Variability Of Climate System Research Articles

Multiple serial correlations in global air temperature anomaly time series.

Serial correlations within temperature time series serve as indicators of the temporal consistency of climate events. This study delves into the serial correlations embedded in global surface air temperature (SAT) data. Initially, we preprocess the SAT time series to eradicate seasonal patterns and linear trends, resulting in the SAT anomaly time series, which encapsulates the inherent variability of Earth's climate system. Employing diverse statistical techniques, we identify three distinct types of serial correlations: short-term, long-term, and nonlinear. To identify short-term correlations, we utilize the first-order autoregressive model, AR(1), revealing a global pattern that can be partially attributed to atmospheric Rossby waves in extratropical regions and the Eastern Pacific warm pool. For long-term correlations, we adopt the standard detrended fluctuation analysis, finding that the global pattern aligns with long-term climate variability, such as the El Niño-Southern Oscillation (ENSO) over the Eastern Pacific. Furthermore, we apply the horizontal visibility graph (HVG) algorithm to transform the SAT anomaly time series into complex networks. The topological parameters of these networks aptly capture the long-term correlations present in the data. Additionally, we introduce a novel topological parameter, Δσ, to detect nonlinear correlations. The statistical significance of this parameter is rigorously tested using the Monte Carlo method, simulating fractional Brownian motion and fractional Gaussian noise processes with a predefined DFA exponent to estimate confidence intervals. In conclusion, serial correlations are universal in global SAT time series and the presence of these serial correlations should be considered carefully in climate sciences.

May–June relative humidity variation recorded by tree ring widths of Pinus armandii Franch since 1863 in the Funiu Mountains, central China

Long-lasting drought records can provide valuable insights into the history of hydroclimate change in central China, but meteorological records are too short to capture long-term variability of the humidity. In this study, we established a tree-ring width chronology of Pinus armandii Franch in the Funiu Mountains region of central China. Correlation analyses showed that tree radial growths were mainly limited by hydrothermal combination in May–June. The results of the moving correlation analysis further showed that the response relationship between tree growth and relative humidity in May–June (RHMJ) was the most stable. This relationship has been reconstructed since 1863. The variance of the reconstructed RHMJ was explained by 41.7% (40.6% after adjusting for degrees of freedom). Over the past 158 years, there were 3 wet periods and 4 dry periods. The spectral analysis revealed that the reconstructed RHMJ exhibited quasi-periods of 2-4a and 31.6a, and cross-spectrum analysis showed that the reconstructed RHMJ may be related to ENSO, PDO, solar activity and the East Asian summer monsoon. The spatial correlation analysis revealed that the reconstructed RHMJ accurately depicted the fluctuations in humidity within the Huanghe-Huaihe Plain. Furthermore, the reconstructed RHMJ exhibited a strong negative correlation with the sea surface temperature (SST) of the subtropical North Pacific, while it displayed a highly significant positive correlation with the SST of the eastern equatorial Pacific from the previous May to the current April. This also indicated a possible link between humidity fluctuations in the Huanghe-Huaihe Plain and the Pacific internal variability in climate system. Therefore, this research aims to expand and complement the existing meteorological records, providing important reference significance for forest management, agriculture, and animal husbandry.

Use Of Factor Analysis And Discriminant Analysis To Determine The Factors Affecting Climate Type And Building Shape In Libya

