{"title":"Sea surface temperature effects on the modelled track and intensity of tropical cyclone Gonu","authors":"M. Alimohammadi, H. Malakooti, M. Rahbani","doi":"10.1080/1755876X.2021.1911125","DOIUrl":null,"url":null,"abstract":"ABSTRACT The seven simulations were performed to investigate the role of the sea surface temperature (SST) in numerical prediction of tropical cyclones (TCs). The TC Gonu, formed over the Arabian Sea in 2007, was selected for this study. The first five simulations were performed using WRF model. In the first simulation as control simulation (CTL), the SST derived from NCEP-MMAB was used. In the second simulation, 1°C was added to input SST, and in the third simulation, 1°C was subtracted to input SST. It was found that the deviation between the simulated track of simulation SST +1 and CTL is more significant than that between simulation SST −1 and CTL. For the fourth simulation, a homogeneous SST field over the entire basin was used. For the fifth simulation, SST anomaly was calculated, and its values were added to the entire domain. Removing the temperature gradient caused TC intensity to decrease and deviation of the track to the northeast; the increasing temperature gradient had a lower impact on the TC intensity but with a significant deviation of the track to the north with respect to the CTL simulation. In the sixth simulation to consider cyclone-induced SST cooling, a one-dimensional oceanic mixed layer scheme was applied. Results showed no significant reduction in TC intensity. In the seventh simulation, the COAWST modelling system was used. The simulated SST of the COAWST model was consistent with the satellite observations, which finally led to improve the simulation of track and intensity of TC Gonu.","PeriodicalId":50105,"journal":{"name":"Journal of Operational Oceanography","volume":"1 1","pages":"89 - 105"},"PeriodicalIF":1.7000,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Operational Oceanography","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/1755876X.2021.1911125","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 1
Abstract
ABSTRACT The seven simulations were performed to investigate the role of the sea surface temperature (SST) in numerical prediction of tropical cyclones (TCs). The TC Gonu, formed over the Arabian Sea in 2007, was selected for this study. The first five simulations were performed using WRF model. In the first simulation as control simulation (CTL), the SST derived from NCEP-MMAB was used. In the second simulation, 1°C was added to input SST, and in the third simulation, 1°C was subtracted to input SST. It was found that the deviation between the simulated track of simulation SST +1 and CTL is more significant than that between simulation SST −1 and CTL. For the fourth simulation, a homogeneous SST field over the entire basin was used. For the fifth simulation, SST anomaly was calculated, and its values were added to the entire domain. Removing the temperature gradient caused TC intensity to decrease and deviation of the track to the northeast; the increasing temperature gradient had a lower impact on the TC intensity but with a significant deviation of the track to the north with respect to the CTL simulation. In the sixth simulation to consider cyclone-induced SST cooling, a one-dimensional oceanic mixed layer scheme was applied. Results showed no significant reduction in TC intensity. In the seventh simulation, the COAWST modelling system was used. The simulated SST of the COAWST model was consistent with the satellite observations, which finally led to improve the simulation of track and intensity of TC Gonu.
期刊介绍:
The Journal of Operational Oceanography will publish papers which examine the role of oceanography in contributing to the fields of: Numerical Weather Prediction; Development of Climatologies; Implications of Ocean Change; Ocean and Climate Forecasting; Ocean Observing Technologies; Eutrophication; Climate Assessment; Shoreline Change; Marine and Sea State Prediction; Model Development and Validation; Coastal Flooding; Reducing Public Health Risks; Short-Range Ocean Forecasting; Forces on Structures; Ocean Policy; Protecting and Restoring Ecosystem health; Controlling and Mitigating Natural Hazards; Safe and Efficient Marine Operations