Search

This paper attempts to enhance our understanding of the causes of Atlantic multidecadal variability (AMV). Following the literature, we define the AMV as the SST averaged over the North Atlantic basin, linearly detrended and low-pass filtered. There is an ongoing debate about the drivers of the AMV, which include internal variability generated from the ocean or atmosphere (or both) and external radiative forcing. We test the role of these factors in explaining the time history, variance, and spatial pattern of the AMV using a 41-member ensemble from a fully coupled version of CESM and a 10-member ensemble of the CESM atmosphere coupled to a slab ocean. The large ensemble allows us to isolate the role of external forcing versus internal variability, and the model differences allow us to isolate the role of coupled ocean circulation. Both with and without coupled ocean circulation, external forcing explains more than half of the variance of the observed AMV time series, indicating its important role in simulating the twentieth-century AMV phases. In this model the net effect of ocean processes is to reduce the variance of the AMV. Dynamical ocean coupling also reduces the ability of the model to simulate the characteristic spatial pattern of the AMV, but forcing has little impact on the pattern. Historical forcing improves the time history and variance of the AMV simulation, while the more realistic ocean representation reduces the variance below that observed and lowers the correlation with observations.

Persistent multiyear cold states of the tropical Pacific Ocean drive hydroclimate anomalies worldwide, including persistent droughts in the extratropical Americas. Here, the atmosphere and ocean dynamics and thermodynamics of multiyear cold states of the tropical Pacific Ocean are investigated using European Centre for Medium-Range Weather Forecasts reanalyses and simplified models of the ocean and atmosphere. The cold states are maintained by anomalous ocean heat flux divergence and damped by increased surface heat flux from the atmosphere to ocean. The anomalous ocean heat flux divergence is contributed to by both changes in the ocean circulation and thermal structure. The keys are an anomalously shallow thermocline that enhances cooling by upwelling and anomalous westward equatorial currents that enhance cold advection. The thermocline depth anomalies are shown to be a response to equatorial wind stress anomalies. The wind stress anomalies are shown to be a simple dynamical response to equatorial SST anomalies as mediated by precipitation anomalies. The cold states are fundamentally maintained by atmosphere-ocean coupling in the equatorial Pacific. The physical processes that maintain the cold states are well approximated by linear dynamics for ocean and atmosphere and simple thermodynamics.

The North Atlantic Oscillation (NAO) is predictable in climate models at near-decadal timescales. Predictive skill derives from ocean initialization, which can capture variability internal to the climate system, and from external radiative forcing. Herein, we show that predictive skill for the NAO in a very large uninitialized multi-model ensemble is commensurate with previously reported skill from a state-of-the-art initialized prediction system. The uninitialized ensemble and initialized prediction system produce similar levels of skill for northern European precipitation and North Atlantic SSTs. Identifying these predictable components becomes possible in a very large ensemble, confirming the erroneously low signal-to-noise ratio previously identified in both initialized and uninitialized climate models. Though the results here imply that external radiative forcing is a major source of predictive skill for the NAO, they also indicate that ocean initialization may be important for particular NAO events (the mid-1990s strong positive NAO), and, as previously suggested, in certain ocean regions such as the subpolar North Atlantic ocean. Overall, we suggest that improving climate models’ response to external radiative forcing may help resolve the known signal-to-noise error in climate models.

The most prominent feature of the time-mean global meridional overturning circulation (MOC) is the Atlantic MOC (AMOC). However, interannual variability of the global MOC is shown here to be dominated by Pacific MOC (PMOC) variability over the full depth of the ocean at most latitudes. This dominance of interannual PMOC variability is robust across modern climate models and an observational state estimate. PMOC interannual variability has large-scale organization, its most prominent feature being a cross-equatorial cell spanning the tropics. Idealized experiments show that this variability is almost entirely wind driven. Interannual anomalies of zonal mean zonal wind stress produce zonally integrated Ekman transport anomalies that are larger in the Pacific Ocean than in the Atlantic Ocean, simply because the Pacific is wider than the Atlantic at most latitudes. This contrast in Ekman transport variability implies greater variability in the near-surface branch of the PMOC when compared with the near-surface branch of the AMOC. These near-surface variations in turn drive compensating flow anomalies below the Ekman layer. Because the baroclinic adjustment time is longer than a year at most latitudes, these compensating flow anomalies have baroclinic structure spanning the full depth of the ocean. Additional analysis reveals that interannual PMOC variations are the dominant contribution to interannual variations of the global meridional heat transport. There is also evidence of interaction between interannual PMOC variability and El Niño–Southern Oscillation.

Significance How the magnitude of El Niño will change is of great societal concern, yet it remains largely unknown. Here we show analysis of how changing El Niño properties, due to 20th century climate change, can shed light on changes to the intensity of El Niño in the future. Since the 1970s, El Niño has changed its origination from the eastern Pacific to the western Pacific, along with increased strong El Niño events due to a background warming in the western Pacific warm pool. This suggests the controlling factors that may lead to increased extreme El Niño events in the future. If the observed background changes continue under future anthropogenic forcing, more frequent extreme El Niño events will induce profound socioeconomic consequences., El Niño’s intensity change under anthropogenic warming is of great importance to society, yet current climate models’ projections remain largely uncertain. The current classification of El Niño does not distinguish the strong from the moderate El Niño events, making it difficult to project future change of El Niño’s intensity. Here we classify 33 El Niño events from 1901 to 2017 by cluster analysis of the onset and amplification processes, and the resultant 4 types of El Niño distinguish the strong from the moderate events and the onset from successive events. The 3 categories of El Niño onset exhibit distinct development mechanisms. We find El Niño onset regime has changed from eastern Pacific origin to western Pacific origin with more frequent occurrence of extreme events since the 1970s. This regime change is hypothesized to arise from a background warming in the western Pacific and the associated increased zonal and vertical sea-surface temperature (SST) gradients in the equatorial central Pacific, which reveals a controlling factor that could lead to increased extreme El Niño events in the future. The Coupled Model Intercomparison Project phase 5 (CMIP5) models’ projections demonstrate that both the frequency and intensity of the strong El Niño events will increase significantly if the projected central Pacific zonal SST gradients become enhanced. If the currently observed background changes continue under future anthropogenic forcing, more frequent strong El Niño events are anticipated. The models’ uncertainty in the projected equatorial zonal SST gradients, however, remains a major roadblock for faithful prediction of El Niño’s future changes.

North Atlantic sea surface temperatures (SST) exhibit a lagged response to the North Atlantic Oscillation (NAO) in both models and observations, which has previously been attributed to changes in ocean heat transport. Here we examine the lagged relationship between the NAO and Atlantic multidecadal variability (AMV) in the context of the two other major components of the AMV: atmospheric noise and external forcing. In preindustrial control runs, we generally find that after accounting for spurious signals introduced by filtering, the SST response to the NAO is only statistically significant in the subpolar gyre. Further, the lagged SST response to the NAO is small in magnitude and offers a limited contribution to the AMV pattern, statistics, or predictability. When climate models include variable external forcing, the relationship between the NAO and AMV is obscured and becomes inconsistent. In these historically forced runs, knowledge of the prior NAO offers reduced predictability. The differences between the preindustrial and the historically forced ensembles suggest that we do not yet have enough observational data to surmise the true NAO–AMV relationship and add evidence that external forcing plays a substantial role in producing the AMV.

