Global Mean Sea Surface Temperature Research Articles

TEOS-10 Equations for Determining the Lifted Condensation Level (LCL) and Climatic Feedback of Marine Clouds

At an energy flux imbalance of about 1 W m–2, the ocean stores 90% of the heat accumulating by global warming. However, neither the causes of this nor the responsible geophysical processes are sufficiently well understood. More detailed investigations of the different phenomena contributing to the oceanic energy balance are warranted. Here, the role of low-level marine clouds in the air–sea interaction is analysed. TEOS-10, the International Thermodynamic Equation of State of Seawater—2010, is exploited for a rigorous thermodynamic description of the climatic trends in the lifted condensation level (LCL) of the marine troposphere. Rising sea surface temperature (SST) at a constant relative humidity (RH) is elevating marine clouds, cooling the cloud base, and reducing downward thermal radiation. This LCL feedback effect is negative and counteracts ocean warming. At the current global mean SST of about 292 K, the net radiative heat flux from the ocean surface to the LCL cloud base is estimated to be 24 W m–2. Per degree of SST increase, this net flux is expected to be enhanced by almost 0.5 W m–2. The climatic LCL feedback effect is relevant for the ocean’s energy balance and may be rigorously thermodynamically modelled in terms of TEOS-10 equations. LCL height may serve as a remotely measured, sensitive estimate for the sea surface’s relative fugacity, or conventional relative humidity.

Highly stratified mid-Pliocene Southern Ocean in PlioMIP2

Abstract. During the mid-Pliocene warm period (mPWP; 3.264–3.025 Ma), atmospheric CO2 concentrations were approximately 400 ppm, and the Antarctic Ice Sheet was substantially reduced compared to today. Antarctica is surrounded by the Southern Ocean, which plays a crucial role in the global oceanic circulation and climate regulation. Using results from the Pliocene Model Intercomparison Project (PlioMIP2), we investigate Southern Ocean conditions during the mPWP with respect to the pre-industrial period. We find that the mean sea surface temperature (SST) warming in the Southern Ocean is 2.8 °C, while global mean SST warming is 2.4 °C. The enhanced warming is strongly tied to a dramatic decrease in sea ice cover over the mPWP Southern Ocean. We also see a freshening of the ocean (sub)surface, driven by an increase in precipitation over the Southern Ocean and Antarctica. The warmer and fresher surface leads to a highly stratified Southern Ocean that can be related to weakening of the deep abyssal overturning circulation. Sensitivity simulations show that the decrease in sea ice cover and enhanced warming is largely a consequence of the reduction in the Antarctic Ice Sheet. In addition, the mPWP geographic boundary conditions are responsible for approximately half of the increase in mPWP SST warming, sea ice loss, precipitation, and stratification increase over the Southern Ocean. From these results, we conclude that a strongly reduced Antarctic Ice Sheet during the mPWP has a substantial influence on the state of the Southern Ocean and exacerbates the changes that are induced by a higher CO2 concentration alone. This is relevant for the long-term future of the Southern Ocean, as we expect melting of the western Antarctic Ice Sheet in the future, an effect that is not currently taken into account in future projections by Coupled Model Intercomparison Project (CMIP) ensembles.

