Phase Anomalies Research Articles

A robust time scale for space applications using the student’s t-distribution

Abstract In this article, the principles of robust estimation are applied to the standard basic time scale equation to obtain a new method of assigning weights to clocks. Specifically, the Student's t-distribution is introduced as a new statistical model for an ensemble of clocks that are experiencing phase jumps, frequency jumps or anomalies in their measurement links. The proposed robust time scale is designed to mitigate the effects of these anomalies without necessarily identifying them, but through applying a method of robust estimation for the parameters of a Student's t-distribution. The proposed time scale algorithm using the Student's t-distribution (ATST) is shown to achieve comparable robustness to phase jumps, frequency jumps, and anomalies in the measurements with respect to the AT1 oracle time scale. The AT1 oracle is a special realization of the AT1 time scale which corrects all anomalies by having prior knowledge of their occurrences. The similar performance of ATST and AT1 oracle suggests that the ATST algorithm is efficient for obtaining robustness with no prior knowledge or detection of the occurrences of anomalies.

Anomalies of 4d SpinG theories

We consider ’t Hooft anomalies of four-dimensional gauge theories whose fermion matter content admits SpinG(4) generalized spin structure, with G either gauged or a global symmetry. We discuss methods to directly compute w2 ∪ w3 ’t Hooft anomalies involving Stiefel-Whitney classes of gauge and flavor symmetry bundles that such theories can have on non-spin manifolds, e.g. M4 = ℂℙ2. Such anomalies have been discussed for SU(2) gauge theory with adjoint fermions, where they were shown to give an effect that was originally found in the Donaldson-Witten topological twist of N\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ \\mathcal{N} $$\\end{document} = 2 SYM theory. We directly compute these anomalies for a variety of theories, including general G gauge theories with adjoint fermions, SU(2) gauge theory with fermions in general representations, and Spin(N) gauge theories with fundamental matter. We discuss aspects of matching these and other ’t Hooft anomalies in the IR phase where global symmetries are spontaneously broken, in particular for general Ggauge theory with Nf adjoint Weyl fermions. For example, in the case of Nf = 2 we discuss anomaly matching in the IR phase consisting of hGgauge∨\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {h}_{G_{\ extrm{gauge}}}^{\\vee } $$\\end{document} copies of a ℂℙ1 non-linear sigma model, including for the w2w3 anomalies when formulated with SpinSU2global4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {\ extrm{Spin}}_{\ extrm{SU}{(2)}_{\ extrm{global}}}(4) $$\\end{document} structure.

Near Real-Time Monitoring of Large Gradient Nonlinear Subsidence in Mining Areas: A Hybrid SBAS-InSAR Method Integrating Robust Sequential Adjustment and Deep Learning

With the increasing availability of satellite monitoring data, the demand for storage and computational resources for updating the results of monitoring the surface subsidence in a mining area continues to rise. Sequential adjustment (SA) models are considered effective for rapidly updating time series interferometry synthetic aperture radar (TS-InSAR) measurements. However, the accuracy of surface subsidence values estimated through traditional sequential adjustment is highly sensitive to abnormal observations or prior information on anomalies. Moreover, the surface subsidence associated with mining exhibits nonlinear and large gradient characteristics, making general InSAR methods challenging for obtaining reliable monitoring results. In this study, we employ the phase unwrapping network (PUNet) to obtain unwrapped values of differential interferograms. To mitigate the impact of abnormal errors in the near real-time small baseline subset InSAR (SBAS-InSAR) sequential updating process in mining areas, a robust sequential adjustment method based on M-estimation is proposed to estimate the temporal deformation parameters by using the equivalent weight model. Using a coal backfilling mining face in Shanxi, China, as the study area and the Sentinel-1 SAR dataset, we comprehensively evaluate the performance of unwrapping methods and subsidence time series estimation techniques and evaluate the effect of filling mining on surface subsidence control. The results are validated using leveling measurements within the study area. The relative error of the proposed method is less than 5%, which can meet the requirements of monitoring the surface subsidence in mining areas. The method proposed in this study not only enhances computational efficiency but also addresses the issue of underestimation encountered by InSAR methods in mining area applications. Furthermore, it also mitigates unwrapping phase anomalies on the monitoring results.

