Extratropical Sea Surface Temperature Research Articles

Drivers of future extratropical sea surface temperature variability changes in the North Pacific

Under anthropogenic warming, future changes to climate variability beyond specific modes such as the El Niño-Southern Oscillation (ENSO) have not been well-characterized. In the Community Earth System Model version 2 Large Ensemble (CESM2-LE) climate model, the future change to sea surface temperature (SST) variability (and correspondingly marine heatwave intensity) on monthly timescales and longer is spatially heterogeneous. We examined these projected changes (between 1960–2000 and 2060–2100) in the North Pacific using a local linear stochastic-deterministic model, which allowed us to quantify the effect of changes to three drivers on SST variability: ocean “memory” (the SST damping timescale), ENSO teleconnections, and stochastic noise forcing. The ocean memory declines in most areas, but lengthens in the central North Pacific. This change is primarily due to changes in air-sea feedbacks and ocean damping, with the shallowing mixed layer depth playing a secondary role. An eastward shift of the ENSO teleconnection pattern is primarily responsible for the pattern of SST variance change.

Local and Remote Causes of the Equatorial Pacific Cold Sea Surface Temperature Bias in the Kiel Climate Model

Abstract We investigate the origin of the equatorial Pacific cold sea surface temperature (SST) bias and its link to wind biases, local and remote, in the Kiel Climate Model (KCM). The cold bias is common in climate models participating in phases 5 and 6 of the Coupled Model Intercomparison Project. In the coupled experiments with the KCM, the interannually varying NCEP/CFSR wind stress is prescribed over four spatial domains: globally, over the equatorial Pacific (EP), the northern Pacific (NP), and the southern Pacific (SP). The corresponding EP SST bias is reduced by 100%, 52%, 12%, and 23%, respectively. Thus, the EP SST bias is mainly attributed to the local wind bias, with small but not negligible contributions from the extratropical regions. Erroneous ocean circulation driven by overly strong winds causes the cold SST bias, while the surface heat flux counteracts it. Extratropical Pacific SST biases contribute to the EP cold bias via the oceanic subtropical gyres, which is further enhanced by dynamical coupling in the equatorial region. The origin of the wind biases is examined by forcing the atmospheric component of the KCM in a stand-alone mode with observed SSTs and simulated SSTs from the coupled experiments. Wind biases over the EP, NP, and SP regions originate in the atmosphere model. The cold EP SST bias substantially enhances the wind biases over all three regions, while the NP and SP SST biases support local amplification of the wind bias. This study suggests that improving surface wind stress, at and off the equator, is a key to improve mean-state equatorial Pacific SST in climate models.

Effects of paleogeographic changes and CO2 variability on northern mid-latitudinal temperature gradients in the Cretaceous

The Cretaceous ‘greenhouse’ period (~145 to ~66 million years ago, Ma) in Earth’s history is relatively well documented by multiple paleoproxy records, which indicate that the meridional sea surface temperature (SST) gradient increased (non-monotonically) from the Valanginian (~135 Ma) to the Maastrichtian (~68 Ma). Changes in atmospheric CO2 concentration, solar constant, and paleogeography are the primary drivers of variations in the spatiotemporal distribution of SST. However, the particular contribution of each of these drivers (and their underlying mechanisms) to changes in the SST distribution remains poorly understood. Here we use data from a suite of paleoclimate simulations to compare the relative effects of atmospheric CO2 variability and paleogeographic changes on mid-latitudinal SST gradient through the Cretaceous. Further, we use a fundamental model of wind-driven ocean gyres to quantify how changes in the Northern Hemisphere paleogeography weaken the circulation in subtropical ocean gyres, leading to an increase in extratropical SSTs.

The Key Role of Cloud–Climate Coupling in Extratropical Sea Surface Temperature Variability

Abstract Cloud radiative effects have long been known to play a key role in governing the mean climate. In recent years, it has become clear that they also contribute to climate variability in the tropics. Here we build on recent work and probe the role of cloud radiative effects in extratropical sea surface temperature (SST) variability. The impact of cloud radiative effects on climate variability is explored in “cloud-locking” simulations run on an Earth System Model. The method involves comparing the output from two climate simulations: one in which clouds are coupled to atmospheric dynamic and thermodynamic processes, and another in which clouds are prescribed and thus decoupled from them. The results reveal that cloud–climate coupling leads to widespread increases in the amplitudes of extratropical SST variability from monthly to decadal time scales. Notably, it leads to ∼40%–100% increases in the amplitude of monthly to decadal variability over both the North Atlantic and North Pacific Oceans. These increases are consistent with the “reddening” of cloud shortwave radiative effects that arises when clouds respond to the dynamic and thermodynamic state of the atmosphere. The results suggest that a notable fraction of observed Northern Hemisphere SST variability—including that associated with North Pacific and North Atlantic decadal variability—is due to cloud–climate coupling.

