Quantifying atmosphere and ocean origins of North American precipitation variability

How atmospheric and oceanic processes control North American precipitation variability has been extensively investigated, and yet debates remain. Here we address this question in a 50 km-resolution flux-adjusted global climate model. The high spatial resolution and flux adjustment greatly improve the model’s ability to realistically simulate North American precipitation, the relevant tropical and midlatitude variability and their teleconnections. Comparing two millennium-long simulations with and without an interactive ocean, we find that the leading modes of North American precipitation variability on seasonal and longer timescales exhibit nearly identical spatial and spectral characteristics, explained fraction of total variance and associated atmospheric circulation. This finding suggests that these leading modes arise from internal atmospheric dynamics and atmosphere-land coupling. However, in the fully coupled simulation, North American precipitation variability still correlates significantly with tropical ocean variability, consistent with observations and prior literature. We find that tropical ocean variability does not create its own type of atmospheric variability but excites internal atmospheric modes of variability in midlatitudes. This oceanic impact on North American precipitation is secondary to atmospheric impacts based on correlation. However, relative to the simulation without an interactive ocean, the fully coupled simulation amplifies precipitation variance over southwest North America (SWNA) during late spring to summer by up to 90%. The amplification is caused by a stronger variability in atmospheric moisture content that is attributed to tropical Pacific sea surface temperature variability. Enhanced atmospheric moisture variations over the tropical Pacific are transported by seasonal mean southwesterly winds into SWNA, resulting in larger precipitation variance.

     

How weather impacts the forced climate response

The new interactive ensemble modeling strategy is used to diagnose how noise due to internal atmospheric dynamics impacts the forced climate response during the twentieth century (i.e., 1870?C1999). The interactive ensemble uses multiple realizations of the atmospheric component model coupled to a single realization of the land, ocean and ice component models in order to reduce the noise due to internal atmospheric dynamics in the flux exchange at the interface of the component models. A control ensemble of so-called climate of the twentieth century simulations of the Community Climate Simulation Model version 3 (CCSM3) are compared with a similar simulation with the interactive ensemble version of CCSM3. Despite substantial differences in the overall mean climate, the global mean trends in surface temperature, 500?mb geopotential and precipitation are largely indistinguishable between the control ensemble and the interactive ensemble. Large differences in the forced response; however, are detected particularly in the surface temperature of the North Atlantic. Associated with the forced North Atlantic surface temperature differences are local differences in the forced precipitation and a substantial remote rainfall response in the deep tropical Pacific. We also introduce a simple variance analysis to separately compare the variance due to noise and the forced response. We find that the noise variance is decreased when external forcing is included. In terms of the forced variance, we find that the interactive ensemble increases this variance relative to the control.     

The role of atmospheric internal variability on the prediction skill of interannual North Pacific sea-surface temperatures

The sensitivity of the sea-surface temperature (SST) prediction skill to the atmospheric internal variability (weather noise) in the North Pacific (20^°–60^°N;120^°E–80^°W) on decadal timescales is examined using state-of-the-art Climate Forecasting System model version 2 (CFS) and a variation of CFS in an Interactive Ensemble approach (CFSIE), wherein six copies of atmospheric components with different perturbed initial states of CFS are coupled with the same ocean model by exchanging heat, momentum and fresh water fluxes dynamically at the air-sea interface throughout the model integrations. The CFSIE experiments are designed to reduce weather noise and using a few ten-year long forecasts this study shows that reduction in weather noise leads to lower SST forecast skill. To understand the pathways that cause the reduced SST prediction skill, two twenty-year long forecasts produced with CFS and CFSIE for 1980-2000 are analyzed for the ocean subsurface characteristics that influence SST due to the reduction in weather noise in the North Pacific. The heat budget analysis in the oceanic mixed layer across the North Pacific reveals that weather noise significantly impacts the heat transport in the oceanic mixed layer. In the CFSIE forecasts, the reduced weather noise leads to increased variations in heat content due to shallower mixed layer, diminished heat storage and enhanced horizontal heat advection. The enhancement of the heat advection spans from the active Kuroshio regions of the east coast of Japan to the west coast of continental United States and significantly diffuses the basin-wide SST anomaly (SSTA) contrasts and leads to reduction in the SST prediction skill in decadal forecasts.     