Tropical Pacific decadal variability (TPDV), though not the totality of Pacific decadal variability, has wide-ranging climatic impacts. It is currently unclear whether this phenomenon is predictable. In this study, we reconstruct the attractor of the tropical Pacific system in long, unforced simulations from an intermediate-complexity model, two general circulation models (GCMs), and the observations with the aim of assessing the predictability of TPDV in these systems. We find that in the intermediate-complexity model, positive (high variance, El Niño–like) and negative (low variance, La Niña–like) phases of TPDV emerge as a pair of regime-like states. The observed system bears resemblance to this behavior, as does one GCM, while the other GCM does not display this structure. However, these last three time series are too short to confidently characterize the full distribution of interdecadal variability. The intermediate-complexity model is shown to lie in highly predictable parts of its attractor 37% of the time, during which most transitions between TPDV regimes occur. The similarities between the observations and this system suggest that the tropical Pacific may be somewhat predictable on interdecadal time scales.

From 1875 to 1878, concurrent multiyear droughts in Asia, Brazil, and Africa, referred to as the Great Drought, caused widespread crop failures, catalyzing the so-called Global Famine, which had fatalities exceeding 50 million people and long-lasting societal consequences. Observations, paleoclimate reconstructions, and climate model simulations are used 1) to demonstrate the severity and characterize the evolution of drought across different regions, and 2) to investigate the underlying mechanisms driving its multiyear persistence. Severe or record-setting droughts occurred on continents in both hemispheres and in multiple seasons, with the “Monsoon Asia” region being the hardest hit, experiencing the single most intense and the second most expansive drought in the last 800 years. The extreme severity, duration, and extent of this global event is associated with an extraordinary combination of preceding cool tropical Pacific conditions (1870–76), a record-breaking El Niño (1877–78), a record strong Indian Ocean dipole (1877), and record warm North Atlantic Ocean (1878) conditions. Composites of historical analogs and two sets of ensemble simulations—one forced with global sea surface temperatures (SSTs) and another forced with tropical Pacific SSTs—were used to distinguish the role of the extreme conditions in different ocean basins. While the drought in most regions was largely driven by the tropical Pacific SST conditions, an extreme positive phase of the Indian Ocean dipole and warm North Atlantic SSTs, both likely aided by the strong El Niño in 1877–78, intensified and prolonged droughts in Australia and Brazil, respectively, and extended the impact to northern and southeastern Africa. Climatic conditions that caused the Great Drought and Global Famine arose from natural variability, and their recurrence, with hydrological impacts intensified by global warming, could again potentially undermine global food security.

The El Nino Southern Oscillation (ENSO) is a major source of interannual climate variability. ENSO life cycles and the associated teleconnections evolve over multiple years at a global scale. This analysis is the first attempt to characterize the structure of the risk posed by trans-Pacific ENSO teleconnections to crop production in the greater Pacific Basin region. In this analysis we identify the large-scale atmospheric dynamics of ENSO teleconnections that affect heat and moisture stress during the growing seasons of maize, wheat and soy. We propose a coherent framework for understanding how trans-Pacific ENSO teleconnections pose a correlated risk to crop yields in major agricultural belts of the Americas, Australia and China over the course of an ENSO life cycle by using observations and a multi-model ensemble of climate anomalies during crop flowering seasons. Trans-Pacific ENSO teleconnections are often (but not always) offsetting between major producing regions in the Americas and those in northern China or Australia. El Ninos tend to create good maize and soybean growing conditions in the US and southeast South America, but poor growing conditions in northern China, southern Mexico and the Cerrado in Brazil. The opposite is true during La Nina. Wheat growing conditions in southeast South America generally have the opposite sign of those in Australia. Furthermore, multi-year La Ninas can force multi-year growing season anomalies in Argentina and Australia. Most ENSO teleconnections relevant for crop flowering seasons are the result of a single trans-Pacific circulation anomaly that develops in boreal summer and persists through the following spring. During the late summer and early fall of a developing ENSO event, the tropical Pacific forces an atmospheric anomaly in the northern midlatitudes that spans the Pacific from northern China to North America and in the southern midlatitudes from Australia to southeast South America. This anomaly directly links the soybean and maize growing seasons of the US, Mexico and China and the wheat growing seasons of Argentina, southern Brazil and Australia. The ENSO event peaks in boreal winter, when the atmospheric circulation anomalies intensify and affect maize and soybeans in southeast South America. As the event decays, the ENSO-induced circulation anomalies persist through the wheat flowering seasons in China and the US.

This paper summarizes advances in research on tropical–polar teleconnections, made roughly over the last decade. Elucidating El Niño–Southern Oscillation (ENSO) impacts on high latitudes has remained an important focus along different lines of inquiry. Tropical to polar connections have also been discovered at the intraseasonal time scale, associated with Madden–Julian oscillations (MJOs). On the time scale of decades, changes in MJO phases can result in temperature and sea ice changes in the polar regions of both hemispheres. Moreover, the long-term changes in SST of the western tropical Pacific, tropical Atlantic, and North Atlantic Ocean have been linked to the rapid winter warming around the Antarctic Peninsula, while SST changes in the central tropical Pacific have been linked to the warming in West Antarctica. Rossby wave trains emanating from the tropics remain the key mechanism for tropical and polar teleconnections from intraseasonal to decadal time scales. ENSO-related tropical SST anomalies affect higher-latitude annular modes by modulating mean zonal winds in both the subtropics and midlatitudes. Recent studies have also revealed the details of the interactions between the Rossby wave and atmospheric circulations in high latitudes. We also review some of the hypothesized connections between the tropics and poles in the past, including times when the climate was fundamentally different from present day especially given a larger-than-present-day global cryosphere. In addition to atmospheric Rossby waves forced from the tropics, large polar temperature changes and amplification, in part associated with variability in orbital configuration and solar irradiance, affected the low–high-latitude connections.

Predictions of changes of the land monsoon rainfall (LMR) in the coming decades are of vital importance for successful sustainable economic development. Current dynamic models, though, have shown little skill in the decadal prediction of the Northern Hemisphere (NH) LMR (NHLMR). The physical basis and predictability for such predictions remain largely unexplored. Decadal change of the NHLMR reflects changes in the total NH continental precipitation, tropical general circulation, and regional land monsoon rainfall over northern Africa, India, East Asia, and North America. Using observations from 1901 to 2014 and numerical experiments, it is shown that the decadal variability of the NHLMR is rooted primarily in (i) the north–south hemispheric thermal contrast in the Atlantic–Indian Ocean sector measured by the North Atlantic–south Indian Ocean dipole (NAID) sea surface temperature (SST) index and (ii) an east–west thermal contrast in the Pacific measured by an extended El Niño–Southern Oscillation (XEN) index. Results from a 500-yr preindustrial control experiment demonstrate that the leading mode of decadal NHLMR and the associated NAID and XEN SST anomalies may be largely an internal mode of Earth’s climate system, although possibly modified by natural and anthropogenic external forcing. A 51-yr, independent forward-rolling decadal hindcast was made with a hybrid dynamic conceptual model and using the NAID index predicted by a multiclimate model ensemble. The results demonstrate that the decadal changes in the NHLMR can be predicted approximately a decade in advance with significant skills, opening a promising way forward for decadal predictions of regional land monsoon rainfall worldwide.