Climate in simple concept commonly known as the rate of the weather , there are many observed elements of the atmosphere that are subject to constant change. These elements generally are: Maximum temperature(X1), Minimum temperature (X2), Relative humidity(X3), Wind speed(X4), Wind direction(X5), Duration of sun shine(X6), Clouds amount(X7) and Rainfall amount(X8).The main objectives of the study are: (i) To define the factors influencing the Climate, and to determine the most important factors of the climatic variables.(ii) To discriminate the Climate by region and define the factors which responsible for that discrimination. (iii) To determine the factors that influencing in the building form.
 To achieve these goals, a simple random sample of ten cities were selected from the Libyan Meteorological Department in Tripoli. These cities are divided into (6) cities as a coastal climate and (4) cities as a desert climate. The data of this study were collected as a series from each city from January of the first year 1970 to December of the last year 2000. Each series consists of 12×30×30×10 monthly observations, and the total data points in the study will be (108,000) from Derna, Benghazi, Jalu, Agedabia, Tripoli, Misurata, Sebha, EL-Kufra, Ghadames and Shahat. To study the variability of climate system of these places needs to explain the observed correlations between the elements and the regions.
 Two different statistical techniques are used in this study to analyze the data to study the first objective, factor analysis is used to determine the importance of the variables and their effect on the climate in both coastal and desert climate in general, and for each city separately. To study the second and third objectives discriminant analysis is used. This study provides a number of variables with significant positive effect on the Type of Climate variable(X9), in the coastal cities, (Derna, Benghazi, Agedabia, Tripoli, Misurata, Shahat) Maximum Temperature(X1), Duration Of Sun Shine(X6),Clouds Amount(X7) and Rainfall Amount (X8) are good representative for all eight original variables. But in the desert cities (Sebha, Jalu, EL-Kufra, Ghadames) the variables Maximum temperature(X1), Minimum temperature(X2), Relative humidity(X3), Wind speed(X4), Duration of sun shine(X6), Clouds amount(X7) and Rainfall amount(X8) all these variables have significant positive effect on the Type of Climate variable(X9).
 The results from discriminant and classification analysis for the dependent variable Type of Climate (X9) show that: There is significant difference between the climate of ten regions. Where, Maximum Temperature(X1), Relative humidity(X3), Duration of Sun Shine(X6), Clouds Amount(X7) and Rainfall Amount(X8) are significant and important, and the Relative humidity(X3) have high correlation with the discriminant function. The results from discriminant and classification analysis for the dependent variable Type of Building(X10) show that: There is significant difference between the building form of the ten regions. Where, Maximum Temperature(X1),Relative humidity(X3), Duration of Sun Shine(X6) and Clouds Amount(X7) have high correlation with the discriminant function or these variables are important and significant and have an effect on the building form in each city.

Identifying quasi-periodic variability using multivariate empirical mode decomposition: a case of the tropical Pacific

Abstract. A variety of statistical tools have been used in climate science to gain a better understanding of the climate system's variability on various temporal and spatial scales. However, these tools are mostly linear, stationary, or both. In this study, we use a recently developed nonlinear and nonstationary multivariate time series analysis tool – multivariate empirical mode decomposition (MEMD). MEMD is a powerful tool for objectively identifying (intrinsic) timescales of variability within a given spatio-temporal system without any timescale pre-selection. Additionally, a red noise significance test is developed to robustly extract quasi-periodic modes of variability. We apply these tools to reanalysis and observational data of the tropical Pacific. This reveals a quasi-periodic variability in the tropical Pacific on timescales ∼ 1.5–4.5 years, which is consistent with El Niño–Southern Oscillation (ENSO) – one of the most prominent quasi-periodic modes of variability in the Earth’s climate system. The approach successfully confirms the well-known out-of-phase relationship of the tropical Pacific mean thermocline depth with sea surface temperature in the eastern tropical Pacific (recharge–discharge process). Furthermore, we find a co-variability between zonal wind stress in the western tropical Pacific and the tropical Pacific mean thermocline depth, which only occurs on the quasi-periodic timescale. MEMD coupled with a red noise test can therefore successfully extract (nonstationary) quasi-periodic variability from the spatio-temporal data and could be used in the future for identifying potential (new) relationships between different variables in the climate system.

Late Cenomanian Plenus event in the Western Interior Seaway

The Late Cenomanian Plenus Cold Event is one of the most enigmatic paleoclimate episodes in Earth history with potential to inform understanding of global climate system variability under greenhouse warming conditions, as well as internal feedback pathways that modulate such variability. Following an interpreted massive addition of volcanic CO2 to the atmosphere and warming that led to a major ocean anoxic event (OAE2), there was a brief interval of cooling recorded in oxygen isotopes and biogeographic data. Here we present evidence that cooling was absent or muted within the Western Interior Seaway (WIS). Clumped isotope data from the basin suggest persistent extreme warmth during the Late Cenomanian, macroinvertebrate fossil assemblages do not record a decrease in temperature, and changes in other paleoceanographic proxies do not correlate temporally with Plenus interval signals from other locales. Using select proxy data to guide construction of GCM model simulations, we explore possible hypotheses to explain these observations. Our results suggest that the paleogeographic configuration of the basin and its gateways to adjoining oceans, which evolved in association with changing pCO2 and sea level, influenced winter sea ice formation at the northern aperture of the seaway, water mass circulation, salinity, temperature, and water column stratification. We propose that northward advection of warm Tethyan water muted expression of Plenus cooling in the seaway. Understanding the unique character of the Western Interior paleoceanographic record provides critical input for the development of robust models of ancient Earth System dynamics and should aid predictions of future climate system dynamics.

