Improving Regional Model Skills During Typhoon Events: A Case Study for Super Typhoon Lingling Over the Northwest Pacific Ocean

Abstract

The ability of forecasting systems to simulate tropical cyclones is still insufficient, and currently, there is an increased interest in improving model performance for intense tropical cyclones. In this study, the impact of reducing surface drag at high wind speeds on modeling wind and wave conditions during the super Typhoon Lingling event over the northwest Pacific Ocean in 2019 is investigated. The model response with respect to the parameterization for momentum exchange at the ocean surface is demonstrated using a fully coupled regional atmosphere model (the Consortium for Small-Scale Modeling-Climate Limited-area Modeling, CCLM) and a wind wave model (WAM). The active two-way coupling between the atmosphere and ocean waves model is enabled through the introduction of sea state-dependent surface drag into the CCLM and updated winds into the WAM. The momentum exchange with the sea surface is modeled via the dependency of the roughness length (Z0) on the surface stress itself and, when applicable, on the wind speed. Several high-resolution runs are performed using one-way or two-way fully coupled regional atmosphere-wave (CCLM-WAM) models. The model simulations are assessed against the best track data as well as against buoy and satellite observations. The results show that the spectral nudging technique can improve the model’s ability to capture the large-scale circulation, track and intensity of Typhoon Lingling at regional scales. Under the precondition of large-scale constraining, the two-way coupling simulation with the proposed new roughness parameterization performs much better than the simulations used in older studies in capturing the maximum wind speed of Typhoon Lingling due to the reduced drag at extreme wind conditions for the new Z0.

Dynamical Projections of the Mean and Extreme Wave Climate in the Bohai Sea, Yellow Sea and East China Sea

“…In this study, the third-generation WAM cycle 4.7 was used to investigate the impact of climate change on the wave conditions in the BYE area. It maintains the basic physics and numeric of the WAM model used in Li et al (2021) and is run in a shallowwater mode, with depth refraction considered. The wave model is configured to use 24 directions and 25 frequencies ranging from 0.04118 to 0.41145 Hz.…”

The Impact of a Reduced High‐Wind Charnock Parameter on Wave Growth With Application to the North Sea, the Norwegian Sea, and the Arctic Ocean

“…After having tested a range of thresholds between 28 and 33 m s −1 (not shown), we chose Uth = 30 m s −1 , whereas Li et al (2021) chose Uth = 28 m s −1 . We set the transition range σ U = 1 m s −1 in accordance with ECMWF (2020) and Li et al (2021). The minimum Charnock parameter now takes the functional form shown in Figure 1.…”

CMEMS-Based Coastal Analyses: Conditioning, Coupling and Limits for Applications

“…Coupling terms should be adapted to metocean and geometry conditions, looking for consistent interactions across scales, such as for instance, the transfer of heat and momentum at the air-sea interface, that should be appropriate for considered climatology (Komen et al, 1984;Breivik et al, 2015;Staneva et al, 2018b;Wu et al, 2019). An accurate reproduction of interaction processes always benefits from local knowledge, using local datasets to compensate for the incomplete control over these interactions and to overcome the history of stand-alone model (atmospheric and oceanographic) calibration (Walters et al, 2015(Walters et al, , 2019Wiese et al, 2019;Li et al, 2021). In fact, most atmospheric and oceanographic models implemented in coupled configurations result from long-term calibrations performed mostly under uncoupled conditions (e.g., Lionello et al, 1992;Skamarock et al, 2008;Staneva et al, 2015).…”

“…In fact, most atmospheric and oceanographic models implemented in coupled configurations result from long-term calibrations performed mostly under uncoupled conditions (e.g., Lionello et al, 1992;Skamarock et al, 2008;Staneva et al, 2015). This means that the main effects of the interactions (Sakamoto et al, 2019), not explicitly reproduced in the uncoupled conditions, were accounted for by ad-hoc parameterizations (Li et al, 2021). For this reason, huge improvements in coupled experiments, compared to stand-alone analysis, should not be automatically expected at this early stage of the coupling development (Cavaleri et al, 2019b;Cerralbo et al, 2019;Lewis et al, 2019;Saulter et al, 2020;Wiese et al, 2020).…”