Persistent La Niñas drive joint soybean harvest failures in North and South America

Abstract. Around 80 % of global soybean supply is produced in southeast South America (SESA), central Brazil (CB) and the United States (US) alone. This concentration of production in few regions makes global soybean supply sensitive to spatially compounding harvest failures. Weather variability is a key driver of soybean variability, with soybeans being especially vulnerable to hot and dry conditions during the reproductive growth stage in summer. El Niño–Southern Oscillation (ENSO) teleconnections can influence summer weather conditions across the Americas, presenting potential risks for spatially compounding harvest failures. Here, we develop causal structural models to quantify the influence of ENSO on soybean yields via mediating variables like local weather conditions and extratropical sea surface temperatures (SSTs). We show that soybean yields are predominately driven by soil moisture conditions in summer, explaining ∼50 %, 18 % and 40 % of yield variability in SESA, CB and the US respectively. Summer soil moisture is strongly driven by spring soil moisture, as well as by remote extratropical SST patterns in both hemispheres. Both of these soil moisture drivers are again influenced by ENSO. Our causal models show that persistent negative ENSO anomalies of −1.5 standard deviation (SD) lead to a −0.4 SD soybean reduction in the US and SESA. When spring soil moisture and extratropical SST precursors are pronouncedly negative (−1.5 SD), then estimated soybean losses increase to −0.9 SD for the US and SESA. Thus, by influencing extratropical SSTs and spring soil moisture, persistent La Niñas can trigger substantial soybean losses in both the US and SESA, with only minor potential gains in CB. Our findings highlight the physical pathways by which ENSO conditions can drive spatially compounding events. Such information may increase preparedness against climate-related global soybean supply shocks.

What Controls the Interannual Variability of the Boreal Winter Atmospheric River Activities over the Northern Hemisphere?

Abstract Interannual variability of the winter atmospheric river (AR) activities over the Northern Hemisphere is investigated. The leading modes of AR variability over the North Pacific and North Atlantic are first identified and characterized. Over the Pacific, the first mode is characterized by a dipole structure with enhanced AR frequency along the AR peak region at about 30°N and reduced AR frequency farther north. The second mode exhibits a tripole structure with a narrow band of positive AR anomalies at about 30°N and sandwiched by negative anomalies. Over the Atlantic, the first mode exhibits an equatorward shift of the ARs with positive anomalies and negative anomalies located on the equatorward and poleward side of the AR peak region at about 40°N, respectively. The second mode is associated with the strengthening and eastward extension of the AR peak region, which is sandwiched by negative anomalies. A large ensemble of atmospheric global climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), which shows high skill in simulating these modes, is then used to quantify the roles of sea surface temperature (SST) forcing versus internal atmospheric variability in driving the formation of these modes. Results show that SST forcing explains about half of the variance for the Pacific leading modes, while that number drops to about a quarter for the Atlantic leading modes, suggesting higher predictability for the Pacific AR variability. An additional ensemble driven only by observed tropical SST is further utilized to demonstrate the more important role that tropical SST plays in controlling the Pacific AR variability while both tropical and extratropical SST exert comparable influences on the Atlantic AR variability.

