scholarly journals Relationship of maximum tropical cyclone intensity to sea surface temperature and tropical cyclone heat potential in the North Pacific Ocean

2012 ◽  
Vol 117 (D11) ◽  
pp. n/a-n/a ◽  
Author(s):  
Akiyoshi Wada ◽  
Norihisa Usui ◽  
Kanako Sato
Keyword(s):  
Tropical Cyclone ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
Tropical Cyclone Intensity ◽  
Cyclone Intensity ◽  
The North ◽  
Tropical Cyclone Heat Potential ◽  
Heat Potential ◽  
Relationship Of ◽  
The North Pacific

Estimation of Tropical Cyclone Heat Potential From Oceanic Measurements

2011 ◽  
Author(s):  
Chung-Ru Ho ◽  
Yen-Hsuan Tsao ◽  
Nan-Jung Kuo ◽  
Shih-Jen Huang
Keyword(s):  
Tropical Cyclone ◽  
North Pacific Ocean ◽  
Heat Content ◽  
Remote Sensing Data ◽  
Sea Surface ◽  
Tropical Cyclone Heat Potential ◽  
Heat Potential ◽  
Typhoon Intensity ◽  
Intensity Changes

The primary purpose of this study is to estimate the tropical cyclone heat potential (TCHP) in the western North Pacific Ocean using in-situ measurements and satellite remote sensing data, as well as to explore the influence of TCHP on the genesis and intensification of typhoon in this region. The TCHP is defined as the integration of heat content from the depth of 26°C isotherm to the sea surface. Sea surface height and sea surface temperature data are used to estimate the TCHP based on a two-layer reduced gravity model. Totally 35 typhoons from 2006 to 2009 are analyzed in this study. The result shows that the typhoon is dramatically developed when it goes through the area with more TCHP than surroundings. From the result of regression analysis, the correlation coefficient between typhoon intensity and accumulated TCHP is above 0.8. It implies that the typhoon intensity changes might be controlled by the TCHP conditions of tropical cyclone formation region.

scholarly journals Neural Network Approach to Retrieving Ocean Subsurface Temperatures from Surface Parameters Observed by Satellites

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 388
Author(s):  
Hao Cheng ◽  
Liang Sun ◽  
Jiagen Li
Keyword(s):  
Neural Network ◽  
Pacific Ocean ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
Satellite Measurements ◽  
Surface Parameters ◽  
The North ◽  
The North Pacific ◽  
Bpnn Model

The extraction of physical information about the subsurface ocean from surface information obtained from satellite measurements is both important and challenging. We introduce a back-propagation neural network (BPNN) method to determine the subsurface temperature of the North Pacific Ocean by selecting the optimum input combination of sea surface parameters obtained from satellite measurements. In addition to sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS) and sea surface wind (SSW), we also included the sea surface velocity (SSV) as a new component in our study. This allowed us to partially resolve the non-linear subsurface dynamics associated with advection, which improved the estimated results, especially in regions with strong currents. The accuracy of the estimated results was verified with reprocessed observational datasets. Our results show that the BPNN model can accurately estimate the subsurface (upper 1000 m) temperature of the North Pacific Ocean. The corresponding mean square errors were 0.868 and 0.802 using four (SSH, SST, SSS and SSW) and five (SSH, SST, SSS, SSW and SSV) input parameters and the average coefficients of determination were 0.952 and 0.967, respectively. The input of the SSV in addition to the SSH, SST, SSS and SSW therefore has a positive impact on the BPNN model and helps to improve the accuracy of the estimation. This study provides important technical support for retrieving thermal information about the ocean interior from surface satellite remote sensing observations, which will help to expand the scope of satellite measurements of the ocean.

Satellite-Derived Tropical Cyclone Intensity in the North Pacific Ocean Using the Deviation-Angle Variance Technique

2014 ◽  
Vol 29 (3) ◽  
pp. 505-516 ◽  
Author(s):  
Elizabeth A. Ritchie ◽  
Kimberly M. Wood ◽  
Oscar G. Rodríguez-Herrera ◽  
Miguel F. Piñeros ◽  
J. Scott Tyo
Keyword(s):  
Tropical Cyclone ◽  
North Atlantic ◽  
North Pacific ◽  
Western North Pacific ◽  
North Pacific Ocean ◽  
Deviation Angle ◽  
Intensity Estimation ◽  
The North ◽  
The North Atlantic ◽  
The North Pacific

