Vulnerability to typhoons: A comparison of consequence and driving factors between Typhoon Hato (2017) and Typhoon Mangkhut (2018)

Understanding the spatial disparity in socio-economic recovery of coastal communities following typhoon disasters

The increasing risk of climate change in the Anthropocene underscores the importance and urgency of enhancing resilience to climate-related disasters. However, the assessment of resilience to disasters with traditional statistical data is spatially inexplicit and timeliness inadequate, and the determinants of resilience remain unclear. In this study, we employed spatially detailed daily nighttime light images to assess socio-economic disturbance and track near real-time recovery of coastal communities in Southeast China following super typhoon Meranti. Furthermore, we constructed a "exposure-sensitivity-adaptive capacity" framework to explore the role of key factors in shaping spatiotemporal patterns of recovery. Our case study showed a significant spatial disparity in socio-economic recovery in the post-typhoon period. Low-urbanized areas recovered relatively rapidly with the weakest socio-economic disturbance they suffered, and middle-urbanized areas experienced the slowest recovery despite the disruption being moderate. Remarkably, high-urbanized areas were the most severely impacted by the typhoon but recovered fast. The exposure to hazard, socio-economic sensitivity, and adaptive capacity in communities explained well the spatial disparity of resilience to the typhoon. Maximum wind speed, percentage of the elderly, and percentage of low-income population significantly negatively correlated with resilience, whereas commercial activity intensity, spatial accessibility of hospitals, drainage capacity, and percentage of green open space showed significantly positive relationships with resilience. Notably, the effects of key factors on resilience were spatially heterogeneous. For instance, maximum wind speed exhibited the strongest influence on resilience in middle-urbanized areas, while the effect of commercial activity intensity was most pronounced in low-urbanized areas. Conversely, spatial accessibility of hospitals and drainage capacity showed the strongest influence in high-urbanized areas. Our study highlights the necessity of linking post-disaster recovery with intensity of hazard, socio-economic sensitivity, and adaptive capacity to understand community resilience for better disaster risk reduction.

Monitoring tree canopy dynamics across heterogeneous urban habitats: A longitudinal study using multi-source remote sensing data

Urban trees have attracted increasing attention to serve as a green prescription for addressing various challenges facing human society like climate change and environmental deterioration. However, without healthy growth of urban trees, they cannot service any environmental, social, and economic benefits in a sustainable manner. By monitoring the canopy development, the tree growth dynamics in different urban habitats can be detected and appropriate management approaches can be executed. Using the Kowloon Peninsula, Hong Kong, as a case, this study explores how remote sensing data can help monitor and understand the impacts of heterogeneous urban habitats on tree canopy dynamics. Four algorithms based on WorldView-2 satellite image are compared to optimize the canopy segmentation. Then the individual tree canopy is integrated with Sentinel-2 satellite data to obtain canopy growth dynamics for each season from 2016 to 2020. Three indicators are applied to reflect tree canopy status, including the fluorescence correction vegetation index (FCVI, tracking leaf chlorophyll density), the soil adjusted total vegetation index (SATVI, measuring the density of woody branches and twigs), and the normalised difference phenology index (NDPI, capturing canopy water content). And four heterogeneous habitats where urban trees stand are specified. The results revealed that urban trees show varying canopy growth status, in a descending order from natural terrains, parks, residential lands, to road verges, suggesting that urban habitats curtail trees' growth significantly. Additionally, two super-typhoons in 2017 and 2018, respectively, caused serious damages to tree canopy. Relevant resiliency of tree varies, echoing the sequence of canopy growth status with those in road verges the least resilient. This study shows how remote sensing data can be used to provide a better understanding of long-term tree canopy dynamics across large-scale heterogeneous urban habitats, which is key to monitoring and maintaining the health and growth of urban trees.

