Decadal Prediction Research Articles

Intercomparison of initialization methods for seasonal-to-decadal climate predictions with the NorCPM

Initialization is essential for accurate seasonal-to-decadal (S2D) climate predictions. The initialization schemes used differ on the component initialized, the Data Assimilation method, or the technique. We compare five popular schemes within NorCPM following the same experimental protocol: reanalysis from 1980 to 2010 and seasonal and decadal predictions initialized from the reanalysis. We compare atmospheric initialization—Newtonian relaxation (nudging)—against ocean initialization—Ensemble Kalman Filter—(ODA). On the atmosphere, we explore the benefit of full-field (NudF-UVT) or anomaly (NudA-UVT) nudging of horizontal winds and temperature (U, V, and T) observations. The scheme NudA-UV nudges horizontal winds to disentangle the role of wind-driven variability. The ODA+NudA-UV scheme is a first attempt at joint initialization of ocean and atmospheric components in NorCPM. During the reanalysis, atmospheric nudging improves the synchronization of the atmosphere and land components with the observed data. Conversely, ODA is more effective at synchronizing the ocean component with observations. The atmospheric nudging schemes are better at reproducing specific events, such as the rapid North Atlantic subpolar gyre shift. An abrupt climatological change using the NudA-UV scheme demonstrates that energy conservation is crucial when only assimilating winds. ODA outperforms atmospheric-initialized versions for S2D global predictions, while atmospheric nudging is preferable for accurately initializing phenomena in specific regions, with the technique’s benefit depending on the prediction’s temporal scale. For instance, atmospheric full-field initialization benefits the tropical Atlantic Niño at 1-month lead time, and atmospheric anomaly initialization benefits longer lead times, reducing hindcast drift. Combining atmosphere and ocean initialization yields sub-optimal results, as sustaining the ensemble’s reliability—required for ODA’s performance—is challenging with atmospheric nudging.

Influence of the Pacific Decadal Oscillation on Winter Temperatures and Precipitation Over the Southern Tibetan Plateau

AbstractWe used observational data and a long‐term piControl simulation from the Community Earth System Model Version 2 to investigate the influence of the Pacific Decadal Oscillation (PDO) on the winter climate over the Tibetan Plateau. The results showed that changes in the phase of the PDO have a significant effect on winter temperatures and precipitation over the southern Tibetan Plateau. Changes in the sea surface temperature (SST) during the positive PDO can weaken the Walker circulation and increase the SST in the Indian Ocean. Our analyses of the moist static energy showed that warming of the tropical troposphere over the Indian Ocean caused by the increased SST has resulted in the horizontal advection of anomalous moist enthalpy by the climatological zonal winds, which was responsible for anomalous ascending motion over the Tibetan Plateau. The additional moisture budget suggests that enhanced vertical motion contributes to the increase in winter precipitation and related total cloud cover over the Tibetan Plateau, leading to the increase of snow depth. The increased total cloud cover and snow depth, in turn, reduces net surface shortwave radiation. The surface air temperature of the Tibetan Plateau is then decreased as a result of the reduction in the net surface shortwave radiation. The PDO therefore has an important modulating role in the interdecadal variability of the winter climate over the Tibetan Plateau. We therefore need to focus on changes in the PDO in research related to the decadal prediction of the climate over the Tibetan Plateau.

Skillful prediction of length of day one year ahead in multiple decadal prediction systems

Despite a small amplitude, Length of Day (LOD) change, which varies from one year to another due to changes in Atmospheric Angular Momentum (AAM), determines the accuracy of Global Positioning System (GPS) time calculation. In this study, we examine the prediction skill of LOD and AAM in nine decadal prediction systems archived for the Decadal Climate Prediction Project. A persistence and rebound in LOD prediction skill at one year or longer lead time is found in most models. A poleward propagation of AAM anomaly via wave-mean flow interaction is also qualitatively well reproduced. This long-lead prediction of LOD and AAM is attributed to reliable predictions of the El Niño–Southern Oscillation (ENSO) and the Quasi-Biennial Oscillation (QBO), the former being more systematically related than the latter. This result indicates that the improved ENSO prediction and atmospheric wave-mean flow interaction may lead to better prediction of LOD, AAM and related extratropical climate in the decadal prediction systems.