Tropical Pacific internal atmospheric dynamics and resolution in a coupled GCM

A noise reduction technique, namely the interactive ensemble (IE) approach is adopted to reduce noise at the air–sea interface due to internal atmospheric dynamics in a state-of-the-art coupled general circulation model (CGCM). The IE technique uses multiple realization of atmospheric general circulation models coupled to a single ocean general circulation model. The ensembles mean fluxes from the atmospheric simulations are communicated to the ocean component. Each atmospheric simulation receives the same SST coming from the ocean component. The only difference among the atmospheric simulations comes from perturbed initial conditions, thus the atmospheric states are, in principle synoptically independent. The IE technique can be used to better understand the importance of weather noise forcing of natural variability such as El Niño Southern Oscillation (ENSO). To study the impact of weather noise and resolution in the context of a CGCM, two IE experiments are performed at different resolutions. Atmospheric resolution is an important issue since the noise statistics will depend on the spatial scales resolved. A simple formulation to extract atmospheric internal variability is presented. The results are compared to their respective control cases where internal atmospheric variability is left unchanged. The noise reduction has a major impact on the coupled simulation and the magnitude of this effect strongly depends on the horizontal resolution of the atmospheric component model. Specifically, applying the noise reduction technique reduces the overall climate variability more effectively at higher resolution. This suggests that “weather noise” is more important in sustaining climate variability as resolution increases. ENSO statistics, dynamics, and phase asymmetry are all modified by the noise reduction, in particular ENSO becomes more regular with less phase asymmetry when noise is reduced. All these effects are more marked for the higher resolution case. In contrast, ENSO frequency is unchanged by the reduction in the weather noise, but its phase-locking to the annual cycle is strongly dependent on noise and resolution. At low resolution the noise structure is similar to the signal, whereas the spatial structure of the noise deviates from the spatial structure of the signal as resolution increases. It is also suggested that event-to-event differences are largely driven by atmospheric noise as opposed to chaotic dynamics within the context of the large-scale coupled system, suggesting that there is a well-defined “canonical” event.     

La Plata basin precipitation variability in spring: role of remote SST forcing as simulated by GCM experiments

An ensemble of nine experiments with the same interannually varying sea surface temperature (SST), as boundary forcing, and different initial conditions is used to investigate the role of tropical oceans in modulating precipitation variability in the region of La Plata Basin (LPB). The results from the ensemble are compared with a twentieth-century experiment performed with a coupled ocean-atmosphere model, sharing the same atmospheric component. A rotated empirical orthogonal functions analysis of South America precipitation shows that the dominant mode of variability in spring is realistically captured in both experiments. Its principal component (RPC1) correlated with global SST and atmospheric fields identifies the pattern related to El Niño Southern Oscillation and its large-scale teleconnections. Overall the pattern is well simulated in the tropical southern Pacific Ocean, mainly in the ensemble, but it is absent or too weak in other oceanic areas. The coupled model experiment shows a more realistic correlation in the subtropical South Atlantic where air-sea interactions contribute to the relationship between LPB precipitation and SST. The correspondence between model and data is much improved when the composite analysis of SST and atmospheric fields is done over the ensemble members having an RPC1 in agreement with the observations: the improvement relies on avoiding climate noise by averaging only over members that are statistically similar. Furthermore, the result suggests the presence of a high level of uncertainty due to internal atmospheric variability. The analysis of some individual years selected from the model and data RPC1 comparison reveals interesting differences among rainy springs in LPB. For example, 1982, which corresponds to a strong El Niño year, represents a clean case with a distinct wave train propagating from the central Pacific and merging with another one from the eastern tropical south Indian Ocean. The year 2003 is an example of a rainy spring in LPB not directly driven by remote SST forcing. In this case the internal variability has a dominant role, as the model is not able to reproduce the correct local precipitation pattern.     

