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Kenneth R. Sperber

Abstract

The Madden–Julian oscillation (MJO) dominates tropical variability on time scales of 30–70 days. During the boreal winter–spring it is manifested as an eastward propagating disturbance, with a strong convective signature over the Eastern Hemisphere. The space–time structure of the MJO is described using the National Centers for Environmental Prediction–National Center for Atmospheric Research reanalysis, Advanced Very High Resolution Radiometer outgoing longwave radiation, observed sea surface temperature, and the Climate Prediction Center Merged Analysis of Precipitation. Empirical orthogonal function analysis is used to identify the convective signature of the MJO, and regression is used to identify key relationships with the convection. Compared to analyzing successive years of data, the selection of years of strong MJO activity results in a more robust lead–lag structure and an increase in explained variance. The MJO exhibits a rich vertical structure, with low-level moisture convergence being well defined when the convective anomalies are strong, and there is evidence that free-tropospheric processes also play a role in the MJO life cycle. The westward vertical tilt is most apparent over the western Pacific. Over the Indian Ocean the system is more vertically stacked, principally because of the strong subsidence of the inactive phase of the MJO, which lies to the east of the convection. As the Kelvin wave decouples from the convection near the date line, a sea level low pressure surge, previously discussed by A. J. Matthews, transits the eastern Pacific and Atlantic Oceans. Here the link of the zonal wind stress and low-level divergence to the pressure surge is explored. The pressure gradient gives rise to westerlies that propagate rapidly to the east, and it may play role in the development of the MJO convection in the western Indian Ocean, which occurs in an easterly basic state, and conditions not consistent with the low-level moisture convergence paradigm.

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Kenneth R. Sperber and Tetsuzo Yasunari
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Emily Black, Julia Slingo, and Kenneth R. Sperber

Abstract

Composites of SST, wind, rainfall, and humidity have been constructed for years of high rainfall during September, October, and November (SON) in equatorial and southern-central East Africa. These show that extreme East African short rains are associated with large-scale SST anomalies in the Indian Ocean that closely resemble those that develop during Indian Ocean dipole or zonal mode (IOZM) events. This is corroborated by the observation that strong IOZM events produce enhanced East African rainfall. However, it is also shown that the relationship between the IOZM and East African rainfall is nonlinear, with only IOZM events that reverse the zonal SST gradient for several months (extreme events) triggering high rainfall.

Comparison of the wind anomalies that develop during extreme IOZM events with those that develop during weaker (moderate) events shows that strong easterly anomalies in the northern-central Indian Ocean are a persistent feature of extreme, but not of moderate, IOZM years. It is suggested that these anomalies weaken the westerly flow that normally transports moisture away from the African continent, out over the Indian Ocean. Thus, during extreme IOZM years, rainfall is enhanced over East Africa and reduced in the central and eastern Indian Ocean basin.

It is also shown that the IOZM cannot be viewed in isolation from the El Niño–Southern Oscillation (ENSO). Instead it is postulated that in some years, a strong ENSO forcing can predispose the Indian Ocean coupled system to an IOZM event and is therefore a contributory factor in extreme East African rainfall. The results of this study imply that the relationship between El Niño and the IOZM explains the previously described association between El Niño and high East African rainfall. Thus, understanding the way that ENSO drives Indian Ocean dynamics may aid the development of predictive scenarios for East African climate that could have significant economic implications.

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Sultan Hameed, Alan Meinster, and Kenneth R. Sperber

Abstract

The Oregon State University coupled upper ocean-atmosphere GCM has been shown to qualitatively simulate the Southern Oscillation. A composite analysis of the warm and cold events simulated in this 23-year integration has been performed. During the low phase of the Southern Oscillation, when warm anomalies occur in the eastern Pacific, the model simulates for the Atlantic region during March–May 1) a deficit of precipitation over the tropical South American continent, 2) Caribbean and Gulf of Mexico sea level pressure and sea surface temperature are in phase with the eastern Pacific anomalies, while those east of the Nordeste region are out of phase, and 3) northeast trade winds are anomalously weak and southwest trade winds are anomalously strong (as inferred from surface current anomalies). The anomalies in the oceanic processes are induced by perturbations in the atmospheric circulation over the Atlantic and are coupled to changes in the Walker circulation. During the high phase of the simulated Southern Oscillation, conditions in the atmosphere and ocean are essentially the reverse of the low phase. The model produces a response in the South American region during the opposing phases of the Southern Oscillation that is in general agreement with observations.

