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  • Author or Editor: Cheng Qian x
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Chad Shouquan Cheng
,
Guilong Li
,
Qian Li
, and
Heather Auld

Abstract

An automated synoptic weather typing and stepwise cumulative logit/nonlinear regression analyses were employed to simulate the occurrence and quantity of daily rainfall events. The synoptic weather typing was developed using principal component analysis, an average linkage clustering procedure, and discriminant function analysis to identify the weather types most likely to be associated with daily rainfall events for the four selected river basins in Ontario. Within-weather-type daily rainfall simulation models comprise a two-step process: (i) cumulative logit regression to predict the occurrence of daily rainfall events, and (ii) using probability of the logit regression, a nonlinear regression procedure to simulate daily rainfall quantities. The rainfall simulation models were validated using an independent dataset, and the results showed that the models were successful at replicating the occurrence and quantity of daily rainfall events. For example, the relative operating characteristics score is greater than 0.97 for rainfall events with daily rainfall ≥10 or ≥25 mm, for both model development and validation. For evaluation of daily rainfall quantity simulation models, four correctness classifications of excellent, good, fair, and poor were defined, based on the difference between daily rainfall observations and model simulations. Across four selected river basins, the percentage of excellent and good simulations for model development ranged from 62% to 84% (of 20 individuals, 16 cases ≥ 70%, 7 cases ≥ 80%); the corresponding percentage for model validation ranged from 50% to 76% (of 20 individuals, 15 cases ≥ 60%, 6 cases ≥ 70%).

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Qian-Jin Zhou
,
Lei Li
,
Pak-Wai Chan
,
Xue-Ling Cheng
,
Chang-Xing Lan
,
Jia-Chen Su
,
Yu-Qing He
, and
Hong-Long Yang

Abstract

Supertyphoons (STs) and strong convection gales (SCGs) are extremely hazardous weather events over land. Knowledge of their processes is crucial for various applications, such as intensity forecasts of gales and the design of high-rise construction and infrastructure. Here, an observational analysis of two strong SCGs and two STs is presented based on data from the Shenzhen meteorological gradient tower, the tallest in Asia. Differences in the intrinsic physical characteristics measured at each event can be associated with different disaster-causing mechanisms. Wind speeds during STs are comparatively much larger but feature slower variations, while those of SCGs are more abrupt. Unlike that observed during STs, the vertical distribution of wind speeds during SCGs obeys a power law or exponential distribution only within 1-h maximum wind speed windows. In comparison with a Gaussian distribution, a generalized extreme value distribution can better characterize the statistical characteristics of the gusts of both STs and SCGs events. Deviations from Kolmogorov’s −5/3 power law were observed in the energy spectra of both phenomena at upper levels, albeit with differences. Different from what is seen in the ST energy spectrum distribution, a clear process of energy increase and decrease could be seen in SCGs during gale evolution. Nonetheless, both SCGs and STs exhibited a high downward transfer of turbulent momentum flux at a 320 m height, which could be attributed to the pulsation of the gusts rather than to the large-scale base flow.

Significance Statement

Strong gales induced by typhoons and severe convection have potential serious impacts on human society. The current study compares and analyzes the characteristics of the gales induced by the two different weather systems using the data observed by a 356-m-tall tower in South China. This paper also shows the relationship between gusts of the near-surface wind and the turbulent momentum fluxes, thus suggesting a possible mechanism leading to destructive forces in surface winds. In terms of social value, this study would contribute to increase the awareness of gales (the instantaneous wind speed over 17 m s−1) and improve the prediction and prevention of different types of gales, as well as the wind-resistant design of high-rise buildings.

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