Study on Gyro Calibration and Attitude Estimation Considering an Induced Phase Anomaly Effect of High-Spin Maneuvering Body

Study on Gyro Calibration and Attitude Estimation Considering an Induced Phase Anomaly Effect of High-Spin Maneuvering Body

CHAWA: Overcoming Phase Anomalies in Sound Localization

CHAWA: Overcoming Phase Anomalies in Sound Localization

Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical images.

Medical anomaly detection is a crucial yet challenging task aimed at recognizing abnormal images to assist in diagnosis. Due to the high-cost annotations of abnormal images, most methods utilize only known normal images during training and identify samples deviating from the normal profile as anomalies in the testing phase. Many readily available unlabeled images containing anomalies are thus ignored in the training phase, restricting the performance. To solve this problem, we introduce one-class semi-supervised learning (OC-SSL) to utilize known normal and unlabeled images for training, and propose Dual-distribution Discrepancy for Anomaly Detection (DDAD) based on this setting. Ensembles of reconstruction networks are designed to model the distribution of normal images and the distribution of both normal and unlabeled images, deriving the normative distribution module (NDM) and unknown distribution module (UDM). Subsequently, the intra-discrepancy of NDM and inter-discrepancy between the two modules are designed as anomaly scores. Furthermore, we propose a new perspective on self-supervised learning, which is designed to refine the anomaly scores rather than directly detect anomalies. Five medical datasets, including chest X-rays, brain MRIs and retinal fundus images, are organized as benchmarks for evaluation. Experiments on these benchmarks comprehensively compare a wide range of anomaly detection methods and demonstrate that our method achieves significant gains and outperforms the state-of-the-art. Code and organized benchmarks are available at https://github.com/caiyu6666/DDAD-ASR.

Effects of a series of large flares from a sunspot group eruption on VLF propagation

Sunspot groups are constantly evolving, causing flare eruption under the action of the solar atmospheric magnetic field. After the flare, the ejected X-rays cause the electron concentration of the Earth’s ionosphere to increase and the equivalent reflection height of the ionosphere to decrease. We studied the correlation between a series of flares erupted by sunspot groups and VLF signal propagation. Using NOAA sunspot activity area data and solar flare data released by the GOES satellite, we counted a series of flares erupted by sunspot groups in 2000. It is found that the AR9077 sunspot group continuously erupted 15 M-class and above flares and 3 X-class flares. Alpha VLF navigation station data were received in Haikou, and the phase anomalies of the VLF signal caused by a series of large flares erupted by AR9077 were observed. According to the phase anomaly, the flare is analyzed, and the relationship between X-ray flux density and ionospheric equivalent reflection height is fitted. We incorporated the change of solar zenith angle at the observation point in our calculation to correct the equivalent reflection height of the ionosphere and thus improve the accuracy of flare prediction. The calculated results are consistent with the data released by the GOES satellite. The observation results show that VLF phase anomaly correlates well with solar flares and sunspots. VLF signal can be used as a reliable scheme to predict the space environment, avoiding the impact of sunspot flares.

Classification of precipitation anomalies in the Rio Grande do Sul in ENSO events in the 20th century

This study investigated the intensity and spatial distribution of precipitation anomalies in Rio Grande do Sul state (RS) during the 20th century by analyzing the influence of El Niño – Southern Oscillation (ENSO) in its three phases. Reanalyzes from the University of Delaware (V5) were used. Precipitation anomalies were divided into three zones (Campaign, Plateau, Coast) to investigate possible differences in precipitation under ENSO influence. Alexandersson's Standard Normal Homogeneity Test was applied to verify possible structural breaks. Wavelets were used to rate the periodicity of precipitation anomalies into three phases. Anomalies that occurred in El Niño and La Niña phases were classified in contingency tables as weak, average, and strong to evaluate the qualitative behavior of these precipitation anomalies. It was found that precipitation anomalies presented a structural break in 1955 when the tendency to positive anomalies increased. From 1955, precipitation anomalies increased at least 0.5 standard deviation while the frequency of these anomalies decreased from 85 to 60 months. Peaks of positive anomalies in El Niño were higher than 200 mm. In neutral cases, anomalies intensified in 0.5 standard deviation since 1970. Negative anomalies did not show specific behavior in any ENSO phase. Contingency tables indicated that La Niña events did not present any visible influence pattern. It could intensify the episodes of positive and negative precipitation anomalies in at least 0.5 (-0.5) standard deviation. Therefore, La Niña events could increase or decrease the monthly anomaly but do not show any tendency to negative anomalies. Weak El Niños tends to contribute to negative precipitation anomalies while strong cases are associated with an average increase of 2 standard deviations in positive anomalies. It was concluded that the influence of ENSO in RS is stronger in El Niño than in La Niña. Still, both may induce negative and positive anomalies, depending on the intensity of each case. Wavelet analysis revealed that cycles that did not coincide with El Niño/La Niña showed an increase (decrease) of 0.5 (-0.5) standard deviation is positive (negative) anomalies. The increase of anomalies in neutral phases indicated that other climatic variability modes and the intensity of meteorological events decreased the 25 and 43 months cycles and increased the precipitation in RS.