Making Ecosystem Modeling Operational–A Novel Distributed Execution Framework to Systematically Explore Ecological Responses to Divergent Climate Trajectories

AbstractMarine Ecosystem Models (MEMs) are increasingly driven by Earth System Models (ESMs) to better understand marine ecosystem dynamics, and to analyze the effects of alternative management efforts for marine ecosystems under potential scenarios of climate change. However, policy and commercial activities typically occur on seasonal‐to‐decadal time scales, a time span widely used in the global climate modeling community but where the skill level assessments of MEMs are in their infancy. This is mostly due to technical hurdles that prevent the global MEM community from performing large ensemble simulations with which to undergo systematic skill assessments. Here, we developed a novel distributed execution framework constructed of low‐tech and freely available technologies to enable the systematic execution and analysis of linked ESM/MEM prediction ensembles. We apply this framework on the seasonal‐to‐decadal time scale, and assess how retrospective forecast uncertainty in an ensemble of initialized decadal ESM predictions affects a mechanistic and spatiotemporal explicit global trophodynamic MEM. Our results indicate that ESM internal variability has a relatively low impact on the MEM variability in comparison to the broad assumptions related to reconstructed fisheries. We also observe that the results are also sensitive to the ESM specificities. Our case study warrants further systematic explorations to disentangle the impacts of climate change, fisheries scenarios, MEM internal ecological hypotheses, and ESM variability. Most importantly, our case study demonstrates that a simple and free distributed execution framework has the potential to empower any modeling group with the fundamental capabilities to operationalize marine ecosystem modeling.

Ross–Weddell Dipole Critical for Antarctic Sea Ice Predictability in MPI–ESM–HR

We use hindcasts from a state-of-the-art decadal climate prediction system initialized between 1979 and 2017 to explore the predictability of the Antarctic dipole—that is, the seesaw between sea ice cover in the Weddell and Ross Seas, and discuss its implications for Antarctic sea ice predictability. Our results indicate low forecast skills for the Antarctic dipole in the first hindcast year, with a strong relaxation of March values toward the climatology contrasting with an overestimation of anomalies in September, which we interpret as being linked to a predominance of local drift processes over initialized large-scale dynamics. Forecast skills for the Antarctic dipole and total Antarctic sea ice extent are uncorrelated. Limited predictability of the Antarctic dipole is also found under preconditioning around strong warm and strong cold events of the El Niño-Southern Oscillation. Initialization timing and model drift are reported as potential explanations for the poor predictive skills identified.

Decadal Prediction of Location of Tropical Cyclone Maximum Intensity Over the Western North Pacific

AbstractAttaining skillful decadal predictions for the western North Pacific tropical cyclone (TC) emerges as a formidable challenge, mainly stemming from the limited prediction skills of Pacific Decadal Variability (PDV) within the state‐of‐the‐art models. Assessing sixth Coupled Model Intercomparison Project models' retrospective predictions finds that the predictability of PDV transcends the expectations set by raw forecasts featured by constrained temporal skills and low signal‐to‐noise ratio. Employing a refined approach, we selectively identify the models that capture the diverse phases of PDV and subsequently adjust their variances. This tailored approach yields a compelling concordance between the predicted PDV and observation in phases and variances. Anchored in the heightened prediction skill of PDV, we establish a sophisticated statistical model adept at predicting the latitude of TC's lifetime maximum intensity (LMI). The near‐term prediction indicates a sustained poleward migration of LMI latitude by 1.53° during 2020–2027, increasing subtropical East Asia's TC‐related disaster vulnerability in the coming decade.