Recent marine heatwaves in the North Pacific warming pool can be attributed to rising atmospheric levels of greenhouse gases

Over the last decade, the northeast Pacific experienced marine heatwaves that caused devastating marine ecological impacts with socioeconomic implications. Here we use two different attribution methods and show that forcing by elevated greenhouse gases levels has virtually certainly caused the multi-year persistent 2019–2021 marine heatwave. There is less than 1% chance that the 2019–2021 event with ~3 years duration and 1.6 ∘C intensity could have happened in the absence of greenhouse gases forcing. We further discover that the recent marine heatwaves are co-located with a systematically-forced outstanding warming pool, which we attribute to forcing by elevated greenhouse gases levels and the recent industrial aerosol-load decrease. The here-detected Pacific long-term warming pool is associated with a strengthening ridge of high-pressure system, which has recently emerged from the natural variability of climate system, indicating that they will provide favorable conditions over the northeast Pacific for even more severe marine heatwave events in the future.

Centennial to millennial variability of greenhouse climate across the mid-Cenomanian event

Abstract Centennial- to millennial-scale climate variations are often attributed to solar forcing or internal climate system variability, but recognition of such variations in the deep-time paleoclimate record is extremely rare. We present an exceptionally well-preserved, millimeter-scale laminated marlstone from a succession of precession-driven limestone-marlstone couplets deposited in the Western Interior Seaway (North America) immediately preceding and during the Cretaceous mid-Cenomanian event (ca. 96.5 Ma). Sedimentological, geochemical, and micropaleontological data indicate that individual pairs of light-dark laminae record alternations in the extent of water-column mixing and oxygenation. Principal component analysis of X-ray fluorescence element counts and a grayscale scan of a continuous thin section through the marlstone reveal variations with 80–100 yr, 200–230 yr, 350–500 yr, ∼1650 yr, and 4843 yr periodicities. A substantial fraction of the data indicates an anoxic bottom water variation with a pronounced 10,784 yr cycle. The centennial to millennial variations are reminiscent of those found in Holocene total solar irradiance variability, and the 10,784 yr anoxia cycle may be a manifestation of semi-precession-influenced Tethyan oxygen minimum zone waters entering the seaway.

MOSAIC: A Satellite Constellation to Enable Groundbreaking Mars Climate System Science and Prepare for Human Exploration

Abstract The Martian climate system has been revealed to rival the complexity of Earth’s. Over the last 20 yr, a fragmented and incomplete picture has emerged of its structure and variability; we remain largely ignorant of many of the physical processes driving matter and energy flow between and within Mars’ diverse climate domains. Mars Orbiters for Surface, Atmosphere, and Ionosphere Connections (MOSAIC) is a constellation of ten platforms focused on understanding these climate connections, with orbits and instruments tailored to observe the Martian climate system from three complementary perspectives. First, low-circular near-polar Sun-synchronous orbits (a large mothership and three smallsats spaced in local time) enable vertical profiling of wind, aerosols, water, and temperature, as well as mapping of surface and subsurface ice. Second, elliptical orbits sampling all of Mars’ plasma regions enable multipoint measurements necessary to understand mass/energy transport and ion-driven escape, also enabling, with the polar orbiters, dense radio occultation coverage. Last, longitudinally spaced areostationary orbits enable synoptic views of the lower atmosphere necessary to understand global and mesoscale dynamics, global views of the hydrogen and oxygen exospheres, and upstream measurements of space weather conditions. MOSAIC will characterize climate system variability diurnally and seasonally, on meso-, regional, and global scales, targeting the shallow subsurface all the way out to the solar wind, making many first-of-their-kind measurements. Importantly, these measurements will also prepare for human exploration and habitation of Mars by providing water resource prospecting, operational forecasting of dust and radiation hazards, and ionospheric communication/positioning disruptions.

