An official website of the United States government
Abstract The Madden‐Julian Oscillation (MJO) is the leading mode of intraseasonal climate variability, having profound impacts on a wide range of weather and climate phenomena. Here, we use a wavelet‐based spectral Principal Component Analysis (wsPCA) to evaluate the skill of 20 state‐of‐the‐art CMIP6 models in capturing the magnitude and dynamics of the MJO. By construction, wsPCA has the ability to focus on desired frequencies and capture each propagative physical mode with one principal component (PC). We show that the MJO contribution to the total intraseasonal climate variability is substantially underestimated in most CMIP6 models. The joint distribution of the modulus and angular frequency of the wavelet PC series associated with MJO is used to rank models relatively to the observations through the Wasserstein distance. Using Hovmöller phase‐longitude diagrams, we also show that precipitation variability associated with MJO is underestimated in most CMIP6 models for the Amazonia, Southwest Africa, and Maritime Continent.
more »
« less
Identification of the Madden–Julian Oscillation With Data‐Driven Koopman Spectral Analysis
Abstract The Madden‐Julian Oscillation (MJO), the dominant mode of tropical intraseasonal variability, is commonly identified using the realtime multivariate MJO (RMM) index based on joint empirical orthogonal function (EOF) analysis of near‐equatorial upper and lower level zonal winds and outgoing longwave radiation. Here, in place of conventional EOFs, we apply an operator‐theoretic formalism based on dynamic systems theory (the Koopman operator) to extract an analog to RMM that exhibits certain features that refine the characterization and predictability of the MJO. In particular, the spectrum of Koopman operator eigenfunctions, with eigenvalues corresponding to mode periods, contains a leading intraseasonal mode with period of ∼50 days. Moreover, the amplitude of this leading intraseasonal eigenfunction exhibits a seasonal modulation clearly peaked in boreal winter. Finally, the phase space formed by the complex Koopman MJO eigenfunction exhibits a smoother temporal evolution and higher degree of autocorrelation than RMM, which may contribute to enhanced predictive skill.
more »
« less
- PAR ID:
- 10414358
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Geophysical Research Letters
- Volume:
- 50
- Issue:
- 10
- ISSN:
- 0094-8276
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The relative importance of preconditioning moistening and global circumnavigating mode in the convective initiation of the October 2011 Madden–Julian Oscillation (MJO) event observed during the Dynamics of the Madden–Julian Oscillation (DYNAMO) field campaign is investigated using a series of convection‐permitting regional model simulations. It is demonstrated that the MJO convective initiation is largely controlled by the global circumnavigating mode at the intraseasonal scales. Rapid moistening closely related to this eastward propagating mode a few days prior to the MJO active phase is crucial to the initiation of deep convection and enhanced rainfall. This moistening process nevertheless cannot be accurately described by the “discharge‐recharge” hypothesis, which speculates the importance a gradual moisture buildup over an approximately 2‐week period leading to the arrival of the active MJO phase.more » « less
-
Abstract Tropical intraseasonal variability (ISV) is dominated by the Madden–Julian oscillation (MJO), and its spatiotemporal characteristics vary with the Indo-Pacific warm-pool background on seasonal and longer time scales. Previous works have suggested ISV dynamics in various frameworks, whereas a unifying view remains challenging. Motivated by the recent advance in moisture mode theory, we revisit the ISV as a leading moisture mode modulated by varying background states derived from a reanalysis, using a moist linear baroclinic model (mLBM) improved with a simple convective scheme relating convective precipitation to tropospheric and boundary layer moisture anomalies and simple cloud-radiative feedback representations. Under a boreal winter background state, this mLBM yielded a large-scale but local eastward-propagating mode with a phase speed of 3–5 m s−1over the warm-pool region, resembling the MJO. Background lower-tropospheric winds and thermodynamic fields are important in determining the growth rate and periodicity of the leading mode, whose stability depends on cloud-radiative feedback and background state variations. We further demonstrate why the MJO is locally contained in the Indo-Pacific warm-pool region. The local thermal/moisture condition and Walker circulation greatly enhance its instability, but outside this region, this mode is heavily damped. Thus, the expansion/contraction of this warm-pool condition may enhance/reduce its instability and expand/reduce its domain of activity. Prescribing El Niño background causes eastward displacement of the wintertime ISV activity, reminiscent of the observed MJO modulations by El Niño. Under a summer background state, the eastward-propagating leading mode resembles the boreal summer ISV but is biased, requiring further model improvements.more » « less
-
null (Ed.)This work serves as a bridge between two approaches to analysis of dynamical systems: the local, geometric analysis, and the global operator theoretic Koopman analysis. We explicitly construct vector fields where the instantaneous Lyapunov exponent field is a Koopman eigenfunction. Restricting ourselves to polynomial vector fields to make this construction easier, we find that such vector fields do exist, and we explore whether such vector fields have a special structure, thus making a link between the geometric theory and the transfer operator theory.more » « less
-
Abstract Koopman operators linearize nonlinear dynamical systems, making their spectral information of crucial interest. Numerous algorithms have been developed to approximate these spectral properties, and dynamic mode decomposition (DMD) stands out as the poster child of projection-based methods. Although the Koopman operator itself is linear, the fact that it acts in an infinite-dimensional space of observables poses challenges. These include spurious modes, essential spectra, and the verification of Koopman mode decompositions. While recent work has addressed these challenges for deterministic systems, there remains a notable gap in verified DMD methods for stochastic systems, where the Koopman operator measures the expectation of observables. We show that it is necessary to go beyond expectations to address these issues. By incorporating variance into the Koopman framework, we address these challenges. Through an additional DMD-type matrix, we approximate the sum of a squared residual and a variance term, each of which can be approximated individually using batched snapshot data. This allows verified computation of the spectral properties of stochastic Koopman operators, controlling the projection error. We also introduce the concept of variance-pseudospectra to gauge statistical coherency. Finally, we present a suite of convergence results for the spectral information of stochastic Koopman operators. Our study concludes with practical applications using both simulated and experimental data. In neural recordings from awake mice, we demonstrate how variance-pseudospectra can reveal physiologically significant information unavailable to standard expectation-based dynamical models.more » « less