The 1991–2020 sea surface temperature normals

AbstractThe 1991–2020 climate normals for sea surface temperature (SST) are computed based on the NOAA Daily Optimum Interpolation SST dataset. This is the first time that high‐resolution SST normals with global coverage can be achieved in the satellite SST era. Normals are one of the fundamental parameters in describing and understanding weather and climate and provide decision‐making information to industry, public, and scientific communities. This product suite includes SST mean, standard deviation, count and extreme parameters at daily, monthly, seasonal and annual time scales on 0.25° spatial grids. The main feature of the SST mean state revealed by the normals is that in the Tropics, the Indo‐Pacific Ocean is dominated by the warm pool (SST ≥ 28°C) while the eastern Pacific is characterized by the cold tongue (SST ≤ 24°C); in the midlatitudes, SSTs are in zonal patterns with high meridional gradients. Daily SST standard deviations are generally small (<1.0°C) except in frontal zones (>1.5°C) mostly associated with ocean currents such as the Gulf Stream, Kuroshio and Equatorial Currents. Compared to the 1982–2011 climatology, the 1991–2020 mean SSTs increased over most global areas but obvious cooling is seen in the Southern Ocean, eastern tropical South Pacific Ocean and North Atlantic warming hole. The Indo‐Pacific warm pool (IPWP) is found to have strengthened in both intensity and coverage since 1982–2011. By a count parameter criterion of ≥300 days annually with SST ≥ 28°C, the IPWP coverage increased 33% from 1982–2011 to 1991–2020. The global mean SST of 1991–2020 is warmer than that of 1982–2011, and the warming rate over 1991–2020 doubles that over 1901–2020.

Tropical Atmospheric Response of Atlantic Niños to Changes in the Ocean Background State

AbstractSince the 1970s, Atlantic Niños during boreal summer have been linked to Pacific La Niñas the following winter. Earlier studies have explained the appearance of the Atlantic‐Pacific teleconnection with changing Atlantic Niño configurations. Here we find that the non‐stationarity of this teleconnection can also be explained by changes in the ocean background state, without changing the Atlantic Niño configuration. Experiments with different atmospheric general circulation models are performed where the same Atlantic Niño pattern is prescribed to different global ocean background states. The 1975–1985 global mean sea surface temperature forces a Walker Circulation response and low‐level convergence over the Maritime Continent, increasing the chance of triggering a La Niña‐like event in the Pacific. These results suggest that ENSO‐predictions could be improved in certain periods by considering tropical Atlantic variability.

Simulated and projected SST of Asian marginal seas based on CMIP6 models

Sea surface temperature (SST) is an important element in studying the global ocean-atmospheric system, as well as its simulation and projection in climate models. In this study, we evaluate the simulation skill of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the climatological SST in the Asian Marginal Seas (AMS), known as the most rapidly warming region over the global ocean. The results show that the spatial patterns and seasonal variability of Asian Marginal Seas (AMS) climatological SST simulated by the CMIP6 models are generally in good agreement with the observations, but there are simulation biases in the values. In boreal winter, the simulated climatological SST tends to be overestimated in the Japan/East Sea and the East China Seas (ECSs) by up to 2°C, while being underestimated in the Sea of Okhotsk by up to 2°C. In boreal summer, the simulated climatological SSTs are overestimated in the Indonesian seas and western Arabian Sea, while being underestimated in the Sea of Okhotsk and the northern ECSs by 1.2–1.5 and 2°C, respectively. Furthermore, we calculate the projected sea surface warming trends in the AMS under different future scenarios in the CMIP6 models. The results show warming trends of 0.8–1.8, 1.7–3.4, and 3.8–6.5°C/century for the Shared Socio-Economic Pathway (SSP) of low- (global radiative forcing of 2.6 W/m² by the year 2100), medium- (global radiative forcing of 4.5 W/m² by 2100) and high-end (8.5 W/m² by 2100) pathways, respectively. In addition, the middle and high latitudes of the AMS are found to have faster warming trends than the low latitudes, with the most rapidly warming occurring in the Sea of Okhotsk, which is around 2 times larger than the global mean SST warming trend. The SST warming trends are relatively slow in the South China Sea and the Indonesian seas, roughly equal to the global mean SST warming trend.