A DPD model of soft spheres with waterlike anomalies and poly(a)morphism.

Core-softened approaches have been employed to understand the behavior of a large variety of systems in soft condensed matter, from biological molecules to colloidal crystals, glassy phases, and water-like anomalies. At the same time, dissipative particle dynamics (DPD) is a powerful tool suitable for studying larger length and time scales. In this sense, we propose a simple model of soft molecules that exhibits a wide range of interesting phenomena: polyamorphism, with three amorphous phases, polymorphysm, including a recently found gyroid phase and a cubic diamond structure, reentrant liquid phase, and density, diffusion, and structural water-like anomalies. Each molecule is constituted by two collapsing beads, representing a harder central core and a softer corona. This induces a competition between distinct conformations that leads to their unique behavior. This provides a basis for the development of more accurate water-like DPD models that can then be parameterized for specific systems and even used to model and understand the self-assembly of colloidal crystals.

Influence of Madden–Julian Oscillation on Precipitation over the Tibetan Plateau in Boreal Summer

The influence of the Madden–Julian oscillation (MJO) on precipitation over the Tibetan Plateau (TP) during boreal summer is investigated using observational and reanalysis data during 1980–2020. The results show that summer precipitation over most areas of the eastern TP increases (decreases) in MJO Phases 1–2 (5–6), especially when the eastward-propagating MJO active convection is located over the Indian Ocean (Western Pacific) in Phase 2 (6). The most significant negative precipitation anomalies in Phase 4 (8) are located over the southern (northeastern) TP. Moreover, MJO has a relatively weakened effect on the TP summer precipitation in Phases 3 and 7 when its convection migrates to the eastern Indian Ocean and the western–central Pacific, respectively. The MJO-phase dependence of the TP summer precipitation anomalies is closely associated with the anomalous atmospheric circulation and evolution of the horizontal moisture flux convergence directly induced by MJO. When the MJO convection centers are located over the western Indian Ocean and the Pacific, high-level anticyclonic and low-level cyclonic anomalous circulations over the TP are excited. In contrast, when MJO locates over the Indian Ocean and the Maritime Continent, its diabatic heating can inspire high-level cyclonic and low-level anticyclonic circulation anomalies over the TP. The vertical motions and moisture transport from the Bay of Bengal caused by the MJO-excited large-scale circulation can modulate the TP summer precipitation. This study advances the understanding of the TP intraseasonal variability.

A3N: Attention-based adversarial autoencoder network for detecting anomalies in video sequence

This paper presents a novel attention-based adversarial autoencoder network (A3N) that consists of a two-stream decoder to detect abnormal events in video sequences. The first stream of the decoder is a reconstructive model responsible for recreating the input frame sequence. However, the second stream is a future predictive model used to predict the future frame sequence through adversarial learning. A global attention mechanism is employed at the decoder side that helps to decode the encoded sequences effectively. The training of A3N is carried out on normal video data. The attention-based reconstructive model is used during the inference stage to compute the anomaly score. A3N delivers a considerable average speed of 0.0227 s (∼44 fps ) for detecting anomalies in the testing phase on used datasets. Several experiments and ablation analyses have been performed on UCSD Pedestrian, CUHK Avenue and ShanghaiTech datasets to validate the efficiency of the proposed model.