Impact of the North Atlantic Sea Surface Temperature Tripole on the Northwestern Pacific Weak Tropical Cyclone Frequency

Abstract Previous studies focused on the intense TCs in the central-southeastern western North Pacific (WNP), whose variability is intimately linked to El Niño–Southern Oscillation and the extratropical sea surface temperature anomaly (SSTA) in the Pacific. Compared with them, weak TCs (WTCs) are more numerous and form farther northwestward. The great number of WTCs and thereby the landfall cases may also cause huge damage to countries in Southeast Asia. However, their modulators are far from fully understood. Our research emphasizes the delayed impact of the early spring North Atlantic tripole SSTA (NAT) on the WTC formation frequency through the “capacitor” effect of sea ice (SIC) and SST in the Barents Sea. Detailed analysis indicates that a positive NAT may modulate an anomalous high in the Barents Sea–North Europe and decrease the local low cloud cover. Thus, more downward solar radiation tends to heat the local SST and decrease the SIC. This warmer Barents Sea could maintain through the typhoon season and excite a significant southeastward wave train, with several centers in the Arctic, central Asia, and East Asia. The abnormal easterly wind to the south of the anticyclone in East Asia facilitates the cyclonic anomaly in the South China Sea, the Philippines, and the subtropical WNP, which reinforces the local monsoon trough and favors the WTC formation there. A physical-based empirical model is developed for the WTC frequency, and hindcast is performed from 1979 to 2018. It shows the early spring NAT effectively improves the prediction skill for the WTC frequency, which can be considered as a crucial source of predictability for WTCs. Significance Statement Previous studies have focused on the western North Pacific intense TCs. The great number of weak TCs (WTCs) and thereby the landfall cases may also cause huge damage. However, modulators for WTCs have not been fully understood. This research emphasizes the potential impact of the early spring North Atlantic tripole SSTA (NAT) pattern on the WTC frequency through the persistent sea ice and sea surface temperature in the Barents Sea. By considering the NAT signal, the seasonal forecasting skill for WTC frequency is effectively improved. Therefore, the NAT signal may help better understand the WTC variability about 1–2 seasons in advance.

Impacts of a Tripolar Sea Surface Temperature Pattern Over Tropical‐North Pacific on Interannual Variations of Spring Extreme Consecutive Dry Days Over Southern China

AbstractIt is well known that the El Niño‐Southern Oscillation (ENSO) has a profound impact on climate over southern China (SC). This study indicates that independent from the ENSO variability, a meridional tripolar sea surface temperature (SST) pattern over tropical‐North Pacific in February has a close relationship with interannual variations in the frequency of spring extreme consecutive dry days (extreme‐CDDs) over SC. Further analyses suggest that the tripolar SST pattern has a good persistence from February to the following spring and could influence the variations of SC extreme‐CDDs through two ways. On one hand, the extratropical SST anomalies of the tripolar pattern can cause the meridional shift of the North Pacific subarctic oceanic front, resulting in a meridional dipole atmospheric pattern over the region from the North Pacific to East Asia through eddy‐mean flow interaction. The meridional atmospheric pattern can influence the East Asian upper‐level jet and western Pacific subtropical high (WPSH), leading to anomalous vertical motion and moisture transport over SC. On the other hand, the SST anomalies of the tripolar pattern over the tropical western Pacific can excite an overturning circulation and influence the WPSH through the Matsuno‐Gill response, also contributing to anomalous vertical motion and moisture transport over SC. These physical processes are further confirmed by numerical simulations. Therefore, through the aforementioned two physical ways, the February tripolar SST pattern can influence the moisture and dynamical conditions associated with the occurrence of extreme‐CDDs, consequently providing a factor and predictor for the variations of SC spring extreme‐CDDs.

Statistical Seasonal Prediction of European Summer Mean Temperature Using Observational, Reanalysis, and Satellite Data

AbstractStatistical climate prediction has sometimes demonstrated higher accuracy than coupled dynamical forecast systems. This study tests the applicability of springtime soil moisture (SM) over Europe and sea surface temperatures (SSTs) of three North Atlantic (NA) regions as statistical predictors of European mean summer temperature (t2m). We set up two statistical-learning (SL) frameworks, based on methods commonly applied in climate research. The SL models are trained with gridded products derived from station, reanalysis, and satellite data (ERA-20C, ERA-Land, CERA, COBE2, CRU, and ESA-CCI). The predictive potential of SM anomalies in statistical forecasting had so far remained elusive. Our statistical models trained with SM achieve high summer t2m prediction skill in terms of Pearson correlation coefficient (r), with r ≥ 0.5 over central and eastern Europe. Moreover, we find that the reanalysis and satellite SM data contain similar information that can be extracted by our methods and used in fitting the forecast models. Furthermore, the predictive potential of SSTs within different areas in the NA basin was tested. The predictive power of SSTs might increase, as in our case, when specific areas are selected. Forecasts based on extratropical SSTs achieve high prediction skill over south Europe. The combined prediction, using SM and SST predictor data, results in r ≥ 0.5 over all European regions south of 50°N and east of 5°W. This is a better skill than the one achieved by other prediction schemes based on dynamical models. Our analysis highlights specific NA midlatitude regions that are more strongly connected to summer mean European temperature.