A 5000‐year paleoclimate record from Nettilling Lake (Baffin Island) based on diatom assemblages and oxygen isotope composition

ABSTRACTSedimentary diatoms have been used to quantitatively reconstruct climate‐related variables, such as temperature at different timescales. Even though temperature is often less of a key driver of diatom ecology than other environmental parameters (water chemistry), diatom inference models have been shown to be reliable in deducing past temperature trends. In addition, the oxygen isotope composition (δ18Odiatom) preserved in buried diatom frustules has demonstrated its potential to reflect climatic and hydrological conditions at the time of frustule formation. This study combines results from both diatom‐based climate proxies to reconstruct summer water and mean annual air temperatures, and hydrological trends in Nettilling Lake, Baffin Island, from ca. 5000 to 500 cal a bp. Diatom‐inferred temperatures revealed an overall ca. 2 °C cooling throughout the Late‐Holocene. The δ18Odiatom values showed an increasing trend up to ca. 1900 cal a bp, where they reached their highest values (+24.8‰ at 15 cm) and thereafter decreased to their lowest values (+21.4‰ at 4 cm). These trends were linked to meltwater inflows associated with Penny Ice Cap thaw rate that was in turn controlled by regional climatic conditions which went from intensified cooling during the Neoglacial period to slight warming thereafter. Our results suggest that diatom‐ and diatom‐isotope‐based temperature and hydrological reconstructions can identify trends related to the natural climate system variability. The diatom oxygen isotopes are useful for paleoenvironmental studies of terrestrial aquatic ecosystems, but not for all hydrological systems are the ideal temperature proxy. Hence, the combination of proxies helps to disentangle temperature and hydrological effects for paleoclimatic reconstructions and may support future studies of postglacial environmental change in northern lakes.

Role of Internal Variability of Climate System in Increase of Air Temperature in Wrocław (Poland) in the Years 1951–2018

Abstract In the course of analysing the annual air temperature in Wrocław (TWr), a rapid change of the thermal regime was found between 1987 and 1989. TWr increased by >1°C, a strong, statistically significant positive trend emerged. The analysis of processes showed that strong warming in the cold season of the year (December–March) occurred as a result of an increase in the NAO intensity and warming in the warm season because of increased sunshine duration in Wrocław (ShWr). Multiple regression analysis has shown that the winter NAO Hurrell's index explains 15% of TWr variance, and the ShWr of the long-day (April–August) period 49%, whereas radiative forcing 5.9%. This indicates that the factors incidental to the internal variability of the climate system explain 64% of the TWr variability and the effect of increased CO2 concentration only ~6%. The reason for this rapid change of the thermal regime was a radical change in macro-circulation conditions in the Atlantic-European circular sector, which took place between 1988 and 1989. The heat, which is the cause of warming in Wrocław, comes from an increase in solar energy inflow (April–August) and also is transported to Europe from the North Atlantic surface by atmospheric circulation (NAO). These results indicate that the role of CO2 in shaping the contemporary temperature increase is overestimated, whereas the internal variability of the climate system is underestimated.

Late 1990s’ cool season climate shift in eastern North America

Changes in the frequency of cold and warm synoptic weather types within eastern North America indicate the occurrence of a cool season climate shift in the late 1990s. This aligns with the timing of shifts toward earlier spring ice out on freshwater lakes within the region and less frequent cold air mass passage over the North American Great Lakes. While a preliminary shift occurred in the early 1980s, a pronounced shift toward more frequent warm weather types during November through April occurred after 1997, when prominent warming of the lower atmosphere over the region began. The late 1990s’ climate shift appears linked to middle atmospheric circulation change associated with phase changes for two influential low-frequency climate teleconnections originating within the Atlantic and Pacific Oceans, the Atlantic Multidecadal Oscillation and the Interdecadal Pacific Oscillation. The climate shift, approximately 20 years after warming within the global climate system commenced, further illustrates the importance of climate system variability within anthropogenically driven climate change.

Millennial to Quasi-Decadal Variability in Antarctic Climate System as Evidenced from High-resolution Ice Core Records

Millennial to Quasi-Decadal Variability in Antarctic Climate System as Evidenced from High-resolution Ice Core Records

Numerical bifurcation methods applied to climate models: analysis beyond simulation

Abstract. In this special issue contribution, I provide a personal view on the role of bifurcation analysis of climate models in the development of a theory of climate system variability. The state of the art of the methodology is shortly outlined, and the main part of the paper deals with examples of what has been done and what has been learned. In addressing these issues, I will discuss the role of a hierarchy of climate models, concentrate on results for spatially extended (stochastic) models (having many degrees of freedom) and evaluate the importance of these results for a theory of climate system variability.