A deep learning model for forecasting global monthly mean sea surface temperature anomalies

Sea surface temperature (SST) variability plays a key role in the global weather and climate system, with phenomena such as El Niño-Southern Oscillation (ENSO) regarded as a major source of interannual climate variability at the global scale. The ability to make long-range forecasts of SST variations and extreme marine heatwave events have potentially significant economic and societal benefits, especially in a warming climate. We have developed a deep learning time series prediction model (Unet-LSTM), based on more than 70 years (1950–2021) of ECMWF ERA5 monthly mean SST and 2-m air temperature data, to predict global 2-dimensional SSTs up to a 24-month lead. Model prediction skills are high in the equatorial and subtropical Pacific. We have assessed the ability of the model to predict SST anomalies in the Niño3.4 region, an ENSO index in the equatorial Pacific, and the Blob marine heatwave events in the northeast Pacific in detail. An assessment of the predictions of the 2019–2020 El Niño and the 2016–2017 and 2017–2018 La Niña show that the model has skill up to 18 months in advance. The prediction of the 2015–2016 extreme El Niño is less satisfactory, which suggests that subsurface ocean information may be crucial for the evolution of this event. Note that the model makes predictions of the 2-d monthly SST field and Nino 3.4 is just one region embedded in the global field. The model also shows long lead prediction skills for the northeast Pacific marine heatwave, the Blob. However, the prediction of the marine heatwaves in the southeast Indian Ocean, the Ningaloo Niño, shows a short lead prediction. These results indicate the significant potential of data-driven methods to yield long-range predictions of SST anomalies.

The latitudinal temperature gradient and its climate dependence as inferred from foraminiferal δ18O over the past 95 million years

SignificanceThe temperature difference between low and high latitudes is one measure of the efficiency of the global climate system in redistributing heat and is used to test the ability of models to represent the climate system through time. Here, we show that the latitudinal temperature gradient has exhibited a consistent inverse relationship with global mean sea-surface temperature for at least the past 95 million years. Our results help reduce conflicts between climate models and empirical estimates of temperature and argue for a fundamental consistency in the dynamics of heat transport and radiative transfer across vastly different background states.

Evolving CO2 Rather Than SST Leads to a Factor of Ten Decrease in GCM Convergence Time.

The high computational cost of Global Climate Models (GCMs) is a problem that limits their use in many areas. Recently an inverse climate modeling (InvCM) method, which fixes the global mean sea surface temperature (SST) and evolves the CO2 mixing ratio to equilibrate climate, has been implemented in a cloud‐resolving model. In this article, we apply InvCM to ExoCAM GCM aquaplanet simulations, allowing the SST pattern to evolve while maintaining a fixed global‐mean SST. We find that InvCM produces the same climate as normal slab‐ocean simulations but converges an order of magnitude faster. We then use InvCM to calculate the equilibrium CO2 for SSTs ranging from 290 to 340 K at 1 K intervals and reproduce the large increase in climate sensitivity at an SST of about 315 K at much higher temperature resolution. The speedup provided by InvCM could be used to equilibrate GCMs at higher spatial resolution or to perform broader parameter space exploration in order to gain new insight into the climate system. Additionally, InvCM could be used to find unstable and hidden climate states, and to find climate states close to bifurcations such as the runaway greenhouse transition.

Evaluation and projection of the AMO and PDO variabilities in the CMIP5 models under different warming scenarios part1: Evaluation

The capabilities of the CMIP5 models to simulate the two most important interdecadal modes, the Atlantic Multi-decadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO), are evaluated by comparing the observed sea surface temperature data from 1880 to 2009 and the CMIP5 simulations under the historical scenario. The multi-model ensemble (MME) historical simulations show deficiency in reproducing characteristics of the PDO mode in the tropics but well simulated the spatial patterns of the AMO and PDO in the high latitudes. The amplitude of the two modes is obviously weaker in the historical simulations than the observation. In terms of periodic simulations, the MME can simulate the 60–70 year period of the AMO and the double periods, namely 20 and 60–70 years, of the PDO. The MME show more realistic simulations of observed spatial and temporal features of AMO and PDO than most models. The CESM1-CAM5, FGOALS-g2, GISS-E2-R-CC, GISS-E2-H-CC and MIROC-ESM-CHEM are the top-performing models. By comparing the individual models, the variances of the AMO and PDO modes decrease when the simulated global mean sea surface temperatures are higher.