Unsupervised Machine Learning, Multi-Attribute Analysis for Identifying Low Saturation Gas Reservoirs within the Deepwater Gulf of Mexico, and Offshore Australia

An effective method of identifying and discriminating undersaturated gas accumulations remains unresolved, resulting in uncertainty in hydrocarbon exploration. To address this problem, an unsupervised machine learning multi-attribute analysis is performed on 3D post-stack seismic data over several blocks within the deepwater Gulf of Mexico and within the Carnarvon Basin, offshore Australia. Results reveal that low-saturation gas (LSG) reservoirs can be discriminated from high-saturation gas (HSG) reservoirs by using a combination of instantaneous attributes that are sensitive to small amplitude, frequency, and phase anomalies with self-organizing maps (SOMs). This methodology shows promise for de-risking prospects, even if it is not quantitative, particularly in frontier and exploration basins where wells may not exist or be very limited. However, this method only proved to be successful within the Gulf of Mexico and yielded limited results in the Carnarvon Basin. This difference is most likely due to the Carnarvon Basin having a different amplitude response resulting from a different burial history and fluid saturations when compared to the Gulf of Mexico. Therefore, this method is non-transferrable, and a different combination of attributes may be needed in other LSG-prone basins.

Weyl anomalies on conformal manifolds and moduli spaces

A Weyl (conformal) anomaly signals a subtle quantum breaking of classical conformal invariance in conformal field theory. Over the years, Weyl anomalies have been used to characterize nonperturbative properties of conformal field theory. Anomalies associated with the energy–momentum tensor, like the coefficients [Formula: see text] and [Formula: see text] in four space–time dimensions, are generic and have been studied extensively. More generally, in even dimensions, there are also conformal anomalies associated with any primary operator that has integer scaling dimension. Some of the most interesting features of Weyl anomalies have to do with their behavior under continuous deformations or in vacua with spontaneously broken conformal symmetry. In this review, we summarize the defining properties of conformal anomalies, their classification into A- and B-type, and their implications on the structure of correlation functions. We point out that type-B anomalies can exhibit complicated dynamics and review recent progress in the study of this dynamics with special focus on four-dimensional [Formula: see text] superconformal field theories. We emphasize two applications of type-B anomalies in this context: potential constraints on the holonomy of superconformal manifolds and the deconstruction of anomalies in higher dimensions from anomalies in broken phases of lower-dimensional conformal field theories.

Influence of the hypermagnetic field noise on the baryon asymmetry generation in the symmetric phase of the early universe

We study a matter turbulence caused by strong random hypermagnetic fields (HMFs) that influence the baryon asymmetry evolution due to the Abelian anomalies in the symmetric phase in the early Universe. Such a matter turbulence is stipulated by the presence of the advection term in the induction equation for which a fluid velocity is dominated by the Lorentz force in the Navier–Stokes equation. For random HMFs, having nonzero mean squared strengths, we calculate the spectra for the HMF energy and the HMF helicity densities. The latter function governs the evolution of the fermion asymmetries in the symmetric phase before the electroweak phase transition (EWPT). In the simplest model based on the first SM generation for the lepton asymmetries of e_mathrm {R,L} and nu _{e_mathrm {L}}, we calculate a decline of all fermion asymmetries including the baryon asymmetry, given by the ‘t Hooft conservation law, when one accounts for a turbulence of HMFs during the universe cooling down to EWPT. We obtain that the stronger the mean squared strength of random initial HMFs is, the deeper the fermion asymmetries decrease, compared to the case in the absence of any turbulence.

