scholarly journals Large Tropical Cyclone Track Forecast Errors of Global Numerical Weather Prediction Models in western North Pacific Basin

2021 ◽  
Author(s):  
Chi Kit Tang ◽  
Johnny C.L. Chan ◽  
Munehiko Yamaguchi
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Prediction Models ◽  
Weather Prediction ◽  
Track Forecast ◽  
Forecast Errors ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Numerical Weather Prediction Models ◽  
North Pacific Basin

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 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).

scholarly journals Impact of Enhanced Satellite-Derived Atmospheric Motion Vector Observations on Numerical Tropical Cyclone Track Forecasts in the Western North Pacific during TPARC/TCS-08

2011 ◽  
Vol 50 (11) ◽  
pp. 2309-2318 ◽  
Author(s):  
Howard Berger ◽  
Rolf Langland ◽  
Christopher S. Velden ◽  
Carolyn A. Reynolds ◽  
Patricia M. Pauley
Keyword(s):  
Tropical Cyclone ◽  
Data Assimilation ◽  
North Pacific ◽  
Western North Pacific ◽  
Forecast Errors ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Rapid Scan ◽  
Atmospheric Motion ◽  
The Impact

AbstractEnhanced atmospheric motion vectors (AMVs) produced from the geostationary Multifunctional Transport Satellite (MTSAT) are assimilated into the U.S. Navy Operational Global Atmospheric Prediction System (NOGAPS) to evaluate the impact of these observations on tropical cyclone track forecasts during the simultaneous western North Pacific Ocean Observing System Research and Predictability Experiment (THORPEX) Pacific Asian Regional Campaign (TPARC) and the Tropical Cyclone Structure—2008 (TCS-08) field experiments. Four-dimensional data assimilation is employed to take advantage of experimental high-resolution (space and time) AMVs produced for the field campaigns by the Cooperative Institute for Meteorological Satellite Studies. Two enhanced AMV datasets are considered: 1) extended periods produced at hourly intervals over a large western North Pacific domain using routinely available MTSAT imagery and 2) limited periods over a smaller storm-centered domain produced using special MTSAT rapid-scan imagery. Most of the locally impacted forecast cases involve Typhoons Sinlaku and Hagupit, although other storms are also examined. On average, the continuous assimilation of the hourly AMVs reduces the NOGAPS tropical cyclone track forecast errors—in particular, for forecasts longer than 72 h. It is shown that the AMVs can improve the environmental flow analyses that may be influencing the tropical cyclone tracks. Adding rapid-scan AMV observations further reduces the NOGAPS forecast errors. In addition to their benefit in traditional data assimilation, the enhanced AMVs show promise as a potential resource for advanced objective data-targeting methods.

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 Spatial Growth of Perturbations in a Turbulent Baroclinic Jet

2011 ◽  
Vol 68 (11) ◽  
pp. 2731-2741
Author(s):  
Rahul B. Mahajan ◽  
Gregory J. Hakim
Keyword(s):  
Prediction Models ◽  
Weather Prediction ◽  
Storm Track ◽  
Spreading Rate ◽  
Forecast Errors ◽  
Far Field ◽  
Quasigeostrophic Model ◽  
Spreading Rates ◽  
Analysis Errors ◽  
Numerical Weather Prediction Models

Abstract The spatial spreading of infinitesimal disturbances superposed on a turbulent baroclinic jet is explored. This configuration is representative of analysis errors in an idealized midlatitude storm track and the insight gained may be helpful to understand the spreading of forecast errors in numerical weather prediction models. This problem is explored through numerical experiments of a turbulent baroclinic jet that is perturbed with spatially localized disturbances. Solutions from a quasigeostrophic model for the disturbance fields are compared with those for a passive tracer to determine whether disturbances propagate faster than the basic-state flow. Results show that the disturbance spreading rate is sensitive to the structure of the initial disturbance. Disturbances that are localized in potential vorticity (PV) have far-field winds that allow the disturbance to travel downstream faster than disturbances that are initially localized in geopotential, which have no far-field wind. Near the jet, the spread of the disturbance field is observed to exceed the tracer field for PV-localized disturbances, but not for the geopotential-localized disturbances. Spreading rates faster than the flow for geopotential-localized disturbances are found to occur only for disturbances located off the jet axis. These results are compared with those for zonal and time-independent jets to qualitatively assess the effects of transience and nonlinearity. This comparison suggests that the average properties of localized perturbations to the turbulent jet can be decomposed into a superposition of dynamics associated with a time-independent parallel flow plus a “diffusion” process.

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.

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