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Y. Zheng, D. E. Waliser, W. F. Stern, and C. Jones

Abstract

This study compares the tropical intraseasonal oscillation (TISO) variability in the Geophysical Fluid Dynamics Laboratory (GFDL) coupled general circulation model (CGCM) and the stand-alone atmospheric general circulation model (AGCM). For the AGCM simulation, the sea surface temperatures (SSTs) were specified using those from the CGCM simulation. This was done so that any differences in the TISO that emerged from the two simulations could be attributed to the coupling process and not to a difference in the mean background state. The comparison focused on analysis of the rainfall, 200-mb velocity potential, and 850-mb zonal wind data from the two simulations, for both summer and winter periods, and included comparisons to analogous diagnostics using NCEP–NCAR reanalysis and Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) rainfall data.

The results of the analysis showed three principal differences in the TISO variability between the coupled and uncoupled simulations. The first was that the CGCM showed an improvement in the spatial variability associated with the TISO mode, particularly for boreal summer. Specifically, the AGCM exhibited almost no TISO variability in the Indian Ocean during boreal summer—a common shortcoming among AGCMs. The CGCM, on the other hand, did show a considerable enhancement in TISO variability in this region for this season. The second was that the wavenumber–frequency spectra of the AGCM exhibited an unrealistic peak in variability at low wavenumbers (1–3, depending on the variable) and about 3 cycles yr−1 (cpy). This unrealistic peak of variability was absent in the CGCM, which otherwise tended to show good agreement with the observations. The third difference was that the AGCM showed a less realistic phase lag between the TISO-related convection and SST anomalies. In particular, the CGCM exhibited a near-quadrature relation between precipitation and SST anomalies, which is consistent with observations, while the phase lag was reduced in the AGCM by about 1.5 pentads (∼1 week). The implications of the above results, including those for the notions of “perfect SST” and “two tier” experiments, are discussed, as are the caveats associated with the study's modeling framework and analysis.

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L. E. Lucas, D. E. Waliser, P. Xie, J. E. Janowiak, and B. Liebmann

Abstract

Due to its long record length (approximately 25 years), the outgoing longwave radiation (OLR) dataset has been used in a multitude of climatological studies including studies on tropical circulation and convection, the El Niño–Southern Oscillation (ENSO) phenomenon, and the earth's radiation budget. Although many of the climatological studies using OLR have proven invaluable, proper interpretation of the low-frequency components of the data could be limited by the presence of biases introduced by changes in the satellite equatorial crossing time (ECT). Since long-term global changes could be masked or contaminated by this instrumental bias, it is necessary to take steps to ensure that the daily, global OLR dataset is free from such biases and is as accurate as possible.

The goal of this study is to derive a method for estimating the ECT biases in the daily, global OLR dataset. Our analysis utilizes a Procrustes targeted empirical orthogonal function rotation (REOF) on an interpolated OLR dataset to try to isolate and remove the two major ECT biases—afternoon satellite orbital drift and the abrupt transitions from a morning satellite to an afternoon satellite—from the dataset. Two targeted REOF analyses are performed to separate and distinguish between these two artificial satellite bias modes. A “common ECT” of approximately 0245 LST is established for the dataset by removing an estimate of these two ECT biases.

Results from the analysis indicate that changes in ECTs can cause large regional biases over both ocean and tropical landmasses. The afternoon satellite ECT drift-bias accounts for 0.4% of the pentad anomaly variance. During a single satellite series (e.g., NOAA-11), the afternoon drift-bias can introduce a difference as large as 10.5 W m−2 in the OLR values collected over most tropical landmasses. The morning to afternoon satellite transition bias accounts for 0.9% of the pentad anomaly variance, and is shown to cause a bias of 12 W m−2 in the OLR values over most tropical landmasses during the NOAA-SR satellite series. The data are corrected by removing a statistically derived synthetic eigenvector that is associated with each of the ECT bias modes. This synthetic eigenvector is used instead of the exact values of the satellite bias eigenvector to ensure that only the artificial variability is removed from the dataset.

The two REOF modes produced in this study are nearly orthogonal to each other having a correlation of only 0.17. This near orthogonality suggests that the use of the two-mode method presented in this study can more adequately describe the individual nature of each of the two ECT biases than a single REOF mode examined in previous studies. However, due to the presence of other forms of variability, it is likely that this study's estimate of the ECT bias includes ECT-related bias as well as some aspects of variability that may be associated with sensor changes, intersatellite calibration and/or natural climate variability. The strengths and limitations of the above technique are discussed, as are suggestions for future efforts.

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Man-Li C. Wu, Siegfried D. Schubert, Max J. Suarez, Philip J. Pegion, and Duane E. Waliser

Abstract

The Madden–Julian oscillation (MJO) is known to have a substantial impact on the variability of the Asian–Australian summer monsoons. An important, but not well understood, aspect of the MJO–monsoon connection is the meridional propagation of bands of enhanced or reduced precipitation that are especially pronounced during the northern summer. In this study, the nature of the seasonality of the MJO is examined, with a focus on the meridional propagation, using both observations and simulations with an atmospheric general circulation model (AGCM).

