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Quantifying signals and uncertainties in climate models is essential for the detection, attribution, prediction and projection of climate change 1 – 3 . Although inter-model agreement is high for large-scale temperature signals, dynamical changes in atmospheric circulation are very uncertain 4 . This leads to low confidence in regional projections, especially for precipitation, over the coming decades 5 , 6 . The chaotic nature of the climate system 7 – 9 may also mean that signal uncertainties are largely irreducible. However, climate projections are difficult to verify until further observations become available. Here we assess retrospective climate model predictions of the past six decades and show that decadal variations in North Atlantic winter climate are highly predictable, despite a lack of agreement between individual model simulations and the poor predictive ability of raw model outputs. Crucially, current models underestimate the predictable signal (the predictable fraction of the total variability) of the North Atlantic Oscillation (the leading mode of variability in North Atlantic atmospheric circulation) by an order of magnitude. Consequently, compared to perfect models, 100 times as many ensemble members are needed in current models to extract this signal, and its effects on the climate are underestimated relative to other factors. To address these limitations, we implement a two-stage post-processing technique. We first adjust the variance of the ensemble-mean North Atlantic Oscillation forecast to match the observed variance of the predictable signal. We then select and use only the ensemble members with a North Atlantic Oscillation sufficiently close to the variance-adjusted ensemble-mean forecast North Atlantic Oscillation. This approach greatly improves decadal predictions of winter climate for Europe and eastern North America. Predictions of Atlantic multidecadal variability are also improved, suggesting that the North Atlantic Oscillation is not driven solely by Atlantic multidecadal variability. Our results highlight the need to understand why the signal-to-noise ratio is too small in current climate models 10 , and the extent to which correcting this model error would reduce uncertainties in regional climate change projections on timescales beyond a decade. Current models are too noisy to predict climate usefully on decadal timescales, but two-stage post-processing of model outputs greatly improves predictions of decadal variations in North Atlantic winter climate.

Purpose of Review Recent Atlantic climate prediction studies are an exciting new contribution to an extensive body of research on Atlantic decadal variability and predictability that has long emphasized the unique role of the Atlantic Ocean in modulating the surface climate. We present a survey of the foundations and frontiers in our understanding of Atlantic variability mechanisms, the role of the Atlantic Meridional Overturning Circulation (AMOC), and our present capacity for putting that understanding into practice in actual climate prediction systems. Recent Findings The AMOC—or more precisely, the buoyancy-forced thermohaline circulation (THC) that encompasses both overturning and gyre circulations—appears to underpin decadal timescale prediction skill in the subpolar North Atlantic in retrospective forecasts. Skill in predicting more wide-ranging climate variations, including those over land, is more limited, but there are indications this could improve with more advanced models. Summary Preliminary successes in the field of initialized Atlantic climate prediction confirm the climate relevance of low-frequency Atlantic Ocean dynamics and suggest that useful decadal climate prediction is a realizable goal.

Regional temperature changes are a crucial factor in affecting agriculture, ecosystems and societies, which depend greatly on local temperatures. We identify a nonuniform warming pattern in summer around the mid-1990s over the Eurasian continent, with a predominant amplified warming over Europe-West Asia and Northeast Asia but much weaker warming over Central Asia. It is found that the nonuniform warming concurs with both the phase shift of the Atlantic Multi-decadal Oscillation (AMO) and the decadal change in the Silk Road Pattern (SRP), which is an upper-tropospheric teleconnection pattern over the Eurasian continent during summer. We suggest that the AMO may modulate the decadal change in SRP and then induce the zonal asymmetry in temperature changes. Our results have important implications for decadal prediction of regional warming pattern in Eurasia based on the predictable AMO.

The Northwest Pacific (NWP) tropical cyclone (TC) activity exhibits significant decadal variations with alternating active and inactive periods. However, it remains unknown whether such kinds of decadal variations are predictable. Here, we develop a dynamic-statistic model for the decadal predictions of the tropical cyclone genesis frequency (TCGF) and accumulated cyclone energy (ACE) index of the NWP TCs. The dynamic-statistic model is a combination of decadal prediction experiments by coupled general circulation models (CGCM) from the CMIP6 Decadal Climate Prediction Project (DCPP) and multiple linear regression models based on the correlation relationships between the NWP TCGF (ACE) and large-scale variability modes of sea surface temperature (SST) anomalies in observations. For the TCGF, we first calculate anomalous SST intensities associated with Atlantic multidecadal variability (AMV), Pacific decadal oscillation (PDO), and global mean SST (GMSST) predicted by the decadal prediction experiments. Then, they are substituted into the regression model trained by the historical observational TCs and SST to predict the NWP TCGF. For the ACE, one more predictor, viz. the anomalous SST in the NWP, is involved in its regression model. The dynamic-statistic model can be applied for both deterministic and probabilistic predictions with multi-model ensemble mean, and individual members of the decadal prediction experiments used, respectively. Retrospective predictions for the past 50 years show that the correlation skill of the deterministic predictions for the NWP TCGF (ACE) in the future 2–5 and 6–9 years reach 0.71 and 0.59 (0.59 and 0.41), respectively. The results of this dynamic-statistic model will provide decision-makers of the western Pacific Rim countries with valuable information to adapt to variations in NWP TC activity over the next 10 years.