Impact of Atlantic multidecadal variability on rainfall intensity distribution and timing of the West African monsoon

Abstract. Previous studies agree on an impact of the Atlantic multidecadal variability (AMV) on the total seasonal rainfall amounts over the Sahel. However, whether and how the AMV affects the distribution of rainfall or the timing of the West African monsoon is not well known. Here we seek to explore these impacts by analyzing daily rainfall outputs from climate model simulations with an idealized AMV forcing imposed in the North Atlantic, which is representative of the observed one. The setup follows a protocol largely consistent with the one proposed by the Component C of the Decadal Climate Prediction Project (DCPP-C). We start by evaluating model's performance in simulating precipitation, showing that models underestimate it over the Sahel, where the mean intensity is consistently smaller than observations. Conversely, models overestimate precipitation over the Guinea coast, where too many rainy days are simulated. In addition, most models underestimate the average length of the rainy season over the Sahel; some are due to a monsoon onset that is too late and others due to a cessation that is too early. In response to a persistent positive AMV pattern, models show an enhancement in total summer rainfall over continental West Africa, including the Sahel. Under a positive AMV phase, the number of wet days and the intensity of daily rainfall events are also enhanced over the Sahel. The former explains most of the changes in seasonal rainfall in the northern fringe, while the latter is more relevant in the southern region, where higher rainfall anomalies occur. This dominance is connected to the changes in the number of days per type of event; the frequency of both moderate and heavy events increases over the Sahel's northern fringe. Conversely, over the southern limit, it is mostly the frequency of heavy events which is enhanced, thus affecting the mean rainfall intensity there. Extreme rainfall events are also enhanced over the whole Sahel in response to a positive phase of the AMV. Over the Sahel, models with stronger negative biases in rainfall amounts compared to observations show weaker changes in response to AMV, suggesting that systematic biases could affect the simulated responses. The monsoon onset over the Sahel shows no clear response to AMV, while the demise tends to be delayed, and the overall length of the monsoon season enhanced between 2 and 5 d with the positive AMV pattern. The effect of AMV on the seasonality of the monsoon is more consistent to the west of 10∘ W, with all models showing a statistically significant earlier onset, later demise, and enhanced monsoon season with the positive phase of the AMV. Our results suggest a potential for the decadal prediction of changes in the intraseasonal characteristics of rainfall over the Sahel, including the occurrence of extreme events.

Using Climate Model Decadal Predictions and Statistical Extrapolations of Location-Specific Near-Term Temperature and Precipitation for Infrastructure Engineering

Using Climate Model Decadal Predictions and Statistical Extrapolations of Location-Specific Near-Term Temperature and Precipitation for Infrastructure Engineering

Decadal prediction of Northeast Asian winter precipitation with CMIP6 models

This study evaluates the decadal prediction skill of 13 forecast systems in predicting winter precipitation over Eurasia, contributing to the Decadal Climate Prediction Project of the Coupled Model Intercomparison Project Phase 6. Northeast Asia stands out as a region with improved decadal prediction skill for forecast years 2–5 due to the initialization. Observations show anticyclonic and cyclonic wind anomalies over the North Pacific and Northeast Asia, respectively, with southwesterly flow to the east of Northeast Asia. Ten forecast systems reproduce such circulation anomalies favoring abundant winter precipitation in Northeast Asia. The significant positive (negative) correlations between the detrended Northeast Asian precipitation (NEAP) and AMV (PDO-like) time series are reproduced by seven (nine) forecast systems. However, most forecast systems underestimate the correlation between the NEAP and the AMV, and have relatively low skill in predicting the PDO. Further improvements in these aspects will help to improve the decadal prediction skill of winter precipitation over Northeast Asia. The multi-model ensemble (MME) is able to reproduce both links of NEAP with AMV and PDO-like variability. The MME demonstrates significant skill and outperforms the individual forecast systems in predicting the NEAP for all 4-year averaged periods in the range of 1–8 years, demonstrating the benefits of using the ensemble mean of multiple models.