Global reference seismological data sets: multimode surface wave dispersion

SUMMARYGlobal variations in the propagation of fundamental-mode and overtone surface waves provide unique constraints on the low-frequency source properties and structure of the Earth’s upper mantle, transition zone and mid mantle. We construct a reference data set of multimode dispersion measurements by reconciling large and diverse catalogues of Love-wave (49.65 million) and Rayleigh-wave dispersion (177.66 million) from eight groups worldwide. The reference data set summarizes measurements of dispersion of fundamental-mode surface waves and up to six overtone branches from 44 871 earthquakes recorded on 12 222 globally distributed seismographic stations. Dispersion curves are specified at a set of reference periods between 25 and 250 s to determine propagation-phase anomalies with respect to a reference Earth model. Our procedures for reconciling data sets include: (1) controlling quality and salvaging missing metadata; (2) identifying discrepant measurements and reasons for discrepancies; (3) equalizing geographic coverage by constructing summary rays for travel-time observations and (4) constructing phase velocity maps at various wavelengths with combination of data types to evaluate inter-dataset consistency. We retrieved missing station and earthquake metadata in several legacy compilations and codified scalable formats to facilitate reproducibility, easy storage and fast input/output on high-performance-computing systems. Outliers can be attributed to cycle skipping, station polarity issues or overtone interference at specific epicentral distances. By assessing inter-dataset consistency across similar paths, we empirically quantified uncertainties in traveltime measurements. More than 95 per cent measurements of fundamental-mode dispersion are internally consistent, but agreement deteriorates for overtones especially branches 5 and 6. Systematic discrepancies between raw phase anomalies from various techniques can be attributed to discrepant theoretical approximations, reference Earth models and processing schemes. Phase-velocity variations yielded by the inversion of the summary data set are highly correlated (R ≥ 0.8) with those from the quality-controlled contributing data sets. Long-wavelength variations in fundamental-mode dispersion (50–100 s) are largely independent of the measurement technique with high correlations extending up to degree ∼25. Agreement degrades with increasing branch number and period; highly correlated structure is found only up to degree ∼10 at longer periods (T > 150 s) and up to degree ∼8 for overtones. Only 2ζ azimuthal variations in phase velocity of fundamental-mode Rayleigh waves were required by the reference data set; maps of 2ζ azimuthal variations are highly consistent between catalogues ( R = 0.6–0.8). Reference data with uncertainties are useful for improving existing measurement techniques, validating models of interior structure, calculating teleseismic data corrections in local or multiscale investigations and developing a 3-D reference Earth model.

Phase unwrapping of digital holographic microscopy using adaptive region segmentation and phase derivative calibration with respect to fringe density

Accurate phase unwrapping of the wrapped phase maps with high noise and uneven fringe densities is an essential problem for phase restoration in digital holographic microscopy. In this paper, a phase unwrapping algorithm using adaptive region segmentation and phase derivative calibration with respect to fringe density is proposed. The dense and sparse fringe regions of the wrapped phase map are adaptively segmented by using the sine/cosine spatial filtering and calculating the second-order phase gradient. Then, the first-order spatial wrapped phase derivative maps are divided into four phase derivative maps, and the phase anomalies on them are calibrated respectively. Finally, the four maps were recombined into two new phase derivative maps, and the unweighted least-squares iterative algorithm is implemented to obtain the continuous phase map. The advantage of our algorithm is that it can detect, calibrate and restore the phase anomalies based on fringe density automatically. Simulation and experimental results demonstrated that the proposed algorithm has better accuracy and effectiveness in dealing with the wrapped phase maps with high fringe density and high noise, which indicates that our algorithm is able to process the wrapped phase maps corrupted by coherent noise and phase aberration in the digital holographic microscopy.

Tropospheric dispersive phase anomalies during heavy rain detected by L-band InSAR and their interpretation

The split-spectrum method (SSM) can largely isolate and correct for the ionospheric contribution in the L-band interferometric synthetic aperture radar (InSAR). The standard SSM is performed on the assumption of only the first-order ionospheric dispersive effect, which is proportional to the total electron content (TEC). It is also known that during extreme atmospheric events, either originated from the ionosphere or in the troposphere, other dispersive effects do exist and potentially provide new insights into the dynamics of the atmosphere, but there have been few detection reports of such signals by InSAR. We apply L-band InSAR into heavy rain cases and examine the applicability and limitation of the standard SSM. Since no events such as earthquakes to cause surface deformation took place, the non-dispersive component is apparently attributable to the large amount of water vapor associated with heavy rain, whereas there are spotty anomalies in the dispersive component that are closely correlated with the heavy rain area. The ionosonde and Global Navigation Satellite System (GNSS) rate of total electron content index (ROTI) map both show little anomalies during the heavy rain, which suggests few ionospheric disturbances. Therefore, we interpret that the spotty anomalies in the dispersive component of the standard SSM during heavy rain are originated in the troposphere. While we can consider two physical mechanisms, one is runaway electron avalanche and the other is the dispersive effect due to rain, comparison with the observations from the ground-based lightning detection network and rain gauge data, we conclude that the rain dispersive effect is spatiotemporally favorable. We further propose a formulation to examine if another dispersive phase than the first-order TEC effect is present and apply it to the heavy rain cases as well as two extreme ionospheric sporadic-E events. Our formulation successfully isolates the presence of another dispersive phase during heavy rain that is in positive correlation with the local rain rate. In comparison with other dispersive phases during Sporadic-E episodes, the dispersive heavy rain phases seem to have the same order of magnitude with the ionospheric higher order effects.

