scholarly journals Decision tree-based detection of blowing snow events in the European Alps

2021 ◽  
Vol 25 (7) ◽  
pp. 3783-3804
Author(s):  
Zhipeng Xie ◽  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Zeyong Hu ◽  
Genhou Sun ◽  
...  
Keyword(s):  
Wind Speed ◽  
Decision Tree ◽  
Maximum Wind Speed ◽  
Optimal Size ◽  
European Alps ◽  
Blowing Snow ◽  
Spatiotemporal Resolution ◽  
Maximum Wind ◽  
Wind Speed Maximum

Abstract. Blowing snow processes are crucial in shaping the strongly heterogeneous spatiotemporal distribution of snow and in regulating subsequent snowpack evolution in mountainous terrain. Although empirical formulae and constant threshold wind speeds have been widely used to estimate the occurrence of blowing snow in regions with sparse observations, the scarcity of in situ observations in mountainous regions contrasts with the demands of models for reliable observations at high spatiotemporal resolution. Therefore, these methods struggle to accurately capture the high local variability of blowing snow. This study investigated the potential capability of the decision tree model (DTM) to detect blowing snow in the European Alps. The DTMs were constructed based on routine meteorological observations (mean wind speed, maximum wind speed, air temperature and relative humidity) and snow measurements (including in situ snow depth observations and satellite-derived products). Twenty repetitions of a random sub-sampling validation test with an optimal size ratio (0.8) between the training and validation subsets were applied to train and assess the DTMs. Results show that the maximum wind speed contributes most to the classification accuracy, and the inclusion of more predictor variables improves the overall accuracy. However, the spatiotemporal transferability of the DTM might be limited if the divergent distribution of wind speed exists between stations. Although both the site-specific DTMs and site-independent DTM show great ability in detecting blowing snow occurrence and are superior to commonly used empirical parameterizations, specific assessment indicators varied between stations and surface conditions. Events for which blowing snow and snowfall occurred simultaneously were detected the most reliably. Although models failed to fully reproduce the high frequency of local blowing snow events, they have been demonstrated to be a promising approach requiring limited meteorological variables and have the potential to scale to multiple stations across different regions.

scholarly journals Decision tree-based detection of blowing snow events in the European Alps

2021 ◽  
Author(s):  
Zhipeng Xie ◽  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Zeyong Hu ◽  
Genhou Sun ◽  
...  
Keyword(s):  
Wind Speed ◽  
Decision Tree ◽  
Maximum Wind Speed ◽  
Optimal Size ◽  
European Alps ◽  
Blowing Snow ◽  
Spatiotemporal Resolution ◽  
Maximum Wind ◽  
Mountainous Regions ◽  
Wind Speed Maximum

Abstract. Blowing snow processes are crucial in shaping the strongly heterogeneous spatiotemporal distribution of snow, and in regulating subsequent snowpack evolution in mountainous terrain. Although empirical formulae and a constant threshold wind speed have been widely used to estimate the occurrence of blowing snow in regions with sparse observations, the scarcity of in-situ observations in mountainous regions contrasts with the demands of models for reliable observations at high spatiotemporal resolution. Therefore, these methods struggle to accurately capture the high local variability of blowing snow. This study investigated the potential capability of the decision tree model (DTM) to detect blowing snow in the European Alps. The DTMs were constructed based on routine meteorological observations (mean wind speed, maximum wind speed, air temperature and relative humidity). Twenty repetitions of random sub-sampling validation test with an optimal size ratio (0.8) between the training and validation subset were applied to train and assess the DTMs. Results show that the maximum wind speed contributes most to the classification accuracy, and the inclusion of more predictor variables improves the overall accuracy. However, the spatiotemporal transferability of the DTM might be limited if divergent distributions exist between stations. Although both the site-specific DTMs and site-independent DTM show strong performance for accurately detecting blowing snow, specific assessment indicators varied between stations and surface conditions. Events for which blowing snow and snowfall occurred simultaneously were detected the most reliably. Although models failed to fully reproduce the high frequency of local blowing snow events, they have been demonstrated a promising approach requiring limited meteorological variables and have the potential to scale to multiple stations across different regions.

Analysis of Boundary Layer Wind Field Statistical Characteristics and Reference Wind Pressure in Wenzhou District

2011 ◽  
Vol 368-373 ◽  
pp. 1424-1430
Author(s):  
Jian Jia Wu ◽  
Wen Hai Shi
Keyword(s):  
Wind Speed ◽  
Wind Field ◽  
Wind Pressure ◽  
Maximum Wind Speed ◽  
Statistical Characteristics ◽  
Annual Maximum ◽  
Maximum Wind ◽  
Wind Speed Maximum ◽  
Mean Wind Speed ◽  
Extreme Wind Speed