中纬度北太平洋依赖于ENSO事件及独立于ENSO事件的变率特征:观测事实与海气耦合模式模拟

观测事实显示,在E1 Ni(?)o发生期间,伴随着赤道中东太平洋的增暖,中纬度北大平洋中部表层海温（SST）常出现冷距平,而北美大陆西海岸SST则出现暖距平。借助观测资料分析和海气耦合模式模拟两种手段,检验了北太平洋对ENSO事件的上述响应。观测证据和数值模拟都支持有关学者提出的“大气桥”概念,即大气对赤道中东太平洋SST异常增暖的响应,随后强迫中纬度北太平洋,并导致那里SST的变冷,从而起到了连接热带和热带外特别是中纬度北太平洋的“桥梁”的作用。关于其机制,本文认为主要是海洋对大气强迫的动力响应导致那里的SST变冷,尽管潜热通量的贡献也很显著。至少模式结果证明短波辐射、长波辐射和感热通量的贡献都是次要的。进一步的分析揭示,北太平洋存在着线性独立于ENSO事件的所谓“北太平洋模态”,在空间型上,它和线性地依赖于ENSO事件的模态非常相近,即它们的纬向结构都呈现出扁平的“双极”型,只是彼此间SST距平极大值的中心位置不同。模拟结果表明,北太平洋模态与大气的耦合作用,主要是通过海气热通量交换实现的,其中短波辐射和长波辐射的作用居主导地位,而潜热通量的贡献则基本可以忽略。     

Atmospheric response to the North Atlantic Ocean variability on seasonal to decadal time scales

The NCEP twentieth century reanalyis and a 500-year control simulation with the IPSL-CM5 climate model are used to assess the influence of ocean-atmosphere coupling in the North Atlantic region at seasonal to decadal time scales. At the seasonal scale, the air-sea interaction patterns are similar in the model and observations. In both, a statistically significant summer sea surface temperature (SST) anomaly with a horseshoe shape leads an atmospheric signal that resembles the North Atlantic Oscillation (NAO) during the winter. The air-sea interactions in the model thus seem realistic, although the amplitude of the atmospheric signal is half that observed, and it is detected throughout the cold season, while it is significant only in late fall and early winter in the observations. In both model and observations, the North Atlantic horseshoe SST anomaly pattern is in part generated by the spring and summer internal atmospheric variability. In the model, the influence of the ocean dynamics can be assessed and is found to contribute to the SST anomaly, in particular at the decadal scale. Indeed, the North Atlantic SST anomalies that follow an intensification of the Atlantic meridional overturning circulation (AMOC) by about 9 years, or an intensification of a clockwise intergyre gyre in the Atlantic Ocean by 6 years, resemble the horseshoe pattern, and are also similar to the model Atlantic Multidecadal Oscillation (AMO). As the AMOC is shown to have a significant impact on the winter NAO, most strongly when it leads by 9 years, the decadal interactions in the model are consistent with the seasonal analysis. In the observations, there is also a strong correlation between the AMO and the SST horseshoe pattern that influences the NAO. The analogy with the coupled model suggests that the natural variability of the AMOC and the gyre circulation might influence the climate of the North Atlantic region at the decadal scale.     

Forced and unforced variability of twentieth century North American droughts and pluvials

Research on the forcing of drought and pluvial events over North America is dominated by general circulation model experiments that often have operational limitations (e.g., computational expense, ability to simulate relevant processes, etc). We use a statistically based modeling approach to investigate sea surface temperature (SST) forcing of the twentieth century pluvial (1905?C1917) and drought (1932?C1939, 1948?C1957, 1998?C2002) events. A principal component (PC) analysis of Palmer Drought Severity Index (PDSI) from the North American Drought Atlas separates the drought variability into five leading modes accounting for 62% of the underlying variance. Over the full period spanning these events (1900?C2005), the first three PCs significantly correlate with SSTs in the equatorial Pacific (PC 1), North Pacific (PC 2), and North Atlantic (PC 3), with spatial patterns (as defined by the empirical orthogonal functions) consistent with our understanding of North American drought responses to SST forcing. We use a large ensemble statistical modeling approach to determine how successfully we can reproduce these drought/pluvial events using these three modes of variability. Using Pacific forcing only (PCs 1?C2), we are able to reproduce the 1948?C1957 drought and 1905?C1917 pluvial above a 95% random noise threshold in over 90% of the ensemble members; the addition of Atlantic forcing (PCs 1?C2?C3) provides only marginal improvement. For the 1998?C2002 drought, Pacific forcing reproduces the drought above noise in over 65% of the ensemble members, with the addition of Atlantic forcing increasing the number passing to over 80%. The severity of the drought, however, is underestimated in the ensemble median, suggesting this drought intensity can only be achieved through internal variability or other processes. Pacific only forcing does a poor job of reproducing the 1932?C1939 drought pattern in the ensemble median, and less than one third of ensemble members exceed the noise threshold (28%). Inclusion of Atlantic forcing improves the ensemble median drought pattern and nearly doubles the number of ensemble members passing the noise threshold (52%). Even with the inclusion of Atlantic forcing, the intensity of the simulated 1932?C1939 drought is muted, and the drought itself extends too far into the southwest and southern Great Plains. To an even greater extent than the 1998?C2002 drought, these results suggest much of the variance in the 1932?C1939 drought is dependent on processes other than SST forcing. This study highlights the importance of internal noise and non SST processes for hydroclimatic variability over North America, complementing existing research using general circulation models.     

