Typhoon-Induced SST Cooling and Rainfall Variations: The Case of Typhoon CHAN-HOM and Nangka

Yu, Shengyan; Subrahmanyam, M. V.

doi:10.4236/oalib.1103967

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…In addition, we used OISST data, even if the SST estimation of OISST was only exactly obtained in clear-sky conditions. Nevertheless, since many studies have used daily mean OISST data, not only for typhoon forecasting but also for the analysis of typhoon-induced SST cooling [36][37][38][39], this study could provide some perspectives (e.g., the importance of higher temporal-resolution of SST data for typhoon forecast) for improvements in typhoon forecast performance.…”

Section: Discussionmentioning

confidence: 99%

Sensitivity of Typhoon Forecast to Prescribed Sea Surface Temperature Data

et al. 2022

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This study investigates the impact of the sea surface temperature (SST) on the forecast of two typhoons, which consecutively hit South Korea in 2020. SST data were obtained from the Daily Optimum Interpolation Sea Surface Temperature (OISST) version 2 and HYbrid Coordinate Ocean Model/Navy Coupled Ocean Data Assimilation (HYCOM/NCODA; GLBy0.08/expt_93.0). When verified using in situ observational data, the OISST data did not accurately estimate the changes in SST during each typhoon’s landfall period compared to the HYCOM data since it has a relatively low temporal resolution. To investigate the impact of these two SST data on typhoon forecasts, we conducted sensitivity experiments using the Weather Research and Forecasting (WRF) model. The results showed that simulated typhoon intensities were significantly improved in the simulations with HYCOM data (HY runs), while typhoon track forecast performances were similar in both runs. In addition, the forecast performances of the maximum wind speed at 10 m during the typhoon landfall period were improved in the HY runs. Therefore, this study showed that the overall typhoon intensity and forecast performances during the landfall period could be improved when the higher temporal-resolution SST data were prescribed in the model boundary conditions for a better representation of typhoon-induced SST changes.

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Section: Discussionmentioning

confidence: 99%

Sensitivity of Typhoon Forecast to Prescribed Sea Surface Temperature Data

et al. 2022

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“…SST cools as seawater is mixed by strong typhoon winds, which is a one‐dimensional response, and a three‐dimensional response also occurs due to the influence of currents in the ocean surface layer or upwelling (Price, 1981; Suzuki et al, 2011; Yablonsky & Ginis, 2009). Quantitatively, rainfall contributes less to SST cooling than other factors (Yu & Subrahmanyam, 2017). In addition, the magnitude of typhoon‐induced SST cooling is related not only to the ocean conditions beneath a typhoon but also to the characteristics of the typhoon, such as Vm , horizontal size, and speed of movement.…”

Section: Introductionmentioning

confidence: 99%

Quantification and attribution of ocean cooling induced by the passages of typhoons Faxai (2019) and Hagibis (2019) over the same region using a high‐resolution ocean model and cooling parameters

Iida

Fudeyasu

Tanaka

et al. 2023

Atmospheric Science Letters

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This study quantitatively evaluated the typhoon‐induced sea surface temperature (SST) cooling caused by typhoons Faxai (2019) and Hagibis (2019) using a high‐resolution ocean model and the cooling parameter (Co). Faxai and Hagibis both passed over the ocean south of the eastern part of the Japanese main island, but the associated average SST decreases differed. Faxai produced a decrease of less than 2°C, whereas Hagibis produced a decrease of more than 2°C. The average Co value was 1.6 for Faxai and 3.6 for Hagibis, indicating that SST was more easily cooled by Hagibis than by Faxai, consistent with the observations. The impact of ocean conditions on the typhoon‐induced SST cooling by Hagibis was 2.6 times larger than the impact by Faxai, indicating that the ocean before Hagibis passes is less hard to cool ocean than Faxai. In short, it is important for ocean cooling not only ocean conditions but also typhoon characteristics because in fact, Hagibis cooled the ocean more than Faxai. In addition, the impact of Hagibis's characteristics on the typhoon‐induced SST cooling was 4.8 times larger than the impact of Faxai's characteristics. Thus, SST was more likely to cool by typhoon characteristics in the case of Hagibis. In particular, among Hagibis's characteristics, typhoon size in the horizontal direction had the most efficient effect on SST cooling. Although Co does not consider the effects of the advection of ocean water, we suggest that Co is a practical indicator for estimating SST cooling caused by a typhoon and comparing factors of typhoon‐induced SST cooling in multiple cases.

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Influence of summer great cyclones on sea ice concentration and area in the Arctic Ocean

Li¹,

Zhu²,

Ke³

et al. 2021

Clim. Res.

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Summer Arctic cyclones occur frequently in the Arctic Ocean and play an important role in sea ice variability. We used a reanalysis dataset and sea ice concentration data to identify and track summer great Arctic cyclones and to quantitatively analyse the contribution of cyclones to variations in sea ice concentration and area. We further explored the process of how cyclones influence sea ice via sea surface temperature, radiation, sea ice motion and ice deformation. The results indicate that cyclones accelerate decreases in sea ice concentration and area. The higher the values of the sea ice concentration index (ratio of maximum variation in sea ice concentration change rate to the minimum value of sea ice concentration change rate caused by the cyclone) and sea ice area responsivity (ratio of sea ice area change caused by cyclones to total sea ice area change) are, the greater is the contribution of cyclones to sea ice reduction. Over time, sea ice concentration decreases, and the impacts of cyclones on sea ice concentration are enhanced. During summer great cyclones, a strong low-pressure system and wind stress lead to increases in sea ice motion, ice divergence and changes in sea surface temperature and net radiation, promoting decreases in sea ice concentration and area. This study aids in the prediction of short-term sea ice change, and is beneficial to the development of coupled atmosphere-ocean-ice models.

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Typhoon-Induced SST Cooling and Rainfall Variations: The Case of Typhoon CHAN-HOM and Nangka

Cited by 4 publications

References 21 publications

Sensitivity of Typhoon Forecast to Prescribed Sea Surface Temperature Data

Sensitivity of Typhoon Forecast to Prescribed Sea Surface Temperature Data

Quantification and attribution of ocean cooling induced by the passages of typhoons Faxai (2019) and Hagibis (2019) over the same region using a high‐resolution ocean model and cooling parameters

Influence of summer great cyclones on sea ice concentration and area in the Arctic Ocean

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