Abstract The deviation-angle variance technique (DAV-T), which was introduced in the North Atlantic basin for tropical cyclone (TC) intensity estimation, is adapted for use in the North Pacific Ocean using the “best-track center” application of the DAV. The adaptations include changes in preprocessing for different data sources [Geostationary Operational Environmental Satellite-East (GOES-E) in the Atlantic, stitched GOES-E–Geostationary Operational Environmental Satellite-West (GOES-W) in the eastern North Pacific, and the Multifunctional Transport Satellite (MTSAT) in the western North Pacific], and retraining the algorithm parameters for different basins. Over the 2007–11 period, DAV-T intensity estimation in the western North Pacific results in a root-mean-square intensity error (RMSE, as measured by the maximum sustained surface winds) of 14.3 kt (1 kt ≈ 0.51 m s−1) when compared to the Joint Typhoon Warning Center best track, utilizing all TCs to train and test the algorithm. The RMSE obtained when testing on an individual year and training with the remaining set lies between 12.9 and 15.1 kt. In the eastern North Pacific the DAV-T produces an RMSE of 13.4 kt utilizing all TCs in 2005–11 when compared with the National Hurricane Center best track. The RMSE for individual years lies between 9.4 and 16.9 kt. The complex environment in the western North Pacific led to an extension to the DAV-T that includes two different radii of computation, producing a parametric surface that relates TC axisymmetry to intensity. The overall RMSE is reduced by an average of 1.3 kt in the western North Pacific and 0.8 kt in the eastern North Pacific. These results for the North Pacific are comparable with previously reported results using the DAV for the North Atlantic basin.

Recent intensified influence of the winter North Pacific sea surface temperature on the withdrawal date of Meiyu

2021 ◽  
pp. 1-53
Author(s):  
Hua Li ◽  
Shengping He ◽  
Ke Fan ◽  
Yong Liu ◽  
Xing Yuan
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Interannual Variability ◽  
North Pacific ◽  
North Pacific Ocean ◽  
Sea Surface ◽  
The North ◽  
Time Period ◽  
The North Pacific ◽  
Sst Anomalies

AbstractThe Meiyu withdrawal date (MWD) is a crucial indicator of flood/drought conditions over East Asia. It is characterized by a strong interannual variability, but its underlying mechanism remains unknown. We investigated the possible effects of the winter sea surface temperature (SST) in the North Pacific Ocean on the MWD on interannual to interdecadal timescales. Both our observations and model results suggest that the winter SST anomalies associated with the MWD are mainly contributed by a combination of the first two leading modes of the winter SST in the North Pacific, which have a horseshoe shape (the NPSST). The statistical results indicate that the intimate linkage between the NPSST and the MWD has intensified since the early 1990s. During the time period 1990–2016, the NPSST-related SST anomalies persisted from winter to the following seasons and affected the SST over the tropical Pacific in July. Subsequently, the SST anomalies throughout the North Pacific strengthened the southward migration of the East Asian jet stream (EAJS) and the southward and westward replacement of the western North Pacific subtropical high (WPSH), leading to an increase in Meiyu rainfall from July 1 to 20. More convincingly, the anomalous EAJS and WPSH induced by the SST anomalies can be reproduced well by numerical simulations. By contrast, the influence of the NPSST on the EASJ and WPSH were not clear between 1961 and 1985. This study further illustrates that the enhanced interannual variability of the NPSST may be attributed to the more persistent SST anomalies during the time period 1990–2016.

Trend Analysis with a New Global Record of Tropical Cyclone Intensity

2013 ◽  
Vol 26 (24) ◽  
pp. 9960-9976 ◽  
Author(s):  
James P. Kossin ◽  
Timothy L. Olander ◽  
Kenneth R. Knapp
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Satellite Data ◽  
Formal Analysis ◽  
P Value ◽  
Tropical Cyclone Intensity ◽  
The South ◽  
Cyclone Intensity ◽  
The North ◽  
South Indian

Abstract The historical global “best track” records of tropical cyclones extend back to the mid-nineteenth century in some regions, but formal analysis of these records is encumbered by temporal heterogeneities in the data. This is particularly problematic when attempting to detect trends in tropical cyclone metrics that may be attributable to climate change. Here the authors apply a state-of-the-art automated algorithm to a globally homogenized satellite data record to create a more temporally consistent record of tropical cyclone intensity within the period 1982–2009, and utilize this record to investigate the robustness of trends found in the best-track data. In particular, the lifetime maximum intensity (LMI) achieved by each reported storm is calculated and the frequency distribution of LMI is tested for changes over this period. To address the unique issues in regions around the Indian Ocean, which result from a discontinuity introduced into the satellite data in 1998, a direct homogenization procedure is applied in which post-1998 data are degraded to pre-1998 standards. This additional homogenization step is found to measurably reduce LMI trends, but the global trends in the LMI of the strongest storms remain positive, with amplitudes of around +1 m s−1 decade−1 and p value = 0.1. Regional trends, in m s−1 decade−1, vary from −2 (p = 0.03) in the western North Pacific, +1.7 (p = 0.06) in the south Indian Ocean, +2.5 (p = 0.09) in the South Pacific, to +8 (p < 0.001) in the North Atlantic.

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