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Lin Chen, Yongqiang Yu, and De-Zheng Sun

Abstract

Previous evaluations of model simulations of the cloud and water vapor feedbacks in response to El Niño warming have singled out two common biases in models from phase 3 of the Coupled Model Intercomparison Project (CMIP3): an underestimate of the negative feedback from the shortwave cloud radiative forcing (SWCRF) and an overestimate of the positive feedback from the greenhouse effect of water vapor. Here, the authors check whether these two biases are alleviated in the CMIP5 models. While encouraging improvements are found, particularly in the simulation of the negative SWCRF feedback, the biases in the simulation of these two feedbacks remain prevalent and significant. It is shown that bias in the SWCRF feedback correlates well with biases in the corresponding feedbacks from precipitation, large-scale circulation, and longwave radiative forcing of clouds (LWCRF). By dividing CMIP5 models into two categories—high score models (HSM) and low score models (LSM)—based on their individual skills of simulating the SWCRF feedback, the authors further find that ocean–atmosphere coupling generally lowers the score of the simulated feedbacks of water vapor and clouds but that the LSM is more affected by the coupling than the HSM. They also find that the SWCRF feedback is simulated better in the models that have a more realistic zonal extent of the equatorial cold tongue, suggesting that the continuing existence of an excessive cold tongue is a key factor behind the persistence of the feedback biases in models.

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Lijuan Hua, Yongqiang Yu, and De-Zheng Sun

Abstract

The potential role that rectification of ENSO plays as a viable mechanism to generate climate anomalies on the decadal and longer time scales demands a thorough study of this process. In this paper, rectification of ENSO was studied using an ocean GCM that has a realistic seasonal cycle. In addition to conducting a pair of forced ocean GCM experiments with and without ENSO fluctuations, as done in a previous study, a forced experiment was also conducted with the sign of wind anomalies reversed, with the goal of clarifying the role of the asymmetry in the wind forcing and more generally to better understand the nonlinear dynamics responsible for the rectification. It is found that the rectification effect of ENSO is to cool the western Pacific warm pool and warm the eastern equatorial Pacific. Further, it is found that when the sign of the wind stress anomalies is reversed the impact of the rectification on the mean state remains almost unchanged. This lack of change is further explained by noting that the upper-ocean temperature and velocity anomalies (T′, u′, υ′, and w′) are found to respond to the wind stress anomalies linearly, except for the strongest El Niño years. Thus, the correlation between T′ and (u′, υ′, w′) [and thus the nonlinear dynamical heating (NDH)] remains the same when the sign of the wind stress anomalies is reversed. Indeed, the spatial patterns of NDH in all four seasons are found to resemble the rectified effect of ENSO in the mean temperature field in the respective seasons, indicating the critical role of NDH in the rectification.

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De-Zheng Sun, Yongqiang Yu, and Tao Zhang

Abstract

By comparing the response of clouds and water vapor to ENSO forcing in nature with that in Atmospheric Model Intercomparison Project (AMIP) simulations by some leading climate models, an earlier evaluation of tropical cloud and water vapor feedbacks has revealed the following two common biases in the models: 1) an underestimate of the strength of the negative cloud albedo feedback and 2) an overestimate of the positive feedback from the greenhouse effect of water vapor. Extending the same analysis to the fully coupled simulations of these models as well as other Intergovernmental Panel on Climate Change (IPCC) coupled models, it is found that these two biases persist. Relative to the earlier estimates from AMIP simulations, the overestimate of the positive feedback from water vapor is alleviated somewhat for most of the coupled simulations. Improvements in the simulation of the cloud albedo feedback are only found in the models whose AMIP runs suggest either a positive or nearly positive cloud albedo feedback. The strength of the negative cloud albedo feedback in all other models is found to be substantially weaker than that estimated from the corresponding AMIP simulations. Consequently, although additional models are found to have a cloud albedo feedback in their AMIP simulations that is as strong as in the observations, all coupled simulations analyzed in this study have a weaker negative feedback from the cloud albedo and therefore a weaker negative feedback from the net surface heating than that indicated in observations. The weakening in the cloud albedo feedback is apparently linked to a reduced response of deep convection over the equatorial Pacific, which is in turn linked to the excessive cold tongue in the mean climate of these models. The results highlight that the feedbacks of water vapor and clouds—the cloud albedo feedback in particular—may depend on the mean intensity of the hydrological cycle. Whether the intermodel variations in the feedback from cloud albedo (water vapor) in the ENSO variability are correlated with the intermodel variations of the feedback from cloud albedo (water vapor) in global warming has also been examined. While a weak positive correlation between the intermodel variations in the feedback of water vapor during ENSO and the intermodel variations in the water vapor feedback during global warming was found, there is no significant correlation found between the intermodel variations in the cloud albedo feedback during ENSO and the intermodel variations in the cloud albedo feedback during global warming. The results suggest that the two common biases revealed in the simulated ENSO variability may not necessarily be carried over to the simulated global warming. These biases, however, highlight the continuing difficulty that models have in simulating accurately the feedbacks of water vapor and clouds on a time scale of the observations available.

