Potential contribution of maximum subsurface temperature anomalies to the climate variability

Abstract

AbstractOn the interannual time scale, sea‐surface temperature anomalies (SSTAs) that are concerned with climate variability at global and regional scales have been widely investigated in previous studies. Through the analysis of the monthly 46‐year (1955–2000) expendable bathythermograph data, we show that subsurface temperature anomalies (STAs) can directly affect the SSTAs in the major air–sea interaction regions. Along the equatorial Pacific, four important features for STAs have been characterized. (1) The STAs and SSTAs are well correlated in the eastern equatorial Pacific (EEP) due to the fact that the thermocline anomalies have only to be mixed with the surface over a very short distance. (2) The STAs are always stronger than SSTAs at any location. (3) In the time between El Niño and La Niña, and vice versa, the STAs propagate eastward along the thermocline without mixing with SSTAs in the central Pacific. (4) An El Niño or La Niña can develop only when the maximum positive or the maximum negative STA propagates to the EEP. Inside and outside the tropical basins the STA was more centred on the thermocline than the 20°C isotherm. These features inform us that the maximum STAs (MSTAs) from each vertical STA profile can be used to indicate the anomalous wave‐propagation signal or thermocline variations in the worldwide oceans. This analysis implies that the MSTA is also a potential factor controlling climate variability and is a better indicator than SSTA, because MSTAs memorize the change in air–sea interaction signals and represent a huge deposit of energy in the upper ocean. The correlations between SSTAs and MSTAs with a coefficient of more than 0.60 are predominantly located in the EEP, the northern North Pacific, the southern subtropical Indian Ocean, and the northern North Atlantic Ocean. These correlations are discussed from case and statistical analyses.The leading pattern of SSTAs and MSTAs in the tropical Pacific, Atlantic and Indian Oceans are decomposed using empirical orthogonal functions (EOFs) and their EOF patterns might be able to explain the difference between MSTAs and SSTAs. Their periods of mode series are performed from a global wavelet spectral analysis. Copyright © 2004 Royal Meteorological Society