Abstarct In this model study the authors explore the possibility that the internal component of the Atlantic multidecadal oscillation (AMO) sea surface temperature (SST) signal is indistinguishable from the response to white noise forcing from the atmosphere and ocean. Here, complex models are compared without externally varying forcing with a one-dimensional noise-driven model for SST. General analytic expressions are obtained for both unfiltered and low-pass filtered lead–lag correlations. It is shown that this simple model reproduces many of the simulated lead–lag relationships among temperature, rate of change of temperature, and surface heat flux. It is concluded that the finding that at low frequencies the ocean loses heat to the atmosphere when the temperature is warm, which has been interpreted as showing that the ocean circulation drives the AMO, is a necessary consequence of the fact that at long periods the net heat flux (ocean plus atmosphere) is zero to a good approximation. It does not distinguish between the atmosphere and ocean as the source of the AMO and is consistent with the hypothesis that the AMO is driven by white noise heat fluxes. It is shown that some results in the literature are artifacts of low-pass filtering, which creates spurious low-frequency signals when the underlying data are white or red noise. It is concluded that in the absence of external forcing the AMO in most GCMs is consistent with being driven by white noise, primarily from the atmosphere.

In this analysis we show how globally coherent teleconnections from life-cycles of the El Nino Southern Oscillation (ENSO) lead to correlated crop production anomalies in North and South America. We estimate the magnitude of ENSO-induced Pan-American production anomalies and discuss how increasing crop harvesting frequency may affect Pan-American production variability. We find that ENSO accounts for ∼72%, 30% and 57% of Pan-American maize, soybean and wheat production variability, respectively. ENSO-induced production anomalies are greatest for maize, with median anomalies of ∼5% of Pan-American production. ENSO-induced yield anomalies for maize and soybeans tend to be of the same sign in North America and southeast South America but of an opposite sign in northeast Brazil. Teleconnections for wheat are more complicated because ENSO affects wheat yields via lagged soil moisture teleconnections in the US and an increased probability of disease in South America, but anomalies tend to be of the same sign in North America and southeast South America. After broadly characterizing ENSO-induced production anomalies, we demonstrate that they are not static in time. Increasing crop harvesting frequency has affected the correlated risks posed by ENSO. We use a soil water balance to show that in Brazil changing to a safrinha cropping cycle increases both the mean water stress and the ENSO-induced soil water content anomalies during flowering in both the maize and soybean seasons, which is a result of increasing evaporative demand during times of lower precipitation and moving the flowering seasons into months with strong ENSO teleconnections. Increasing crop harvesting frequency in Brazil has therefore increased ENSO-induced production variability of soybeans and maize.

Focusing on ENSO seasonal phase locking, diversity in peak location, and propagation direction, as well as the El Niño–La Niña asymmetry in amplitude, duration, and transition, a set of empirical probabilistic diagnostics (EPD) is introduced to investigate how the ENSO behaviors reflected in SST may change in a warming climate. EPD is first applied to estimate the natural variation of ENSO behaviors. In the observations El Niños and La Niñas mainly propagate westward and peak in boreal winter. El Niños occur more at the eastern Pacific whereas La Niñas prefer the central Pacific. In a preindustrial control simulation of the GFDL CM2.1 model, the El Niño–La Niña asymmetry is substantial. La Niña characteristics generally agree with observations but El Niño’s do not, typically propagating eastward and showing no obvious seasonal phase locking. So an alternative approach is using a stochastically forced simulation of a nonlinear data-driven model, which exhibits reasonably realistic ENSO behaviors and natural variation ranges. EPD is then applied to assess the potential changes of ENSO behaviors in the twenty-first century using CMIP5 models. Other than the increasing SST climatology, projected changes in many aspects of ENSO reflected in SST anomalies are heavily model dependent and generally within the range of natural variation. Shifts favoring eastward-propagating El Niño and La Niña are the most robust. Given various model biases for the twentieth century and lack of sufficient model agreements for the twenty-first-century projection, whether the projected changes for ENSO behaviors would actually take place remains largely uncertain.

The characteristic evolution of El Nino Southern Oscillation (ENSO) on timescales of months to years means that risks to agriculture have structure between seasons and years. The potential for consecutive ENSO-induced yield anomalies is of particular interest in major food producing areas, where modest changes in yield have significant effects on global markets. In this study, we analyse how multi-year El Nino and La Nina life cycles relate to climate sensitive portions of major crop-growing seasons in North and South America. We analyse the dynamics underlying these life cycles to illustrate which aspects of the system are most important for agriculture. In North America, the same-season teleconnections affecting soybean and maize have been well studied, but we demonstrate the importance of lagged soil moisture teleconnections for wheat in the southern Great Plains. In South America, peak ENSO sea surface temperature (SST) teleconnections are concurrent with, and therefore critical for, wheat and maize growing seasons while soil moisture memory in Argentina plays an important role during the soybean growing season. Finally, we show that ENSO teleconnection life cycles are consistent with historical yield anomalies. Both El Nino and La Nina life cycles tend to force consecutive seasons of either above or below expected yields. While the magnitude of the yield anomalies forced by ENSO is often modest, they occur in major crop-producing regions.

The Atlantic Multidecadal Oscillation (AMO) affects climate variability in the North Atlantic basin and adjacent continents with potential societal impacts. Previous studies based on model simulations and short-term satellite retrievals hypothesized an important role for cloud radiative forcing in modulating the persistence of the AMO in the tropics, but this mechanism remains to be tested with long-term observational records. Here we analyze datasets that span multiple decades and present new observational evidence for a positive feedback between total cloud amount, sea-surface temperature (SST), and atmospheric circulation that can strengthen the persistence and amplitude of the tropical branch of the AMO. In addition, we estimate cloud amount feedback from observations and quantify its impact on SST with idealized modeling experiments. From these experiments we conclude that cloud feedbacks can account for 10% to 31% of the observed SST anomalies associated with the AMO over the tropics.

In a suite of idealized experiments with the Community Atmospheric Model version 3 coupled to a slab ocean, we show that the atmospheric circulation response to CO2 increase is sensitive to extratropical cloud feedback that is potentially nonlinear. Doubling CO2 produces a poleward shift of the Southern Hemisphere (SH) midlatitude jet that is driven primarily by cloud shortwave feedback and modulated by ice albedo feedback, in agreement with earlier studies. More surprisingly, for CO2 increases smaller than ~25 %, the SH jet shifts equatorward. Nonlinearities are also apparent in the Northern Hemisphere, but with less zonal symmetry. Baroclinic instability theory and climate feedback analysis suggest that as the CO2 forcing amplitude is reduced, there is a transition from a regime in which cloud and circulation changes are largely decoupled to a regime in which they are highly coupled. In the dynamically coupled regime, there is an apparent cancellation between cloud feedback due to warming and cloud feedback due to the shifting jet, and this allows the ice albedo feedback to dominate in the high latitudes. The extent to which dynamical coupling effects exceed thermodynamic forcing effects is strongly influenced by cloud microphysics: an alternate model configuration with slightly increased cloud liquid (LIQ) produces poleward jet shifts regardless of the amplitude of CO2 forcing. Altering the cloud microphysics also produces substantial spread in the circulation response to CO2 doubling: the LIQ configuration produces a poleward SH jet shift approximately twice that produced under the default configuration. Analysis of large ensembles of the Canadian Earth System Model version 2 demonstrates that nonlinear, cloud-coupled jet shifts are also possible in comprehensive models. We still expect a poleward trend in SH jet latitude for timescales on which CO2 increases by more than ~25 %. But on shorter timescales, our results give good reason to expect significant equatorward deviations. We also discuss the implications for understanding the circulation response to small external forcings from other sources, such as the solar cycle.