The variability of the East Asian summer monsoon and its relationship to ENSO in a partially coupled climate model

The variability of the East Asian summer monsoon (EASM) is studied using a partially coupled climate model (PCCM) in which the ocean component is driven by observed monthly mean wind stress anomalies added to the monthly mean wind stress climatology from a fully coupled control run. The thermodynamic coupling between the atmospheric and oceanic components is the same as in the fully coupled model and, in particular, sea surface temperature (SST) is a fully prognostic variable. The results show that the PCCM simulates the observed SST variability remarkably well in the tropical and North Pacific and Indian Oceans. Analysis of the rainfall-SST and rainfall-SST tendency correlation shows that the PCCM exhibits local air-sea coupling as in the fully coupled model and closer to what is seen in observations than is found in an atmospheric model driven by observed SST. An ensemble of experiments using the PCCM is analysed using a multivariate EOF analysis to identify the two major modes of variability of the EASM. The PCCM simulates the spatial pattern of the first two modes seen in the ERA40 reanalysis as well as part of the variability of the first principal component (correlation up to 0.5 for the model ensemble mean). Different from previous studies, the link between the first principal component and ENSO in the previous winter is found to be robust for the ensemble mean throughout the whole period of 1958–2001. Individual ensemble members nevertheless show the breakdown in the relationship before the 1980’s as seen in the observations.     

Ocean–atmosphere Teleconnections Play a Key Role in the Interannual Variability of Seasonal Gross Primary Production in China

Since the 1950s, the terrestrial carbon uptake has been characterized by interannual variations, which are mainly determined by interannual variations in gross primary production (GPP). Using an ensemble of seven-member TRENDY (Trends in Net Land–Atmosphere Carbon Exchanges) simulations during 1951–2010, the relationships of the interannual variability of seasonal GPP in China with the sea surface temperature (SST) and atmospheric circulations were investigated. The GPP signals that mostly relate to the climate forcing in terms of Residual Principal Component analysis (hereafter, R-PC) were identified by separating out the significant impact from the linear trend and the GPP memory. Results showed that the seasonal GPP over China associated with the first R-PC1 (the second R-PC2) during spring to autumn show a monopole (dipole or tripole) spatial structure, with a clear seasonal evolution for their maximum centers from springtime to summertime. The dominant two GPP R-PC are significantly related to Sea Surface Temperature (SST) variability in the eastern tropical Pacific Ocean and the North Pacific Ocean during spring to autumn, implying influences from the El Ni?o–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). The identified SST and circulation factors explain 13%, 23% and 19% of the total variance for seasonal GPP in spring, summer and autumn, respectively. A clearer understanding of the relationships of China’s GPP with ocean–atmosphere teleconnections over the Pacific and Atlantic Ocean should provide scientific support for achieving carbon neutrality targets.     

SST and ENSO variability and change simulated in historical experiments of CMIP5 models

This work documents the diversity in Coupled Model Inter-comparison Project Phase 5 (CMIP5) models in simulating different aspects of sea surface temperature (SST) variability, particularly those associated with the El Niño–Southern Oscillation (ENSO), as well as the impact of low-frequency variations on the ENSO variability and its global teleconnection. The historical simulations (1870–2005) include 10 models with ensemble member ranging from 3 to 10 that are forced with observed atmospheric composition changes reflecting both natural and anthropogenic forcings. It is shown that the majority of the CMIP5 models capture the relative large SST anomaly variance in the tropical central and eastern Pacific, as well as in North Pacific and North Atlantic. The frequency of ENSO is not well captured by almost all models, particularly for the period of 5–6 years. The low-frequency variations in SST caused by external forcings affect the SST variability and also modify the global teleconnection of ENSO. The models reproduce the global averaged SST low-frequency variations, particularly since 1970s. However, majority of the models are unable to correctly simulate the spatial pattern of the observed SST trends. These results suggest that it is still a challenge to reproduce the features of global historical SST variations with the state-of-the-art coupled general circulation model.     

