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<md:lastName>Zhang</md:lastName>
<md:firstName>Jishi</md:firstName>
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<md:lastName>Lin</md:lastName>
<md:firstName>Yanluan</md:firstName>
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<md:author id="dataset.author71949">
<md:lastName>Chavas</md:lastName>
<md:firstName>Daniel R</md:firstName>
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<md:author id="dataset.author71950">
<md:lastName>Mei</md:lastName>
<md:firstName>Wei</md:firstName>
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<md:year>2023</md:year>
<md:title>Tropical cyclone cold wake size dataset (AVHRR-only)</md:title>
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<md:abstract>Mixing of the upper ocean by the wind field associated with tropical cyclones (TCs) creates observable cold wakes in sea surface temperature and may potentially influence ocean heat uptake. The relationship between cold wake size and storm size, however, has yet to be explored. Here we apply two objective methods to observed daily sea surface temperature data to quantify the size of TC-induced cold wakes. The obtained cold wake sizes agree well with the TC sizes estimated from the QuikSCAT-R wind field database with a correlation coefficient of 0.51 and 0.59, respectively. Furthermore, our new estimate of the total cooling that incorporates the variations in the cold wake size provides improved estimates of TC power dissipation and TC-induced ocean heat uptake. This study thus highlights the importance of cold wake size in evaluating the climatological effects of TCs.
The cold wake size (rROI) dataset uploaded here is based on the daily NOAA 1/4° Optimum Interpolation Sea Surface Temperature, AVHRR-only subset  (1981–2017). This is corresponding to the AVHRR+AMSR subset (2002-2011) uploaded to doi:10.1594/PANGAEA.907551. 
The objective cold wake size metrics (rROI) is derived based on an image processing methods -- the Region of Interest method. More information about the pretreatment and derivation of rROI please refer to Zhang et al. (2019).</md:abstract>
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<md:year>2019</md:year>
<md:title>Tropical cyclone cold wake size and its applications to power dissipation and ocean heat uptake estimates</md:title>
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