Matthew Newman

Understanding ENSO Diversity

El Nino–Southern Oscillation (ENSO) is a naturally occurring mode of tropical Pacific variability, with global impacts on society and natural ecosystems. While it has long been known that El Nino events display a diverse range of amplitudes, triggers, spatial patterns, and life cycles, the realization that ENSO’s impacts can be highly sensitive to this event-to-event diversity is driving a renewed interest in the subject. This paper surveys our current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions.

Stratiform Precipitation, Vertical Heating Profiles, and the Madden-Julian Oscillation

The observed profile of heating through the troposphere in the Madden‐Julian oscillation (MJO) is found to be very top heavy: more so than seasonal-mean heating and systematically more so than all of the seven models for which intraseasonal heating anomaly profiles have been published. Consistently, the Tropical Rainfall Measuring Mission (TRMM) precipitation radar shows that stratiform precipitation (known to heat the upper troposphere and cool the lower troposphere) contributes more to intraseasonal rainfall variations than it does to seasonal-mean rainfall. Stratiform rainfall anomalies lag convective rainfall anomalies by a few days. Reasons for this lag apparently include increased wind shear and middle‐upper tropospheric humidity, which also lag convective (and total) rainfall by a few days. A distinct rearward tilt is seen in anomalous heating time‐height sections, in both the strong December 1992 MJO event observed by the Tropical Ocean Global Atmosphere Coupled Ocean‐Atmosphere Response Experiment (TOGA COARE) and a composite MJO constructed from multiyear datasets. Interpretation is aided by a formal partitioning of the COARE heating section into convective, stratiform, and radiative components. The tilted structure after the maximum surface rainfall appears to be largely contributed by latent and radiative heating in enhanced stratiform anvils. However, the tilt of anomalous heating ahead of maximum rainfall is seen within the convective component, suggesting a change from shallower to deeper convective heating as the wet phase of the MJO approached the longitude of the observations.

The Pacific Decadal Oscillation, Revisited

AbstractThe Pacific decadal oscillation (PDO), the dominant year-round pattern of monthly North Pacific sea surface temperature (SST) variability, is an important target of ongoing research within the meteorological and climate dynamics communities and is central to the work of many geologists, ecologists, natural resource managers, and social scientists. Research over the last 15 years has led to an emerging consensus: the PDO is not a single phenomenon, but is instead the result of a combination of different physical processes, including both remote tropical forcing and local North Pacific atmosphere–ocean interactions, which operate on different time scales to drive similar PDO-like SST anomaly patterns. How these processes combine to generate the observed PDO evolution, including apparent regime shifts, is shown using simple autoregressive models of increasing spatial complexity. Simulations of recent climate in coupled GCMs are able to capture many aspects of the PDO, but do so based on a balance of ...

A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.

Distinguishing the Roles of Natural and Anthropogenically Forced Decadal Climate Variability: Implications for Prediction

Abstract Given that over the course of the next 10–30 years the magnitude of natural decadal variations may rival that of anthropogenically forced climate change on regional scales, it is envisioned that initialized decadal predictions will provide important information for climate-related management and adaptation decisions. Such predictions are presently one of the grand challenges for the climate community. This requires identifying those physical phenomena—and their model equivalents—that may provide additional predictability on decadal time scales, including an assessment of the physical processes through which anthropogenic forcing may interact with or project upon natural variability. Such a physical framework is necessary to provide a consistent assessment (and insight into potential improvement) of the decadal prediction experiments planned to be assessed as part of the IPCCs Fifth Assessment Report.

Medium-Range Forecast Errors Associated with Active Episodes of the Madden-Julian Oscillation

Abstract Systematic forecast errors associated with active episodes of the tropical Madden–Julian oscillation (MJO) are examined using five winters of dynamical extended range forecasts from the National Centers for Environmental Prediction reanalysis model. Active episodes of the MJO are identified as those periods when the amplitude of either of the first two empirical orthogonal functions of intraseasonally filtered outgoing longwave radiation, which efficiently capture the MJO, is large. Forecasts initialized during active episodes of the MJO are found not to capture the eastward propagation of the tropical precipitation and circulation anomalies associated with the MJO. Rather, the MJO-induced anomalies of precipitation and winds are systematically forecast to weaken and even retrograde. By about day 7 of the forecast the convectively coupled, tropical circulation anomalies produced by the MJO are largely gone. Systematic errors in the extratropical 200-mb streamfunction also fully develop by day 10....