A suite of empirical model experiments under the empirical model reduction framework are conducted to advance the understanding of ENSO diversity, nonlinearity, seasonality, and the memory effect in the simulation and prediction of tropical Pacific sea surface temperature (SST) anomalies. The model training and evaluation are carried out using 4000-yr preindustrial control simulation data from the coupled model GFDL CM2.1. The results show that multivariate models with tropical Pacific subsurface information and multilevel models with SST history information both improve the prediction skill dramatically. These two types of models represent the ENSO memory effect based on either the recharge oscillator or the time-delayed oscillator viewpoint. Multilevel SST models are a bit more efficient, requiring fewer model coefficients. Nonlinearity is found necessary to reproduce the ENSO diversity feature for extreme events. The nonlinear models reconstruct the skewed probability density function of SST anomalies and improve the prediction of the skewed amplitude, though the role of nonlinearity may be slightly overestimated given the strong nonlinear ENSO in GFDL CM2.1. The models with periodic terms reproduce the SST seasonal phase locking but do not improve the prediction appreciably. The models with multiple ingredients capture several ENSO characteristics simultaneously and exhibit overall better prediction skill for more diverse target patterns. In particular, they alleviate the spring/autumn prediction barrier and reduce the tendency for predicted values to lag the target month value.

The authors investigate a sea surface temperature anomaly (SSTA)-only vector autoregressive (VAR) model for prediction of El Niño–Southern Oscillation (ENSO). VAR generalizes the linear inverse method (LIM) framework to incorporate an extended state vector including many months of recent prior SSTA in addition to the present state. An SSTA-only VAR model implicitly captures subsurface forcing observable in the LIM residual as red noise. Optimal skill is achieved using a state vector of order 14–17 months in an exhaustive 120-yr cross-validated hindcast assessment. It is found that VAR outperforms LIM, increasing forecast skill by 3 months, in a 30-yr retrospective forecast experiment.

We use a multilevel vector autoregressive model (VAR-L), to forecast sea surface temperature anomalies (SSTAs) in the Atlantic hurricane Main Development Region (MDR). VAR-L is a linear regression model using global SSTA data from L prior months as predictors. In hindcasts for the recent 30 years, the multilevel VAR-L outperforms a state-of-the-art dynamic forecast model, as well as the commonly used linear inverse model (LIM). The multilevel VAR-L model shows skill in 6–12 month forecasts, with its greatest skill in the months of the active hurricane season. The optimized model for the best long-range skill score in the MDR, chosen by a cross-validation procedure, has 12 time levels and 12 empirical orthogonal function modes. We investigate the optimal initial conditions for MDR SSTA prediction using a generalized singular vector decomposition of the propagation matrix. We find that the added temporal degrees of freedom for the predictands in VAR12 as compared with a LIM model, which allow the model to capture both the local wind–evaporation–SST feedback in the Tropical Atlantic and the impact on the Atlantic of an improved medium-range ENSO forecast, elevate the long-range forecast skill in the MDR.

El Nino diversity and its genesis are debated. An overview of existing work along with a fuzzy clustering analysis and simulations suggest that the asymmetry, irregularity and extremes of El Nino result from westerly wind bursts.

Significance: There is evidence that the 2007−2010 drought contributed to the conflict in Syria. It was the worst drought in the instrumental record, causing widespread crop failure and a mass migration of farming families to urban centers. Century-long observed trends in precipitation, temperature, and sea-level pressure, supported by climate model results, strongly suggest that anthropogenic forcing has increased the probability of severe and persistent droughts in this region, and made the occurrence of a 3-year drought as severe as that of 2007−2010 2 to 3 times more likely than by natural variability alone. We conclude that human influences on the climate system are implicated in the current Syrian conflict. Abstract: Before the Syrian uprising that began in 2011, the greater Fertile Crescent experienced the most severe drought in the instrumental record. For Syria, a country marked by poor governance and unsustainable agricultural and environmental policies, the drought had a catalytic effect, contributing to political unrest. We show that the recent decrease in Syrian precipitation is a combination of natural variability and a long-term drying trend, and the unusual severity of the observed drought is here shown to be highly unlikely without this trend. Precipitation changes in Syria are linked to rising mean sea-level pressure in the Eastern Mediterranean, which also shows a long-term trend. There has been also a long-term warming trend in the Eastern Mediterranean, adding to the drawdown of soil moisture. No natural cause is apparent for these trends, whereas the observed drying and warming are consistent with model studies of the response to increases in greenhouse gases. Furthermore, model studies show an increasingly drier and hotter future mean climate for the Eastern Mediterranean. Analyses of observations and model simulations indicate that a drought of the severity and duration of the recent Syrian drought, which is implicated in the current conflict, has become more than twice as likely as a consequence of human interference in the climate system.

A multiscale-modeling framework for daily rainfall is considered and diagnostic results are presented for an application to the winter season in Northwest India. The daily rainfall process is considered to follow a hidden Markov model (HMM), with the hidden states assumed to be an unknown random function of slowly varying climatic modulation of the winter jet stream and moisture transport dynamics. The data used are from 14 stations over Satluj River basin in winter (December–January–February–March). The period considered is 1977/78–2005/06. The HMM identifies four discrete weather states, which are used to describe daily rainfall variability over study region. Each state was found to be associated with a distinct atmospheric circulation pattern, with the driest and drier states, State 1 and 2 respectively, characterized by a lack of synoptic wave activity. In contrast, the wetter and wettest states, States 3 and 4 respectively, are characterized by a zonally oriented wave train extending across Eurasia between 20N and 40N, identified with ‘western disturbances’ (WD). The occurrence of State 4 is strongly conditioned by the El Nino and Indian Ocean Dipole (IOD) phenomena in winter, which is demonstrated using large-scale correlation maps based on mean sea level pressure and sea surface temperature. This suggests that there is a tendency of higher frequency of the wet days and intense WD activities in winter during El Nino and positive IOD years. These findings, derived from daily rainfall station records, help clarify the sequence of Northern Hemisphere mid-latitude storms bringing winter rainfall over Northwest India, and their association with potentially predictable low frequency modes on seasonal time scales and longer.

The presence of rich ENSO variability in the long unforced simulation of GFDL's CM2.1 motivates the use of tools from dynamical systems theory to study vari- ability in ENSO predictability, and its connections to ENSO magnitude, frequency, and physical evolution. Local Lyapunov exponents (LLEs) estimated from the monthly NINO3 SSTa model output are used to charac- terize periods of increased or decreased predictability. The LLEs describe the growth of infinitesimal perturbations due to internal variability, and are a measure of the immediate predictive uncertainty at any given point in the system phase-space. The LLE-derived predictability esti- mates are compared with those obtained from the error growth in a set of re-forecast experiments with CM2.1. It is shown that the LLEs underestimate the error growth for short forecast lead times (less than 8 months), while they overestimate it for longer lead times. The departure of LLE-derived error growth rates from the re-forecast rates is a linear function of forecast lead time, and is also sensitive to the length of the time series used for the LLE calcula- tion. The LLE-derived error growth rate is closer to that estimated from the re-forecasts for a lead time of 4 months. In the 2,000-year long simulation, the LLE-derived pre- dictability at the 4-month lead time varies (multi)decadally only by 9-18 %. Active ENSO periods are more predict- able than inactive ones, while epochs with regular peri- odicity and moderate magnitude are classified as the most predictable by the LLEs. Events with a deeper thermocline in the west Pacific up to five years prior to their peak, along with an earlier deepening of the thermocline in the east Pacific in the months preceding the peak, are classified as more predictable. Also, the GCM is found to be less pre- dictable than nature under this measure of predictability.

