Numerical experiments of storm winds, surges, and waves on the southern coast of Korea during Typhoon Sanba: the role of revising wind force

Abstract

Abstract. The southern coastal area of Korea has often been damaged by storm surges and waves due to the repeated approach of strong typhoons every year. The integrated model system is applied to simulate typhoon-induced winds, storm surges, and surface waves in this region during Typhoon Sanba in 2012. The TC96 planetary boundary layer wind model is used for atmospheric forcing and is modified to incorporate the effect of the land's roughness on the typhoon wind. Numerical experiments are carried out to investigate the effects of land-dissipated wind on storm surges and waves using the three-dimensional, unstructured grid, Finite Volume Coastal Ocean Model (FVCOM), which includes integrated storm surge and wave models with highly refined grid resolutions along the coastal region of complex geometry and topography. Compared to the measured data, the numerical models have successfully simulated storm winds, surges, and waves. Better agreement between the simulated and measured storm winds has been found when considering the effect of wind dissipation by land roughness. In addition, this modified wind force leads to clearly improved results in storm surge simulations, whereas the wave results have shown only slight improvement. The study results indicate that the effect of land dissipation on wind force plays a significant role in the improvement of water level modeling inside coastal areas.

Optimisation technique for improving wind downscaling results by estimating roughness parameters

“…Reservoirs 0.00025 [38] 0.0001 [38] -0.005 [40] 0 [28,39] -AES Estuaries 0.0002 [41] 0.0001 [38] -0.01 [31] 0 [28,39] -ALC Coastal Lagoons 0.005 [40] 0.0001 [38] -0.01 [31] 0 [28,39] -ALG Water body. Lakes and Lagoons 0.0005 [42] 0.0001 [38] -0.005 [40] 0 [28,39] -AMO Seas and Oceans 0.0002 [41] 0.0001 [38] -0.03 [35] 0 [28,39] -ARR Rocky Outcrops and Rocks 0.005 [31] 0.0003 [43] -0.18 [44] 0.03 [28] 0 [28] -0.96 [28] CCH Screes 0.1 [35] 0.05 [45] -0.15 [46] 0.6 [47] 0.56 [47] -0.66 [47] CLC Quaternary lava ow 0.0286 [48] 0.0013 [48] -0.0735 [48] 0.15 [28] 0 [28] -0.4 [28] CNF Forest. Conifers 1.28 [49] 0.25 [50] -1.93 [51] 13.1 [52,…”

Characterization of Geographical and Meteorological Parameters

“…(a) [24], (b) [73], (c) [3], (d) [90], (e) [6], ( f ) [10], (g) [12], (h) [4], (i) [75], ( j) [98], (k) [101], (l) [51], (m) [13], (n) [79], (o) [5], (p) [18], (q) [36], (r) [67], (s) [86,87], (t) [83], (u) [46],…”

“…Also in Table 2.1, there are some values of z 0 and d arising from applications of specific numerical models with their land cover databases. For example, [75] used them in lakes and lagoons; [101] in rocky outcrops and rocks, evergreen forests, salt marshes, wetlands, bare soils, and artificial coverages; [21] in evergreen forests; [57] used in no citrus fruit trees; [82] in grasslands; and [81] in ravine and road, parking or unvegetated pedestrian areas.…”

Three-dimensional numerical simulation of mud flow from a tailing dam failure across complex terrain

“…Another key factor that makes it difficult to analyze and predict tailing run-out routing by numerical modeling is the difficulty of building the boundary of large-scale complex downstream terrains. Recently, some initial work, such as laboratory experiments and relatively simple deposition simulations of tailing fluid, has been attempted (Mizani et al, 2013;Zhang et al, 2015;Babaoglu and Simms, 2017;Gao and Fourie, 2019;Luo et al, 2017). These studies discussed the flow and rheological properties of tailing fluids in detail but did not take into account the influence of real terrain on the movement distance of tailing fluids.…”