Investigating Atmospheric Responses to and Mechanisms Governing North Atlantic Sea Surface Temperatures over 10-Year Periods

Abstract North Atlantic sea surface temperature (SST) variability plays a critical role in modulating the climate system. However, characterizing patterns of North Atlantic SST variability and diagnosing the associated mechanisms is challenging because they involve coupled atmosphere–ocean interactions with complex spatiotemporal relationships. Here we address these challenges by applying a time-evolving self-organizing map approach to a long preindustrial coupled control simulation and identify a variety of 10-yr spatiotemporal evolutions of winter SST anomalies, including but not limited to those associated with the North Atlantic Oscillation–Atlantic multidecadal variability (NAO–AMV)-like interactions. To assess mechanisms and atmospheric responses associated with various SST spatiotemporal evolutions, composites of atmospheric and oceanic variables associated with these evolutions are investigated. Results show that transient-eddy activities and atmospheric circulation responses exist in almost all the evolutions that are closely correlated to the details of the SST pattern. In terms of the mechanisms responsible for generating various SST evolutions, composites of ocean heat budget terms demonstrate that contributions to upper-ocean temperature tendency from resolved ocean advection and surface heat fluxes rarely oppose each other over 10-yr periods in the subpolar North Atlantic. We further explore the potential for predictability for some of these 10-yr SST evolutions that start with similar states but end with different states. However, we find that these are associated with abrupt changes in atmospheric variability and are unlikely to be predictable. In summary, this study broadly investigates the atmospheric responses to and the mechanisms governing the North Atlantic SST evolutions over 10-yr periods. Significance Statement Climate variability in the North Atlantic Ocean has wide-ranging impacts on global and regional climate. However, the processes involved include interactions between the ocean and atmosphere that vary across both space and time, making it challenging to characterize and predict. Using a novel machine learning approach, this study identifies various time evolutions of North Atlantic sea surface temperature patterns over 10-yr periods. This includes evolutions with similar start states but different trajectories, which have important implications for predictability. Furthermore, we investigate the mechanisms responsible for these evolutions and how different sea surface temperature patterns affect atmospheric circulation through small-scale atmospheric disturbances. These new insights into the complex ocean–atmosphere interactions over time are critical for improving decadal prediction skill.

Improvement in the skill of CMIP6 decadal hindcasts for extreme rainfall events over the Indian summer monsoon region

Decadal climate predictions have been widely used to predict the near-term climate information relevant for decision-making at multi-year timescales. In the present study, we evaluate the quality of the Coupled Model Intercomparison Project phase-6 (CMIP6) Decadal Climate Prediction Project (DCPP) hindcasts in capturing the extreme rainfall events (EREs) over the monsoon core region during Indian summer monsoon season (June–September) up to lead years 1–10. For the first time, in this study, we have used quantile mapping approach to downscale and bias correct the DCPP CMIP6 simulation/hindcast rainfall for the better representation of EREs. Detailed analysis suggests that the models in general strongly underestimate the rainfall variability over the summer monsoon region. However, after the downscaling and bias correction, the representation of rainfall variability and intensity improved multifold. The bias-corrected decadal hindcasts in fact show ~ 80% improvement in capturing the frequency, intensity, and spatial distribution of rainfall associated with the EREs. Present study brought out a downscaled DCPP product, with potential prediction skill for EREs over India. It is important to highlight that the models predict an increase in the small and medium-area EREs as compared to the large-area EREs over the monsoon core region for the decade 2019–2028.