The impact of ENSO periodicity on North Pacific SST variability

The periodicity of ENSO in nature varies. Here we examine how changes in the frequency of ENSO impacts remote teleconnections in the North Pacific. The numerical experiments presented here are designed to simulate perfectly periodic ENSO in the tropical Pacific, and to enable the air–sea interaction in other regions (i.e., the North Pacific) via a simple mixed layer ocean model. The temporal evolution and spatial structure of the North Pacific SST teleconnection patterns are relatively insensitive to the frequency of ENSO, but the amplitude of the variability is sensitive. Specifically, the 2-year period ENSO experiment (P2) shows weak event-by-event consistency in the ENSO response mature pattern. This is because there is not enough time to damp the previously forced ENSO teleconnections (i.e., 1 year earlier). The 4-year period ENSO experiment (P4) has 1 year damping time before a successive ENSO event matures, so the structure of the response pattern is stably repeated. However, the event-by-event variance of anomaly magnitude, specifically responding to El Niño, is still larger than that in the 6-year ENSO experiment (P6), which has 2-year damping time between consecutive ENSO events. In addition, we tested whether the variability due to tropical remote forcing is linearly independent of the extratropical local variability. Statistical tests indicate that tropical remote forcing can constructively or destructively interfere with local variability in the North Pacific. Lastly, there is a non-linear rectification of the ENSO events that can be detected in the climatology.     

The global distribution of sources of atmospheric decadal variability and mechanisms over the tropical Pacific and southern North America

 Understanding natural atmospheric decadal variability is an important element of climate research, and here we investigate the geographic and seasonal diversity in the balance between its competing sources. Data are provided by an ensemble of multi-decadal atmospheric general circulation model experiments, forced by observed sea surface temperatures (SSTs), and verified against observations. First, the nature of internal atmospheric variability is studied. By assessing its spectral character, we refute the idea that internal modes may persist or oscillate on multi-annual time-scales, either through mechanisms purely internal to the atmosphere, or via coupling to the land surface; instead, they behave as a white noise process. Second, and more importantly, the role of oceanic forcing, relative to internal variability, is investigated by extending the ‘analysis of variance’ technique to the frequency domain. Significance testing and confidence intervals are also discussed. In the tropics, atmospheric decadal variability is usually dominated by oceanic forcing, although for some regions less so than at interannual time-scales. A moderate oceanic impact is also found for some extratropical regions in some seasons. Verification against observed mean sea-level pressure (MSLP) data suggests that many of these influences are realistic, although some model errors are also revealed. In other mid- and high-latitude regions, local simulated decadal variability is dominated by random processes, i.e. the integrated effects of chaotic weather systems. Third, we focus on the mechanisms of decadal variability in two specific regions (where the model is well behaved). Over the tropical Pacific, the relative impact of SSTs on decadal MSLP is strongly seasonal such that it peaks in September to November (SON). This is explained by noting that the model atmosphere is responsive to SSTs a little farther west in SON than it is in other seasons, and here it picks up relatively more decadal power from the ocean (the western Pacific being less dominated by ENSO time-scales), causing atmospheric ‘signal-to-noise ratios’ to be enhanced at decadal timescales in SON. Over southern North America, a strong SST impact is found in summer and autumn, resulting in an upward trend of MSLP over recent decades. We suggest this is caused by decadal SST variability in the Caribbean (and to some extent the tropical northeast Pacific in summer), which induces anomalous convective heating over these regions and hence the wider MSLP response. Received: 30 November 1998 / Accepted: 22 April 1999     

冬季北太平洋海表热通量异常和海气相互作用——基于一个全球海气耦合模式长期积分的诊断分析

利用一个全球海气耦合模式长期积分所给出的资料,分析了冬季北太平洋海表湍流热通量（潜热和感热）异常及其对海表温度（SST）异常的影响,并比较了海表热通量诸分量和海洋内部的动力学过程对SST变化的相对重要性。结果表明,冬季热带外海洋上的湍流热通量是影响SST的主要因子,但在北太平洋中部海水的平流作用也不可忽视。冬季热带外海洋向大气释放的潜热和感热通量与SST倾向（而不是SST本身）之间存在着显著的相关,这同Cayan和Reynolds等利用COADS资料和NCEP资料同化模式分析的结果是一致的。模式诊断的结果支持这样一种看法：和热带海洋不同,冬季热带外海洋上的海气相互作用主要地表现为大气对海洋的强迫作用,而不是相反。模式给出的SST倾向的第一个EOF分量及其与海平面气压场的相关特征同Wallace等从观测资料分析所得到的结果是一致的;进一步的分析表明：在冬季北太平洋的大部分区域（特别是西太平洋）,大尺度大气环流异常在很大程度上决定着SST的异常,而这种决定作用正是通过它对湍流热通量的强烈影响来实现的。     