The recent California drought was associated with a persistent ridge at the west coast of North America that has been associated with, in part, forcing from warm SST anomalies in the tropical west Pacific. Here it is considered whether there is a role for human-induced climate change in favoring such a west coast ridge. The models from phase 5 of the Coupled Model Intercomparison Project do not support such a case either in terms of a shift in the mean circulation or in variance that would favor increased intensity or frequency of ridges. The models also do not support shifts toward a drier mean climate or more frequent or intense dry winters or to tropical SST states that would favor west coast ridges. However, reanalyses do show that over the last century there has been a trend toward circulation anomalies over the Pacific–North American domain akin to those during the height of the California drought. The trend has been associated with a trend toward preferential warming of the Indo–west Pacific, an arrangement of tropical oceans and Pacific–North American circulation similar to that during winter 2013/14, the driest winter of the California drought. These height trends, however, are not reproduced in SST-forced atmosphere model ensembles. In contrast, idealized atmosphere modeling suggests that increased tropical Indo-Pacific zonal SST gradients are optimal for forcing height trends that favor a west coast ridge. These results allow a tenuous case for human-driven climate change driving increased gradients and favoring the west coast ridge, but observational data are not sufficiently accurate to confirm or reject this case.

Summary Here we analyze the variability of MAM (March–April–May) and JJAS (June–July–August–September) seasonal Satluj River flow into the Bhakra dam in India through Pearson anomaly correlation and composite analyses with antecedent and concurrent seasonal climatic and atmospheric circulation patterns. The MAM seasonal inflow of Bhakra dam is significantly correlated with winter (DJF/FM) precipitation and temperature of the Satluj basin while the correlation with FM was more prominent for precipitation (snow = +0.72, rainfall = +0.60), and temperature (diurnal temperature range (DTR) = −0.76 and maximum temperature ( T max ) = −0.57). The JJAS inflow was also positively correlated with DJF/FM as well as JJAS precipitation of the Satluj basin while the correlation with basin average FM was the largest (+0.54). These suggested that both MAM and JJAS inflow anomalies are linked with DJF/FM climate over the Western Himalayas and adjoining north and central Indian plains, which were also found to be linked with the fluctuation of equatorial concurrent Sea Surface Temperature anomalies over the western Indian Ocean (max anomaly correlation was > +0.70) and mean sea level pressure over western pole of the Southern Oscillation sea-saw region (max Pearson anomaly correlation was ∼ +0.60). Low (high) MAM inflow was found to be associated with negative (positive) precipitation anomalies over the basin and north India in DJF and FM while FM precipitation anomaly is more concentrated over the Western Himalayas. In addition, low (high) JJAS inflow is also associated with negative (positive) precipitation anomalies over the basin and north India in DJF and over the Western Himalaya in FM and JJAS. Negative geopotential height anomaly at 500 h Pa (Z500) over Siberia and northwestern pacific in DJF, and positive Z500 anomaly over the northwest India in FM were noticed in low MAM inflow years. Whereas high inflow in MAM was linked with a negative Z500 anomaly between two positive Z500 anomaly regions – one over eastern Siberia stretched up to northern Pacific and second over the Eastern Europe in DJF, which gets stronger in FM. We also found southwesterly (northeasterly) wind vectors at 850 h Pa pressure level (uv850) bringing more (less) moisture to the Western Himalayas in DJF and FM in high (low) MAM/JJAS flow years.

Strong El Nino events are followed by massive summer monsoon flooding over the Yangtze River basin (YRB), home to about a third of the population in China. Although the El Nino–Southern Oscillation (ENSO) provides the main source of seasonal climate predictability for many parts of the Earth, the mechanisms of its connection to the East Asian monsoon remain largely elusive. For instance, the traditional Nino3.4 ENSO index only captures precipitation anomalies over East Asia in boreal winter but not during the summer. Here we show that there exists a robust year-round and predictable relationship between ENSO and the Asian monsoon. This connection is revealed by combining equatorial (Nino3.4) and off-equatorial Pacific sea surface temperature anomalies (Nino-A index) into a new metric that captures ENSO's various aspects, such as its interaction with the annual cycle and its different flavors. This extended view of ENSO complexity improves predictability of YRB summer flooding events.

By analyzing a set of the Coupled Model Intercomparison Project phase 3 (CMIP3) climate model projections of the twenty-first century, it is found that the shallow meridional overturning of the Pacific subtropical cells (STCs) show contrasting trends between two hemispheres in a warming climate. The strength of STCs and equivalently the STC surface-layer transport tend to be weakening (strengthening) in the Northern (Southern) Hemisphere as a response to large-scale surface wind changes over the tropical Pacific. The STC pycnocline transport convergence into the equatorial Pacific Ocean from higher latitudes shows a robust weakening in the twenty-first century. This weakening is mainly through interior pathways consistent with the relaxation of the zonal pycnocline tilt, whereas the transport change through western boundary pathways is small and not consistent across models. It is found that the change of the western boundary pycnocline transport is strongly affected by the shoaling of the pycnocline base. In addition, there is a robust weakening of the Indonesian Throughflow (ITF) transport in a warming climate. In the multimodel ensemble mean, the response to greenhouse warming of the upper-ocean mass balance associated with the STCs is such that the weakening of the equatorward pycnocline transport convergence is balanced by a weakening of the poleward surface-layer transport divergence and the ITF transport of similar amounts.

Storm tracks play a major role in regulating the precipitation and hydrological cycle in midlatitudes. The changes in the location and amplitude of the storm tracks in response to global warming will have significant impacts on the poleward transport of heat, momentum and moisture and on the hydrological cycle. Recent studies have indicated a poleward shift of the storm tracks and the midlatitude precipitation zone in the warming world that will lead to subtropical drying and higher latitude moistening. This study agrees with this key feature for not only the annual mean but also different seasons and for the zonal mean as well as horizontal structures based on the analysis of Geophysical Fluid Dynamics Laboratory (GFDL) CM2.1 model simulations. Further analyses show that the meridional sensible and latent heat fluxes associated with the storm tracks shift poleward and intensify in both boreal summer and winter in the late twenty-first century (years 2081-2100) relative to the latter half of the twentieth century (years 1961-2000). The maximum dry Eady growth rate is examined to determine the effect of global warming on the time mean state and associated available potential energy for transient growth. The trend in maximum Eady growth rate is generally consistent with the poleward shift and intensification of the storm tracks in the middle latitudes of both hemispheres in both seasons. However, in the lower troposphere in northern winter, increased meridional eddy transfer within the storm tracks is more associated with increased eddy velocity, stronger correlation between eddy velocity and eddy moist static energy, and longer eddy length scale. The changing characteristics of baroclinic instability are, therefore, needed to explain the storm track response as climate warms. Diagnosis of the latitude-by-latitude energy budget for the current and future climate demonstrates how the coupling between radiative and surface heat fluxes and eddy heat and moisture transport influences the midlatitude storm track response to global warming. Through radiative forcing by increased atmospheric carbon dioxide and water vapor, more energy is gained within the tropics and subtropics, while in the middle and high latitudes energy is reduced through increased outgoing terrestrial radiation in the Northern Hemisphere and increased ocean heat uptake in the Southern Hemisphere. This enhanced energy imbalance in the future climate requires larger atmospheric energy transports in the midlatitudes which are partially accomplished by intensified storm tracks. Finally a sequence of cause and effect for the storm track response in the warming world is proposed that combines energy budget constraints with baroclinic instability theory.

