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Domingues, R., Kuwano-Yoshida, A., Chardon-Maldonado, P., Todd, R. E., Halliwell, G., Kim, H. - S., et al. (2019). Ocean Observations in Support of Studies and Forecasts of Tropical and Extratropical Cyclones. Front. Mar. Sci., 6, 446.
Abstract: Over the past decade, measurements from the climate-oriented ocean observing system have been key to advancing the understanding of extreme weather events that originate and intensify over the ocean, such as tropical cyclones (TCs) and extratropical bomb cyclones (ECs). In order to foster further advancements to predict and better understand these extreme weather events, a need for a dedicated observing system component specifically to support studies and forecasts of TCs and ECs has been identified, but such a system has not yet been implemented. New technologies, pilot networks, targeted deployments of instruments, and state-of-the art coupled numerical models have enabled advances in research and forecast capabilities and illustrate a potential framework for future development. Here, applications and key results made possible by the different ocean observing efforts in support of studies and forecasts of TCs and ECs, as well as recent advances in observing technologies and strategies are reviewed. Then a vision and specific recommendations for the next decade are discussed.
|Goni, G., DeMaria, M., Knaff, J., Sampson, C., Ginis, I., Bringas, F., et al. (2009). Applications of Satellite-Derived Ocean Measurements to Tropical Cyclone Intensity Forecasting. Oceanog., 22(3), 190–197.|
Ali, M. M. (2020). Is it high time to use ocean mean temperature for monsoon prediction? Atmosphera, .
Abstract: A monsoon is a seasonal reversal in the prevailing wind direction, that is usually initiated by the land sea temperature contrast. The Indian summer monsoon, for example, is triggered when the land gets heated up more than the surrounding sea during the summer creating a pressure gradient between the land and the sea. It is well known that the ocean thermal energy required for fueling monsoon circulations comes from the upper layer of the ocean (e.g. Venugopal et al. 2018). But such amount of energy does not come from the top thin layer represented by sea surface temperature (SST) alone. Nevertheless, often SST does not represent the thermal energy available in the upper ocean, although this parameter has been the only oceanographic input to the cyclone and monsoon atmospheric numerical and statistical models.
|Krishnamurti, T. N., Jana, S., Krishnamurti, R., Kumar, V., Deepa, R., Papa, F., et al. (2017). Monsoonal intraseasonal oscillations in the ocean heat content over the surface layers of the Bay of Bengal. Journal of Marine Systems, 167, 19–32.|
|Zheng, Y., Ali, M. M., & Bourassa, M. A. (2016). Contribution of Monthly and Regional Rainfall to the Strength of Indian Summer Monsoon. Mon. Wea. Rev., 144(9), 3037–3055.|
|Ali, M. M., Bourassa, M. A., Bhowmick, S. A., Sharma, R., & Niharika, K. (2016). Retrieval of Wind Stress at the Ocean Surface From AltiKa Measurements. IEEE Geosci. Remote Sensing Lett., 13(6), 821–825.|
|Ali, M. M., Bhowmick, S. A., Sharma, R., Chaudhury, A., Pezzullo, J. C., Bourassa, M. A., et al. (2015). An Artificial Neural Network Model Function (AMF) for SARAL-Altika Winds. IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing, 8(11), 5317–5323.|
|Ali, M. M., Bhat, G. S., Long, D. G., Bharadwaj, S., & Bourassa, M. A. (2013). Estimating Wind Stress at the Ocean Surface From Scatterometer Observations. IEEE Geosci. Remote Sensing Lett., 10(5), 1129–1132.|
|Ali, M. M., Nagamani, P. V., Sharma, N., Venu Gopal, R. T., Rajeevan, M., Goni, G. J., et al. (2015). Relationship between ocean mean temperatures and Indian summer monsoon rainfall. Atmos. Sci. Lett., 16(3), 408–413.|
|Purna Chand, C., Rao, M. V., Ramana, I. V., Ali, M. M., Patoux, J., & Bourassa, M. A. (2014). Estimation of sea level pressure fields during Cyclone Nilam from Oceansat-2 scatterometer winds. Atmos. Sci. Lett., 15(1), 65–71.|