Comparison of climate change from Cenozoic surface uplift and glacial-interglacial episodes in the Himalaya-Tibet region: Insights from a regional climate model and proxy data

Abstract Assessing paleo-climatic changes and the underlying driving mechanisms are an essential (and often poorly understood) first-step for understanding if natural variability in Earth's climate system from tectonic processes and orbital forcing could produce observed changes in surface processes. In this study, we take this first step of evaluating climate change in the Tibetan Plateau region for different distinct climate states. We do this using a high-resolution regional climate model parameterized for the Cenozoic rise of the Plateau and prominent Quaternary glacial and interglacial episodes. The main objective is to delimit the range of climate variability due to important natural drivers in the region by comparing climate changes during the main Cenozoic uplift period with climate anomalies during the last glacial maximum and the mid-Holocene optimum. This helps to interpret environmental changes documented by proxy data and to benchmark man-made climate changes expected during the 21st century. The innovative aspects of this study pertain to the use of a consistent high-resolution modeling framework and a multivariate statistical assessment of climate types and their shift during the various paleo-climatic episodes. Reduced plateau elevation leads to regionally differentiated patterns of higher temperature and lower precipitation amounts on the plateau itself, whereas surrounding regions are subject to colder conditions. In particular, Central Asia receives much more precipitation prior to the uplift, mainly due to a shift of the stationary wave train over Eurasia. Cluster analysis indicates that the continental-desert type climate, which is widespread over Central Asia today, appears with the Tibetan Plateau reaching 50% of its present-day elevation. The mid-Holocene is characterized by slightly colder temperatures, and the last glacial maximum by considerably colder conditions over most of central and southern Asia. Precipitation anomalies during these episodes are less pronounced and spatially heterogeneous over the Tibetan Plateau. The simulated changes are in good agreement with available paleo-climatic reconstructions from proxy data. The present-day climate classification is only slightly sensitive to the changed boundary conditions in the Quaternary. However, it is shown that in some regions of the Tibetan Plateau the climate anomalies during the Quaternary have been as strong as the changes occurring during the uplift period.

On climate prediction: how much can we expect from climate memory?

Slowing variability in climate system is an important source of climate predictability. However, it is still challenging for current dynamical models to fully capture the variability as well as its impacts on future climate. In this study, instead of simulating the internal multi-scale oscillations in dynamical models, we discussed the effects of internal variability in terms of climate memory. By decomposing climate state x(t) at a certain time point t into memory part M(t) and non-memory part varepsilon (t), climate memory effects from the past 30 years on climate prediction are quantified. For variables with strong climate memory, high variance (over 20%) in x(t) is explained by the memory part M(t), and the effects of climate memory are non-negligible for most climate variables, but the precipitation. Regarding of multi-steps climate prediction, a power law decay of the explained variance was found, indicating long-lasting climate memory effects. The explained variances by climate memory can remain to be higher than 10% for more than 10 time steps. Accordingly, past climate conditions can affect both short (monthly) and long-term (interannual, decadal, or even multidecadal) climate predictions. With the memory part M(t) precisely calculated from Fractional Integral Statistical Model, one only needs to focus on the non-memory part varepsilon (t), which is an important quantity that determines climate predictive skills.

Lower Tropospheric Temperatures 1978-2016: The Role Played By Anthropogenic Global Warming

The slowdown in tropospheric temperature increase between 1997-2016 led some commentators in Australia (and elsewhere) to repeat earlier assertions that there is an absence of any relationship between anthropogenic carbon dioxide increase and global air temperature. Here we test the null hypothesis that anthropogenic greenhouse forcing makes no contribution to global mean tropospheric temperature by analysing a satellite-derived lower tropospheric temperature record since 1978. A well-known heuristic model that separates variance in air temperature into components from different sources of climate variability is employed to determine what contribution anthropogenic greenhouse gases made to satellite-measured lower tropospheric temperature. Over the satellite record from December 1978 to the January 2016 the anthropogenic contribution to lower tropospheric temperature is estimated to be between +0.29 and +0.34K. Over the shorter segment of the record from December 1997 to January 2016 an anthropogenic contribution of +0.15K to the satellite-derived lower tropospheric air temperature was found. The slowdown in rate of temperature increase in that period is found simply to be a consequence of internal climate system variability that at other times has the opposite effect. The null hypothesis of no relationship between lower troposphere temperature and greenhouse gas increase is rejected.

