No abstract

A 0.24°C jump of record warm global mean surface temperature (GMST) over the past three consecutive record‐breaking years (2014–2016) was highly unusual and largely a consequence of an El Niño that released unusually large amounts of ocean heat from the subsurface layer of the northwestern tropical Pacific. This heat had built up since the 1990s mainly due to greenhouse‐gas (GHG) forcing and possible remote oceanic effects. Model simulations and projections suggest that the fundamental cause, and robust predictor of large record‐breaking events of GMST in the 21st century, is GHG forcing rather than internal climate variability alone. Such events will increase in frequency, magnitude, and duration, as well as impact, in the future unless GHG forcing is reduced.

During 1998–2012, climate change and sea level rise (SLR) exhibit two notable features: a slowdown of global surface warming (hiatus) and a rapid SLR in the tropical western Pacific. To quantify their relationship, we analyze the long‐term control simulations of 38 climate models. We find a significant and robust correlation between the east‐west contrast of dynamic sea level (DSL) in the Pacific and global mean surface temperature (GST) variability on both interannual and decadal time scales. Based on linear regression of the multimodel ensemble mean, the anomalously fast SLR in the western tropical Pacific observed during 1998–2012 indicates suppression of a potential global surface warming of 0.16° ± 0.06°C. In contrast, the Pacific contributed 0.29° ± 0.10°C to the significant interannual GST increase in 1997/1998. The Pacific DSL anomalies observed in 2015 suggest that the strong El Niño in 2015/2016 could lead to a 0.21° ± 0.07°C GST jump.

A notable feature in the first 20-year satellite altimetry records is an anomalously fast sea level rise (SLR) in the western Pacific impacting island nations in this region. This observed trend is due to a combination of internal variability and external forcing. The dominant mode of dynamic sea level (DSL) variability in the tropical Pacific presents as an east-west see-saw pattern. To assess model skill in simulating this variability mode, we compare 38 Coupled Model Intercomparison Project Phase 5 (CMIP5) models with 23-year satellite data, 55-year reanalysis products, and 60-year sea level reconstruction. We find that models underestimate variance in the Pacific sea level see-saw, especially at decadal, and longer, time scales. The interannual underestimation is likely due to a relatively low variability in the tropical zonal wind stress. Decadal sea level variability may be influenced by additional factors, such as wind stress at higher latitudes, subtropical gyre position and strength, and eddy heat transport. The interannual variability of the Niño 3.4 index is better represented in CMIP5 models despite low tropical Pacific wind stress variability. However, as with sea level, variability in the Niño 3.4 index is underestimated on decadal time scales. Our results show that DSL should be considered, in addition to sea surface temperature (SST), when evaluating model performance in capturing Pacific variability, as it is directly related to heat content in the ocean column.