A key result is that the AGCM, when forced with idealized eastward propagating equatorial dipole heating anomalies, reproduces the salient features of the observed seasonality in the precipitation and wind fields associated with the MJO, including meridional propagation into the Indian and Australian summer monsoon regions. An analysis of the simulations and observations shows that the off-equatorial precipitation anomalies are initiated by surface frictional convergence/divergence associated with the Rossby wave response to the leading pole of the equatorial heating dipole. The off-equatorial precipitation anomalies develop further by interacting with the trailing pole of the equatorial dipole heating to produce a northwest–southeast (or southwest–northeast) oriented line of surface convergence/divergence that propagates to the east. Since the prescribed heating does not vary by season, the seasonal asymmetry in the response must be the result of the seasonal changes in the background state. In particular, the results suggest that seasonal changes in both the vertical wind shear and static stability play a role.

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G. Cesana, D. E. Waliser, D. Henderson, T. S. L’Ecuyer, X. Jiang, and J.-L. F. Li

Abstract

We assess the vertical distribution of radiative heating rates (RHRs) in climate models using a multimodel experiment and A-Train satellite observations, for the first time. As RHRs rely on the representation of cloud amount and properties, we first compare the modeled vertical distribution of clouds directly against lidar–radar combined cloud observations (i.e., without simulators). On a near-global scale (50°S–50°N), two systematic differences arise: an excess of high-level clouds around 200 hPa in the tropics, and a general lack of mid- and low-level clouds compared to the observations. Then, using RHR profiles calculated with constraints from A-Train and reanalysis data, along with their associated maximum uncertainty estimates, we show that the excess clouds and ice water content in the upper troposphere result in excess infrared heating in the vicinity of and below the clouds as well as a lack of solar heating below the clouds. In the lower troposphere, the smaller cloud amount and the underestimation of cloud-top height is coincident with a shift of the infrared cooling to lower levels, substantially reducing the greenhouse effect, which is slightly compensated by an erroneous excess absorption of solar radiation. Clear-sky RHR differences between the observations and the models mitigate cloudy RHR biases in the low levels while they enhance them in the high levels. Finally, our results indicate that a better agreement between observed and modeled cloud profiles could substantially improve the RHR profiles. However, more work is needed to precisely quantify modeled cloud errors and their subsequent effect on RHRs.

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Xianan Jiang, Eric D. Maloney, Jui-Lin F. Li, and Duane E. Waliser

Abstract

As a key component of tropical atmospheric variability, intraseasonal variability (ISV) over the eastern North Pacific Ocean (ENP) exerts pronounced influences on regional weather and climate. Since general circulation models (GCMs) are essential tools for prediction and projection of future climate, current model deficiencies in representing this important variability leave us greatly disadvantaged in studies and prediction of climate change. In this study, the authors have assessed model fidelity in representing ENP ISV by analyzing 16 GCMs participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Among the 16 CMIP5 GCMs examined in this study, only seven GCMs capture the spatial pattern of the leading ENP ISV mode relatively well, although even these GCMs exhibit biases in simulating ISV amplitude. Analyses indicate that model fidelity in representing ENP ISV is closely associated with the ability to simulate a realistic summer mean state. The presence of westerly or weak mean easterly winds over the ENP warm pool region could be conducive to more realistic simulations of the ISV. One hypothesis to explain this relationship is that a realistic mean state could produce the correct sign of surface flux anomalies relative to the ISV convection, which helps to destabilize local intraseasonal disturbances. The projected changes in characteristics of ENP ISV under the representative concentration pathway 8.5 (RCP8.5) projection scenario are also explored based on simulations from three CMIP5 GCMs. Results suggest that, in a future climate, the amplitude of ISV could be enhanced over the southern part of the ENP while reduced over the northern ENP off the coast of Mexico/Central America and the Caribbean.

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Bin Wang, Sun-Seon Lee, Duane E. Waliser, Chidong Zhang, Adam Sobel, Eric Maloney, Tim Li, Xianan Jiang, and Kyung-Ja Ha

Abstract

Realistic simulations of the Madden–Julian oscillation (MJO) by global climate models (GCMs) remain a great challenge. To evaluate GCM simulations of the MJO, the U.S. CLIVAR MJO Working Group developed a standardized set of diagnostics, providing a comprehensive assessment of statistical properties of the MJO. Here, a suite of complementary diagnostics has been developed that provides discrimination and assessment of MJO simulations based on the perception that the MJO propagation has characteristic dynamic and thermodynamic structures. The new dynamics-oriented diagnostics help to evaluate whether a model produces eastward-propagating MJOs for the right reasons. The diagnostics include 1) the horizontal structure of boundary layer moisture convergence (BLMC) that moistens the lower troposphere to the east of a convection center, 2) the preluding eastward propagation of BLMC that leads the propagation of MJO precipitation by about 5 days, 3) the horizontal structure of 850-hPa zonal wind and its equatorial asymmetry (Kelvin easterly versus Rossby westerly intensity), 4) the equatorial vertical–longitudinal structure of the equivalent potential temperature and convective instability index that reflects the premoistening and predestabilization processes, 5) the equatorial vertical–longitudinal distribution of diabatic heating that reflects the multicloud structure of the MJO, 6) the upper-level divergence that reflects the influence of stratiform cloud heating, and 7) the MJO available potential energy generation that reflects the amplification and propagation of an MJO. The models that simulate better three-dimensional dynamic and thermodynamic structures of MJOs generally reproduce better eastward propagations. This evaluation identifies a number of shortcomings in representing dynamical and heating processes relevant to the MJO simulation and reveals potential sources of the shortcomings.