Future sea level rise exacerbates compound floods induced by rainstorm and storm tide during super typhoon events: A case study from Zhuhai, China

Compound floods are becoming a growing threat in coastal cities against a background of global sea level rise (SLR), and may cause increasing impacts on societal safety and economy. How to quantify the impact of SLR and compound effects among various flood causes on compound flood have become important challenges. We propose a modeling framework which integrates atmospheric, storm tide and urban flood (IASTUF) models to characterize the various physical processes related to compound flood. Future SLR projections under various shared socioeconomic and respective concentration pathway emission scenarios are considered. Hengqin Island (Zhuhai City, China) frequently experiences typhoon conditions combined with rainstorm and storm surge events. Its population has increased more than sixfold during the past decade, stimulating urgent demands for assessments of the potential risks associated with future compound floods in the context of potential SLR. A compound flood event in northern Hengqin Island, caused by the super typhoon Mangkhut in 2018, is selected as a case study to verify the proposed modeling framework. Results show that the IASTUF modeling framework can capture well the combined processes of typhoon, rainstorm, storm tide and inland flooding and demonstrates good performance in quantifying compound flood magnitudes. Compared to the current scenario, the node flooding volume (from the drainage system) and the maximum inundation area (with inundation depths >1 m) in 2050 are projected to increase by 20-26 % and 41-85 %, respectively, and these increases rise to 46-84 % and 23-71 times by 2100. The inundation volumes and water depths due to compound events are larger than the sum of those caused by the corresponding single-cause events, indicating that concurrent rainstorm and storm surge induce positive compound effects on flood magnitude. These findings can provide guidance for the management and mitigation of future compound flood hazards driven by super typhoon events.

Impact of uncertainty induced by fatality function on future tropical cyclone risk assessment

Tropical cyclones (TCs) are among the deadliest extreme events occurring under a warming climate. Future TC risk assessment depend on TC projection from climate models and impact function relating TC to its possible consequence. Few studies have explored the uncertainty of impact function in future TC risk assessment compared to uncertainty in future TC characteristics. In this study, we investigate the uncertainty in TC fatality risk assessment induced by geographic and TC category-dependence of fatality function. We focus on all provinces in the mainland of China with historically recorded TC-induced fatalities and examine their TC fatality risks by assessing the difference in the annual average fatalities between current and future climate conditions. Synthetic TCs derived from four climate models and fatality functions parameterized from three grouped historical TC disaster datasets are used to observe the uncertainty induced by climate model and fatality function. Results show that the changes in the TC frequency, wind, TC-induced rainfall intensity, and exposure due to climate change in each province are dependent on the climate models. And the changes in the annual average fatality of each province are dependent on both the climate models and fatality functions. Climate models play a dominant role in determining the spatial pattern of future risk, while the fatality functions can alter the direction and magnitude of the risk change for certain provinces. Our results highlight the role of fatality function in detecting future TC risk under climate change, and inspire further TC impact studies that consider the heterogeneity of both climate conditions and geographical locations.

The contribution of typhoon local and remote forcings to storm surge along the Makou-Dahengqin tidal reach of Pearl River Estuary

Due to the interaction between upstream discharge and astronomical tides in tidal reaches, the typhoon-induced storm surge processes are quite different from that in other coastal regions. Investigating the contributions of driving factors is essential to deepen the understanding of storm surges in tidal reaches. In this study, a coupled hydrological-hydrodynamic storm surge model is first developed to explore the main driving factors of storm surges in Makou-Dahengqin tidal reach during the three most influential typhoon events (Hagupit, Hato and Mangkhut). After that, the machine learning method is integrated to assess the water level in response to storm surges. The driving factors of storm surge are decomposed into remote forcing (upstream discharge, astronomical tide) and direct local forcing (wind stress, atmospheric pressure). The relative contributions of remote forcing are the highest near the estuary mouth. The relative contributions of local forcing to water levels are higher in the sections 40-80 km away from the estuary mouth. The most impacting period of the local forcing is about 48 h, while the relative contributions of remote forcing increase before and after the period. The local forcing-induced surges are highest at the upper reach during Hagupit, while it causes extreme surges at the estuary mouth during more powerful typhoons (Hato, Mangkhut). The maximum water levels and remote forcing-induced maximum surges invariably appear at the upper reach. However, when local and remote forcings are in the same phase, the maximum storm surge appears in the lower reaches during Hato. If local and remote forcings are in the same phase, the peak water levels would be amplified by up to 15.04 %, 36.23 % and 40.68 % during Hagupit, Hato and Mangkhut, respectively. Moreover, Remote forcing contributes more to the amplification of peak water levels than local forcing does, accounting for 68.5 % to 100 %.