The modes of variability that arise from the slow-decadal (potentially predictable) and intra-decadal (unpredictable) components of decadal mean temperature and precipitation over China are examined, in a 1000 year (850–1850 AD) experiment using the CCSM4 model. Solar variations, volcanic aerosols, orbital forcing, land use, and greenhouse gas concentrations provide the main forcing and boundary conditions. The analysis is done using a decadal variance decomposition method that identifies sources of potential decadal predictability and uncertainty. The average potential decadal predictabilities (ratio of slow-to-total decadal variance) are 0.62 and 0.37 for the temperature and rainfall over China, respectively, indicating that the (multi-)decadal variations of temperature are dominated by slow-decadal variability, while precipitation is dominated by unpredictable decadal noise. Possible sources of decadal predictability for the two leading predictable modes of temperature are the external radiative forcing, and the combined effects of slow-decadal variability of the Arctic oscillation (AO) and the Pacific decadal oscillation (PDO), respectively. Combined AO and PDO slow-decadal variability is associated also with the leading predictable mode of precipitation. External radiative forcing as well as the slow-decadal variability of PDO are associated with the second predictable rainfall mode; the slow-decadal variability of Atlantic multi-decadal oscillation (AMO) is associated with the third predictable precipitation mode. The dominant unpredictable decadal modes are associated with intra-decadal/inter-annual phenomena. In particular, the El Niño–Southern Oscillation and the intra-decadal variability of the AMO, PDO and AO are the most important sources of prediction uncertainty.

The eastward‐moving large‐scale convective system associated with the Madden‐Julian Oscillation (MJO) significantly impact global weather and climate. Recent decades have seen notable changes in the MJO's lifecycle due to non‐uniform tropical ocean warming, with the roles of natural climate variability and anthropogenic influence still requiring quantification. This study examines observed and projected long‐term changes in the MJO phase speed using four twentieth‐century reanalyses and CMIP6 simulations. We find a substantial increase in MJO phase speed in three reanalyses during the twentieth century (0.6–1.2 m s⁻1 century⁻1) and further increase in MJO phase speed during the twenty‐first century (0.3–1.5 m s⁻1 century⁻1), with notable multidecadal fluctuations. We attribute the overall acceleration of the MJO to the global warming‐driven increase in the meridional moisture gradient around the warm pool while attributing the multidecadal variability in the MJO phase speed to changes in the zonal moisture gradient associated with the Pacific Decadal Oscillation. Plain Language Summary The Madden‐Julian Oscillation (MJO) is a crucial phenomenon in the tropics that impacts weather and climate globally. Although earlier research has discussed the observed changes in the MJO lifecycle due to tropical ocean warming, we still need to understand the role of natural climate variability associated with the MJO lifecycle. This study uses twentieth century reanalyses and future climate model projections to investigate how the speed of the MJO propagation has changed over time. We find that the speed of the MJO's eastward propagation has increased significantly in three of the reanalyses during the twentieth century and continues rising in the twenty‐first century. We believe that the overall increase in MJO speed is due to global warming, which enhances the meridional moisture difference around the warm pool area. We also noted significant multidecadal variation in the MJO propagation speed. The multidecadal changes in MJO speed are linked to variations in the zonal moisture difference influenced by the Pacific Decadal Oscillation. Key Points Increasing MJO phase speed is identified in three twentieth‐century reanalyses We attribute the MJO's eastward acceleration to the long‐term changes in the meridional moisture gradient Pacific Decadal Oscillation influences multidecadal variation in the MJO phase speed