Development of grapevine plants under hydroponic copper-enriched solutions induced morpho-histological, biochemical and cytogenetic changes

Copper (Cu) is an essential micronutrient for plants, but when present in excess, it induces toxicity. In this study, cuttings of four wine-producing varieties of Vitis vinifera L. were used: ‘Tinta Barroca’, ‘Tinto Cão’, ‘Malvasia Fina’ and ‘Viosinho’. The grapevine cuttings were distributed by hydroponic solutions enriched with different Cu concentrations (1, 10, 25 and 50 μM) plus control. At the end of the experiment, the root growth was evaluated, and individual roots were collected, fixed, and used for histological sections and chromosome spreads preparation. The higher Cu concentrations induced toxicity and inhibited root growth. However, the grapevine varieties responded with the thickening of the root exodermis and endodermis. In the chromosome spreads, normal and abnormal interphase and mitotic cells were observed in all varieties and treatments. The increase of Cu concentration decreased the nucleolar activity, as seen by reducing the nucleolar number and area. It increased the frequency of interphase cells with anomalies (ICA), but it did not influence total soluble protein concentration. The augment of Cu concentration also decreased the mitotic index (MI) and increased the percentage of dividing cells with anomalies (DCA). Different types of chromosomal anomalies in all mitotic phases, treatments and varieties were found. Overall, the white wine varieties, ‘Malvasia Fina’ and ‘Viosinho’, appeared to be more tolerant to the Cu-induced stress because they showed higher root growth and mean MI and lower mean DCA than the red wine varieties.

A robust Kalman filter time scale algorithm with data anomaly

Kalman filtering is utilized in many fields because of its capability to separate data from white phase noise. In time and frequency domain, employing Kalman filter is particularly important because of its use in building time scales. The studied time scale algorithms have been usually based on an ensemble of clocks without data anomaly, or the anomaly data is processed in advance to secure the reliability of the data used in Kalman filter algorithm. This increases the amount of computation and affects the real-time performance of the algorithm. In this study a robust Kalman filter is employed to present a method of time scale calculation. It extends a previously published Kalman filter algorithm that is useful for an ensemble of clocks without phase anomalies. In the algorithm, the inflation factor and the optimal adaptive factor are applied to the clock ensemble. The introduced algorithm may be useful for an ensemble of clocks with measurement outliers and phase jumps. The effectiveness of the proposed method can be verified through simulation and experimental analysis. The analysis result shows that the robust Kalman filter algorithm can resist the influence of measurement outliers and phase jumps on time scale performance. So, the accuracy and the stability of time scale can be improved.

Synchronized spatial shifts of Hadley and Walker circulations

Abstract. The El Niño–Southern Oscillation (ENSO) influences the most extensive tropospheric circulation cells on our planet, known as Hadley and Walker circulations. Previous studies have largely focused on the effect of ENSO on the strength of these cells. However, what has remained uncertain is whether interannual sea surface temperature anomalies can also cause synchronized spatial shifts of these circulations. Here, by examining the spatiotemporal relationship between Hadley and Walker cells in observations and climate model experiments, we demonstrate that the seasonally evolving warm-pool sea surface temperature (SST) anomalies in the decay phase of an El Niño event generate a meridionally asymmetric Walker circulation response, which couples the zonal and meridional atmospheric overturning circulations. This process, which can be characterized as a phase-synchronized spatial shift in Walker and Hadley cells, is accompanied by cross-equatorial northwesterly low-level flow that diverges from an area of anomalous drying in the western North Pacific and converges towards a region with anomalous moistening in the southern central Pacific. Our results show that the SST-induced concurrent spatial shifts of the two circulations are climatically relevant as they can further amplify extratropical precipitation variability on interannual timescales.