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D. Kim, K. Sperber, W. Stern, D. Waliser, I.-S. Kang, E. Maloney, W. Wang, K. Weickmann, J. Benedict, M. Khairoutdinov, M.-I. Lee, R. Neale, M. Suarez, K. Thayer-Calder, and G. Zhang

Abstract

The ability of eight climate models to simulate the Madden–Julian oscillation (MJO) is examined using diagnostics developed by the U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group. Although the MJO signal has been extracted throughout the annual cycle, this study focuses on the boreal winter (November–April) behavior. Initially, maps of the mean state and variance and equatorial space–time spectra of 850-hPa zonal wind and precipitation are compared with observations. Models best represent the intraseasonal space–time spectral peak in the zonal wind compared to that of precipitation. Using the phase–space representation of the multivariate principal components (PCs), the life cycle properties of the simulated MJOs are extracted, including the ability to represent how the MJO evolves from a given subphase and the associated decay time scales. On average, the MJO decay (e-folding) time scale for all models is shorter (∼20–29 days) than observations (∼31 days). All models are able to produce a leading pair of multivariate principal components that represents eastward propagation of intraseasonal wind and precipitation anomalies, although the fraction of the variance is smaller than observed for all models. In some cases, the dominant time scale of these PCs is outside of the 30–80-day band.

Several key variables associated with the model’s MJO are investigated, including the surface latent heat flux, boundary layer (925 hPa) moisture convergence, and the vertical structure of moisture. Low-level moisture convergence ahead (east) of convection is associated with eastward propagation in most of the models. A few models are also able to simulate the gradual moistening of the lower troposphere that precedes observed MJO convection, as well as the observed geographical difference in the vertical structure of moisture associated with the MJO. The dependence of rainfall on lower tropospheric relative humidity and the fraction of rainfall that is stratiform are also discussed, including implications these diagnostics have for MJO simulation. Based on having the most realistic intraseasonal multivariate empirical orthogonal functions, principal component power spectra, equatorial eastward propagating outgoing longwave radiation (OLR), latent heat flux, low-level moisture convergence signals, and vertical structure of moisture over the Eastern Hemisphere, the superparameterized Community Atmosphere Model (SPCAM) and the ECHAM4/Ocean Isopycnal Model (OPYC) show the best skill at representing the MJO.

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I.-S. Kang, K. Jin, K.-M. Lau, J. Shukla, V. Krishnamurthy, S. D. Schubert, D. E. Waliser, W. F. Stern, V. Satyan, A. Kitoh, G. A. Meehl, M. Kanamitsu, V. Ya. Galin, Akimasa Sumi, G. Wu, Y. Liu, and J.-K. Kim

Abstract

The atmospheric anomalies for the 1997/98 El Niño–Southern Oscillation (ENSO) period have been analyzed and intercompared using the data simulated by the atmospheric general circulation models (GCMs) of 11 groups participating in the Monsoon GCM Intercomparison Project initiated by the Climate Variability and Prediction Program (CLIVAR)/Asian–Australian Monsoon Panel. Each participating GCM group performed a set of 10 ensemble simulations for 1 September 1996–31 August 1998 using the same sea surface temperature (SST) conditions but with different initial conditions. The present study presents an overview of the intercomparison project and the results of an intercomparison of the global atmospheric anomalies during the 1997/98 El Niño period. Particularly, the focus is on the tropical precipitation anomalies over the monsoon–ENSO region and the upper-tropospheric circulation anomalies in the Pacific–North American (PNA) region.

The simulated precipitation anomalies show that all of the models simulate the spatial pattern of the observed anomalies reasonably well in the tropical central Pacific, although there are large differences in the amplitudes. However, most of the models have difficulty in simulating the negative anomalies over the Maritime Continent during El Niño. The 200-hPa geopotential anomalies over the PNA region are reasonably well reproduced by most of the models. But, the models generally underestimate the amplitude of the PNA pattern. These weak amplitudes are related to the weak precipitation anomalies in the tropical Pacific. The tropical precipitation anomalies are found to be closely related to the SST anomalies not only during the El Niño seasons but also during the normal seasons that are typified by weak SST anomalies in the tropical Pacific. In particular, the pattern correlation values of the 11-model composite of the precipitation anomalies with the observed counterparts for the normal seasons are near 0.5 for the tropical region between 30°S and 30°N.

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