Sea Surface Temperature Intercomparison in the Framework of the Copernicus Climate Change Service (C3S)

AbstractA joint effort between the Copernicus Climate Change Service (C3S) and the Group for High Resolution Sea Surface Temperature (GHRSST) has been dedicated to an intercomparison study of eight global gap-free sea surface temperature (SST) products to assess their accurate representation of the SST relevant to climate analysis. In general, all SST products show consistent spatial patterns and temporal variability during the overlapping time period (2003–18). The main differences between each product are located in the western boundary current and Antarctic Circumpolar Current regions. Linear trends display consistent SST spatial patterns among all products and exhibit a strong warming trend from 2012 to 2018 with the Pacific Ocean basin as the main contributor. The SST discrepancy between all SST products is very small compared to the significant warming trend. Spatial power spectral density shows that the interpolation into 1° spatial resolution has negligible impacts on our results. The global mean SST time series reveals larger differences among all SST products during the early period of the satellite era (1982–2002) when there were fewer observations, indicating that the observation frequency is the main constraint of the SST climatology. The maturity matrix scores, which present the maturity of each product in terms of documentation, storage, and dissemination but not the scientific quality, demonstrate that ESA-CCI and OSTIA SST are well documented for users’ convenience. Improvements could be made for MGDSST and BoM SST. Finally, we have recommended that these SST products can be used for fundamental climate applications and climate studies (e.g., El Niño).

Rapid Warming of Sea Surface Temperature along the Kuroshio and the China Coast in the East China Sea during the Twentieth Century

AbstractIt has been reported that the sea surface temperature (SST) trend of the East China Sea during the twentieth century was a couple of times larger than the global mean SST trend. However, the detailed spatial structure of the SST trend in the East China Sea and its mechanism have not been understood. The present study examines the SST trend in the East China Sea from 1901 to 2010 using observational data and a Regional Ocean Modeling System (ROMS) with an eddy-resolving horizontal resolution. A comparison among two observational datasets and the model output reveals that enhanced SST warming occurred along the Kuroshio and along the coast of China over the continental shelf. In both regions, the SST trends were the largest in winter. The heat budget analysis using the model output indicates that the upper-layer temperature rises in both regions were induced by the trend of ocean advection, which was balanced in relation to the increase of surface net heat release. In addition, the rapid SST warming along the Kuroshio was induced by the acceleration of the Kuroshio. Sensitivity experiments revealed that this acceleration was likely caused by the negative wind stress curl anomalies over the North Pacific. In contrast, the enhanced SST warming along the China coast resulted from the ocean circulation change over the continental shelf by local atmospheric forcing.

Kinematics of global mean thermosteric sea level during 1993–2019

Abstract Because oceans cover 71% of Earth’s surface, ocean warming, consequential for thermal expansion of sea water, has been the largest contributor to the global mean sea level rise averaged over the 20 th and the early 21 st century. This study first generates quasi-observed monthly globally averaged thermosteric sea level time series by removing the contributions of global mean sea level budget components, namely, Glaciers, Greenland, Antarctica, and Terrestrial Water Storage from satellite altimetry measured global sea level changes during 1993–2019. A baseline kinematic model with global mean thermosteric sea level trend and a uniform acceleration is solved to evaluate the performance of a rigorous mixed kinematic model. The model also includes coefficients of monthly lagged 60 yearlong cumulative global mean sea surface temperature gradients and control variables of lunisolar origins and representations for first order autoregressive disturbances. The mixed kinematic model explains 94% (Adjusted R 2)1 of the total variability in quasi-observed monthly and globally averaged thermosteric time series compared to the 46% of the baseline kinematic model’s Adjusted R 2. The estimated trend, 1.19±0.03 mm/yr., is attributed to the long-term ocean warming. Whereas eleven statistically significant (α = 0.05) monthly lagged cumulative global mean sea surface temperature gradients each having a memory of 60 years explain the remainder transient global mean thermosteric sea level changes due to the episodic ocean surface warming and cooling during this period. The series also exhibit signatures of a statistically significant contingent uniform global sea level acceleration and periodic lunisolar forcings.