Understanding the variability of the rainfall dipole in West Africa using the EC-Earth last millennium simulation

There is a well-known mode of rainfall variability associating opposite hydrological conditions over the Sahel region and the Gulf of Guinea, forming a dipole pattern. Previous meteorological observations show that the dipole pattern varies at interannual timescales. Using an EC-Earth climate model simulation for last millennium (850–1850 CE), we investigate the rainfall variability in West Africa over longer timescales. The 1000-year-long simulation data show that this rainfall dipole presents at decadal to multidecadal and centennial variability and long-term trend. Using the singular value decomposition (SVD) analysis, we identified that the rainfall dipole present in the first SVD mode with 60% explained variance and associated with the variabilities in tropical Atlantic sea surface temperature (SST). The second SVD mode shows a monopole rainfall variability pattern centred over the Sahel, associated with the extra-tropical Atlantic SST variability. We conclude that the rainfall dipole-like pattern is a natural variability mode originated from the local ocean–atmosphere-land coupling in the tropical Atlantic basin. The warm SST anomalies in the equatorial Atlantic Ocean favour an anomalous low pressure at the tropics. This low pressure weakens the meridional pressure gradient between the Saharan Heat Low and the tropical Atlantic. It leads to anomalous northeasterly, reduces the southwesterly moisture flux into the Sahel and confines the Gulf of Guinea's moisture convergence. The influence from extra-tropical climate variability, such as Atlantic multidecadal oscillation, tends to modify the rainfall dipole pattern to a monopole pattern from the Gulf of Guinea to Sahara through influencing the Sahara heat low. External forcing—such as orbital forcing, solar radiation, volcanic and land-use—can amplify/dampen the dipole mode through thermal forcing and atmosphere dynamical feedback.

Intermodel Diversity of Simulated Long-term Changes in the Austral Winter Southern Annular Mode: Role of the Southern Ocean Dipole

The Southern Annular Mode (SAM) plays an important role in regulating Southern Hemisphere extratropical circulation. State-of-the-art models exhibit intermodel spread in simulating long-term changes in the SAM. Results from Atmospheric Model Intercomparison Project (AMIP) experiments from 28 models archived in CMIP5 show that the intermodel spread in the linear trend in the austral winter (June−July−August) SAM is significant, with an intermodel standard deviation of 0.28 (10 yr)−1, larger than the multimodel ensemble mean of 0.18 (10 yr)−1. This study explores potential factors underlying the model difference from the aspect of extratropical sea surface temperature (SST). Extratropical SST anomalies related to the SAM exhibit a dipole-like structure between middle and high latitudes, referred to as the Southern Ocean Dipole (SOD). The role of SOD-like SST anomalies in influencing the SAM is found in the AMIP simulations. Model performance in simulating the SAM trend is linked with model skill in reflecting the SOD−SAM relationship. Models with stronger linkage between the SOD and the SAM tend to simulate a stronger SAM trend. The explained variance is about 40% in the AMIP runs. These results suggest improved simulation of the SOD−SAM relationship may help reproduce long-term changes in the SAM.

Factors responsible for consecutive deficit Indian monsoons during 2014 and 2015

Increased frequency of droughts in the recent decade (2002, 2004, 2009, 2014, 2015 being drought years) and the severity of their impact makes drought prediction an inherent component of forecasts for drought mitigation and preparedness. The research and development activities cannot prove their full potential unless they can produce a long lead skillful prediction of extreme conditions like flood or drought. During 2014 and 2015, India experienced deficit monsoon for two successive years. The present study explores the various factors responsible for the droughts during 2014 and 2015 and how well the state-of-the-art coupled model capture the consecutive droughts. The study shows that not only tropical sea surface temperatures (SSTs) but also extratropical SSTs can influence the rainfall over India. Extratropical SSTs impacted the rainfall during 2014 by modulating the strength and location of subtropical jet and tropospheric temperature gradient. On the other hand, tropical SSTs over Pacific Ocean influenced the rainfall during 2015 by modulating the atmospheric teleconnections via Walker circulation. The present-day models considered in this study could not capture consecutively the Indian monsoon droughts and the associated atmosphere and ocean conditions.

