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.

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.

Uncertainty of Tropical Cyclone Best-Track Information

2012 ◽  
Vol 27 (3) ◽  
pp. 715-729 ◽  
Author(s):  
Ryan D. Torn ◽  
Chris Snyder
Keyword(s):  
Wind Speed ◽  
Tropical Cyclone ◽  
Maximum Wind Speed ◽  
Sea Level Pressure ◽  
Position Uncertainty ◽  
Maximum Wind ◽  
Intensity Information ◽  
Weather And Climate ◽  
The Mean ◽  
National Hurricane Center

Abstract With the growing use of tropical cyclone (TC) best-track information for weather and climate applications, it is important to understand the uncertainties that are contained in the TC position and intensity information. Here, an attempt is made to quantify the position uncertainty using National Hurricane Center (NHC) advisory information, as well as intensity uncertainty during times without aircraft data, by verifying Dvorak minimum sea level pressure (SLP) and maximum wind speed estimates during times with aircraft reconnaissance information during 2000–09. In a climatological sense, TC position uncertainty decreases for more intense TCs, while the uncertainty of intensity, measured by minimum SLP or maximum wind speed, increases with intensity. The standard deviation of satellite-based TC intensity estimates can be used as a predictor of the consensus intensity error when that consensus includes both Dvorak and microwave-based estimates, but not when it contains only Dvorak-based values. Whereas there has been a steady decrease in seasonal TC position uncertainty over the past 10 yr, which is likely due to additional data available to NHC forecasters, the seasonal TC minimum SLP and maximum wind speed values are fairly constant, with year-to-year variability due to the mean intensity of all TCs during that season and the frequency of aircraft reconnaissance.

scholarly journals Joint Use of Spaceborne Microwave Sensor Data and CYGNSS Data to Observe Tropical Cyclones

2020 ◽  
Vol 12 (19) ◽  
pp. 3124
Author(s):  
Shiwei Wang ◽  
Shuzhu Shi ◽  
Binbin Ni
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Inner Core ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Maximum Wind Speed ◽  
Sensor Data ◽  
Maximum Wind ◽  
Microwave Sensor ◽  
The Mean

The joint use of spaceborne microwave sensor data and Cyclone Global Navigation Satellite System (CYGNSS) data to observe tropical cyclones (TCs) is presented in this paper. The Soil Moisture Active and Passive (SMAP) radiometer was taken as an example of a spaceborne microwave sensor, and its data and the CYGNSS data were fused to fix the center of a TC and to measure the maximum wind speed around the TC inner core. This process included data preprocessing, image fusion, determination of the TC center position, and the estimation of the TC’s intensity. For all of the observed hurricanes, the experimental results demonstrated that the proposed method obtains a more complete structure of the TC and can measure the surface wind speed around the TC inner core at more frequent intervals compared to the case where the SMAP radiometer data or the CYGNSS data are employed alone. Furthermore, when comparing the TC tracks obtained by the proposed method with the best tracks provided by the National Hurricane Center (NHC), we found that the mean absolute error values ranged between 18.4 and 46 km, the standard deviation varied between 15.1 and 28.2 km, and both of these were smaller than the values obtained by only using the CYGNSS data. In addition, when comparing the maximum wind speed around the TC inner core obtained by the proposed method with the best track peak winds estimated by the NHC, we found that the mean absolute error values ranged between 7.7 and 15.7 m/s, the root-mean-square difference values varied between 8.6 and 18 m/s, the correlation coefficients varied between 0.1782 and 0.9877, the bias values varied between −8.5 and 4.5 m/s, and all of these values were smaller in most cases, than those obtained by only using the CYGNSS data.

scholarly journals Estimation of the Upper-Layer Rotation and Maximum Wind Speed of Tropical Cyclones via Satellite Imagery

2011 ◽  
Vol 50 (3) ◽  
pp. 750-766 ◽  
Author(s):  
Chun-Chieh Chao ◽  
Gin-Rong Liu ◽  
Chung-Chih Liu
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Satellite Imagery ◽  
Satellite Images ◽  
Rotation Speed ◽  
Maximum Wind Speed ◽  
Maximum Wind ◽  
The Mean ◽  
Wind Intensity ◽  
The Relationship

Abstract The movement of convective rainbands embedded in a tropical cyclone (TC) is usually derived from satellite images via the atmospheric motion vector (AMV) method or through the calculation of a radar’s echo track. In estimating the rotation speed of a TC rainband, however, the land-based radar can only detect approaching tropical cyclones within the vicinity. The AMV method is unable to fully account for the TC eyewall movement, thus making it difficult to estimate the TC intensity. The widely used method in estimating the TC maximum wind speed is the Dvorak technique in which the cloud pattern is extracted from only one image. In this study, the rainband rotation speeds are computed via satellite imagery and further applied in estimating the TC maximum wind speed. In contrast to previous research, this study adopts an innovative method by using two subsequent geostationary satellite images. The TC spin rates observed by weather satellites could often be seen to be positively related to the TC intensity. Analyses of the relationship between the typhoon wind intensity and estimated rotation speed at the 130–260-km ring via infrared channels are conducted for major typhoon cases that occurred during 2000–05 in the northwestern Pacific Ocean. Results show that the correlation between the wind intensity and estimated rotation speeds is strong for most of the cases. The highest R2 value from the individual cases could reach 0.93, and on an annual basis it could attain a value of 0.67. The mean R2 value for the 2000–05 dataset was roughly 0.53. The correlation between the wind intensity and estimated rotation speeds is further improved by factoring in the previous 6-h average rotation speeds. A regression equation is derived from the chosen typhoon cases between 2000 and 2005, which is utilized in verifying the major typhoon occurrences during 2006–08. The mean absolute error (MAE) of the hourly and 6-h average intensity estimates during 2000–08 was 20 and 18.7 kt, respectively (1 kt ≃ 0.5 m s−1). The best verification result occurred during 2008, for which the R2 value and MAE could reach 0.7 and 15.6, respectively. These research results demonstrate the suitability of using geostationary satellite image data in estimating the maximum wind speed. Nevertheless, the drawback of this study is that sometimes the rotation speeds will become slower when tropical cyclones mature because of the strong outflow of the secondary circulation. It is assumed that the relationship between the estimated rotation speeds and wind intensity can be further improved if the outflow speed of the tropical cyclones is also considered.

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.

Sign in / Sign up

Export Citation Format

Share Document