Intercomparison of Empirical Formulations of Maximum Wind Radius in Parametric Tropical Storm Modeling over Zhoushan Archipelago

The Holland (2010) parametric wind model has been extensively utilized in tropical cyclone and storm surge-related coastal hazard mitigation and management studies. The only remaining input parameter, the radius of maximum wind speed (Rm), is usually generated by previously proposed empirical relations which are, however, sensitivity to study areas in producing better performed numerical results. In order to acquire optimal Rm formulations over the region of Zhoushan Archipelago, East China Sea, 16 empirical relations were compiled into the Holland (2010) model to produce time series of the pressure, wind speed, and wind direction in comparison to observational records taken at three stations during the tropical cyclone events of Ampil and Rumbai. Their respective agreements were evaluated by error metrices including the root mean square error, correlation coefficient, mean bias error, and scatter index, whilst the overall performances of the 16 formulations were ranked according to a proposed comprehensive error. In the following order, the Rm formulations of Lu (2012), Zhou (2005), Kato (2018), and Jiang (2008) ranked the best for both events in terms of their minimum comprehensive errors; however, recommendations on the application of specific empirical formulations for the region of Zhoushan Archipelago are also provided herein from the perspective of conservation and accuracy.

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Evaluation of NASA POWER Reanalysis Products to Estimate Daily Weather Variables in a Hot Summer Mediterranean Climate

Agronomy ◽

10.3390/agronomy11061207 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1207

Author(s):

Gonçalo C. Rodrigues ◽

Ricardo P. Braga

Keyword(s):

Wind Speed ◽

Bias Correction ◽

Goodness Of Fit ◽

Mediterranean Climate ◽

Weather Data ◽

Coefficient Of Determination ◽

Mean Bias Error ◽

Bias Error ◽

Weather Variables ◽

Weather Stations

This study aims to evaluate NASA POWER reanalysis products for daily surface maximum (Tmax) and minimum (Tmin) temperatures, solar radiation (Rs), relative humidity (RH) and wind speed (Ws) when compared with observed data from 14 distributed weather stations across Alentejo Region, Southern Portugal, with a hot summer Mediterranean climate. Results showed that there is good agreement between NASA POWER reanalysis and observed data for all parameters, except for wind speed, with coefficient of determination (R2) higher than 0.82, with normalized root mean square error (NRMSE) varying, from 8 to 20%, and a normalized mean bias error (NMBE) ranging from –9 to 26%, for those variables. Based on these results, and in order to improve the accuracy of the NASA POWER dataset, two bias corrections were performed to all weather variables: one for the Alentejo Region as a whole; another, for each location individually. Results improved significantly, especially when a local bias correction is performed, with Tmax and Tmin presenting an improvement of the mean NRMSE of 6.6 °C (from 8.0 °C) and 16.1 °C (from 20.5 °C), respectively, while a mean NMBE decreased from 10.65 to 0.2%. Rs results also show a very high goodness of fit with a mean NRMSE of 11.2% and mean NMBE equal to 0.1%. Additionally, bias corrected RH data performed acceptably with an NRMSE lower than 12.1% and an NMBE below 2.1%. However, even when a bias correction is performed, Ws lacks the performance showed by the remaining weather variables, with an NRMSE never lower than 19.6%. Results show that NASA POWER can be useful for the generation of weather data sets where ground weather stations data is of missing or unavailable.

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An Evaluation of NDFD Weather Forecasts for Wildland Fire Behavior Prediction

Weather and Forecasting ◽

10.1175/waf-d-17-0121.1 ◽

2018 ◽

Vol 33 (1) ◽

pp. 301-315 ◽

Cited By ~ 6

Author(s):

Wesley G. Page ◽

Natalie S. Wagenbrenner ◽

Bret W. Butler ◽

Jason M. Forthofer ◽

Chris Gibson

Keyword(s):