Role of sea surface temperature patterns for the Southern Hemisphere jet stream response to CO2 forcing

The Southern Hemisphere (SH) eddy-driven jet stream has been shown to move poleward in climate models in response to greenhouse gas forcing, but the magnitude of the shift is uncertain. Here we address the fact that the latest Coupled Model Intercomparison Project phase 6 (CMIP6) models simulate, on average, a smaller jet shift in response to an abrupt quadrupling in CO2 than the predecessor models (Coupled Model Intercomparison Project phase 5 (CMIP5)), despite producing larger global average surface warming. We focus on the response in the first decade when the majority of the long-term jet shift occurs and when the difference between CMIP5 and CMIP6 models emerges. We hypothesise the smaller poleward jet shift is related to the weaker increase in the meridional sea surface temperature (SST) gradient across the southern extratropics in CMIP6 models. We impose the multi-model mean SST patterns alongside a quadrupling in CO2 in an intermediate complexity general circulation model (IGCM4) and show that many of the regional and seasonal differences in lower tropospheric zonal winds between CMIP5 and CMIP6 models are reproduced by prescribing the SST patterns. The main exception is in austral summer when the imposed SST patterns and CO2 increase in IGCM4 produce weaker differences in zonal wind response compared to those simulated by CMIP5/6 models. Further IGCM4 experiments that prescribe only SH extratropical SSTs simulate a weaker jet shift for CMIP6 SSTs than for CMIP5, comparable to the full experiment. The results demonstrate that SH SST patterns are an important source of uncertainty for the shift of the midlatitude circulation in response to CO2 forcing. The study also provides an alternative explanation than was proposed by Curtis et al (2020 Environ. Res. Lett. 15 64011), who suggested model improvements in jet biases could account for the smaller jet shift in CMIP6 models in the extended austral winter season.

A Linear Inverse Model of Tropical and South Pacific Climate Variability: Optimal Structure and Stochastic Forcing

AbstractA stochastically forced linear inverse model (LIM) of the combined modes of variability from the tropical and South Pacific Oceans is used to investigate the linear growth of optimal initial perturbations and to identify the spatiotemporal features of the stochastic forcing associated with the atmospheric Pacific–South American patterns 1 and 2 (PSA1 and PSA2). Optimal initial perturbations are shown to project onto El Niño–Southern Oscillation (ENSO) and South Pacific decadal oscillation (SPDO), where the inclusion of subsurface South Pacific Ocean temperature variability significantly increases the multiyear linear predictability of the deterministic system. We show that the optimal extratropical sea surface temperature (SST) precursor is associated with the South Pacific meridional mode, which takes from 7 to 9 months to linearly evolve into the final ENSO and SPDO peaks in both the observations and as simulated in an atmosphere-forced ocean model. The optimal subsurface precursor resembles its peak phase, but with a weak amplitude, representing oceanic Rossby waves in the extratropical South Pacific. The stochastic forcing is estimated as the residual by removing the deterministic dynamics from the actual tendency under a centered difference approximation. The resulting stochastic forcing time series satisfies the Gaussian white noise assumption of the LIM. We show that the PSA-like variability is strongly associated with stochastic SST forcing in the tropical and South Pacific Oceans and contributes not only to excite the optimal initial perturbations associated with ENSO and the SPDO but in general to activate the entire stochastic SST forcing, especially in austral summer.

Four-dimensional structure and sub-seasonal regulation of the Indian summer monsoon multi-decadal mode

