Operational Evaluation of a Selective Consensus in the Western North Pacific Basin

2007 ◽  
Vol 22 (3) ◽  
pp. 671-675 ◽  
Author(s):  
Charles R. Sampson ◽  
John A. Knaff ◽  
Edward M. Fukada
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Systematic Approach ◽  
Prediction Models ◽  
Weather Prediction ◽  
Pacific Basin ◽  
Joint Typhoon Warning Center ◽  
Numerical Weather Prediction Models ◽  
North Pacific Basin

Abstract The Systematic Approach Forecast Aid (SAFA) has been in use at the Joint Typhoon Warning Center since the 2000 western North Pacific season. SAFA is a system designed for determination of erroneous 72-h track forecasts through identification of predefined error mechanisms associated with numerical weather prediction models. A metric for the process is a selective consensus in which model guidance suspected to have 72-h error greater than 300 n mi (1 n mi = 1.85 km) is first eliminated prior to calculating the average of the remaining model tracks. The resultant selective consensus should then provide improved forecasts over the nonselective consensus. In the 5 yr since its introduction into JTWC operations, forecasters have been unable to produce a selective consensus that provides consistent improved guidance over the nonselective consensus. Also, the rate at which forecasters exercised the selective consensus option dropped from approximately 45% of all forecasts in 2000 to 3% in 2004.

scholarly journals Forecasting Tropical Cyclones in the Western North Pacific Basin Using the NCEP Operational HWRF: Real-Time Implementation in 2012

2015 ◽  
Vol 30 (5) ◽  
pp. 1355-1373 ◽  
Author(s):  
Vijay Tallapragada ◽  
Chanh Kieu ◽  
Samuel Trahan ◽  
Zhan Zhang ◽  
Qingfu Liu ◽  
...  
Keyword(s):  
Real Time ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Environmental Modeling ◽  
Pacific Basin ◽  
Forecast Errors ◽  
Storm Intensity ◽  
Intensity Forecast ◽  
North Pacific Basin

Abstract This study documents the recent efforts of the hurricane modeling team at the National Centers for Environmental Prediction’s (NCEP) Environmental Modeling Center (EMC) in implementing the operational Hurricane Weather Research and Forecasting Model (HWRF) for real-time tropical cyclone (TC) forecast guidance in the western North Pacific basin (WPAC) from May to December 2012 in support of the operational forecasters at the Joint Typhoon Warning Center (JTWC). Evaluation of model performance for the WPAC in 2012 reveals that the model has promising skill with the 3-, 4-, and 5-day track errors being 125, 220, and 290 nautical miles (n mi; 1 n mi = 1.852 km), respectively. Intensity forecasts also show good performance, with the most significant intensity error reduction achieved during the first 24 h. Stratification of the track and intensity forecast errors based on storm initial intensity reveals that HWRF tends to underestimate storm intensity for weak storms and overestimate storm intensity for strong storms. Further analysis of the horizontal distribution of track and intensity forecast errors over the WPAC suggests that HWRF possesses a systematic negative intensity bias, slower movement, and a rightward bias in the lower latitudes. At higher latitudes near the East China Sea, HWRF shows a positive intensity bias and faster storm movement. This appears to be related to underestimation of the dominant large-scale system associated with the western Pacific subtropical high, which renders weaker steering flows in this basin.

scholarly journals Using eXtreme Gradient BOOSTing to Predict Changes in Tropical Cyclone Intensity over the Western North Pacific

Atmosphere ◽  
2019 ◽  
Vol 10 (6) ◽  
pp. 341 ◽  
Author(s):  
Qingwen Jin ◽  
Xiangtao Fan ◽  
Jian Liu ◽  
Zhuxin Xue ◽  
Hongdeng Jian
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Prediction Models ◽  
Weather Prediction ◽  
Back Propagation ◽  
Absolute Error ◽  
Gradient Boosting ◽  
Lead Times ◽  
Intensity Prediction ◽  
Extreme Gradient Boosting

Coastal cities in China are frequently hit by tropical cyclones (TCs), which result in tremendous loss of life and property. Even though the capability of numerical weather prediction models to forecast and track TCs has considerably improved in recent years, forecasting the intensity of a TC is still very difficult; thus, it is necessary to improve the accuracy of TC intensity prediction. To this end, we established a series of predictors using the Best Track TC dataset to predict the intensity of TCs in the Western North Pacific with an eXtreme Gradient BOOSTing (XGBOOST) model. The climatology and persistence factors, environmental factors, brainstorm features, intensity categories, and TC months are considered inputs for the models while the output is the TC intensity. The performance of the XGBOOST model was tested for very strong TCs such as Hato (2017), Rammasum (2014), Mujiage (2015), and Hagupit (2014). The results obtained show that the combination of inputs chosen were the optimal predictors for TC intensification with lead times of 6, 12, 18, and 24 h. Furthermore, the mean absolute error (MAE) of the XGBOOST model was much smaller than the MAEs of a back propagation neural network (BPNN) used to predict TC intensity. The MAEs of the forecasts with 6, 12, 18, and 24 h lead times for the test samples used were 1.61, 2.44, 3.10, and 3.70 m/s, respectively, for the XGBOOST model. The results indicate that the XGBOOST model developed in this study can be used to improve TC intensity forecast accuracy and can be considered a better alternative to conventional operational forecast models for TC intensity prediction.