United States ◽

Wind Speed ◽

Relative Humidity ◽

Air Temperature ◽

Wildland Fire ◽

Fire Behavior ◽

The United States ◽

Mean Bias Error ◽

Bias Error ◽

Behavior Prediction

Abstract Wildland fire managers in the United States currently utilize the gridded forecasts from the National Digital Forecast Database (NDFD) to make fire behavior predictions across complex landscapes during large wildfires. However, little is known about the NDFDs performance in remote locations with complex topography for weather variables important for fire behavior prediction, including air temperature, relative humidity, and wind speed. In this study NDFD forecasts for calendar year 2015 were evaluated in fire-prone locations across the conterminous United States during periods with the potential for active fire spread using the model performance statistics of root-mean-square error (RMSE), mean fractional bias (MFB), and mean bias error (MBE). Results indicated that NDFD forecasts of air temperature and relative humidity performed well with RMSEs of about 2°C and 10%–11%, respectively. However, wind speed was increasingly underpredicted when observed wind speeds exceeded about 4 m s−1, with MFB and MBE values of approximately −15% and −0.5 m s−1, respectively. The importance of accurate wind speed forecasts in terms of fire behavior prediction was confirmed, and the forecast accuracies needed to achieve “good” surface head fire rate-of-spread predictions were estimated as ±20%–30% of the observed wind speed. Weather station location, the specific forecast office, and terrain complexity had the largest impacts on wind speed forecast error, although the relatively low variance explained by the model (~37%) suggests that other variables are likely to be important. Based on these results it is suggested that wildland fire managers should use caution when utilizing the NDFD wind speed forecasts if high wind speed events are anticipated.

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A Novel Multiscale Intensity Metric for Evaluation of Tropical Cyclone Intensity Forecasts

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-13-0153.1 ◽

2014 ◽

Vol 71 (4) ◽

pp. 1292-1304 ◽

Cited By ~ 21

Author(s):

Tomislava Vukicevic ◽

Eric Uhlhorn ◽

Paul Reasor ◽

Bradley Klotz

Keyword(s):

Wind Speed ◽

Tropical Cyclone ◽

Microwave Radiometer ◽

Maximum Speed ◽

Forecast Errors ◽

Cyclone Intensity ◽

Maximum Wind ◽

Tropical Cyclone Intensity Forecasts ◽

The Difference ◽

The Impact

Abstract In this study, a new multiscale intensity (MSI) metric for evaluating tropical cyclone (TC) intensity forecasts is presented. The metric consists of the resolvable and observable, low-wavenumber intensity represented by the sum of amplitudes of azimuthal wavenumbers 0 and 1 for wind speed within the TC vortex at the radius of maximum wind and a stochastic residual, all determined at 10-m elevation. The residual wind speed is defined as the difference between an estimate of maximum speed and the low-wavenumber intensity. The MSI metric is compared to the standard metric that includes only the maximum speed. Using stepped-frequency microwave radiometer wind speed observations from TC aircraft reconnaissance to estimate the low-wavenumber intensity and the National Hurricane Center’s best-track (BT) intensity for the maximum wind speed estimate, it is shown that the residual intensity is well represented as a stochastic quantity with small mean, standard deviation, and absolute norm values that are within the expected uncertainty of the BT estimates. The result strongly suggests that the practical predictability of TC intensity is determined by the observable and resolvable low-wavenumber intensity within the vortex. Verification of a set of high-resolution numerical forecasts using the MSI metric demonstrates that this metric provides more informative and more realistic estimates of the intensity forecast errors. It is also shown that the maximum speed metric allows for error compensation between the low-wavenumber and residual intensities, which could lead to forecast skill overestimation and inaccurate assessment of the impact of forecast system change on the skill.

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Characteristics of LDAPS-Predicted Surface Wind Speed and Temperature at Automated Weather Stations with Different Surrounding Land Cover and Topography in Korea

Atmosphere ◽

10.3390/atmos11111224 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1224

Author(s):

Dong-Ju Kim ◽

Geon Kang ◽

Do-Yong Kim ◽

Jae-Jin Kim

Keyword(s):

Wind Speed ◽

Land Cover ◽

Local Heating ◽

Surface Wind ◽

Surface Wind Speed ◽

Mean Bias Error ◽

Bias Error ◽

Flat Terrain ◽

Weather Stations ◽

Grid Points

We investigated the characteristics of surface wind speeds and temperatures predicted by the local data assimilation and prediction system (LDAPS) operated by the Korean Meteorological Administration. First, we classified automated weather stations (AWSs) into four categories (urban flat (Uf), rural flat (Rf), rural mountainous (Rm), and rural coastal (Rc) terrains) based on the surrounding land cover and topography, and selected 25 AWSs representing each category. Then we calculated the mean bias error of wind speed (WE) and temperature (TE) using AWS observations and LDAPS predictions for the 25 AWSs in each category for a period of 1 year (January–December 2015). We found that LDAPS overestimated wind speed (average WE = 1.26 m s−1) and underestimated temperature (average TE = −0.63 °C) at Uf AWSs located on flat terrain in urban areas because it failed to reflect the drag and local heating caused by buildings. At Rf, located on flat terrain in rural areas, LDAPS showed the best performance in predicting surface wind speed and temperature (average WE = 0.42 m s−1, average TE = 0.12 °C). In mountainous rural terrain (Rm), WE and TE were strongly correlated with differences between LDAPS and actual altitude. LDAPS underestimated (overestimated) wind speed (temperature) for LDAPS altitudes that were lower than actual altitude, and vice versa. In rural coastal terrain (Rc), LDAPS temperature predictions depended on whether the grid was on land or sea, whereas wind speed did not depend on grid location. LDAPS underestimated temperature at grid points on the sea, with smaller TE obtained for grid points on sea than on land.