nas), a pattern that is shifted southward (northward) compared with climatology. Paths of coherent phase propagation of transient eddies and of the propagation of wave packets are analyzed. A coherent path of propagation across the Pacific towards North America is identified that is more zonal during El Niwinters and, during La Nihas a dominant path heading northeastward to the Pacific Northwest. A second path heading southeastward from the central Pacific to the tropical east Pacific is more accentuated during La Ni˜ nas than El Ni˜ nos. These changes in wave propagation are reproduced in an ensemble of seasonal integrations of a general circulation model forced by a tropical Pacific sea-surface temperature pattern, confirming that the changes are forced by changes in the mean atmospheric state arising from changes in tropical sea-surface temperature. A simplified model with a specified basic state is used to model the storm tracks for El Ni˜ no and La Ni˜ na winters. The results suggest that the changes in transient eddy propagation and the eddy statistics can be understood in terms of the refraction of transient eddies within different basic states. Copyright c � 2010 Royal Meteorological Society

Decadal variations of very small amplitude [∼0.3°C in sea surface temperature (SST)] in the tropical Pacific Ocean, the genesis region of the interannual El Niño–Southern Oscillation (ENSO) phenomenon, have been shown to have powerful impacts on global climate. Future projections from different climate models do not agree on how this critical feature will change under the influence of anthropogenic forcing. A number of attempts have been made to resolve this issue by examining observed trends from the 1880s to the present, a period of rising atmospheric concentrations of greenhouse gases. A recent attempt concluded that the three major datasets disagreed on the trend in the equatorial gradient of SST. Using a corrected version of one of these datasets, and extending the analysis to the seasonal cycle, it is shown here that all agree that the equatorial Pacific zonal SST gradient has strengthened from 1880 to 2005 during the boreal fall when this gradient is normally strongest. This result appears to favor a theory for future changes based on ocean dynamics over one based on atmospheric energy considerations. Both theories incorporate the expectation, based on ENSO theory, that the zonal sea level pressure (SLP) gradient in the tropical Pacific is coupled to SST and should therefore strengthen along with the SST gradient. While the SLP gradient has not strengthened, it is found that it appears to have weakened only during boreal spring, consistent with the SST seasonal trends. Most of the coupled models included in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report underestimate the strengthening SST gradient in boreal fall, and show almost no change in the SLP gradient in any season. The observational analyses herein suggest that both theories are at work but with relative strengths that vary seasonally, and that the two theories need not be inconsistent with each other.

The response of the equatorial Indian Ocean climate to global warming is investigated using model outputs submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report. In all of the analyzed climate models, the SSTs in the western equatorial Indian Ocean warm more than the SSTs in the eastern equatorial Indian Ocean under global warming; the mean SST gradient across the equatorial Indian Ocean is anomalously positive to the west in a warmer twenty-first-century climate compared to the twentieth-century climate, and it is dynamically consistent with the anomalous westward zonal wind stress and anomalous positive zonal sea level pressure (SLP) gradient to the east at the equator. This change in the zonal SST gradient in the equatorial Indian Ocean is detected even in the lowest-emission scenario, and the size of the change is not necessarily larger in the higher-emission scenario. With respect to the change over the equatorial Pacific in climate projections, the subsurface central Pacific displays the strongest cooling or weakest warming around the thermocline depth compared to that above and below in all of the climate models, whereas changes in the zonal SST gradient and zonal wind stress around the equator are model dependent and not straightforward.

It has recently been proposed, within the framework of the linear shallow-water equations, that tropical Pacific decadal variability (PDV) can be accounted for by basin modes with eigenperiods of 10 to 20 yr, amplifying a midlatitude wind forcing with an essentially white spectrum. Here the authors use a different formalism of linear equatorial wave theory. The Green’s function is computed for the wind-forced response of a linear equatorial shallow-water ocean and use the earlier results of Cane and Moore to obtain a compact, closed form expression for the motion of the equatorial thermocline, which applies to all frequencies lower than seasonal. This expression is new and allows a systematic comparison of the effect of low- and high-latitude winds on the equatorial thermocline. At very low frequencies (decadal time scales), the planetary geostrophic solution used by Cessi and Louazel is recovered, as well as the equatorial wave solution of Liu, and a formal explanation for this convergence is given. Nonetheless, this more general solution leads one to a different interpretation of the results. In contrast to the aforementioned studies, the authors find that the equatorial thermocline is inherently more sensitive to local than to remote wind forcing and that planetary Rossby modes only weakly alter the spectral characteristics of the response. Tropical winds are able to generate a strong equatorial response with periods of 10 to 20 yr, while midlatitude winds can only do so for periods longer than about 50 yr. The results suggest that ocean basin modes are an unlikely explanation of decadal fluctuations in tropical Pacific sea surface temperature.

The monthly summer monsoon rainfall over the Homogeneous Indian Monsoon region (HI) that represents most of the variance of all-India monsoon rainfall is investigated using observational data from 1880 to 2002. Severe droughts in July occur mostly during El Nino events of the boreal summer monsoon season. They occurred frequently in the late 19th to early 20th century, rarely in the middle of the 20th century, and again occasionally occurred after the 1960s. During El Nino events, severe droughts in July over HI are significantly associated with smaller sea surface temperature- (SST) based Indian Ocean Dipole mode index (SSTDMI) in May and July compared to the years without these outstanding events. The evolution of SSTDMI that usually starts around May/June during El Nino events tends to delay when July precipitation over HI is abnormally low. Nino3 values from May through October are not significantly associated with severe droughts over HI in July during El Nino events indicating that the strength of El Nino events is not related to the occurrences of severe droughts in July. Copyright © 2008 Royal Meteorological Society

Could the Dust Bowl drought of the 1930s have been predicted in advance if the SST anomalies of the 1930s had been foreknown? Ensembles of model simulations forced with historical observed SSTs in the global ocean, and also separately in the tropical Pacific and Atlantic Oceans, are compared with an ensemble begun in January 1929 with modeled atmosphere and land initial conditions and integrated through the 1930s with climatological SSTs. The ensemble with climatological SSTs produces values for the precipitation averaged over 1932–39 that are not statistically different from model climatology. In contrast, the ensembles with global SST forcing produce a drought centered in the central plains and southwestern North America that is clearly separated from the model climatology. Both the tropical Pacific and northern tropical Atlantic SST anomalies produce a statistically significant model drought in this region. The modeled drought has a spatial pattern that is different from the observed drought, which was instead centered in the central and northern plains and also impacted the northern Rocky Mountain states but not northeastern Mexico. The model error in extending the Dust Bowl drought too far south is attributed to an incorrect response of the model to warm subtropical North Atlantic SST anomalies. The model error in the northern states cannot be attributed to an incorrect response to tropical SST anomalies. The model also fails to reproduce the strong surface air warming across most of the continent during the 1930s. In contrast, the modeled patterns of precipitation reduction and surface air temperature warming during the 1950s drought are more realistic. Tree-ring records show that the Dust Bowl pattern of drought has occurred before, suggesting that while the extensive human-induced land surface degradation and dust aerosol loading of the 1930s drought may have played an important role in generating the observed drought pattern, natural processes, possibly including land interactions, are capable of generating droughts centered to the north of the main ENSO teleconnection region. Despite this caveat, advance knowledge of tropical SSTs alone would have allowed a high-confidence prediction of a multiyear and severe drought, but one centered too far south and without strong cross-continental warming.