A better understanding of the drivers and teleconnection mechanisms responsible for the multi decadal mode (MDM) of variability of the Indian summer monsoon rainfall (ISMR) with major socio-economic impacts in the region through clustering of large-scale floods or droughts is key to improving the poor simulation of ISMR MDM by most climate models. Here, using the longest instrumental record of ISMR available (1813–2006) and longest atmospheric and oceanic re-analyses, the global four dimensional (space–time) structures of atmospheric and oceanic fields of the multi-decadal mode of ISMR and sub-seasonal evolution of the teleconnection mechanism are brought out, essential for understanding underlying drivers but lacking so far. The relationships between the spatial structure of winds, Sea Surface Temperature (SST) and thermocline depth with the ISMR MDM indicate that the tropical ocean over the Indo-Pacific domain is passive responding primarily to the surface winds associated with the mode. A close association between the Atlantic Meridional Overturning Circulation (AMOC), north Atlantic (NA) SST, NA sea surface salinity (SSS) and the ISMR MDM indicate a slow oceanic pathway linking NA SST and the ISMR. In addition to strong correlation (~ 0.9) between global spatial patterns of JJAS SST associated with the MDMs of ISMR, NA SST and AMOC, strong temporal coherence (correlations ~ 0.9) between them is suggestive of regulation of the ISMR MDM (T ~ 65-years) by the NA SST associated with the Atlantic Multidecadal Oscillation (AMO) through a ‘fast’ atmospheric bridge. On a seasonal time scale, the atmospheric bridge manifests in the form of a stationary Rossby wave train generated by an anticyclonic (cyclonic) barotropic vorticity located above positive (negative) SST anomaly over NA in two phases of the AMO. That the AMO SST is the driver of the ISMR MDM is further supported when we unravel the sub-seasonal face of the teleconnection between the two. We show that phase locking of active (break) spells with annual cycle during positive (negative) phases of the ISMR MDM are forced by a similar phase locking of barotropic anticyclonic (cyclonic) vorticity over the NA SST with the annual cycle through the generation of a quasi-stationary Rossby wave train with an anticyclonic (cyclonic) vorticity at upper level over the Indian region with the NA columnar vorticity leading Indian monsoon rainfall by about a week. Our findings provide a basis for enhanced predictability of tropical climate through slow modulation by extra-tropical SST.

The North Atlantic as a Driver of Summer Atmospheric Circulation

AbstractSkill in seasonal forecasts in the Northern Hemisphere extratropics is mostly limited to winter. Drivers of summer circulation anomalies over the North Atlantic–European (NAE) sector are poorly understood. Here, we investigate the role of North Atlantic sea surface temperatures (SSTs) in driving summer atmospheric circulation changes. The summer North Atlantic Oscillation (SNAO), the leading mode of observed summer atmospheric circulation variability in the NAE sector, is correlated with a distinct SST tripole pattern in the North Atlantic. An atmospheric general circulation model is used to test whether there are robust atmospheric circulation responses over the NAE sector to concurrent SSTs related to the SNAO. The most robust responses project onto the summer east Atlantic (SEA) pattern, the second dominant mode of observed summer atmospheric circulation variability in the NAE sector, and are most evident at the surface in response to tropical SSTs and at altitude in response to extratropical SSTs. The tropical-to-extratropical teleconnection appears to be due to Rossby wave propagation from SST anomalies, and in turn precipitation anomalies, in the Caribbean region. We identify key biases in the model, which may be responsible for the overly dominant SEA pattern variability, compared to the SNAO, and may also explain why the responses resemble the SEA pattern, rather than the SNAO. Efforts to eradicate these biases, perhaps achieved by higher-resolution simulations or with improved model physics, would allow for an improved understanding of the true response to North Atlantic SST patterns.

A Linear Inverse Model of Tropical and South Pacific Seasonal Predictability

AbstractA multivariate linear inverse model (LIM) is developed to demonstrate the mechanisms and seasonal predictability of the dominant modes of variability from the tropical and South Pacific Oceans. We construct a LIM whose covariance matrix is a combination of principal components derived from tropical and extratropical sea surface temperature, and South Pacific Ocean vertically averaged temperature anomalies. Eigen-decomposition of the linear deterministic system yields stationary and/or propagating eigenmodes, of which the least damped modes resemble El Niño–Southern Oscillation (ENSO) and the South Pacific decadal oscillation (SPDO). We show that although the oscillatory periods of ENSO and SPDO are distinct, they have very close damping time scales, indicating that the predictive skill of the surface ENSO and SPDO is comparable. The most damped noise modes occur in the midlatitude South Pacific Ocean, reflecting atmospheric eastward-propagating Rossby wave train variability. We argue that these ocean wave trains occur due to the high-frequency atmospheric variability of the Pacific–South American pattern imprinting onto the surface ocean. The ENSO spring predictability barrier is apparent in LIM predictions initialized in March–May (MAM) but displays a significant correlation skill of up to ~3 months. For the SPDO, the predictability barrier tends to appear in June–September (JAS), indicating remote but delayed influences from the tropics. We demonstrate that subsurface processes in the South Pacific Ocean are the main source of decadal variability and further that by characterizing the upper ocean temperature contribution in the LIM, the seasonal predictability of both ENSO and the SPDO variability is increased.