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Estimating Tropical Cyclone Intensity from Infrared Image Data

Weather and Forecasting ◽

10.1175/waf-d-10-05062.1 ◽

2011 ◽

Vol 26 (5) ◽

pp. 690-698 ◽

Cited By ~ 35

Author(s):

Miguel F. Piñeros ◽

Elizabeth A. Ritchie ◽

J. Scott Tyo

Keyword(s):

Wind Speed ◽

Tropical Cyclone ◽

Tropical Cyclones ◽

North Atlantic Ocean ◽

Infrared Image ◽

Ocean Basin ◽

Maximum Wind Speed ◽

Tropical Cyclone Intensity ◽

Cyclone Intensity ◽

Maximum Wind

Abstract This paper describes results from a near-real-time objective technique for estimating the intensity of tropical cyclones from satellite infrared imagery in the North Atlantic Ocean basin. The technique quantifies the level of organization or axisymmetry of the infrared cloud signature of a tropical cyclone as an indirect measurement of its maximum wind speed. The final maximum wind speed calculated by the technique is an independent estimate of tropical cyclone intensity. Seventy-eight tropical cyclones from the 2004–09 seasons are used both to train and to test independently the intensity estimation technique. Two independent tests are performed to test the ability of the technique to estimate tropical cyclone intensity accurately. The best results from these tests have a root-mean-square intensity error of between 13 and 15 kt (where 1 kt ≈ 0.5 m s−1) for the two test sets.

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Comparative assessment of validity of gradient wind models for a translating tropical cyclone

SN Applied Sciences ◽

10.1007/s42452-021-04406-w ◽

2021 ◽

Vol 3 (4) ◽

Author(s):

Yuzuru Eguchi ◽

Yasuo Hattori ◽

Mitsuharu Nomura

Keyword(s):

Wind Speed ◽

Tropical Cyclone ◽

Wind Field ◽

Comparative Assessment ◽

Maximum Wind Speed ◽

Observation Data ◽

High Wind ◽

Maximum Wind ◽

Gradient Wind ◽

The Difference

AbstractAccurate and conservative evaluations of the gradient wind in the free atmosphere are needed to account for high-wind hazards when designing wind resistance for critical infrastructure. This paper compared the validity of three existing gradient wind models to select an appropriate evaluation model, which enables us to accurately compute the asymmetric gradient wind field of a translating tropical cyclone under the condition of a symmetric pressure distribution and a constant translation velocity. The validity of the three models was assessed by evaluating the residuals in momentum conservation equations for the gradient wind under a specific tropical cyclone condition. The magnitude of the residuals was considered to be the measure of error in the gradient wind derived from each model. The results showed that the most frequently used model yielded the largest magnitude of residuals with the lowest maximum wind speed among the three models. The wind characteristics of the three models were validated using archived observation data of hurricanes. The physical reason for the difference in maximum wind speed among the three models was explained by the difference in the streamline feature of the gradient wind field. It was also revealed that the differences in maximum wind speed and magnitude of residuals became more pronounced as the translation speed and the intensity of a tropical cyclone increased. The comparative assessment of the three gradient wind models allowed us to identify the best model for use in conservative wind-resistant design and high-wind risk estimates.

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A Study of the Effects of the Ice-Microphysics, Surface Friction, and Surface Heat Flux on Tropical Cyclone Formation§

The Open Atmospheric Science Journal ◽

10.2174/1874282301307010110 ◽

2013 ◽

Vol 7 (1) ◽

pp. 110-118

Author(s):

Masanori¶ Yamasaki

Keyword(s):