The interannual variation of Nordeste rainfall is shown to be dominated by a few band-limited frequencies. These frequencies are found in the SST series of those regions of the Atlantic and Pacific oceans where strong correlations with Nordeste precipitation exist.

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Yi Zhang, Kenneth R. Sperber, and James S. Boyle

Abstract

This paper presents the climatology and interannual variation of the East Asian winter monsoon based on the 1979–95 National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis. In addition to documenting the frequency, intensity, and preferred propagation tracks of cold surges and the evolution patterns of related fields, the authors discuss the temporal distribution of the Siberian high and cold surges. Further, the interannual variation of the cold surges and winter monsoon circulation and its relationship with ENSO were examined.

There are on average 13 cold surges in each winter season (October–April), of which two are strong cases. The average intensity of cold surges, measured by maximum sea level pressure, is 1053 hPa. The cold surges originate from two source regions: 1) northwest of Lake Baikal, and 2) north of Lake Balkhash. The typical evolution of a cold surge occurs over a period of 5–14 days. Trajectory and correlation analyses indicate that, during this time, high pressure centers propagate southeastward around the edge of the Tibetan Plateau from the mentioned source regions. Some of these high pressure centers then move eastward and diminish over the oceans, while others proceed southward. The signatures of the associated temperature, wind, and pressure fields propagate farther southward and eastward. The affected area encompasses the bulk of the maritime continent. Although the intensity of the Siberian high peaks during December and January, the frequency of cold surges reaches a maximum in November and in March. This result suggests that November through March should be considered as the East Asian winter monsoon season.

Two stratifications of cold surges are used to examine the relationship between ENSO and the interannual variation of the winter monsoon. The first one, described as conventional cold surges, indicates that the surge frequency reaches a minimum a year after El Niño events. The second one, defined as a maximum wind event near the South China Sea, shares the same origin as the first. The surge frequency is in good agreement with the Southern Oscillation index (SOI). A low (high) SOI event coincides with a low (high) frequency of cold surges.

The interannual variation of winter northerlies near the South China Sea is dominated by the South China Sea cold surges and is well correlated (R = 0.82) with the SOI. Strong wind seasons are associated with La Niña and high SOI years; on the other hand, weak wind seasons are associated with El Niño and low SOI years. This pattern is restricted to an area north of the equator within the region of (0°–20°N, 100°–130°E) and is confined to the near-surface layer. The SST variation in the same region is similar to the wind pattern but lags the wind for approximately 1–5 months, which suggests that the SST variation is forced by the wind. The surface Siberian high, 500-hPa trough, and200-hPa jet stream, all representing the large-scale monsoon flow, are weaker than normal during El Niño years. In particular, the interannual variation of the Siberian high is in general agreement with the SOI.

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Harry H. Hendon, Kenneth R. Sperber, Duane E. Waliser, and Matthew C. Wheeler

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Ping Liu, Bin Wang, Kenneth R. Sperber, Tim Li, and Gerald A. Meehl

Abstract

The boreal winter Madden–Julian oscillation (MJO) remains very weak and irregular in the National Center for Atmospheric Research (NCAR) Community Atmosphere Model version 2 (CAM2) as in its direct predecessor, the Community Climate Model version 3 (CCM3). The standard version of CAM2 uses the deep convective scheme of Zhang and McFarlane, as in CCM3, with the closure dependent on convective available potential energy (CAPE). Here, sensitivity tests using several versions of the Tiedtke convective scheme are conducted. Typically, the Tiedtke convection scheme gives an improved mean state, intraseasonal variability, space–time power spectra, and eastward propagation compared to the standard version of the model. Coherent eastward propagation of MJO-related precipitation is also much improved, particularly over the Indian–western Pacific Oceans. A composite life cycle of the model MJO indicates that over the Indian Ocean wind-induced surface heat exchange (WISHE) functions, while over the western/central Pacific Ocean aspects of frictional moisture convergence are evident in the maintenance and eastward propagation of the oscillation.