Interannual to Decadal Predictability of Tropical and North Pacific Sea Surface Temperatures

Abstract A multivariate empirical model is used to show that predictability of the dominant patterns of tropical and North Pacific oceanic variability, El Nino–Southern Oscillation (ENSO), and the Pacific decadal oscillation (PDO), is mostly limited to little more than a year, despite the presence of spectral peaks on decadal time scales. The model used is a linear inverse model (LIM) derived from the observed simultaneous and 1-yr lag correlation statistics of July–June-averaged SST from the Hadley Centre Global Sea Ice and Sea Surface Temperature (HadISST) dataset for the years 1900–2002. The model accurately reproduces the power spectra of the data, including interannual and interdecadal spectral peaks that are significant relative to univariate red noise. Eigenanalysis of the linear dynamical operator yields propagating eigenmodes that correspond to these peaks but have very short decay times and, thus, limited predictability. Longer-term predictability does exist, however, due to two stationary eigen...

A caveat concerning singular value decomposition

Abstract An assessment is made of the ability of the singular value decomposition (SYD) technique to recover the relationship between two variables x and y from a time series of their observations. It is shown that SVD is rigorously successful only in the special cases when either (i) the transformation linking x and y is orthogonal or (ii) the covariance matrix of either x or y is the identity matrix. The behavior of the method when theSE conditions are not met is also studied in a simple two-dimensional case. That this caveat can be relevant in a meteorological context is demonstrated by performing an SVD analysis of a time series of global upper-tropospheric streamfunction and vorticity fields. Although these fields are linked by the two-dimensional Laplacian operator on the sphere, it is shown that the pairs of singular patterns resulting from the SVD analysis are not so related. The problem is apparent even for the first SVD pair and generally becomes worse for succeeding pairs These results suggest ...

Multiplicative Noise and Non-Gaussianity: A Paradigm for Atmospheric Regimes?

Abstract Atmospheric circulation statistics are not strictly Gaussian. Small bumps and other deviations from Gaussian probability distributions are often interpreted as implying the existence of distinct and persistent nonlinear circulation regimes associated with higher-than-average levels of predictability. In this paper it is shown that such deviations from Gaussianity can, however, also result from linear stochastically perturbed dynamics with multiplicative noise statistics. Such systems can be associated with much lower levels of predictability. Multiplicative noise is often identified with state-dependent variations of stochastic feedbacks from unresolved system components, and may be treated as stochastic perturbations of system parameters. It is shown that including such perturbations in the damping of large-scale linear Rossby waves can lead to deviations from Gaussianity very similar to those observed in the joint probability distribution of the first two principal components (PCs) of weekly av...

A Linear Model of Wintertime Low-Frequency Variability. Part I: Formulation and Forecast Skill

A linear inverse model (LIM) suitable for studies of atmospheric extratropical variability on longer than weekly timescales is constructed using observations of the past 30 years. Notably, it includes tropical diabatic heating as an evolving model variable rather than as a forcing, and also includes, in effect, the feedback of the extratropical weather systems on the more slowly varying circulation. Both of these features are shown to be important contributors to the model’s realism. Forecast skill is an important test of any model’s usefulness as a diagnostic tool. The LIM is better at forecasting week 2 anomalies than a dynamical model based on the linearized baroclinic equations of motion (with many more than the LIM’s 37 degrees of freedom) that is forced with observed (as opposed to the LIM’s predicted) tropical heating throughout the forecast. Indeed, at week 2 the LIM’s skill is competitive with that of the global nonlinear medium-range forecast (MRF) model with nominally O(106) degrees of freedom in use at the National Centers for Environmental Prediction (NCEP). Importantly, this encouraging model performance is not limited