Combined Impact of El Niño–Southern Oscillation and Pacific Decadal Oscillation on the Northern Winter Stratosphere

Using reanalysis and the sea surface temperature (SST) analysis, the combined impact of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on the northern winter stratosphere is investigated. The warm and weak stratospheric polar vortex response to El Niño simply appears during positive PDO, whereas the cold and strong stratospheric polar vortex response to La Niña is preferable during negative PDO in the reanalysis. Two mechanisms may account for the enhanced stratospheric response when ENSO and PDO are in phase. First, the asymmetries of the intensity and frequency between El Niño and La Niña can be identified for the two PDO phases. Second, the extratropical SST anomalies in the North Pacific may also play a role in the varying extratropical response to ENSO. The North Pacific SST anomalies related to PDO superimpose ENSO SST anomalies when they are in phase but undermine them when they are out of phase. The superimposed North Pacific SST anomalies help to increase SST meridional gradient anomalies between tropical and extratropics, as well as to lock the local height response to ENSO. Therefore, the passages for the upward propagation of waves from the troposphere is more unimpeded when positive PDO is configured with El Niño, and vice versa when negative PDO is configured with La Niña.

The Role of Extratropical Ocean Warming in the Coupled Climate Response to Arctic Sea Ice Loss

AbstractThe role of extratropical ocean warming in the coupled climate response to Arctic sea ice loss is investigated using coupled atmosphere–ocean general circulation model (AOGCM) and uncoupled atmospheric-only (AGCM) experiments. Coupled AOGCM experiments driven by sea ice albedo reduction and greenhouse gas–dominated radiative forcing are used to diagnose the extratropical sea surface temperature (SST) response to sea ice loss. Sea ice loss is then imposed in AGCM experiments both with and without these extratropical SST changes, which are found to extend beyond the regions where sea ice is lost. Sea ice loss in isolation drives warming that is confined to the Arctic lower troposphere and only a weak atmospheric circulation response. When the extratropical SST response caused by sea ice loss is also included in the forcing, the warming extends into the Arctic midtroposphere during winter. This coincides with a stronger atmospheric circulation response, including an equatorward shift in the eddy-driven jet, a deepening of the Aleutian low, and an expansion of the Siberian high. Similar results are found whether the extratropical SST forcing is taken directly from the AOGCM driven by sea ice loss, or whether they are diagnosed using a two-parameter pattern scaling technique where tropical adjustment to sea ice loss is removed. These results suggest that AGCM experiments that are driven by sea ice loss and only local SST increases will underestimate the Arctic midtroposphere warming and atmospheric circulation response to sea ice loss, compared to AOGCM simulations and the real world.

Evolution of the Global Coupled Climate Response to Arctic Sea Ice Loss during 1990–2090 and Its Contribution to Climate Change

The role of transient Arctic sea ice loss in the projected greenhouse gas–induced late-twentieth- to late-twenty-first-century climate change is investigated using the Geophysical Fluid Dynamics Laboratory’s Coupled Model version 3. Two sets of simulations have been conducted, one with representative concentration pathway (RCP) 8.5 radiative forcing and the second with RCP forcing but with Arctic sea ice nudged to its 1990 state. The difference between the two five-member sets indicates the influence of decreasing Arctic sea ice on the climate system. Within the Arctic, sea ice loss is found to be a primary driver of the surface temperature and precipitation changes. Arctic sea ice depletion also plays a dominant role in projected Atlantic meridional overturning circulation weakening and changes in North Atlantic extratropical sea surface temperature and salinity, especially in the first half century. The effect of present-day Arctic sea ice loss on Northern Hemisphere (NH) extratropical atmospheric circulation is small relative to internal variability and the future sea ice loss effect on atmospheric circulation is distinct from the projected anthropogenic change. Arctic sea ice loss warms NH extratropical continents and is an important contributor to global warming not only over high latitudes but also in the eastern United States. Last, the Arctic sea ice loss displaces the Pacific intertropical convergence zone (ITCZ) equatorward and induces a “mini-global warming” in the tropical upper troposphere.