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ACI Avances en Ciencias e Ingenierías

SECTION B: LIFE SCIENCES

Vol. 13 No. 2 (2021)

Seasonal-To-Interannual Variability of Sea-Surface Temperatures in The Inter-Americas Seas: Pattern-Dependent Biases in The Regional Ocean Modeling System

DOI
https://doi.org/10.18272/aci.v13i2.2046
Submitted
October 30, 2020
Published
2021-11-11

Abstract

The Inter-Americas Seas (IAS), involving the Gulf of Mexico, the Caribbean and a section of the eastern tropical Pacific Ocean bordering Central America, Colombia and Ecuador, exhibits very active ocean-land-atmosphere interactions that impact socio­economic activities within and beyond the region, and that are still not well understood or represented in state-of-the-art models. On seasonal-to-interannual timescales, the main source of variability of this geographical area is related to interactions between the Pacific and the Atlantic oceans, involving anomalous sea-surface temperature (SST) patterns like El Nino-Southern Oscillation (ENSO), and regional features in the Caribbean linked to the bi-modal seasonality of the Caribbean Low-Level Jet. This study investigates seasonal-to-interannual IAS surface-temperature anomalies in observations, and their representation in an eddy-permitting, 1/9° or 0.11°; approximately 10 km) resolution simulation using the Regional Ocean Modeling System (ROMS), interannually-forced by the Climate Forecast System Reanalysis for the study period 1999-2008. Here, rather than analyzing model biases locally (i.e., gridbox-by-gridbox), a non-local SST pattern­based diagnostic was conducted via a principal component analysis. Regarding spatial resolution, the results of this study suggest that even at eddy-permitting resolutions of 0.11o several biases remain, which contrast with the general consensus in the literature. The approach permitted the identification of magnitude, variance and spatial systematic errors in SST patterns related to the Western Hemisphere Warm Pool, ENSO, the Inter-Americas Seas Dipole, and several other variability modes. These biases are mainly related to errors in surface heat fluxes, misrepresentation of air-sea interactions impacting surface latent cooling in the Caribbean, and too strong sub-surface thermal stratification, mostly off the coast of Ecuador and northern Peru.

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