The relationship between all-India summer monsoon rainfall (ISMR) and the timing of (El Niño–Southern Oscillation) ENSO-related warming/cooling is investigated, using observational data during the period from 1881 to 1998. The analysis of the evolutions of Indo-Pacific sea surface temperature (SST) anomalies suggests that when ISMR is not below normal despite the co-occurrence of an El Niño event, warming over the eastern equatorial Pacific starts from boreal winter and evolves early so that the western-central Pacific and Indian Ocean are warmer than normal during the summer monsoon season. In contrast, when the more usual El Niño–dry ISMR relationship holds, the eastern equatorial Pacific starts warming rapidly only about a season before the reference summer so that the western-central Pacific and Indian Oceans remain cold during the monsoon season.

The state of the Indian Ocean dipole representing the SST anomaly difference between the western and southeastern regions of the ocean is investigated using historical SST reconstructions from 1880 to 2004. First, the western and eastern poles of the SST-based dipole mode index are analyzed separately. Both the western and eastern poles display warming trends over this period, particularly after the 1950s. The western pole tends to be anomalously colder than the eastern pole from 1880 to 1919, whereas in the interval 1950–2004 the SST anomalies over the western pole are comparable to those over the eastern pole though there are occasional outliers where the eastern pole is anomalously colder than the western pole.The tendencies of the occurrences of positive and negative dipole events in September–November show three distinct regimes during the period analyzed. In 1880–1919, negative dipole events associated with La Niña events occur more frequently than positive events. In 1920–49, some weak positive events occur relatively independently of El Niño events over the Pacific. The period of 1960–2004 is characterized by strong and frequent occurrences of positive events associated with El Niño events.

This study quantifies the effects of stressful weather and elevated air pollution levels on cause-specific mortality in Santiago, Chile, during the austral winters from 1988 to 1996. A temporal synoptic index (TSI) is used to form weather classes and air pollution classes. Prior applications of the TSI have formed classes solely on the basis of weather and may have systematically underestimated the impact of air pollution levels on daily mortality. In Santiago, the attribution of increased mortality risk was found to be largely dependent on the type of class formed (weather or pollution). High-mortality weather classes were associated with cold, dry and high-pressure conditions, while high-mortality pollution classes were associated with elevated NO2 and PM10–2.5 concentrations. Cardiovascular disease mortality was more sensitive to weather conditions, and respiratory mortality was more sensitive to pollution levels. Respiratory mortality was most sensitive to stressful conditions at longer lag times (3–6 days), while cardiovascular mortality was most sensitive at shorter lag times (0–2 days). By understanding the relative magnitudes of health risks associated with stressful weather and air pollution conditions we can improve existing air pollution/weather watch systems and better anticipate future risks associated with global climate change. Copyright © 2007 Royal Meteorological Society

Severe drought is the greatest recurring natural disaster to strike North America. A remarkable network of centuries-long annual tree-ring chronologies has now allowed for the reconstruction of past drought over North America covering the past 1000 or more years in most regions. These reconstructions reveal the occurrence of past “megadroughts” of unprecedented severity and duration, ones that have never been experienced by modern societies in North America. There is strong archaeological evidence for the destabilizing influence of these past droughts on advanced agricultural societies, examples that should resonate today given the increasing vulnerability of modern water-based systems to relatively short-term droughts. Understanding how these megadroughts develop and persist is a timely scientific problem. Very recently, climate models have succeeded in simulating all of the major droughts over North America from the Civil War to the severe 1998–2004 drought in the western U.S. These numerical experiments indicate the dominating importance of tropical Pacific Ocean sea surface temperatures (SSTs) in determining how much precipitation falls over large parts of North America. Of central importance to drought formation is the development of cool “La Nina-like” SSTs in the eastern tropical Pacific region. This development appears to be partially linked to changes in radiative forcing over that region, which affects the Bjerknes feedback mechanism of the ENSO cycle there. Paradoxically, warmer conditions over the tropical Pacific region lead to the development of cool La Nina-like SSTs there, which is drought inducing over North America. Whether or not this process will lead to a greater prevalence of drought in the future as the world warms due to accumulating greenhouse gases is unclear at this time.

We examine the relationship between the state of the equatorial Indian Ocean, ENSO, and the Indian summer monsoon rainfall using data from 1881 to 1998. The zonal wind anomalies and SST anomaly gradient over the equatorial Indian Ocean are used as indices that represent the condition of the Indian Ocean. Although the index defined by the zonal wind anomalies correlates poorly with Indian summer monsoon rainfall, the linear reconstruction of Indian summer monsoon rainfall on the basis of a multiple regression from the NINO3 and this wind index better specifies the Indian summer monsoon rainfall than the regression with only NINO3. Using contingency tables, we find that the negative association between the categories of Indian summer monsoon rainfall and the wind index is significant during warm years (El Nino) but not during cold years (La Nina). Composite maps of land precipitation also indicate that this relationship is significant during El Nino events. We conclude that there is a significant negative association between Indian summer monsoon rainfall and the zonal wind anomalies over the equatorial Indian Ocean during El Nino events. A similar investigation of the relationship between the SST index and Indian summer monsoon rainfall does not reveal a significant association. Copyright © 2006 Royal Meteorological Society.

Ocean circulation changes not needed What causes the pattern of sea surface temperature change that is seen in the North Atlantic Ocean? This naturally occurring quasi-cyclical variation, known as the Atlantic Multidecadal Oscillation (AMO), affects weather and climate. Some have suggested that the AMO is a consequence of variable large-scale ocean circulation. Clement et al. suggest otherwise. They find that the pattern of AMO variability can be produced in a model that does not include ocean circulation changes, but only the effects of changes in air temperatures and winds. Science , this issue p. 320

The seasonal and interannual predictability of ENSO variability in a version of the Zebiak–Cane coupled model is examined in a perturbation experiment. Instead of assuming that the model is “perfect,” it is assumed that a set of optimal initial conditions exists for the model. These states, obtained through a nonlinear minimization of the misfit between model trajectories and the observations, initiate model forecasts that correlate well with the observations. Realistic estimates of the observational error magnitudes and covariance structures of sea surface temperatures, zonal wind stress, and thermocline depth are used to generate ensembles of perturbations around these optimal initial states, and the error growth is examined. The error growth in response to subseasonal stochastic wind forcing is presented for comparison.In general, from 1975 to 2002, the large-scale uncertainty in initial conditions leads to larger error growth than continuous stochastic forcing of the zonal wind stress fields. Forecast ensemble spread is shown to depend most on the calendar month at the end of the forecast rather than the initialization month, with the seasons of greatest spread corresponding to the seasons of greatest anomaly variance. It is also demonstrated that during years with negative (and rapidly decaying) Niño-3 SST anomalies (such as the time period following an El Niño event), there is a suppression of error growth. In years with large warm ENSO events, the ensemble spread is no larger than in moderately warm years. As a result, periods with high ENSO variance have greater potential prediction utility.In the realistic range of observational error, the ensemble spread has more sensitivity to the initial error in the thermocline depth than to the sea surface temperature or wind stress errors. The thermocline depth uncertainty is the principal reason why initial condition uncertainties are more important than wind noise for ensemble spread.