Based on large amount of meteorological wind field records observed in Wenzhou district, this paper analyzed the annual maximum wind speed (maximum 10 minute mean wind speed), annual extreme wind speed (maximum 3 seconds mean wind speed), reference wind pressure and wind field characteristics of typhoon in Wenzhou. The results shows that the annual maximum wind speed have a decreased trend on the whole in different areas of Wenzhou, and the trend in coastal area is more obvious than that in inland areas; the annual maximum wind speed in different areas of Wenzhou is unsteady and the typhoons have great effect on it; the value of reference wind pressure in Dongtou is greater than the value given by the design load code of China (GB50009-2001, 2002), but the values of other areas are less than the value of Code. Based on the wind field of three typhoon records, some significant results about the variation and routine characteristics of typhoon are also discussed.

scholarly journals Estimating the Intensity of Hurricanes from Historical Radar Data Using the Hyperbolic-logarithmic approximation of Spiral Rainbands

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
Boris S. Yurchak ◽  
Keyword(s):  
Wind Speed ◽  
Logarithmic Spiral ◽  
Radar Data ◽  
Maximum Wind Speed ◽  
Logarithmic Approximation ◽  
Maximum Wind ◽  
Radar Signature ◽  
The Mean ◽  
Spiral Rainbands

To increase the amount of information on the intensities of tropical cyclones (TC) used in climate research, the possibility of additional estimates of the intensity of a TC by exploring historical data of conventional (non-Doppler) airborne and coastal radars is considered. Based on the hyperbolic-logarithmic spiral (HLS) model of the streamline in the TC, an assessment of the maximum wind speed in hurricanes Cleo (1958), Carolina (1975) and Alicia (1983) was made. Literature sources containing radar signatures of spiral cloud-rain bands (SCRBs) of these hurricanes and the corresponding results of synchronous aircraft soundings were used. The HLS-approximation of the radar signature of the SCRB consisted of determining the “expected” (mean) spiral of a set of HLSs “fitted” into a pattern of the signature. The maximum wind speed was determined from coefficients of the mean HLS. The estimates obtained were in satisfactory agreement with in situ aircraft measurements. The considered examples manifest the possibility of applying the HLS-approximation to determine the intensity of hurricanes by using the historical radar data with satisfactory accuracy.

A COMPREHENSIVE STUDY ON RADIUS TO TYPHOON-GENERATED MAXIMUM WIND SPEED BASED ON DATA ANALYSES

2020 ◽  
Vol 76 (2) ◽  
pp. I_223-I_228
Author(s):  
Masataka YAMAGUCHI ◽  
Kunimitsu INOUCHI ◽  
Yoshihiro UTSUNOMIYA ◽  
Hirokazu NONAKA ◽  
Yoshio HATADA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Maximum Wind Speed ◽  
Maximum Wind ◽  
Data Analyses ◽  
Comprehensive Study

EFFECTS OF MAXIMUM WIND SPEED RADIUS AND TRANSLATION SPEED OF SCENARIO TYPHOON ON STORM SURGE AND WAVE

2018 ◽  
Vol 74 (2) ◽  
pp. I_583-I_588
Author(s):  
Masafumi KIMIZUKA ◽  
Tomotsuka TAKAYAMA ◽  
Hiroyasu KAWAI ◽  
Masafumi MIYATA ◽  
Katsuya HIRAYAMA ◽  
...  
Keyword(s):  
Wind Speed ◽  
Storm Surge ◽  
Maximum Wind Speed ◽  
Translation Speed ◽  
Maximum Wind

scholarly journals Uncertainty Propagation in Coupled Atmosphere–Wave–Ocean Prediction System: A Study of Hurricane Earl (2010)

2019 ◽  
Vol 147 (1) ◽  
pp. 221-245 ◽  
Author(s):  
Guotu Li ◽  
Milan Curcic ◽  
Mohamed Iskandarani ◽  
Shuyi S. Chen ◽  
Omar M. Knio
Keyword(s):  
Wind Speed ◽  
Initial Conditions ◽  
Uncertainty Propagation ◽  
Storm Track ◽  
Coupled Model ◽  
Surrogate Models ◽  
Maximum Wind Speed ◽  
Track Forecast ◽  
Initial Strength ◽  
Maximum Wind

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.

scholarly journals Joint Modeling of Severe Dust Storm Events in Arid and Hyper Arid Regions Based on Copula Theory: A Case Study in the Yazd Province, Iran

Climate ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 64 ◽  
Author(s):  
Tayyebeh Mesbahzadeh ◽  
Maryam Mirakbari ◽  
Mohsen Mohseni Saravi ◽  
Farshad Soleimani Sardoo ◽  
Nir Y. Krakauer
Keyword(s):  
Wind Speed ◽  
Natural Disasters ◽  
Return Period ◽  
Vertical Velocity ◽  
Geopotential Height ◽  
Dust Storms ◽  
Maximum Wind Speed ◽  
Near Surface ◽  
Copula Theory ◽  
Maximum Wind

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.

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