Long‐term evolution of global sea surface temperature trend

2021 ◽  
Author(s):  
Zhenhao Xu ◽  
Fei Ji ◽  
Bo Liu ◽  
Taichen Feng ◽  
Yuan Gao ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Long Term Evolution ◽  
Temperature Trend ◽  
Sea Surface ◽  
Term Evolution ◽  
Global Sea Surface Temperature

Non-linear, long-term evolution of sea surface temperature across the World Ocean

2020 ◽  
Author(s):  
Benjamin Martinez-Lopez
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
World Ocean ◽  
Sea Surface ◽  
Second Derivative ◽  
Term Evolution ◽  
The World ◽  
Non Linear

<p>Sea surface temperature (SST) is the only oceanic parameter on which depend heat fluxes between ocean and atmosphere and, therefore, SST is one of the key factors that influence climate and its variability. Over the twentieth century, SSTs have significantly increased around the global ocean, warming that has been attributed to anthropogenic climate change, although it is not yet clear how much of it is related to natural causes and how much is due to human activities. A considerable part of available literature regarding climate change has been built based on the global or hemispheric analysis of surface temperature trends. There are, however, some key open questions that need to be answered and for this task estimates of long-term SST trend patterns represent a source of valuable information. Unfortunately, long-term SST trend patterns have large uncertainties and although SST constitutes one of the most-measured ocean variables of our historic records, their poor spatial and temporal sampling, as well as inhomogeneous measurements technics, hinder an accurate determination of long-term SST trends, which increases their uncertainty and, therefore, limit their physical interpretation as well as their use in the verification of climate simulations.<br>Most of the long-term SST trend patterns have been built using linear techniques, which are very usefull when they are used to extract information of measurements satisfying two key assumptions: linearity and stationarity. The global warming resulting of our economic activities, however, affect the state of the World Ocean and the atmosphere inducing changes in the climate that may result in oscillatory modes of variability of different frequencies, which may undergo non-stationary and non-linear evolutions. In this work, we construct long-term SST trend patterns by using non-linear techniques to extract non-linear, long-term trends in each grid-point of two available global SST datasets: the National Oceanic and Atmospheric Administration Extended Reconstructed SST (ERSST) and from the Hadley Centre sea ice and SST (HadISST). The used non-linear technique makes a good job even if the SST data are non-linear and non-stationary. Additionally, the nonlinearity of the extracted trends allows the use of the first and second derivative to get more information about the global, long-term evolution of the SST fields, favoring thus a deeper understanding and interpretation of the observed changes in SST. Particularly, our results clearly show, in both ERSST and HadISST datasets, the non-uniform warming observed in the tropical Pacific, which seems to be related to the enhanced vertical heat flux in the eastern equatorial Pacific and the strengthening of the warm pool in the western Pacific. By using the second derivative of the nonlinear SST trends, emerges an interesting pattern delimiting several zones in the Pacific Ocean which have been responded in a different way to the impose warming of the last century.</p>

Dominant Influence of ENSO-Like and Global Sea Surface Temperature Patterns on Changes in Prevailing Boreal Summer Tropical Cyclone Tracks over the Western North Pacific

2020 ◽  
Vol 33 (22) ◽  
pp. 9551-9565
Author(s):  
Haikun Zhao ◽  
Philp J. Klotzbach ◽  
Shaohua Chen
Keyword(s):  
Tropical Cyclone ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Time Scales ◽  
North Pacific ◽  
Western North Pacific ◽  
Sea Surface ◽  
Track Pattern ◽  
Global Sea Surface Temperature