A global mean sea surface temperature dataset for the Last Interglacial (129–116 ka) and contribution of thermal expansion to sea level change

Abstract. A valuable analogue for assessing Earth's sensitivity to warming is the Last Interglacial (LIG; 129–116 ka), when global temperatures (0 to +2 ∘C) and mean sea level (+6 to 11 m) were higher than today. The direct contribution of warmer conditions to global sea level (thermosteric) is uncertain. We report here a global network of LIG sea surface temperatures (SST) obtained from various published temperature proxies (e.g. faunal and floral plankton assemblages, Mg ∕ Ca ratios of calcareous organisms, and alkenone U37K′). We summarize the current limitations of SST reconstructions for the LIG and the spatial temperature features of a naturally warmer world. Because of local δ18O seawater changes, uncertainty in the age models of marine cores, and differences in sampling resolution and/or sedimentation rates, the reconstructions are restricted to mean conditions. To avoid bias towards individual LIG SSTs based on only a single (and potentially erroneous) measurement or a single interpolated data point, here we report average values across the entire LIG. Each site reconstruction is given as an anomaly relative to 1981–2010, corrected for ocean drift, and where available seasonal estimates are provided (189 annual, 99 December–February, and 92 June–August records). To investigate the sensitivity of the reconstruction to high temperatures, we also report maximum values during the first 5 millennia of the LIG (129–124 ka). We find mean global annual SST anomalies of 0.2 ± 0.1 ∘C averaged across the LIG and an early maximum peak of 0.9 ± 0.1 ∘C, respectively. The global dataset provides a remarkably coherent pattern of higher SST increases at polar latitudes than in the tropics (demonstrating the polar amplification of surface temperatures during the LIG), with comparable estimates between different proxies. Polewards of 45∘ latitude, we observe annual SST anomalies averaged across the full LIG of > 0.8 ± 0.3 ∘C in both hemispheres with an early maximum peak of > 2.1 ± 0.3 ∘C. Using the reconstructed SSTs suggests a mean LIG global thermosteric sea level rise of 0.08 ± 0.1 m and a peak contribution of 0.39 ± 0.1 m, respectively (assuming warming penetrated to 2000 m depth). The data provide an important natural baseline for a warmer world, constraining the contributions of Greenland and Antarctic ice sheets to global sea level during a geographically widespread expression of high sea level, and can be used to test the next inter-comparison of models for projecting future climate change. The dataset described in this paper, including summary temperature and thermosteric sea level reconstructions, is available at https://doi.org/10.1594/PANGAEA.904381 (Turney et al., 2019).

Data Revisions and the Statistical Relation of Global Mean Sea Level and Surface Temperature

We study the stability of estimated linear statistical relations of global mean temperature and global mean sea level with regard to data revisions. Using four different model specifications proposed in the literature, we compare coefficient estimates and long-term sea level projections using two different vintages of each of the annual time series, covering the periods 1880–2001 and 1880–2013. We find that temperature and sea level updates and revisions have a substantial influence both on the magnitude of the estimated coefficients of influence (differences of up to 50%) and therefore on long-term projections of sea level rise following the RCP4.5 and RCP6 scenarios (differences of up to 40 cm by the year 2100). This shows that in order to replicate earlier results that informed the scientific discussion and motivated policy recommendations, it is crucial to have access to and to work with the data vintages used at the time.