Heat Flux ◽

Wind Speed ◽

Tropical Cyclone ◽

Surface Heat Flux ◽

Numerical Experiments ◽

Surface Friction ◽

Surface Heat ◽

Maximum Wind Speed ◽

Maximum Wind ◽

Ice Microphysics

This paper describes results from numerical experiments which have been performed to understand the effects of the ice microphysics, surface friction, and surface heat flux on tropical cyclone (TC) formation. This study uses the author’s non-hydrostatic model that intends to resolve cumulus convection. However, the horizontal grid size is taken to be somewhat large; 2 km in an area of 600 km x 600 km. A non-uniform coarse grid is used in the surrounding area with 4,000-km square. Several buoyancy perturbations arranged in the west-east direction, and a weak vortex with the maximum wind speed of 5 m s–1 are given at the initial time of the numerical time integrations. It is confirmed from two numerical experiments with and without ice microphysics that the development of a vortex is slower, and TC formation is delayed, in the presence of ice microphysics. It is also confirmed that a vortex can develop even without surface friction. It is shown that a strong vortex with the maximum wind speed of 20~25 m s–1 can be obtained. As expected, however, no eye forms, and further development does not occur. That is, it is confirmed that surface friction is indispensable to eye formation and a very strong TC having an eye. As for the third concern of this study, it is shown that a vortex with the maximum wind speed of about 5 m s–1 does not develop in the absence of the surface heat flux. That is, the surface heat flux plays an important role even in a weak vortex. Important backgrounds and understandings that are concerned with these results are described, based on studies on TCs in the past 50 years.

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Dropsonde Observations of Intense Typhoons in 2017 and 2018 in the T-PARCII Project

10.5194/egusphere-egu2020-12614 ◽

2020 ◽

Author(s):

Kazuhisa Tsuboki ◽

Hiroyuki Yamada ◽

Tadayasu Ohigashi ◽

Taro Shinoda ◽

Kosuke Ito ◽

...

Keyword(s):

Wind Speed ◽

Tropical Cyclone ◽

North Pacific ◽

Western North Pacific ◽

Maximum Wind Speed ◽

Central Pressure ◽

The South ◽

Main Island ◽

Maximum Wind ◽

Typhoon Intensity

Typhoon is a tropical cyclone in the western North Pacific and the South China Sea. It is the most devastating weather system in East Asia. Strong winds and heavy rainfalls associated with a typhoon often cause severe disasters in these regions. There are many cases of typhoon disasters even in the recent decades in these regions. Furthermore, future projections of typhoon activity in the western North Pacific show that its maximum intensity will increase with the climate change. However, the historical data of typhoon (best track data) include large uncertainty after the US aircraft reconnaissance of typhoon was terminated in 1987. Another problem is that prediction of typhoon intensity has not been improved for the last few decades. To improve these problems, in situ observations of typhoon using an aircraft are indispensable. The T-PARCII (Tropical cyclone-Pacific Asian Research Campaign for Improvement of Intensity estimations/forecasts) project is aiming to improve estimations and forecasts of typhoon intensity as well as storm track forecasts.In 2017, the T-PARCII team performed dropsonde observations of intense Typhoon Lan in collaboration with Taiwan DOTSTAR, which was the most intense typhoon in 2017 and caused huge disaster over the central Japan. It was categorized as a supertyphoon by JTWC and as a very intense and huge typhoon by JMA. Typhoon Lan moved northeastward to the east of the Okinawa main island and it was located around 23 N on 21 and 28 N on 22 October. In these two days, we made dropsonde observations at the center of the eye and in the surrounding area of the eyewall. The observations showed that the central pressure of Lan slightly increases from 926 hPa on 21 to 928 hPa on 22 October with the northward movement. On the other hand, The JMA best track data indicate that the central pressure decreases from 935 hPa on 21 to 915 hPa on 22 October. The observations also showed a significant double warm core structure in the eye and the maximum wind speed along the eyewall. The dropsonde data were used for forecast experiments. The result shows an improvement of typhoon track prediction.The T-PARCII team also made aircraft observations of Typhoon Trami during the period from 25 to 28 September 2018 in collaboration with the SATREPS ULAT group and DOTSTAR. Trami was almost stationary during the period to the south of the Okinawa main island. Then, it moved northward and finally made a landfall over the central part of Japan. This also caused a big disaster and electricity was shut down for several days in the central part of Japan. Typhoon Trami showed a drastic change of intensity from 25 to 26 September with a large change of eye size from about a diameter of 60 km to 200 km. Dropsonde observations showed the change of central pressure and maximum wind speed as well as the thermodynamic structure of the eye.

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Uncertainty of Tropical Cyclone Best-Track Information

Weather and Forecasting ◽

10.1175/waf-d-11-00085.1 ◽

2012 ◽

Vol 27 (3) ◽

pp. 715-729 ◽

Cited By ~ 79

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.

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