Solar Irradiance Modulates the Asian Summer Monsoon—ENSO Relationship Over the Last Millennium

AbstractThe Asian summer monsoon (ASM) is teleconnected to the El Niño Southern Oscillation (ENSO), but this relationship is nonstationary and has shifted significantly in recent decades. Characterizing the drivers of such shifts is crucial for improving ASM prediction and extreme event preparedness. Paleoclimate records indicate a link between ASM strength and solar activity on multidecadal‐to‐centennial timescales, but 20th‐century data are too short to test mechanisms. Here we evaluate how solar irradiance influences the ASM‐ENSO relationship using last‐millennium paleoclimate data assimilation reconstructions and model simulations. We find that high solar irradiance weakens the ENSO‐East Asian summer monsoon (EASM) correlation, but strengthens the ENSO‐South Asian summer monsoon (SASM) correlation. Solar irradiance likely influences the strength of the ENSO‐EASM and ENSO‐SASM teleconnections via changes in the Western Pacific Subtropical High and the amplitude of ENSO events, respectively. We suggest a need for considering solar activity in decadal ASM rainfall predictions under global warming scenarios.

Initialization shock in the ocean circulation reduces skill in decadal predictions of the North Atlantic subpolar gyre

Due to large northward heat transport, the Atlantic meridional overturning circulation (AMOC) strongly affects the climate of various regions. Its internal variability has been shown to be predictable decades ahead within climate models, providing the hope that synchronizing ocean circulation with observations can improve decadal predictions, notably of the North Atlantic subpolar gyre (SPG). Climate predictions require a starting point which is a reconstruction of the past climate. This is usually performed with data assimilation methods that blend available observations and climate model states together. There is no unique method to derive the initial conditions. Moreover, this can be performed using full-field observations or their anomalies superimposed on the model's climatology to avoid strong drifts in predictions. How critical ocean circulation drifts are for prediction skill has not been assessed yet. We analyze this possible connection using the dataset of 12 decadal prediction systems from the World Meteorological Organization Lead Centre for Annual-to-Decadal Climate Prediction. We find a variety of initial AMOC errors within the predictions related to a dynamically imbalanced ocean states leading to strongly displaced or multiple maxima in the overturning structures. This likely results in a blend of what is known as model drift and initial shock. We identify that the AMOC initialization influences the quality of the SPG predictions. When predictions show a large initial error in their AMOC, they usually have low skill for predicting internal variability of the SPG for a time horizon of 6-10 years. Full-field initialized predictions with low AMOC drift show better SPG skill than those with a large AMOC drift. Nevertheless, while the anomaly-initialized predictions do not experience large drifts, they show low SPG skill when skill also present in historical runs is removed using a residual correlation metric. Thus, reducing initial shock and model biases for the ocean circulation in prediction systems might help to improve their prediction for the SPG beyond 5 years. Climate predictions could also benefit from quality-check procedure for assimilation/initialization because currently the research groups only reveal the problems in initialization once the set of predictions has been completed, which is an expensive effort.

Drift Correction and Sub‐Ensemble Predictive Skill Evaluation of the Decadal Prediction Large Ensemble With Application to Regional Studies

AbstractA large ensemble of experiments is required to reveal the predictable climate signal masked by the background noise in the decadal climate prediction (DCP). This is one of the main obstacles which complicates the generation of high‐resolution decadal climate information at regional scale, given the computing cost of the task. In this study, a set of representative sub‐ensembles of three members (ENS3) from the Decadal Prediction Large Ensemble has been selected to produce dynamically downscaled DCPs in future studies, minimizing the amount of computing resources required to conduct the regionalization while reducing as much as possible the loss of predictive skill with respect to the full ensemble (ENS40). The procedure to follow comprises two steps: first, an analysis to choose the most appropriate method of drift correction to remove the model drift; second, the selection of three members to build ENS3 and the evaluation of its performance and the impact of ensemble size on sub‐ensemble performance. The study has been focused on sea surface temperature (SST), near‐surface temperature anomaly and sea level pressure over some Coordinated Regional Climate Downscaling Experiment regions: Europe, South America and North America. The initial condition‐based approach has been shown to be the most suitable method in the three domains. Although there is an inevitable loss of predictive skill when reducing the ensemble size, ENS3 has shown to be a relatively good alternative to ENS10 and ENS40 when facing computing constraints and the analysis is focused on SST.

