Dataset on Wind and Waves to Study Tropical Cyclones
M. V. Yurovskaya
Marine Hydrophysical Institute of RAS, Sevastopol, Russian Federation
e-mail: mvkosnik@gmail.com
Abstract
Purpose. The aim of the paper is to systematize information on the characteristics of the wind field and the wave heights along the altimeter tracks in the region of tropical cyclones, as well as to visualize this information in detail for assessing the data availability and applicability to a particular cyclone in order to use the obtained information for various scientific studies.
Methods and Results. To form the database, the open source data were used including the tropical cyclone parameters (Best Track Data) in 2020–2022, and the along-track altimeter measurements performed from seven satellites. For each cyclone, in which the maximum wind speed exceeded 30 m/s, the files in the NetCDF and MAT formats were created; they contained altimetry data on the significant wave heights and wind speed in a cyclone area, information on the trajectory of each cyclone and its main characteristics renewed every 3 hours. To describe the radial distribution of wind speed, the standard data on the distances from a cyclone centre to the points where the wind speeds achieved 34, 50, and 64 knots, were proposed to be approximated using the Holland analytical function. Each cyclone is provided with the graphical files illustrating the evolution of its main parameters (radius, maximum wind speed, and translation velocity), the quality of approximation of the wind speed radial distribution, the location of altimeter tracks, and the along-track values of wave heights and wind speed. The developed MATLAB computer programs allow automatic updating of the created data array. By the time of paper publication, the dataset had been supplemented with the information on tropical cyclones and the available altimetry measurements for 1985–2018.
Conclusions. The structured dataset has been created to provide the information on waves and wind speed of all the intense tropical cyclones for the period from 2020 to 2022. The data and the corresponding illustrations can be used for planning and implementing the case studies, and for validating the models of tropical cyclones formation and wave development under their action.
Keywords
tropical cyclones, dataset, satellite altimetry, wave height, wind speed, wind field, extreme conditions
Acknowledgements
The study was carried out with the basic support provided by the Russian Science Foundation grant No. 21-17-00236; the information and computing resources were provided within the framework of state assignment FNNN-2021-0004. The database was formed using the NOAA (data on cyclones) and CMEMS (altimetry data) archives.
Original russian text
Original Russian Text © M. V. Yurovskaya, 2023, published in MORSKOY GIDROFIZICHESKIY ZHURNAL, Vol. 39, Iss. 2, pp. 220-233 (2023)
For citation
Yurovskaya, M.V., 2023. Dataset on Wind and Waves to Study Tropical Cyclones. Physical Oceanography, 30(2), pp. 202-214. doi:10.29039/1573-160X-2023-2-202-214
DOI
10.29039/1573-160X-2023-2-202-214
References
- Kovalev, P.D., Squire, V.A., Kovalev, D.P. and Zaytsev, A.I., 2022. Features of Formation of the Cyclone Wakes (Fluctuations in Seawater Temperature) in the Area of Cape Svobodny, the Southeastern Part of the Sakhalin Island. Physical Oceanography, 29(1), pp. 30-46. doi:10.22449/1573-160X-2022-1-30-46
- Semenov, E.K., Petrov, E.O., Sokolikhina, N.N. and Tatarinovich, E.V., 2018. Typhoon Transformation in Mid-Latitudes as a Factor of the Catastrophic Flood in Primorye in Autumn of 2016. Meteorologiya i Gidrologiya, 9, pp. 104-113 (in Russian).
- Dubina, V.A., Shamov, V.V. and Plotnikov, V.V., 2018. Disastrous Flood in August 2018 in Primorye (South Pacific Russia). Sovremennye Problemy Distantsionnogo Zondirovaniya Zemli iz Kosmosa, 5(5), pp. 253-256. doi:10.21046/2070-7401-2018-15-5-253-256 (in Russian).