Multi-decadal thermohaline variability in an ocean–atmosphere general circulation model

A century scale integration of a near-global atmosphere–ocean model is used to study the multi-decadal variability of the thermohaline circulation (THC) in the Atlantic. The differences between the coupled and two supplementary ocean-only experiments suggest that a significant component of this variability is controlled by either a collective behavior of the ocean and the atmosphere, particularly in the form of air-sea heat exchange, or sub-monthly random noise present in the coupled system. Possible physical mechanisms giving rise to the mode of this THC variability are discussed. The SST anomaly associated with the THC variability resembles an interdecadal SST pattern extracted from observational data, as well as a pattern associated with the 50–60 year THC variability in the GFDL coupled model. In each case, a warming throughout the subpolar North Atlantic but concentrated along the Gulf Stream and its extension is indicated when the THC is strong. Concomitantly, surface air temperature has positive anomalies over the warmer ocean, with the strongest signal located downwind of the warmest SST anomalies and intruding into the western Eurasian Continent. In addition to the thermal response, there are also changes in the atmospheric flow pattern. More specifically, an anomalous northerly wind develops over the Labrador Sea when the THC is stronger than normal, suggesting a local primacy of the atmospheric forcing in the thermohaline perturbation structure.     

Global SST influence on twentieth century NAO variability

Recent studies have suggested that sea surface temperature (SST) is an important source of variability of the North Atlantic Oscillation (NAO). Here, we deal with four basic aspects contributing to this issue: (1) we investigate the characteristic time scales of this oceanic influence; (2) quantify the scale-dependent hindcast potential of the NAO during the twentieth century as derived from SST-driven atmospheric general circulation model (AGCM) ensembles; (3) the relevant oceanic regions are identified, corresponding SST indices are defined and their relationship to the NAO are evaluated by means of cross spectral analysis and (4) our results are compared with long-term coupled control experiments with different ocean models in order to ensure whether the spectral relationship between the SST regions and the NAO is an intrinsic mode of the coupled climate system, involving the deep ocean circulation, rather than an artefact of the unilateral SST forcing. The observed year-to-year NAO fluctuations are barely influenced by the SST. On the decadal time scales the major swings of the observed NAO are well reproduced by various ensembles from the middle of the twentieth century onward, including the negative state in the 1960s and part of the positive trend afterwards. A six-member ECHAM4-T42 ensemble reveals that the SST boundary condition affects 25% of total decadal-mean and interdecadal-trend NAO variability throughout the twentieth century. The most coherent NAO-related SST feature is the well-known North Atlantic tripole. Additional contributions may arise from the southern Pacific and the low-latitude Indian Ocean. The coupled climate model control runs suggest only the North Atlantic SST-NAO relationship as being a true characteristic of the coupled climate system. The coherence and phase spectra of observations and coupled simulations are in excellent agreement, confirming the robustness of this decadal-scale North Atlantic air–sea coupled mode.     

Pacific interdecadal variability driven by tropical–extratropical interactions

Interactions between the tropical and subtropical northern Pacific at decadal time scales are examined using uncoupled oceanic and atmospheric simulations. An atmospheric model is forced with observed Pacific sea surface temperatures (SST) decadal anomalies, computed as the difference between the 2000–2009 and the 1990–1999 period. The resulting pattern has negative SST anomalies at the equator, with a global pattern reminiscent of the Pacific decadal oscillation. The tropical SST anomalies are responsible for driving a weakening of the Hadley cell and atmospheric meridional heat transport. The atmosphere is then shown to produce a significant response in the subtropics, with wind-stress-curl anomalies having the opposite sign from the climatological mean, consistent with a weakening of the oceanic subtropical gyre (STG). A global ocean model is then forced with the decadal anomalies from the atmospheric model. In the North Pacific, the shallow subtropical cell (STC) spins down and the meridional heat transport is reduced, resulting in positive tropical SST anomalies. The final tropical response is reached after the first 10 years of the experiment, consistent with the Rossby-wave adjustment time for both the STG and the STC. The STC provides the connection between subtropical wind stress anomalies and tropical SSTs. In fact, targeted simulations show the importance of off-equatorial wind stress anomalies in driving the oceanic response, whereas anomalous tropical winds have no role in the SST signal reversal. We further explore the connection between STG, STC and tropical SST with the help of an idealized model. We argue that, in our models, tropical SST decadal variability stems from the forcing of the Pacific subtropical gyre through the atmospheric response to ENSO. The resulting Ekman pumping anomaly alters the STC and oceanic heat transport, providing a negative feedback on the SST. We thus suggest that extratropical atmospheric responses to tropical forcing have feedbacks onto the ocean dynamics that lead to a time-delayed response of the tropical oceans, giving rise to a possible mechanism for multidecadal ocean-atmosphere coupled variability.     

