On the Seasonal Cycle of the Statistical Properties of Sea Surface Temperature. Issue 8 (16th April 2022)

• Record Type: Journal Article
• Authors: Isern‐Fontanet, J.; Capet, X.; Turiel, A.; Olmedo, E.; González‐Haro, C.
• Is Part Of: Geophysical research letters. Volume 49:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-04-16
• Subjects: Sea Surface Temperature -- ocean fronts -- turbulence -- Califronia current system -- structure functions -- multifractal; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1029/2022GL098038
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The contribution of ocean fronts to the properties and temporal evolution of Sea Surface Temperature (SST) structure functions have been investigated using a numerical model of the California Current system. First, the intensity of fronts have been quantified by using singularity exponents. Then, leaning on the multifractal theory of turbulence, we show that the departure of the scaling of the structure functions from a straight line, known as anomalous scaling, depends on the intensity of the strongest fronts. These fronts, at their turn, are closely related to the seasonal change of intensity of the coastal upwelling characteristics of this area. Our study points to the need to correctly reproduce the intensity of the strongest fronts and, consequently, properly model processes such as coastal upwelling in order to reproduce SST statistics in ocean models. Plain Language Summary: Forecasting the evolution of the Earth's climate requires to predict the evolution of the statistical characteristics of essential climate variables such as the Sea Surface Temperature. In this study, it has been found that some of such statistical properties depend on the intensity of the strongest fronts in the ocean. This implies that those ocean, or climate, models that fail to correctly predict their intensity will not be able to correctly reproduce the statistical characteristics of key variables such as temperature. The area analyzed in this study is the California Current system, where the strongest fronts are modulated by the seasonal evolution of the upwelling. Therefore, our results imply that such a system has to be correctly modeled, or parametrized, in order to properly reproduce the statistics of ocean temperatures. Key Points: The intensity of Sea Surface Temperature (SST) fronts is quantified using singularity exponents, which measure the continuity of the field Anomalous scaling of SST structure functions is correlated to the the intensity of the strongest fronts The variability of the strongest fronts depends on the seasonal variability of the coastal upwelling in the area of study