Lessons from a high-CO<sub>2</sub> world: an ocean view from ∼ 3 million years ago

Abstract. A range of future climate scenarios are projected for high atmospheric CO2 concentrations, given uncertainties over future human actions as well as potential environmental and climatic feedbacks. The geological record offers an opportunity to understand climate system response to a range of forcings and feedbacks which operate over multiple temporal and spatial scales. Here, we examine a single interglacial during the late Pliocene (KM5c, ca. 3.205±0.01 Ma) when atmospheric CO2 exceeded pre-industrial concentrations, but were similar to today and to the lowest emission scenarios for this century. As orbital forcing and continental configurations were almost identical to today, we are able to focus on equilibrium climate system response to modern and near-future CO2. Using proxy data from 32 sites, we demonstrate that global mean sea-surface temperatures were warmer than pre-industrial values, by ∼2.3 ∘C for the combined proxy data (foraminifera Mg∕Ca and alkenones), or by ∼3.2–3.4 ∘C (alkenones only). Compared to the pre-industrial period, reduced meridional gradients and enhanced warming in the North Atlantic are consistently reconstructed. There is broad agreement between data and models at the global scale, with regional differences reflecting ocean circulation and/or proxy signals. An uneven distribution of proxy data in time and space does, however, add uncertainty to our anomaly calculations. The reconstructed global mean sea-surface temperature anomaly for KM5c is warmer than all but three of the PlioMIP2 model outputs, and the reconstructed North Atlantic data tend to align with the warmest KM5c model values. Our results demonstrate that even under low-CO2 emission scenarios, surface ocean warming may be expected to exceed model projections and will be accentuated in the higher latitudes.

A joint role for forced and internally-driven variability in the decadal modulation of global warming

Despite the observed monotonic increase in greenhouse-gas concentrations, global mean temperature displays important decadal fluctuations typically attributed to both external forcing and internal variability. Here, we provide a robust quantification of the relative contributions of anthropogenic, natural, and internally-driven decadal variability of global mean sea surface temperature (GMSST) by using a unique dataset consisting of 30-member large initial-condition ensembles with five Earth System Models (ESM-LE). We present evidence that a large fraction (~29–53%) of the simulated decadal-scale variance in individual timeseries of GMSST over 1950–2010 is externally forced and largely linked to the representation of volcanic aerosols. Comparison with the future (2010–2070) period suggests that external forcing provides a source of additional decadal-scale variability in the historical period. Given the unpredictable nature of future volcanic aerosol forcing, it is suggested that a large portion of decadal GMSST variability might not be predictable.

Decomposing the response of the stratospheric Brewer–Dobson circulation to an abrupt quadrupling in CO<sub>2</sub>

Abstract. We perform time-slice experiments using HadGEM3-A to decompose the long-term (years 101–150) response of the Brewer–Dobson circulation (BDC) to an abrupt quadrupling in CO2 (4×CO2) into (1) a rapid atmospheric adjustment, (2) a contribution from the global-average sea surface temperature (SST) change (+3.4 K), and (3) an SST pattern effect. The SST fields are derived from the CMIP5 multi-model ensemble. Two further experiments explore the impact on the BDC of the spread in global-average SST response to 4×CO2 across the CMIP5 models (range 2.1–4.9 K). At 70 hPa (10 hPa) the annual-mean tropical upward mass flux increases by 45 % (35 %) due to the 4×CO2 perturbation. At 70 hPa, around 70 % of the increase is from the global-uniform SST warming, with the remainder coming in similar contributions from the rapid adjustment and SST pattern effect. In contrast, at 10 hPa the increase in mass flux comes mainly from the rapid adjustment (∼40 %) and the uniform SST warming (∼45 %), with a small contribution from the SST pattern. At 10 hPa, the effect of the multi-model spread in global-mean SST is comparable in magnitude to the rapid adjustment. Conversely, at 70 hPa the effect of spread in global-mean SST is substantially larger than both the rapid adjustment and the SST pattern effect. We derive an approximately linear sensitivity of the tropical upward mass flux to global surface air temperature change of 0.62×109 kg s−1 K−1 (9 % K−1) at 70 hPa and 0.10×109 kg s−1 K−1 (6 % K−1) at 10 hPa. The results confirm the most important factor for the acceleration of the BDC in the lower stratosphere under increased CO2 is global SST changes. We also quantify for the first time that the rapid adjustment to CO2 is of similar importance to SSTs for the increased BDC in the upper stratosphere. This demonstrates a potential for a fast and slow timescale of the response of the BDC to greenhouse gas forcing, with the relative prominence of those timescales being height dependent.