Predicting precipitation on the decadal timescale: A prototype climate service for the hydropower sector

Decadal predictions present an emerging opportunity for various socio-economic sectors affected by climate variability. However, the development of associated climate services is still in an incipient stage. This study focuses on developing a prototype climate service for an end-user in the hydropower sector. The service aimed at predicting precipitation in three drainage basins (Guadalquivir, Ebro and Po) for the next ten years, and was developed in close collaboration with the user. In this paper we do not provide the real-time forecasts, but we focus on describing and evaluating the methods and the models used. Using a European multi-model ensemble, the predictive skill for precipitation is found to vary with the calendar season, the forecast range and the drainage basin considered, though it is generally low for the purposes of supporting such a climate service. To overcome this deficiency, a hybrid approach was developed making combined use of the good skill in predicting the North Atlantic Oscillation (NAO) and the observed dominant influence of the latter on the decadal variability of precipitation in the areas of interest. Implementing this hybrid approach, which combines predictive information from the dynamical models with statistical information from observations, brings significant skill improvements in all basins during the extended cold season (November-March) for the first 10 forecast years. The hybrid model outperforms the direct multi-model ensemble output, exhibiting statistically significant skill for all basins. Our results suggest that utilising large-scale predictors can significantly improve regional predictions, and provide usable information for the hydropower sector.

Comprehensive Representation of Tropical–Extratropical Teleconnections Obstructed by Tropical Pacific Convection Biases in CMIP6

Abstract The central role of tropical sea surface temperature (SST) variability in modulating Northern Hemisphere (NH) extratropical climate has long been known. However, the prevailing pathways of teleconnections in observations and the ability of climate models to replicate these observed linkages remain elusive. Here, we apply maximum covariance analysis between atmospheric circulation and tropical SST to reveal two coexisting tropical–extratropical teleconnections albeit with distinctive spatiotemporal characteristics. The first mode, resembling the Pacific–North American (PNA) pattern, favors a tropical–Arctic in-phase (warm Pacific–warm Arctic) teleconnection in boreal spring and winter. However, the second mode, with a slight seasonal preference of summer, is manifested as an elongated Rossby wave train emanating from the tropical eastern Pacific that features an out-of-phase relationship (cold Pacific–warm Arctic) between tropical central Pacific SSTs and temperature variability over the Arctic (referred to as the PARC mode). While climate models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) appear to successfully simulate the PNA mode and its temporal characteristics, the majority of models’ skill in reproducing the PARC mode is obstructed to some extent by biases in simulating low-frequency SST and rainfall variability over the tropical eastern Pacific and the climatological mean flow over the North Pacific during boreal summer. Considering the contribution of the PARC mode in shaping low-frequency climate variations over the past 42 years from the tropics to the Arctic, improving models’ capability to capture the PARC mode is essential to reduce uncertainties associated with decadal prediction and climate change projection over the NH. Significance Statement This study focuses on the skill of models in phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating two leading observed Northern Hemisphere (NH) teleconnections that show distinctive spatial and temporal characteristics. The first one, the Pacific–North American (PNA) mode, exhibits a warm Pacific–warm Arctic pattern in boreal spring and winter, and the second one, the Pacific–Arctic (PARC) mode, features a cold Pacific–warm Arctic out-of-phase relationship. We find that models are skillful in simulating the PNA mode but not the PARC mode. This limitation may be rooted in unrealistic simulations of the mean state of winds and the low-frequency sea surface temperature variability in the tropical eastern Pacific. These biases call for caution when interpreting current models’ projections of extratropical circulations on multidecadal time scales.

