Impacts of climate change on tropical cyclones and induced storm surges in the Pearl River Delta region using pseudo-global-warming method

Chen, Ji‐Long; Wang, Ziqian; Tam, Chi‐Yung; Lau, Ngar‐Cheung; Lau, Dick-Shum Dickson; Mok, H. Y.

doi:10.1038/s41598-020-58824-8

Cited by 71 publications

(61 citation statements)

References 27 publications

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“…In addition to the characteristic changes discussed so far, increases in sea level, coupled with greater coastal development, is expected to compound oceanic impacts from tropical cyclones [5,6,15,57,58]. In this study, changes in the TC-ocean characteristics are examined in terms of the significant wave height.…”

Section: Significant Wave Heightmentioning

confidence: 98%

Projected Characteristic Changes of a Typical Tropical Cyclone under Climate Change in the South West Indian Ocean

et al. 2021

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During 2 January 2014, Cyclone Bejisa passed near La Réunion in the southwestern Indian Ocean, bringing wind speeds of 41 m s−1, an ocean swell of 7 m, and rainfall accumulations of 1025 mm over 48 h. As a typical cyclone to impact La Réunion, we investigate how the characteristics of this cyclone could change in response to future warming via high-resolution, atmosphere–ocean coupled simulations of Bejisa-like cyclones in historical and future environments. Future environments are constructed using the pseudo global warming method whereby perturbations are added to historical analyses from six Coupled Model Intercomparison Project 5 (CMIP5) climate models. These models follow the Intergovernmental Panel for Climate Change’s (IPCC) Representative Concentration Pathways (RCP) RCP8.5 emissions scenario and project ocean surface warming of 1.1–4.2 °C by 2100. Under these conditions, we find that future Bejisa-like cyclones are 6.5% more intense on average and reach their lifetime maximum intensity 2 degrees further poleward. Additionally, future cyclones produce heavier rainfall, with a 33.8% average increase in the median rainrate, and are 9.2% smaller, as measured by the radius of 17.5 m s−1 winds. Furthermore, when surface wind output is used to run an ocean wave model in post, we find a 4.6% increase in the significant wave height.

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Section: Significant Wave Heightmentioning

confidence: 98%

Projected Characteristic Changes of a Typical Tropical Cyclone under Climate Change in the South West Indian Ocean

et al. 2021

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“…Thus, even though we only use 13 years of simulated weather for our study, the climate change signal itself is based on traditional 30 years averages imposed on the same weather. This approach avoids problems caused by internal variability (Deser et al, 2012), and is comparable to approaches used to study hurricanes in similar studies (Lackmann, 2015;Carroll-Smith, 2018;Jung and Lackmann, 2019;Chen et al, 2020). Inputs to the radiative transfer scheme are also modified to account for projected changes in greenhouse gases.…”

Section: Wrf Modelmentioning

confidence: 99%

“…In general, coastal storm surges must be explicitly modeled using numerical simulation (Jelesnianski et al, 1992;Luettich et al, 1992;Mandli and Dawson, 2014). While an increasing number of studies have taken various approaches to exploring how climate change will impact coastal flood risk in the future (Lin et al, 2012;Needham et al, 2012;Murdukhayeva et al, 2013;Yates et al, 2014;Takayabu et al, 2015;Lin and Emanuel, 2016;Garner et al, 2017;Rahmstorf, 2017;Marsooli et al, 2019;Chen et al, 2020;Yin et al, 2020), it is unclear how these impacts specifically relate to individual tropical cyclone characteristics. Few studies have considered climate change impacts to tropical cyclone characteristics at all, and fewer studies have focused exclusively on the effects on storm surges, i.e., without introducing uncertainties related to sea level rise.…”

Section: Introductionmentioning

confidence: 99%

Projected Climate Change Impacts on Hurricane Storm Surge Inundation in the Coastal United States

Camelo

Mayo

Gutmann

2020

Front. Built Environ.