Exploring multi-model atmospheric GCM ensembles with ANOVA

Analysis of variance (ANOVA) is a powerful statistical technique for making inferences about experiments that are influenced by multiple factors. Whilst common in many other scientific fields, its use within the climate community has been limited to date. Here we review the basis for ANOVA and how, in particular, it can be applied to partition the variance in a multi-model ensemble of Atmospheric General Circulation Model simulations. We examine an ensemble of four AGCMs forced with observed twentieth century sea surface temperatures (SST). We show that the dominant contributions to the total variance of seasonal mean sea level pressure arise from between-model differences (the bias term) and internal noise (the noise term). However, which term is most important varies from region to region. Of particular interest is the interaction term, which describes differences between the models in their responses to common SST forcing. The interaction term is found to be largest over the Indian Ocean (in all seasons), and over the subtropical Northwest Pacific in boreal summer. The differences between the model responses in these regions suggest differences in their simulation of atmospheric teleconnections, with potentially important implications, e.g. for seasonal predictions of the South and East Asian Monsoons. Examination of these differences may lead to an understanding of the reasons why models respond differently to common forcing, and ultimately to improvements in the performance of climate models.     

Non-stationarity of the signal and noise characteristics of seasonal precipitation anomalies

In order to improve seasonal-to-interannual precipitation forecasts and their application by decision makers, there is a clear need to understand when, where, and to what extent seasonal precipitation anomalies are driven by potentially predictable surface–atmosphere interactions versus to chaotic interannual atmospheric dynamics. Using a simple Monte Carlo approach, interannual variability and linear trends in the SST-forced signal and potential predictability of boreal winter precipitation anomalies is examined in an ensemble of twentieth century AGCM simulations. Signal and potential predictability are shown to be non-stationary over more than 80% of the globe, while chaotic noise is shown to be stationary over most of the globe. Correlation analysis with respect to magnitudes of the four leading modes of global SST variability suggests that interannual variability and trends in signal and potential predictability over 35% of the globe is associated with ENSO-related SST variability; signal and potential predictability are not significantly associated with SST modes characterized by a global SST trend, North Atlantic SST variability, and North Pacific SST variability, respectively. Results suggest that mechanisms other than SST variability contribute to the non-stationarity of signal and noise characteristics of hydroclimatic variability over mid- and high-latitude regions.     

Multidecadal-to-centennial SST variability in the MPI-ESM simulation ensemble for the last millennium

We assess the responses of North Atlantic, North Pacific, and tropical Indian Ocean Sea Surface Temperatures (SSTs) to natural forcing and their linkage to simulated global surface temperature (GST) variability in the MPI-Earth System Model simulation ensemble for the last millennium. In the simulations, North Atlantic and tropical Indian Ocean SSTs show a strong sensitivity to external forcing and a strong connection to GST. The leading mode of extra-tropical North Pacific SSTs is, on the other hand, rather resilient to natural external perturbations. Strong tropical volcanic eruptions and, to a lesser extent, variability in solar activity emerge as potentially relevant sources for multidecadal SST modes’ phase modulations, possibly through induced changes in the atmospheric teleconnection between North Atlantic and North Pacific that can persist over decadal and multidecadal timescales. Linkages among low-frequency regional modes of SST variability, and among them and GST, can remarkably vary over the integration time. No coherent or constant phasing is found between North Pacific and North Atlantic SST modes over time and among the ensemble members. Based on our assessments of how multidecadal transitions in simulated North Atlantic SSTs compare to reconstructions and of how they contribute characterizing simulated multidecadal regional climate anomalies, past regional climate multidecadal fluctuations seem to be reproducible as simulated ensemble-mean responses only for temporal intervals dominated by major external forcings.