s):  
Daquan Zhang ◽  
Lijuan Chen
Keyword(s):  
North Pacific ◽  
Lead Time ◽  
Western North Pacific ◽  
Large Scale ◽  
Interannual Variation ◽  
Forecast Model ◽  
Track Density ◽  
Climate System Model ◽  
Enso Events ◽  
Forecast Lead Time

Abstract Compared with total account of basin-wide tropical cyclones (TC) genesis, the prevailing tracks of TC activity and its potential of landfalling is more important for disaster prevention. Despite its relatively lower predictability, a statistical-dynamical hybrid prediction model was developed based on the knowledge of the physical mechanism between western North Pacific (WNP) TC activity and related large-scale environmental fields from July to September. The leading modes of spatial-temporal variation of WNP TC tracks density its climatological peak season (July to September) was extracted using empirical orthogonal function (EOF) decomposition. The interannual variation of leading EOF modes of WNP TC track density was predicted using multiple linear regressions (MLR) method based on predictors selected by correlation analysis of both observational and Beijing Climate Center climate system model version 1.1 (BCC_CSM1.1) hindcast data. The predicted spatial distribution of WNP TC tracks density was obtained through weighted composite of forecasting EOF modes according to its variance explained respectively. Results of one-year-out cross validation indicates that forecast model well captures the interannual variation of WNP TC prevailing moving tracks, especially in South China Sea (SCS) and southeastern quadrant of WNP. The prediction skill enhanced with decreased forecast lead time, with anomaly correlation coefficient (ACC) of northern SCS and southeast quadrant of WNP reaches 0.6 for the period 1991-2020 with one month forecast lead time. Forecast assessment based on different ENSO phases indicate that source of predictability of WNP TC tracks was mainly originate from ENSO events, especially strong El Niño events.

scholarly journals Experiments with a Simple Tropical Cyclone Intensity Consensus

2008 ◽  
Vol 23 (2) ◽  
pp. 304-312 ◽  
Author(s):  
Charles R. Sampson ◽  
James L. Franklin ◽  
John A. Knaff ◽  
Mark DeMaria
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Ensemble Methods ◽  
Forecast Model ◽  
Dynamical Model ◽  
Consensus Forecasts ◽  
Intensity Forecast ◽  
Forecast Models ◽  
The Individual

Abstract Consensus forecasts (forecasts created by combining output from individual forecasts) have become an integral part of operational tropical cyclone track forecasting. Consensus aids, which generally have lower average errors than individual models, benefit from the skill and independence of the consensus members, both of which are present in track forecasting, but are limited in intensity forecasting. This study conducts experiments with intensity forecast aids on 4 yr of data (2003–06). First, the skill of the models is assessed; then simple consensus computations are constructed for the Atlantic, eastern North Pacific, and western North Pacific basins. A simple (i.e., equally weighted) consensus of three top-performing intensity forecast models is found to generally outperform the individual members in both the Atlantic and eastern North Pacific, and a simple consensus of two top-performing intensity forecast models is found to generally outperform the individual members in the western North Pacific. An experiment using an ensemble of dynamical model track forecasts and a selection of model fields as input in a statistical–dynamical intensity forecast model to produce intensity consensus members is conducted for the western North Pacific only. Consensus member skill at 72 h is low (−0.4% to 14.2%), and there is little independence among the members. This experiment demonstrates that a consensus of these highly dependent members yields an aid that performs as well as the most skillful member. Finally, adding a less skillful, but more independent, dynamical model-based forecast aid to the consensus yields an 11-member consensus with mixed yet promising performance compared with the 10-model consensus. Based on these findings, the simple three-member consensus model could be used as a standard of comparison for other deterministic ensemble methods for the Atlantic and eastern North Pacific. Both the two- and three-member consensus forecasts may also provide useful guidance for operational forecasters. Likewise, in the western North Pacific, the 10- and 11-member consensus could be used as operational forecast aids and standards of comparison for other ensemble intensity forecast methods.

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