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The properties of hurricanes directly influence storm surges; however, the implications of projected changes to the climate are unclear. Here, we simulate the storm surges of historical storms under present day and end of century climate scenarios to assess the impact of climate change on storm surge inundation. We simulate 21 storms that impacted the Gulf of Mexico and Atlantic Coasts of the continental U.S. from 2000 to 2013. We find that the volume of inundation increases for 14 storms and the average change for all storms is +36%. The extent of inundation increases for 13 storms, and the average change for all storms is +25%. Notable increases in inundation occur near Texas, Louisiana, Mississippi, the west coast of Florida, the Carolinas, and New Jersey. Our calculations of inundation volume and extent suggest that at the end of the century, we can expect hurricanes to produce larger storm surge magnitudes in concentrated areas, as opposed to surges with lower magnitudes that are widespread. We examine changes in maximum wind speed, minimum central pressure, translation speed, and radius of the 33 ms−1 wind to assess the impacts of individual storm characteristics on storm surge. We find that there is no single storm characteristic that directly relates to storm surge inundation or its climate induced changes. Even when all the characteristics are considered together, the resulting influences are difficult to anticipate. This is likely due to the complexity of the hydrodynamics and interactions with local geography. This illustrates that even as climate change research advances and more is known about projected impacts to hurricanes, implications for storm surge will be difficult to predict without explicit numerical simulation.

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“…The physical parameterizations used in this study include the new Tiedtke cumulus scheme (Zhang and Wang 2017), the WSM6 cloud physics scheme (Hong and Lim 2006), the Noah land surface scheme (Tewari et al 2004), the Yonsei University (YSU) planetary boundary layer (PBL) scheme , the Monin-Obukhov surface layer (Janjić 2001) and the RRTMG scheme for long-and short-wave radiation (Iacono et al 2008). Furthermore, WRF version 4.0 was utilized for comparisons with MPAS-A (see Chen et al 2020). The model physics employed in WRF experiments are identical to those in MPAS-A experiments.…”

Section: Model Configurations and Experimental Set-upmentioning

confidence: 99%

“…During the TC peak season, western North Pacific (WNP) tropical cyclones (TCs) bring strong winds, extreme precipitation and high storm surges to the coastal cities in southern China (Chen et al 2020), posing great threats to public safety and economic activity. Super typhoons Hato (2017) and Mangkhut (2018), for instance, caused at least 23 and 6 casualties, respectively, and hundreds of injuries during their landfalls in southern China.…”

Section: Introductionmentioning

confidence: 99%

Performance of MPAS-A and WRF in predicting and simulating western North Pacific tropical cyclone tracks and intensities

Lui¹,

Tse²,

Tam

et al. 2020

Theor Appl Climatol

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Performances of the Model for Prediction Across Scales-Atmosphere (MPAS-A) in predicting and the Weather Research and Forecasting (WRF) model in simulating western North Pacific (WNP) tropical cyclone (TC) tracks and intensities have been compared. Parallel simulations of the same historical storms that made landfall over southern China, namely, TCs Hope (1979), Gordon (1989), Koryn (1993), Imbudo (2003), Dujuan (2003), Molave (2009), Hato (2017) and Mangkhut (2018), were carried out using WRF and MPAS-A, with initial conditions (and, for WRF, lateral boundary conditions as well) taken from ERA-interim. For MPAS-A, the model was integrated using a standard 60-to-3-km variable-resolution global grid mesh and also on 160-to-2-km grids customized to cover the TC tracks with the highest resolution mesh. The WRF model was integrated using a 15-km/3-km nested domain. No TC bogus scheme was applied when initializing the MPAS-A and WRF simulations. It was found that while TC tracks were reasonably captured by the two models configured variously, the storm intensities were underestimated in general. Given MPAS-A runs were initial value predictions whereas WRF runs were dynamically downscaled from ERA-interim, the finding that MPAS-A has comparable (or slightly better) performance as (than) WRF is noteworthy. To further examine the sensitivity of the MPAS-A TC forecasts to the initial data, additional experiments were carried out for TCs Molave and Hope using ERA5 reanalysis as initial conditions. The ERA5 initialized runs showed significant (slight) improvement in intensity (track) evolution, suggesting that the underestimated TC intensity is likely related to inferior representation of storms in the ERA-interim initial fields. Furthermore, additional runs using another customized 60-to-2-km mesh showed a reasonable improvement in capturing the TC tracks, suggesting that the track forecast accuracy of MPAS-A in TC can be sensitive to the grid resolution in the coarsest part of the variable-resolution mesh used.

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Impacts of climate change on tropical cyclones and induced storm surges in the Pearl River Delta region using pseudo-global-warming method

Cited by 71 publications

References 27 publications

Projected Characteristic Changes of a Typical Tropical Cyclone under Climate Change in the South West Indian Ocean

Projected Characteristic Changes of a Typical Tropical Cyclone under Climate Change in the South West Indian Ocean

Projected Climate Change Impacts on Hurricane Storm Surge Inundation in the Coastal United States

Performance of MPAS-A and WRF in predicting and simulating western North Pacific tropical cyclone tracks and intensities

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