- Shimura, T., Mori, N., Urano, D., Takemi, T. and Mizuta, R., 2022. Tropical Cyclone Characteristics Represented by the Ocean Wave-Coupled Atmospheric Global Climate Model Incorporating Wave-Dependent Momentum Flux. Journal of Climate, 35(2), pp. 499-515. doi:10.1175/JCLI-D-21-0362.1
- Collins, C., Hesser, T., Rogowski, P. and Merrifield, S., 2022. Correction: Collins et al. Altimeter Observations of Tropical Cyclone-Generated Sea States: Spatial Analysis and Operational Hindcast Evaluation. Journal of Marine Science and Engineering, 10(5), 690. doi:10.3390/jmse10050690
- Kossin, J.P., Knapp, K.R., Vimont, D.J., Murnane, R.J. and Harper, B.A., 2007. A Globally Consistent Reanalysis of Hurricane Variability and Trends. Geophysical Research Letters, 34(4), L04815. doi:10.1029/2006GL028836
- Miller, R.J., Schrader, A.J., Sampson, C.R. and Tsui, T.L., 1990. The Automated Tropical Cyclone Forecasting System (ATCF). Weather and Forecasting, 5(4), pp. 653-660. doi:10.1175/1520-0434(1990)005<0653:TATCFS>2.0.CO;2
- Mouche, A.A., Chapron, B., Zhang, B. and Husson, R., 2017. Combined Co- and Cross- Polarized SAR Measurements under Extreme Wind Conditions. IEEE Transactions on Geoscience and Remote Sensing, 55(12), pp. 6746-6755. doi:10.1109/TGRS.2017.2732508
- Reul, N., Chapron, B., Zabolotskikh, E., Donlon, C., Quilfen, Y., Guimbard, S. and Piolle, J.F., 2016. A Revised L-Band Radio-Brightness Sensitivity to Extreme Winds under Tropical Cyclone: the Five Year SMOS-Storm Database. Remote Sensing of Environment, 180, pp. 274-291. doi:10.1016/j.rse.2016.03.011
- Yurovskaya, M., Kudryavtsev, V., Mironov, A., Mouche, A., Collard, F. and Chapron, B., 2022. Surface Wave Developments under Tropical Cyclone Goni (2020): Multi-Satellite Observations and Parametric Model Comparisons. Remote Sensing, 14(9), 2032. doi:10.3390/rs14092032
- Lau, K.-M., Zhou, Y.P. and Wu, H.-T., 2008. Have Tropical Cyclones Been Feeding More Extreme Rainfall? Journal of Geophysical Research: Atmospheres, 113(D23), D23113. doi:10.1029/2008JD009963
- Knapp, K.R., Kruk, M.C., Levinson, D.H., Diamond, H.J. and Neumann, C.J., 2010. The International Best Track Archive for Climate Stewardship (IBTrACS): Unifying Tropical Cyclone Data. Bulletin of the American Meteorological Society, 91(3), pp. 363-376. doi:10.1175/2009BAMS2755.1
- Holland, G.J., 1980. An Analytic Model of the Wind and Pressure Profiles in Hurricanes. Monthly Weather Review, 108(8), pp. 1212-1218. doi:10.1175/1520- 0493(1980)108<1212:AAMOTW>2.0.CO;2
- Zieger, S., Vinoth, J. and Young, I.R., 2009. Joint Calibration of Multiplatform Altimeter Measurements of Wind Speed and Wave Height over the Past 20 Years. Journal of Atmospheric and Oceanic Technology, 26(12), pp. 2549-2564. doi:10.1175/2009JTECHA1303.1
- Quilfen, Y., Vandemark, D., Chapron, B., Feng, H. and Sienkiewicz, J., 2011. Estimating Gale to Hurricane Force Winds Using the Satellite Altimeter. Journal of Atmospheric and Oceanic Technology, 28(4), pp. 453-458. doi:10.1175/JTECH-D-10-05000.1
- Yurovskaya, M., Kudryavtsev, V. and Chapron, B., 2023. A Self-Similar Description of the Wave Fields Generated by Tropical Cyclones. Ocean Modelling, 183, 102184. doi:10.1016/j.ocemod.2023.102184
- Pierson, W.J. and Moskowitz, L., 1964. A Proposed Spectral Form for Fully Developed Wind Seas Based on the Similarity Theory of S.A. Kitaigorodskii. Journal of Geophysical Research, 69(24), pp. 5181-5190. doi:10.1029/JZ069i024p05181
- Bowyer, P.J. and MacAfee, A.W., 2005. The Theory of Trapped-Fetch Waves with Tropical Cyclones – An Operational Perspective. Weather and Forecasting, 20(3), pp. 229-244. doi:10.1175/WAF849.1
- Young, I.R., 1988. Parametric Hurricane Wave Prediction Model. Journal of Waterway, Port, Coastal, and Ocean Engineering, 114(5), pp. 637-652. doi:10.1061/(ASCE)0733- 950X(1988)114:5(637)
- Kudryavtsev, V., Golubkin, P. and Chapron, B., 2015. A Simplified Wave Enhancement Criterion for Moving Extreme Events. Journal of Geophysical Research: Oceans, 120(11), pp. 7538-7558. doi:10.1002/2015JC011284