Using Late Pleistocene sea surface temperature reconstructions to constrain future greenhouse warming

Future greenhouse warming projections conducted with coupled climate models still exhibit a substantial spread in response to a given anthropogenic greenhouse gas concentration scenario. In order to constrain this spread and to provide robust warming projections, our understanding of Earth's global-mean surface temperature response to radiative forcing (referred to as climate sensitivity) needs to be further refined. Here we estimate an averaged glacial/interglacial climate sensitivity using 25 transient Earth system model simulations of the Last Glacial Cycle and a global-mean sea surface temperature (SST) reconstruction derived from 64 globally-distributed paleo-proxies of SST. Our results document that Earth's averaged Late Pleistocene equilibrium climate sensitivity is in the order of ∼4.2 K per CO2 doubling. Using the Representative Concentration Pathway 8.5 for future greenhouse radiative forcing, this value translates into a global-mean surface warming of ∼5.0 K by the year 2100 relative to pre-industrial levels. This estimate is in excellent agreement with the ensemble-mean projection of climate simulations conducted as part of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Our uncertainty analysis reveals further that the lack of robust reconstructions of glacial aerosol forcing is a key contributor to the overall uncertainty of paleo-based estimates of climate sensitivity.

A Multivariate AMV Index and Associated Discrepancies Between Observed and CMIP5 Externally Forced AMV

AbstractAtlantic Multidecadal Variability (AMV) is a multivariate phenomenon. Here for the first time we obtain a multivariate AMV index and associated patterns using Multivariate Empirical Orthogonal Function (MEOF) analysis to explore the multivariate nature of AMV. Coherent multidecadal variability that is unique to the Atlantic is found in the observed MEOF‐extracted AMV, various AMV‐related indices, and an Atlantic Meridional Overturning Circulation fingerprint. When the signal associated with global mean sea surface temperature is removed from both observations and Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations, the residual CMIP5 forced basin‐wide sea surface temperature‐based AMV index disagrees strongly with the observed residual. Only the observed residual basin‐wide sea surface temperature‐based AMV index retains a strong AMV signal. The MEOF approach still extracts a residual CMIP5 forced AMV signal that is unique to the Atlantic, although very different from observations. Our findings suggest that the observed AMV is not dominated by external forcing.

The Importance of Unresolved Biases in Twentieth-Century Sea Surface Temperature Observations

Abstract A new analysis of sea surface temperature (SST) observations indicates notable uncertainty in observed decadal climate variability in the second half of the twentieth century, particularly during the decades following World War II. The uncertainties are revealed by exploring SST data binned separately for the two predominant measurement types: “engine-room intake” (ERI) and “bucket” measurements. ERI measurements indicate large decreases in global-mean SSTs from 1950 to 1975, whereas bucket measurements indicate increases in SST over this period before bias adjustments are applied but decreases after they are applied. The trends in the bias adjustments applied to the bucket data are larger than the global-mean trends during the period 1950–75, and thus the global-mean trends during this period derive largely from the adjustments themselves. This is critical, since the adjustments are based on incomplete information about the underlying measurement methods and are thus subject to considerable uncertainty. The uncertainty in decadal-scale variability is particularly pronounced over the North Pacific, where the sign of low-frequency variability through the 1950s to 1970s is different for each measurement type. The uncertainty highlighted here has important—but in our view widely overlooked—implications for the interpretation of observed decadal climate variability over both the Pacific and Atlantic basins during the mid-to-late twentieth century.