Briefing: Global surface temperature records: an update

In the past 3 years, global surface temperatures have spiked considerably. In early 2016 it is possible that they briefly exceeded 1·5 K above ‘pre-industrial’ levels. This spike was the result of a combination of the underlying trend and internal climate system variability. Up until about 2015, there was much discussion of a potential ‘hiatus’ feature in the recent records and the implications thereof for the understanding of climate and the verity of projections. The general message across a broad range of literature is that some combination of internal climate system variability and external forcing effects principally from volcanoes and the sun was responsible for some part of this. However, there has also been renewed interest in analyses of historical records, from which several new and revised data products have arisen. These have served to highlight the roles of both modern marine data biases and spatial coverage. Accounting for these reduces the magnitude of the apparent muted warming in the early twenty-first century. Global mean temperatures have increased on multidecadal timescales, and only invoking human influences can explain these rises adequately. Natural variability can mask or exacerbate the underlying trend for periods of up to a decade or so.

Influence of internal variability on population exposure to hydroclimatic changes

Future freshwater supply, human water demand, and people’s exposure to water stress are subject to multiple sources of uncertainty, including unknown future pathways of fossil fuel and water consumption, and ‘irreducible’ uncertainty arising from internal climate system variability. Such internal variability can conceal forced hydroclimatic changes on multi-decadal timescales and near-continental spatial-scales. Using three projections of population growth, a large ensemble from a single Earth system model, and assuming stationary per capita water consumption, we quantify the likelihoods of future population exposure to increased hydroclimatic deficits, which we define as the average duration and magnitude by which evapotranspiration exceeds precipitation in a basin. We calculate that by 2060, ∽31%–35% of the global population will be exposed to >50% probability of hydroclimatic deficit increases that exceed existing hydrological storage, with up to 9% of people exposed to >90% probability. However, internal variability, which is an irreducible uncertainty in climate model predictions that is under-sampled in water resource projections, creates substantial uncertainty in predicted exposure: ∽86%–91% of people will reside where irreducible uncertainty spans the potential for both increases and decreases in sub-annual water deficits. In one population scenario, changes in exposure to large hydroclimate deficits vary from −3% to +6% of global population, a range arising entirely from internal variability. The uncertainty in risk arising from irreducible uncertainty in the precise pattern of hydroclimatic change, which is typically conflated with other uncertainties in projections, is critical for climate risk management that seeks to optimize adaptations that are robust to the full set of potential real-world outcomes.

Lower Tropospheric Temperatures 1978-2016: The Role Played By Anthropogenic Global Warming

The slowdown in tropospheric temperature increase between 1997-2016 led some commentators in Australia (and elsewhere) to repeat earlier assertions that there is an absence of any relationship between anthropogenic carbon dioxide increase and global air temperature. Here we test the null hypothesis that anthropogenic greenhouse forcing makes no contribution to global mean tropospheric temperature by analysing a satellite-derived lower tropospheric temperature record since 1978. A well-known heuristic model that separates variance in air temperature into components from different sources of climate variability is employed to determine what contribution anthropogenic greenhouse gases made to satellite-measured lower tropospheric temperature. Over the satellite record from December 1978 to the January 2016 the anthropogenic contribution to lower tropospheric temperature is estimated to be between +0.29 and +0.34K. Over the shorter segment of the record from December 1997 to January 2016 an anthropogenic contribution of +0.15K to the satellite-derived lower tropospheric air temperature was found. The slowdown in rate of temperature increase in that period is found simply to be a consequence of internal climate system variability that at other times has the opposite effect. The null hypothesis of no relationship between lower troposphere temperature and greenhouse gas increase is rejected.

Decadal shifts of East Asian summer monsoon in a climate model free of explicit GHGs and aerosols.

The East Asian summer monsoon (EASM) experienced decadal transitions over the past few decades, and the associated "wetter-South-drier-North" shifts in rainfall patterns in China significantly affected the social and economic development in China. Two viewpoints stand out to explain these decadal shifts, regarding the shifts either a result of internal variability of climate system or that of external forcings (e.g. greenhouse gases (GHGs) and anthropogenic aerosols). However, most climate models, for example, the Atmospheric Model Intercomparison Project (AMIP)-type simulations and the Coupled Model Intercomparison Project (CMIP)-type simulations, fail to simulate the variation patterns, leaving the mechanisms responsible for these shifts still open to dispute. In this study, we conducted a successful simulation of these decadal transitions in a coupled model where we applied ocean data assimilation in the model free of explicit aerosols and GHGs forcing. The associated decadal shifts of the three-dimensional spatial structure in the 1990s, including the eastward retreat, the northward shift of the western Pacific subtropical high (WPSH), and the south-cool-north-warm pattern of the upper-level tropospheric temperature, were all well captured. Our simulation supports the argument that the variations of the oceanic fields are the dominant factor responsible for the EASM decadal transitions.