A new index is developed for the Interdecadal Pacific Oscillation, termed the IPO Tripole Index (TPI). The IPO is associated with a distinct ‘tripole’ pattern of sea surface temperature anomalies (SSTA), with three large centres of action and variations on decadal timescales, evident in the second principal component (PC) of low-pass filtered global SST. The new index is based on the difference between the SSTA averaged over the central equatorial Pacific and the average of the SSTA in the Northwest and Southwest Pacific. The TPI is an easily calculated, non-PC-based index for tracking decadal SST variability associated with the IPO. The TPI time series bears a close resemblance to previously published PC-based indices and has the advantages of being simpler to compute and more consistent with indices used to track the El Niño–Southern Oscillation (ENSO), such as Niño 3.4. The TPI also provides a simple metric in physical units of °C for evaluating decadal and interdecadal variability of SST fields in a straightforward manner, and can be used to evaluate the skill of dynamical decadal prediction systems. Composites of SST and mean sea level pressure anomalies reveal that the IPO has maintained a broadly stable structure across the seven most recent positive and negative epochs that occurred during 1870–2013. The TPI is shown to be a robust and stable representation of the IPO phenomenon in instrumental records, with relatively more variance in decadal than shorter timescales compared to Niño 3.4, due to the explicit inclusion of off-equatorial SST variability associated with the IPO.

This study reveals distinct co‐variability between the North Pacific and the North Atlantic‐European (NAE) region at multi‐decadal and interannual timescales using reanalysis data. On interannual to decadal timescales, sea surface temperature (SST) anomalies in the North Pacific appear in phase with the traditional Pacific Decadal Oscillation (PDO), while in the tropics resemble El Niño‐Southern Oscillation (ENSO). The extratropical signal is the ENSO‐forced wave train in the troposphere correlating with a weaker stratospheric polar vortex. On multi‐decadal timescales (20–25 years), SST anomalies are stronger over the Kuroshio‐Oyashio Extension, and turbulent heat flux anomalies suggest a potential oceanic influence. The tropospheric teleconnection evolves differently through North America projecting onto the Pacific North American pattern, resulting in a stronger polar vortex. Consistently, the corresponding impacts on NAE surface climate are mostly out of phase. Results highlight the challenge of interpreting past and future trends in the Pacific‐NAE teleconnection.

The performance of a new historical reanalysis, the NOAA–CIRES–DOE Twentieth Century Reanalysis version 3 (20CRv3), is evaluated via comparisons with other reanalyses and independent observations. This dataset provides global, 3-hourly estimates of the atmosphere from 1806 to 2015 by assimilating only surface pressure observations and prescribing sea surface temperature, sea ice concentration, and radiative forcings. Comparisons with independent observations, other reanalyses, and satellite products suggest that 20CRv3 can reliably produce atmospheric estimates on scales ranging from weather events to long-term climatic trends. Not only does 20CRv3 recreate a ‘‘best estimate’’ of the weather, including extreme events, it also provides an estimate of its confidence through the use of an ensemble. Surface pressure statistics suggest that these confidence estimates are reliable. Comparisons with independent upper-air observations in the Northern Hemisphere demonstrate that 20CRv3 has skill throughout the twentieth century. Upper-air fields from 20CRv3 in the late twentieth century and early twenty-first century correlate well with full-input reanalyses, and the correlation is predicted by the confidence fields from 20CRv3. The skill of analyzed 500-hPa geopotential heights from 20CRv3 for 1979–2015 is comparable to that of modern operational 3–4-day forecasts. Finally, 20CRv3 performs well on climate time scales. Long time series and multidecadal averages of mass, circulation, and precipitation fields agree well with modern reanalyses and station- and satellite-based products. 20CRv3 is also able to capture trends in tropospheric-layer temperatures that correlate well with independent products in the twentieth century, placing recent trends in a longer historical context.

The tropical cyclone (TC) genesis number in the western North Pacific (WNP) exhibits a pronounced decadal decrease around the mid-1990s, with prominent seasonal and spatial inhomogeneity. This decadal shift of TC activity is mostly confined to the southeastern part of the WNP and occurs mainly during the second half of the calendar year. Accordingly, westward and northeastward TC recurving movements strongly decreased in recent decades after 1995 compared with TC tracks in the earlier period (1979–1994). We find that this TC activity decadal change is associated with tropical Pacific decadal variability, which is measured here by a low-pass filtered Niño3.4 index. In contrast to the earlier period, the anomalous cold mean state in the tropical Pacific during recent decades favored the enhancement of zonal vertical wind shear (UVWS) and suppressed TC activity. This tropical Pacific mean state change is possibly related to decadal changes of El Niño–Southern Oscillation (ENSO) properties (i.e., more La Niña events occurred during recent decades). This relationship between tropical Pacific mean state change and the UVWS in the southeastern WNP on decadal timescales is further validated based on longer observations (1951–2017) and control simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The statistical relationships between TC activity and the Pacific Decadal Oscillation (PDO) or Atlantic Multidecadal Oscillation (AMO) are weaker and insignificant, both for the observations and for simulations. Our results imply that decadal variations of the tropical Pacific mean state should be taken into account when predicting WNP TC activities on decadal timescales.