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Jiwoo Lee, Kenneth R. Sperber, Peter J. Gleckler, Karl E. Taylor, and Céline J. W. Bonfils

Abstract

We evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, CMIP5, and CMIP6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the observed northern annular mode (NAM), North Atlantic Oscillation (NAO), Pacific–North America pattern (PNA), southern annular mode (SAM), Pacific decadal oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a common basis function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and high-top vertical coordinate); however, the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the postdominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious postdominant season amplitude errors found in many models can be addressed in an atmospheric-only framework, making it more tractable to address in the model development process.

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Clara Orbe, Luke Van Roekel, Ángel F. Adames, Amin Dezfuli, John Fasullo, Peter J. Gleckler, Jiwoo Lee, Wei Li, Larissa Nazarenko, Gavin A. Schmidt, Kenneth R. Sperber, and Ming Zhao

Abstract

We compare the performance of several modes of variability across six U.S. climate modeling groups, with a focus on identifying robust improvements in recent models [including those participating in phase 6 of the Coupled Model Intercomparison Project (CMIP)] compared to previous versions. In particular, we examine the representation of the Madden–Julian oscillation (MJO), El Niño–Southern Oscillation (ENSO), the Pacific decadal oscillation (PDO), the quasi-biennial oscillation (QBO) in the tropical stratosphere, and the dominant modes of extratropical variability, including the southern annular mode (SAM), the northern annular mode (NAM) [and the closely related North Atlantic Oscillation (NAO)], and the Pacific–North American pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g., the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

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W. Lawrence Gates, James S. Boyle, Curt Covey, Clyde G. Dease, Charles M. Doutriaux, Robert S. Drach, Michael Fiorino, Peter J. Gleckler, Justin J. Hnilo, Susan M. Marlais, Thomas J. Phillips, Gerald L. Potter, Benjamin D. Santer, Kenneth R. Sperber, Karl E. Taylor, and Dean N. Williams

The Atmospheric Model Intercomparison Project (AMIP), initiated in 1989 under the auspices of the World Climate Research Programme, undertook the systematic validation, diagnosis, and intercomparison of the performance of atmospheric general circulation models. For this purpose all models were required to simulate the evolution of the climate during the decade 1979–88, subject to the observed monthly average temperature and sea ice and a common prescribed atmospheric CO2 concentration and solar constant. By 1995, 31 modeling groups, representing virtually the entire international atmospheric modeling community, had contributed the required standard output of the monthly means of selected statistics. These data have been analyzed by the participating modeling groups, by the Program for Climate Model Diagnosis and Intercomparison, and by the more than two dozen AMIP diagnostic subprojects that have been established to examine specific aspects of the models' performance. Here the analysis and validation of the AMIP results as a whole are summarized in order to document the overall performance of atmospheric general circulation–climate models as of the early 1990s. The infrastructure and plans for continuation of the AMIP project are also reported on.

Although there are apparent model outliers in each simulated variable examined, validation of the AMIP models' ensemble mean shows that the average large-scale seasonal distributions of pressure, temperature, and circulation are reasonably close to what are believed to be the best observational estimates available. The large-scale structure of the ensemble mean precipitation and ocean surface heat flux also resemble the observed estimates but show particularly large intermodel differences in low latitudes. The total cloudiness, on the other hand, is rather poorly simulated, especially in the Southern Hemisphere. The models' simulation of the seasonal cycle (as represented by the amplitude and phase of the first annual harmonic of sea level pressure) closely resembles the observed variation in almost all regions. The ensemble's simulation of the interannual variability of sea level pressure in the tropical Pacific is reasonably close to that observed (except for its underestimate of the amplitude of major El Niños), while the interannual variability is less well simulated in midlatitudes. When analyzed in terms of the variability of the evolution of their combined space–time patterns in comparison to observations, the AMIP models are seen to exhibit a wide range of accuracy, with no single model performing best in all respects considered.

Analysis of the subset of the original AMIP models for which revised versions have subsequently been used to revisit the experiment shows a substantial reduction of the models' systematic errors in simulating cloudiness but only a slight reduction of the mean seasonal errors of most other variables. In order to understand better the nature of these errors and to accelerate the rate of model improvement, an expanded and continuing project (AMIP II) is being undertaken in which analysis and intercomparison will address a wider range of variables and processes, using an improved diagnostic and experimental infrastructure.

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