The high‐latitude ice/snow‐albedo feedback is a principal element in many paleoclimate theories and global warming scenarios. The strength of this feedback is determined by the ice/snow effects on the top‐of atmosphere (TOA) albedo, which is also strongly affected by clouds. Using currently available satellite observations, we estimate the radiative effectiveness (RE) of ice and snow with regards to the TOA albedo, which we define as the change in the TOA albedo corresponding to changes of 0% to 100% in the ice or snow cover. The REs of the northern hemisphere (NH) sea ice, land snow, and southern hemisphere (SH) sea ice are found to be 0.22, 0.23 and 0.16, respectively. This means that, for an incident solar flux of about 400 W m−2 reaching the TOA in the polar latitudes in summer, local reduction in ice/snow concentrations from 100% to 0% will result in a decrease in reflected short wave radiation of approximately 80 W m−2. These changes in the TOA albedo are significant, yet smaller than the a...

A time-dependent trajectory algorithm is used to determine the sources of the Pacific Ocean Equatorial Undercurrent (EUC) in a global climate model with ¼° (eddy permitting) resolution and forced with realistic winds. The primary sources and pathways are identified, and the transformation of properties in temperature/salinity space is explored. An estimate for the quantity of recirculation, a notoriously difficult property to estimate from observational data, is given. Over two-thirds of the water in the Pacific EUC at 140°W originates south of the equator; 70% of the EUC is ventilated outside of the Tropics (poleward of 13°S or 10°N): three-quarters of these extratropical trajectories travel through the western boundary currents between their subduction and incorporation into the EUC, and one-fifth of the extratropical trajectories enter and leave the tropical band at least once before entering the EUC.

Using satellite estimates of snow depth, we examine the interannual variability of the monsoon rains of Bangladesh, an area greatly affected by land surface hydrological processes including Himalayan snowpack size, snowmelt river flooding, and Bay of Bengal storm surge. For the twentieth century, we found Bangladesh monsoon rainfall (BMR) to be uncorrelated with the All-Indian Monsoon Index. This result is consistent with previous findings for shorter time records. We next used a short 9-year record of satellite estimates of April snow

We review forecasts of the future of El Nino and the Southern Oscillation (ENSO), a coupled instability of the ocean–atmosphere system in the tropical Pacific with global impacts. ENSO in the modern world is briefly described, and the physics of the ENSO cycle is discussed. Particular attention is given to the Bjerknes feedback, the instability mechanism which figures prominently in ENSO past and future. Our knowledge of ENSO in the paleoclimate record has expanded rapidly within the last 5 yr. The ENSO cycle is present in all relevant records, going back 130 kyr. It was systematically weaker during the early and middle Holocene, and model studies indicate that this results from reduced amplification in the late summer and early fall, a consequence of the altered mean climate in response to boreal summer perihelion. Data from corals shows substantial decadal and longer variations in the strength of the ENSO cycle within the past 1000 yr; it is suggested that this may be due to solar and volcanic variations in solar insolation, amplified by the Bjerknes feedback. There is some evidence that this feedback has operated in the 20th century and some model results indicate that it will hold sway in the greenhouse future, but it is very far from conclusive. The comprehensive general circulation models used for future climate projections leave us with an indeterminate picture of ENSO's future. Some predict more ENSO activity, some less, with the highly uncertain consensus forecast indicating little change.

The Zebiak–Cane (ZC) model for simulation of the El Nino–Southern Oscillation is shown to be capable of producing sequences of variability that exhibit shifts in the time-mean state of the eastern equatorial Pacific that resemble observations of tropical Pacific decadal variability. The model's performance in predicting these shifts is compared to two naive forecasting strategies. It is found that the ZC model consistently outperforms the two naive forecasts that serve as a null hypothesis in assessing the significance of results. Forecasts initialized during anomalously warm and anomalously cold decades are shown to have the highest predictability. These modeling results suggest that, to a moderate extent, the state of the tropical Pacific in one decade can predetermine its time-mean state in the following decade. However, even in this idealized context decadal forecasting skill is modest. Results are discussed in the context of their implications for the ongoing debate over the origin of decada...

A bimonthly coral-based record of the postbomb radiocarbon content of Solomon Sea surface waters is interpreted to reflect mixing of subtropical surface water and that advected in from the east by the equatorial branch of the South Equatorial Current (SEC). Annual mean D14C has a dynamic range of nearly 175‰, with a total range of nearly 200‰. Prebomb values average 256‰ and the annual mean postbomb maxima occurs in 1985 with a value of 1117%. Interannual variability in the record reflects surface current variations in

Pacific Ocean oceanic heat transport is studied in an ocean model coupled to an atmospheric mixed-layer model. The shallow meridional overturning circulation cells in the Tropics and subtropics transport heat away from the equator. The heat transport by the horizontal gyre circulation in the Tropics is smaller and directed toward the equator. The response of the Pacific oceanic heat transport to El Nino-like winds, extratropical winds, and variations in the Indonesian Throughflow is studied. Large, opposing changes are found in the heat transport by the meridional overturning and the horizontal gyres in response to El Nino-like winds. Consequently, the change in total heat transport is relatively small. The overturning transport decreases and the gyres spin down when the winds decrease in the Tropics. This compensation breaks down when the Indonesian Throughflow is allowed to vary in the model. A reduced Indonesian Throughflow, as observed during El Nino-like conditions, causes a large reduction of poleward heat transport in the South Pacific and affects the ocean heat transport in the southern tropical Pacific. Extratropical atmospheric anomalies can affect tropical ocean heat transport as the tropical thermocline is ventilated from the extratropics. The authors find that changes in the heat loss in the midlatitudes affect tropical ocean heat transport by driving an enhanced buoyancy-driven overturning that reaches into the Tropics. The results are related to observed changes in the overturning circulation in the Pacific in the 1990s, sea surface temperarture changes, and changes in atmospheric circulation. The results imply that the ratio of heat transport in the ocean to that in the atmosphere can change.

Disease transmission forecasts can help minimize human and domestic animal health risks by indicating where disease control and prevention efforts should be focused. For disease systems in which weather-related variables affect pathogen proliferation, dispersal, or transmission, the potential for disease forecasting exists. We present a seasonal forecast of St. Louis encephalitis virus transmission in Indian River County, Florida. We derive an empirical relationship between modeled land surface wetness and levels of SLEV transmission in humans. We then use these data to forecast SLEV transmission with a seasonal lead. Forecast skill is demonstrated, and a real-time seasonal forecast of epidemic SLEV transmission is presented. This study demonstrates how weather and climate forecast skill verification analyses may be applied to test the predictability of an empirical disease forecast model.