scholarly journals Structural and Intensity Changes of Concentric Eyewall Typhoons in the Western North Pacific Basin

2013 ◽  
Vol 141 (8) ◽  
pp. 2632-2648 ◽  
Author(s):  
Yi-Ting Yang ◽  
Hung-Chi Kuo ◽  
Eric A. Hendricks ◽  
Melinda S. Peng
Keyword(s):  
Environmental Conditions ◽  
North Pacific ◽  
Western North Pacific ◽  
Extended Period ◽  
Vertical Shear ◽  
Pacific Basin ◽  
Internal Dynamics ◽  
Intensity Changes ◽  
North Pacific Basin ◽  
Replacement Cycle

Abstract An objective method is developed to identify concentric eyewalls (CEs) for typhoons using passive microwave satellite imagery from 1997 to 2011 in the western North Pacific basin. Three CE types are identified: a CE with an eyewall replacement cycle (ERC; 37 cases), a CE with no replacement cycle (NRC; 17 cases), and a CE that is maintained for an extended period (CEM; 16 cases). The inner eyewall (outer eyewall) of the ERC (NRC) type dissipates within 20 h after CE formation. The CEM type has its CE structure maintained for more than 20 h (mean duration time is 31 h). Structural and intensity changes of CE typhoons are demonstrated using a T–Vmax diagram (where T is the brightness temperature and Vmax is the best-track estimated intensity) for a time sequence of the intensity and convective activity (CA) relationship. While the intensity of typhoons in the ERC and CEM cases weakens after CE formation, the CA is maintained or increases. In contrast, the CA weakens in the NRC cases. The NRC (CEM) cases typically have fast (slow) northward translational speeds and encounter large (small) vertical shear and low (high) sea surface temperatures. The CEM cases have a relatively high intensity (63 m s−1), and the moat size (61 km) and outer eyewall width (70 km) are approximately 50% larger than the other two categories. Both the internal dynamics and environmental conditions are important in the CEM cases, while the NRC cases are heavily influenced by the environment. The ERC cases may be dominated by the internal dynamics because of more uniform environmental conditions.

scholarly journals Operational Performance of a New Barotropic Model (WBAR) in the Western North Pacific Basin

2006 ◽  
Vol 21 (4) ◽  
pp. 656-662 ◽  
Author(s):  
Charles R. Sampson ◽  
James S. Goerss ◽  
Harry C. Weber
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Prediction Models ◽  
Weather Prediction ◽  
Track Forecast ◽  
Forecast Performance ◽  
Barotropic Model ◽  
The North ◽  
Forecasting System ◽  
The Impact

Abstract The Weber barotropic model (WBAR) was originally developed using predefined 850–200-hPa analyses and forecasts from the NCEP Global Forecasting System. The WBAR tropical cyclone (TC) track forecast performance was found to be competitive with that of more complex numerical weather prediction models in the North Atlantic. As a result, WBAR was revised to incorporate the Navy Operational Global Atmospheric Prediction System (NOGAPS) analyses and forecasts for use at the Joint Typhoon Warning Center (JTWC). The model was also modified to analyze its own storm-dependent deep-layer mean fields from standard NOGAPS pressure levels. Since its operational installation at the JTWC in May 2003, WBAR TC track forecast performance has been competitive with the performance of other more complex NWP models in the western North Pacific. Its TC track forecast performance combined with its high availability rate (93%–95%) has warranted its inclusion in the JTWC operational consensus. The impact of WBAR on consensus TC track forecast performance has been positive and WBAR has added to the consensus forecast availability (i.e., having at least two models to provide a consensus forecast).

Estimating the Intensity of Tropical Cyclone in Western North Pacific Basin with AMSU-A Brightness Temperature

2008 ◽  
Vol 51 (1) ◽  
pp. 42-48 ◽  
Author(s):  
Zhe LIU ◽  
Wan-Biao LI ◽  
Zhi-Gang HAN ◽  
Zhi-Gang YAO ◽  
Feng-Ying ZHANG ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Brightness Temperature ◽  
North Pacific ◽  
Western North Pacific ◽  
Pacific Basin ◽  
North Pacific Basin
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