AbstractA conventional empirical orthogonal function (EOF) analysis is performed on summertime (May–October) western North Pacific (WNP) tropical cyclone (TC) track density anomalies during 1970–2012. The first leading EOF mode is characterized by a consistent spatial distribution across the WNP basin, which is closely related to an El Niño–Southern Oscillation (ENSO)-like pattern that prevails on both interannual and interdecadal time scales. The second EOF mode is represented by a tripole pattern with consistent changes in westward and recurving tracks but with an opposite change for west-northwestward TC tracks. This second EOF pattern is dominated by consistent global sea surface temperature anomaly (SSTA) patterns on interannual and interdecadal time scales, along with a long-term increasing global temperature trend. Observed WNP TC tracks have three distinct interdecadal epochs (1970–86, 1987–97, and 1998–2012) based on EOF analyses. The interdecadal change is largely determined by the changing impact of ENSO-like and consistent global SSTA patterns. When global SSTAs are cool (warm) during 1970–86 (1998–2012), these SSTAs exert a dominant impact and generate a tripole track pattern that is similar to the positive (negative) second EOF mode. In contrast, a predominately El Niño–like SSTA pattern during 1987–97 contributed to increasing TC occurrences across most of the WNP during this 11-yr period. These findings are consistent with long-term trends in TC tracks, with a tripole track pattern observed as global SSTs increase. This study reveals the potential large-scale physical mechanisms driving the changes of WNP TC tracks in association with climate change.

scholarly journals Long-Term Sea Surface Temperature Variability along the U.S. East Coast

2010 ◽  
Vol 40 (5) ◽  
pp. 1004-1017 ◽  
Author(s):  
R. Kipp Shearman ◽  
Steven J. Lentz
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
East Coast ◽  
Atmospheric Temperature ◽  
Coastal Ocean ◽  
Temperature Trend ◽  
Sea Surface ◽  
Temperature Trends ◽  
Cape Hatteras

Abstract Sea surface temperature variations along the entire U.S. East Coast from 1875 to 2007 are characterized using a collection of historical observations from lighthouses and lightships combined with recent buoy and shore-based measurements. Long-term coastal temperature trends are warming in the Gulf of Maine [1.0° ± 0.3°C (100 yr)−1] and Middle Atlantic Bight [0.7° ± 0.3°C (100 yr)−1], whereas trends are weakly cooling or not significant in the South Atlantic Bight [−0.1° ± 0.3°C (100 yr)−1] and off Florida [−0.3° ± 0.2°C (100 yr)−1]. Over the last century, temperatures along the northeastern U.S. coast have warmed at a rate 1.8–2.5 times the regional atmospheric temperature trend but are comparable to warming rates for the Arctic and Labrador, the source of coastal ocean waters north of Cape Hatteras (36°N). South of Cape Hatteras, coastal ocean temperature trends match the regional atmospheric temperature trend. The observations and a simple model show that along-shelf transport, associated with the mean coastal current system running from Labrador to Cape Hatteras, is the mechanism controlling long-term temperature changes for this region and not the local air–sea exchange of heat.

Testing for Deterministic Trends in Global Sea Surface Temperature

2011 ◽  
Vol 24 (10) ◽  
pp. 2516-2522 ◽  
Author(s):  
Susana M. Barbosa
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Linear Model ◽  
Linear Trend ◽  
Statistical Significance ◽  
Sea Surface ◽  
Deterministic Trend ◽  
Parametric Statistical Test ◽  
Global Sea Surface Temperature

Abstract Long-term variability in global sea surface temperature (SST) is often quantified by the slope from a linear regression fit. Attention is then focused on assessing the statistical significance of the derived slope parameter, but the adequacy of the linear model itself, and the inherent assumption of a deterministic linear trend, is seldom tested. Here, a parametric statistical test is applied to test the hypothesis of a linear deterministic trend in global sea surface temperature. The results show that a linear slope is not adequate for describing the long-term variability of sea surface temperature over most of the earth’s surface. This does not mean that sea surface temperature is not increasing, rather that the increase should not be characterized by the slope from a linear fit. Therefore, describing the long-term variability of sea surface temperature by implicitly assuming a deterministic linear trend can give misleading results, particularly in terms of uncertainty, since the actual increase could be considerably larger than the one predicted by a deterministic linear model.

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