scholarly journals DEVELOPMENT OF GLOBAL STOCHASTIC TROPICAL CYCLONE MODEL BASED ON TEMPORAL CORRELATION OF TROPICAL CYCLONE PARAMETERS

2013 ◽  
Vol 69 (1) ◽  
pp. 64-76
Author(s):  
Sota NAKAJO ◽  
Nobuhito MORI ◽  
Tomohiro YASUDA ◽  
Hajime MASE
Keyword(s):  
Tropical Cyclone ◽  
Temporal Correlation ◽  
Model Based

scholarly journals Configuration and Evaluation of a Global Unstructured Mesh Model based on the Variable-Resolution Approach

2020 ◽  
Author(s):  
Yihui Zhou ◽  
Yi Zhang ◽  
Jian Li ◽  
Rucong Yu ◽  
Zhuang Liu
Keyword(s):  
Tropical Cyclone ◽  
Transition Zone ◽  
Climate Model ◽  
Model Performance ◽  
Horizontal Resolution ◽  
Fine Scale ◽  
Variable Resolution ◽  
Model Based ◽  
Mesh Model ◽  
Scale Structures

Abstract. Targeting a long-term effort towards a global weather and climate model with a local refinement function, this study systematically configures and evaluates the performance of an unstructured model based on the variable-resolution (VR) approach. Aided by the idealized dry- and moist-atmosphere tests, the model performance is examined in an intermediate degree of complexity. The dry baroclinic wave simulations suggest that the 3D VR-model can reproduce comparable solutions in the refined regions as a fine-resolution quasi-uniform (QU) mesh model, although the global errors increase. The variation of the mesh resolution in the transition zone does not adversely affect the wave pattern. In the coarse-resolution area, the VR model simulates a similar wave distribution to the low-resolution QU model. Two multi-region refinement approaches, including the hierarchical and polycentric refinement modes, further testify the model performance under a more challenging environment. The moist idealized tropical cyclone test further enables us to examine the model ability in terms of resolving fine-scale structures. It is found that the VR model can have the tropical cyclone stably pass the transition zone in various configurations. A series of sensitivity tests examines the model performance in a hierarchical refinement mode, and the solutions exhibit consistency even when the VR mesh is slightly perturbed by one of the three parameters that control the density function. Moreover, only the finest resolution has a dominant impact on the fine-scale structures in the refined region. The tropical cyclone, starting from the 2nd-refinement region and passing through the inner transition zone, gets intensified and possesses a smaller area coverage in the refined regions, as compared to the QU-mesh model that has the same number of grid points. Such variations are consistent with the behavior that one may observe when uniformly refining the QU-mesh model. Besides the horizontal resolution, the intensity of the tropical cyclone is also influenced by the Smagorinsky horizontal diffusion coefficient. The VR model exhibits higher sensitivity in this regard, suggesting the importance of parameter tuning and proper model configurations.

scholarly journals BASIC EXAMINATION OF FUTURE CHANGE OF TROPICAL CYCLONE AND STORM SURGE PROPERTIES UNDER CLIMATE CHANGE

2012 ◽  
Vol 1 (33) ◽  
pp. 23
Author(s):  
Sota Nakajo ◽  
Nobuhito Mori ◽  
Tomohiro Yasuda ◽  
Hajime Mase
Keyword(s):  
Tropical Cyclone ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Temporal Correlation ◽  
Future Change ◽  
Ensemble Averaging ◽  
Global Climate Changes ◽  
Correlation Algorithm ◽  
Future Prediction

Recently high-resolution Global Climate Model (GCM) shows that global climate changes may cause the future change of the Tropical Cyclone (TC) characteristics, such as frequency, developing process and intensity. However, there are two difficulties for assessment of future TC disaster, one is uncertainty of future prediction in GCM, and another is shortage of sample TC data. In this paper, we estimated future changes of TC properties and reduced uncertainty by ensemble averaging of multi-GCM prediction results, and generated many synthetic TC data with Global Stochastic Tropical Cyclone Model (GSTCM). In addition, GSTCM which have empirical temporal correlation algorithm was improved for the reproducibility of arrival TC statistics by cluster analysis of TC data. This upgrade could pave the way to local future prediction of TC disaster.

Tropical Cyclone Center Automatic Determination Model Based on HY-2 and QuikSCAT Wind Vector Products

2019 ◽  
Vol 57 (2) ◽  
pp. 709-721 ◽  
Author(s):  
Tangao Hu ◽  
Yiyue Wu ◽  
Gang Zheng ◽  
Dengrong Zhang ◽  
Yuzhou Zhang ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Wind Vector ◽  
Automatic Determination ◽  
Cyclone Center ◽  
Model Based ◽  
Tropical Cyclone Center

scholarly journals A Region-Dependent Seasonal Forecasting Framework for Tropical Cyclone Genesis Frequency in the Western North Pacific

2019 ◽  
Vol 32 (23) ◽  
pp. 8415-8435 ◽  
Author(s):  
Chao Wang ◽  
Bin Wang ◽  
Liguang Wu
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Prediction Models ◽  
Temporal Correlation ◽  
Tropical Cyclone Genesis ◽  
Regional Variability ◽  
Empirical Prediction ◽  
Genesis Frequency

ABSTRACT It has been a common practice to predict total tropical cyclone (TC) genesis frequency over the entire western North Pacific (WNP). Here we show that TC genesis (TCG) exhibits distinct regional variability and sources of predictability. Therefore, we divide the WNP into four quadrants with 140°E and 17°N being dividing lines plus the South China Sea (SCS) to predict five subregional TCG frequencies as well as the entire WNP TCG frequency. Besides the well-known ENSO-induced seesaw relationship between the TCGs in the southeast and northwest quadrants, we found that 1) an enhanced TCG in the northeast WNP is associated with a pronounced anomalous cyclonic circulation, which is maintained through its interaction with the underlying sea surface temperature (SST) anomalies; 2) an active TCG in the southwest WNP is accompanied by a zonally elongated positive vorticity anomaly and SST warming over the equatorial eastern Pacific; and 3) the SCS TCG is influenced by the upper-level South Asia high through modulating large-scale environmental parameters. Physically meaningful predictors are identified and a set of empirical prediction models for TCG frequency is established for each subregion. Both the cross-validated reforecast for 1965–2000 and independent forecast for 2001–16 show significant temporal correlation skills. Moreover, the sum of the predicted TCG frequency in five subregions yields a basinwide TCG frequency prediction with a temporal correlation skill of 0.76 for the independent forecast period of 2001–16. The results indicate its potential utility to improve the TC forecasting in the WNP.

scholarly journals A Novel Data-Driven Tropical Cyclone Track Prediction Model Based on CNN and GRU With Multi-Dimensional Feature Selection

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 97114-97128 ◽  
Author(s):  
Jie Lian ◽  
Pingping Dong ◽  
Yuping Zhang ◽  
Jianguo Pan ◽  
Kehao Liu
Keyword(s):  
Feature Selection ◽  
Tropical Cyclone ◽  
Prediction Model ◽  
Data Driven ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Model Based
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