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Comparison of SST diurnal variation models over the Tropical Warm Pool region

Zhang, H., Beggs, H., Merchant, C. J., Wang, X. H., Majewski, L., Kiss, A. E., Rodriguez, J., Thorpe, L., Gentemann, C. and Brunke, M. (2018) Comparison of SST diurnal variation models over the Tropical Warm Pool region. Journal of Geophysical Research: Oceans, 123 (5). pp. 3467-3488. ISSN 2169-9291

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To link to this item DOI: 10.1029/2017JC013517


Four sea surface temperature (SST) diurnal variation (DV) models have been compared against Multi-functional Transport Satellite - 1R (MTSAT-1R) SST measurements over the Tropical Warm Pool region (TWP, 90°E-170°E, 25°S-15°N) for four months from January to April 2010. The four models include one empirical model formulated by Chelle Gentemann (hereafter CG03), one physical model proposed by Zeng and Beljaars in 2005 (ZB05) and its updated version (ZB+T), and one air-sea coupled model (the Met Office Unified Model Global Coupled configuration 2, GC2) with ZB05 warm layer scheme added on top of the standard configuration. The sensitivity of the v3 MTSAT-1R data to the “true” changes in SST is first investigated using drifting buoys and is estimated to be 0.60 ± 0.05. This being significantly different from 1, the models are validated against MTSAT-1R data and the same data scaled by the inverse of the sensitivity (representing an estimate of the true variability). Results indicate that all models are able to capture the general DV patterns but with differing accuracies and features. Specifically, CG03 and ZB+T underestimate strong (> 2 K) DV events’ amplitudes especially if we assume that sensitivity-scaled MTSAT-1R variability is most realistic. ZB05 can effectively capture the DV cycles under most DV and wind conditions, as well as the DV spatial distribution. GC2 tends to overestimate small-moderate (< 2 K) DV events but can reasonably predict large DV events. 1-3 hr lags in warming start and peak times are found in GC2.

Item Type:Article
Divisions:Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO)
Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:76724
Publisher:American Geophysical Union


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