Optimization of the parallel semi-Lagrangian scheme in the YHGSM based on the adaptive maximum wind speed

Author(s):  
Dazheng Liu ◽  
Jianping Wu ◽  
Tao Jiang ◽  
Yingjie Wang ◽  
Xiaotian Pan ◽  
...  
Author(s):  
Masataka YAMAGUCHI ◽  
Kunimitsu INOUCHI ◽  
Yoshihiro UTSUNOMIYA ◽  
Hirokazu NONAKA ◽  
Yoshio HATADA ◽  
...  

Author(s):  
Masafumi KIMIZUKA ◽  
Tomotsuka TAKAYAMA ◽  
Hiroyasu KAWAI ◽  
Masafumi MIYATA ◽  
Katsuya HIRAYAMA ◽  
...  

2019 ◽  
Vol 147 (1) ◽  
pp. 221-245 ◽  
Author(s):  
Guotu Li ◽  
Milan Curcic ◽  
Mohamed Iskandarani ◽  
Shuyi S. Chen ◽  
Omar M. Knio

This study focuses on understanding the evolution of Hurricane Earl (2010) with respect to random perturbations in the storm’s initial strength, size, and asymmetry in wind distribution. We rely on the Unified Wave Interface-Coupled Model (UWIN-CM), a fully coupled atmosphere–wave–ocean system to generate a storm realization ensemble, and use polynomial chaos (PC) expansions to build surrogate models for time evolution of both the maximum wind speed and minimum sea level pressure in Earl. The resulting PC surrogate models provide statistical insights on probability distributions of model responses throughout the simulation time span. Statistical analysis of rapid intensification (RI) suggests that initial perturbations having intensified and counterclockwise-rotated winds are more likely to undergo RI. In addition, for the range of initial conditions considered RI seems mostly sensitive to azimuthally averaged maximum wind speed and asymmetry orientation, rather than storm size and asymmetry magnitude; this is consistent with global sensitivity analysis of PC surrogate models. Finally, we combine initial condition perturbations with a stochastic kinetic energy backscatter scheme (SKEBS) forcing in the UWIN-CM simulations and conclude that the storm tracks are substantially influenced by the SKEBS forcing perturbations, whereas the perturbations in initial conditions alone had only limited impact on the storm-track forecast.


Climate ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 64 ◽  
Author(s):  
Tayyebeh Mesbahzadeh ◽  
Maryam Mirakbari ◽  
Mohsen Mohseni Saravi ◽  
Farshad Soleimani Sardoo ◽  
Nir Y. Krakauer

Natural disasters such as dust storms are random phenomena created by complicated mechanisms involving many parameters. In this study, we used copula theory for bivariate modeling of dust storms. Copula theory is a suitable method for multivariate modeling of natural disasters. We identified 40 severe dust storms, as defined by the World Meteorological Organization, during 1982–2017 in Yazd province, central Iran. We used parameters at two spatial vertical levels (near-surface and upper atmosphere) that included surface maximum wind speed, and geopotential height and vertical velocity at 500, 850, and 1000 hPa. We compared two bivariate models based on the pairs of maximum wind speed–geopotential height and maximum wind speed–vertical velocity. We determined the bivariate return period using Student t and Gaussian copulas, which were considered as the most suitable functions for these variables. The results obtained for maximum wind speed–geopotential height indicated that the maximum return period was consistent with the observed frequency of severe dust storms. The bivariate modeling of dust storms based on maximum wind speed and geopotential height better described the conditions of severe dust storms than modeling based on maximum wind speed and vertical velocity. The finding of this study can be useful to improve risk management and mitigate the impacts of severe dust storms.


2020 ◽  
Vol 33 (7) ◽  
pp. 2793-2816 ◽  
Author(s):  
Gangfeng Zhang ◽  
Cesar Azorin-Molina ◽  
Deliang Chen ◽  
Jose A. Guijarro ◽  
Feng Kong ◽  
...  

AbstractAssessing change in daily maximum wind speed and its likely causes is crucial for many applications such as wind power generation and wind disaster risk governance. Multidecadal variability of observed near-surface daily maximum wind speed (DMWS) from 778 stations over China is analyzed for 1975–2016. A robust homogenization protocol using the R package Climatol was applied to the DMWS observations. The homogenized dataset displayed a significant (p < 0.05) declining trend of −0.038 m s−1 decade−1 for all China annually, with decreases in winter (−0.355 m s−1 decade−1, p < 0.05) and autumn (−0.108 m s−1 decade−1; p < 0.05) and increases in summer (+0.272 m s−1 decade−1, p < 0.05) along with a weak recovery in spring (+0.032 m s−1 decade−1; p > 0.10); that is, DMWS declined during the cold semester (October–March) and increased during the warm semester (April–September). Correlation analysis of the Arctic Oscillation, the Southern Oscillation, and the west Pacific modes exhibited significant correlation with DMWS variability, unveiling their complementarity in modulating DMWS. Further, we explored potential physical processes relating to the atmospheric circulation changes and their impacts on DMWS and found that 1) overall weakened horizontal airflow [large-scale mean horizontal pressure gradient (from −0.24 to +0.02 hPa decade−1) and geostrophic wind speed (from −0.6 to +0.6 m s−1 decade−1)], 2) widely decreased atmospheric vertical momentum transport [atmospheric stratification thermal instability (from −3 to +1.5 decade−1) and vertical wind shear (from −0.4 to +0.2 m s−1 decade−1)], and 3) decreased extratropical cyclones frequency (from −0.3 to 0 month decade−1) are likely causes of DMWS change.


2014 ◽  
Vol 14 (5) ◽  
pp. 1371-1381 ◽  
Author(s):  
P. R. Shanas ◽  
V. Sanil Kumar

Abstract. Temporal variations in wind speed and significant wave height (SWH) at a location in the eastern Arabian Sea are studied using ERA-Interim reanalysis data from 1979 to 2012. A shallow water location is selected for the study since measured buoy data are available close to the location for comparison with the reanalysis data. The annual mean wind speed shows a statistically significant decreasing trend of 1.5 cm s−1 year−1, whereas a statistically insignificant increasing trend of 3.6 cm s−1 year−1 is observed for annual maximum wind speed due to the local events that altered the trend in annual maximum wind speed. Weakening of SWH during one of the peak monsoon months (August) is identified from the monthly analysis of SWH, which shows a higher upward trend in SWH during the southwest monsoon period, with an exception during August. The annual mean SWH shows a slight upward trend (0.012 cm year−1), whereas a larger upward trend (1.4 cm year−1) is observed for annual maximum SWH. Both identified trends are statistically insignificant. The influence of tropical cyclone activity is also studied and it is found that the maximum SWH and wind speed during 1996 are directly related to the cyclonic event.


2006 ◽  
Vol 14 (2) ◽  
pp. 145-155
Author(s):  
Takafumi AMANO ◽  
Osamu AKETA ◽  
Takeshi SUZUKI

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