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De-Zheng Sun, Tao Zhang, Yan Sun, and Yongqiang Yu

Abstract

To better understand the causes of climate change in the tropical Pacific on the decadal and longer time scales, the rectification effect of ENSO events is delineated by contrasting the time-mean state of two forced ocean GCM experiments. In one of them, the long-term mean surface wind stress of 1950–2011 is applied, while in the other, the surface wind stress used is the long-term mean surface wind stress of 1950–2011 plus the interannual monthly anomalies over the period. Thus, the long-term means of the surface wind stress in the two runs are identical. The two experiments also use the same relaxation boundary conditions, that is, the SST is restored to the same prescribed values. The two runs, however, are found to yield significantly different mean climate for the tropical Pacific. The mean state of the run with interannual fluctuations in the surface winds is found to have a cooler warm pool, warmer thermocline water, and warmer eastern surface Pacific than the run without interannual fluctuations in the surface winds. The warming of the eastern Pacific has a pattern that resembles the observed decadal warming. In particular, the pattern features an off-equator maximum as the observed decadal warming. The spatial pattern of the time-mean upper-ocean temperature differences between the two experiments is shown to resemble that of the differences in the nonlinear dynamic heating, underscoring the role of the nonlinear ocean dynamics in the rectification. The study strengthens the suggestion that rectification of ENSO can be a viable mechanism for climate change of decadal and longer time scales.

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Tingting Qian, Junhong Wei, Yongqiang Sun, Yinghui Lu, and James H. Ruppert Jr.

Abstract

This paper investigates the limitation in calculating the vertical wavelength of downward phase propagating gravity waves from the vertical fluctuation of idealized radiosonde balloons in a homogeneous background environment. The wave signals are artificially observed by an idealized weather balloon with a constant ascent rate. The apparent vertical wavelengths obtained from the moving radiosonde balloon are compared to the true vertical wavelength obtained from the dispersion relation, both in the no-wind case and in the constant zonal flow case. The node method and FFT method are employed to calculate the apparent vertical wavelength from the sounding profile. The difference between the node apparent vertical wavelength and the true vertical wavelength is attributed to the fact that the ascent rate of the balloon and the downward phase speed induce a strong Doppler-shifting bias on the apparent vertical wavelength from the observation records. The difference between the FFT apparent vertical wavelength and the true vertical wavelength includes both the Doppler-shifting bias and the mathematical bias. The extent to which the apparent vertical wavelength is reliable is discussed. The Coriolis parameter has negligible effects on the comparison between the true vertical wavelength and the apparent one.

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Yongqiang Zhang, Ray Leuning, Francis H. S. Chiew, Enli Wang, Lu Zhang, Changming Liu, Fubao Sun, Murray C. Peel, Yanjun Shen, and Martin Jung

Abstract

Satellite and gridded meteorological data can be used to estimate evaporation (E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in “wet” regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation; 2) , a Budyko-style hydrometeorological model; and 3) , the Penman–Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation and gridded meteorological fields and it is concluded that these data are, as yet, not sufficiently accurate to explain trends in E for wet regions. This provides a significant challenge for satellite-based energy-balance methods. Trends in for 87 “dry” catchments are strongly correlated to trends in precipitation (R 2 = 0.85). These trends were best captured by , which explicitly includes precipitation and available energy as model inputs.

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Baoqiang Xiang, Lucas Harris, Thomas L. Delworth, Bin Wang, Guosen Chen, Jan-Huey Chen, Spencer K. Clark, William F. Cooke, Kun Gao, J. Jacob Huff, Liwei Jia, Nathaniel C. Johnson, Sarah B. Kapnick, Feiyu Lu, Colleen McHugh, Yongqiang Sun, Mingjing Tong, Xiaosong Yang, Fanrong Zeng, Ming Zhao, Linjiong Zhou, and Xiaqiong Zhou

Abstract

A subseasonal-to-seasonal (S2S) prediction system was recently developed using the GFDL Seamless System for Prediction and Earth System Research (SPEAR) global coupled model. Based on 20-yr hindcast results (2000–19), the boreal wintertime (November–April) Madden–Julian oscillation (MJO) prediction skill is revealed to reach 30 days measured before the anomaly correlation coefficient of the real-time multivariate (RMM) index drops to 0.5. However, when the MJO is partitioned into four distinct propagation patterns, the prediction range extends to 38, 31, and 31 days for the fast-propagating, slow-propagating, and jumping MJO patterns, respectively, but falls to 23 days for the standing MJO. A further improvement of MJO prediction requires attention to the standing MJO given its large gap with its potential predictability (38 days). The slow-propagating MJO detours southward when traversing the Maritime Continent (MC), and confronts the MC prediction barrier in the model, while the fast-propagating MJO moves across the central MC without this prediction barrier. The MJO diversity is modulated by stratospheric quasi-biennial oscillation (QBO): the standing (slow-propagating) MJO coincides with significant westerly (easterly) phases of QBO, partially explaining the contrasting MJO prediction skill between these two QBO phases. The SPEAR model shows its capability, beyond the propagation, in predicting their initiation for different types of MJO along with discrete precursory convection anomalies. The SPEAR model skillfully predicts the observed distinct teleconnections over the North Pacific and North America related to the standing, jumping, and fast-propagating MJO, but not the slow-propagating MJO. These findings highlight the complexities and challenges of incorporating MJO prediction into the operational prediction of meteorological variables.

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