Near-term temperature extremes in Iran using the decadal climate prediction project (DCPP)

Near-term temperature extremes in Iran using the decadal climate prediction project (DCPP)

Enhanced multi-year predictability after El Niño and La Niña events

Several aspects of regional climate including near-surface temperature and precipitation are predictable on interannual to decadal time scales. Despite indications that some climate states may provide higher predictability than others, previous studies analysing decadal predictions typically sample a variety of initial conditions. Here we assess multi-year predictability conditional on the phase of the El Niño–Southern Oscillation (ENSO) at the time of prediction initialisation. We find that predictions starting with El Niño or La Niña conditions exhibit higher skill in predicting near-surface air temperature and precipitation multiple years in advance, compared to predictions initialised from neutral ENSO conditions. This holds true in idealised prediction experiments with the Community Climate System Model Version 4 and to a lesser extent also real-world predictions using the Community Earth System Model and a multi-model ensemble of hindcasts contributed to the Coupled Model Intercomparison Project Phase 6 Decadal Climate Prediction Project. This enhanced predictability following ENSO events is related to phase transitions as part of the ENSO cycle, and related global teleconnections. Our results indicate that certain initial states provide increased predictability, revealing windows of opportunity for more skillful multi-year predictions.

Predictable decadal forcing of the North Atlantic jet speed by sub-polar North Atlantic sea surface temperatures

Abstract. It has been demonstrated that decadal variations in the North Atlantic Oscillation (NAO) can be predicted by current forecast models. While Atlantic Multidecadal Variability (AMV) in sea surface temperatures (SSTs) has been hypothesised as the source of this skill, the validity of this hypothesis and the pathways involved remain unclear. We show, using reanalysis and data from two forecast models, that the decadal predictability of the NAO can be entirely accounted for by the predictability of decadal variations in the speed of the North Atlantic eddy-driven jet, with no predictability of decadal variations in the jet latitude. The sub-polar North Atlantic (SPNA) is identified as the only obvious common source of an SST-based signal across the models and reanalysis, and the predictability of the jet speed is shown to be consistent with a forcing from the SPNA visible already within a single season. The pathway is argued to be tropospheric in nature, with the SPNA-associated heating extending up to the mid-troposphere, which alters the meridional temperature gradient around the climatological jet core. The relative roles of anthropogenic aerosol emissions and the Atlantic Meridional Overturning Circulation (AMOC) at generating predictable SPNA variability are also discussed. The analysis is extensively supported by the novel use of a set of seasonal hindcasts spanning the 20th century and forced with prescribed SSTs.

Divergent response of eastern China precipitation to the Pacific decadal oscillation during the last Interglacial

Understanding the role of the Pacific Decadal Oscillation (PDO) during the Last Interglacial (LIG, ∼127 ka) may advance our knowledge on decadal climate variability in a warmer world. In this study, we investigate the PDO–precipitation relationship over eastern China during the LIG based on the NorESM2-LM, which shows the best performance in capturing the observed PDO pattern and the PDO–precipitation relationship among 12 models from the Paleoclimate Modelling Intercomparison Project Phase 4. Composite analysis shows that summer precipitation during the LIG is generally increased over eastern China in the positive PDO phases relative to the negative phases, which is different from the “drier-wetter-drier” triple pattern in the present day. The discrepant precipitation patterns between the LIG and preindustrial are caused by different responses of composite atmospheric circulations. Moreover, moisture budget analysis indicates that variations of vertical velocity over eastern China largely explain the PDO-linked precipitation patterns during both LIG and preindustrial, although the main causes for vertical motion changes are different across regions and periods based on the quasi-geostrophic ω equation. Additionally, these discrepancies in composite atmospheric circulations are largely linked to differences in PDO patterns and mean climate states between the LIG and preindustrial. Our results suggest a varying relationship between the PDO and precipitation over eastern China in a warmer-than-present world induced by Earth's orbit, which have important implications for PDO reconstructions during the LIG via the PDO-precipitation relationship reported here and shed light on decadal variability of precipitation as well as the associated decadal predictions in a future warmer world.