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Jin Wu and Yi Wei

Abstract

An optical-electronic technique has been developed for simultaneous, remote measurements of the surface tension and wave attenuation over the water surface. The technique has been fully tested in a laboratory tank, and tried in the field. Sample results of measurements are presented to illustrate that the technique is an effective method for studying the surfactants on the air–sea interface.

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Wei Wu and Greg M. McFarquhar

Abstract

We welcome the opportunity to correct the misunderstandings and misinterpretations contained in Yano’s comment that led him to incorrectly state that Wu and McFarquhar misunderstood the maximum entropy (MaxEnt) principle. As correctly stated by Yano, the principle itself does not suffer from the problem of a lack of invariance. But, as restated in this reply and in Wu and McFarquhar, the commonly used Shannon–Gibbs entropy does suffer from a lack of invariance for coordinate transform when applied in continuous cases, and this problem is resolved by the use of the relative entropy. Further, it is restated that the Wu and McFarquhar derivation of the PSD form using MaxEnt is more general than the formulation by Yano and allows more constraints with any functional relations to be applied. The derivation of Yano is nothing new but the representation of PSDs in other variables.

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Wei Wu and Greg M. McFarquhar

Abstract

Knowledge of ice crystal particle size distributions (PSDs) is critical for parameterization schemes for atmospheric models and remote sensing retrieval schemes. Two-dimensional in situ images captured by cloud imaging probes are widely used to derive PSDs in term of maximum particle dimension (). In this study, different definitions of for nonspherical particles recorded by 2D probes are compared. It is shown that the derived PSDs can differ by up to a factor of 6 for μm and mm. The large differences for μm are caused by the strong dependence of sample volume on particle size, whereas differences for mm are caused by the small number of particles detected. Derived bulk properties can also vary depending on the definitions of because of discrepancies in the definition of used to characterize the PSDs and that used to describe the properties of individual ice crystals. For example, the mass-weighted mean diameter can vary by 2 times, the ice water content (IWC) by 3 times, and the mass-weighted terminal velocity by 6 times. Therefore, a consistent definition of should be used for all data and single-particle properties. As an invariant measure with respect to the orientation of particles in the imaging plane for 2D probes, the diameter of the smallest circle enclosing the particle () is recommended as the optimal definition of . If the 3D structure of a particle is observed, then the technique can be extended to determine the minimum enclosing sphere.

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Wei Gu, Qin Xu, and Rongsheng Wu

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A spectral model is developed to study the three-dimensional instability of nonlinear viscous symmetric circulations. Two-dimensional solutions of steady nonlinear viscous symmetric circulations are found to be unstable in three dimensions. Four types of unstable modes are identified. The type I mode is characterized by horizontally tilted bands, similar to the tilted primary mode obtained previously by other investigators. This mode may be viewed as a gradual emergence of the tilted primary mode in three dimensions. The remaining three modes are highly three-dimensional and emerge consecutively as the basic-state Richardson number decreases significantly below the critical value. Implications of these modes to the possible secondary instabilities of tilted primary nonlinear circulations are discussed.

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Wei Wu and Greg M. McFarquhar

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Several functional forms of cloud particle size distributions (PSDs) have been used in numerical modeling and remote sensing retrieval studies of clouds and precipitation, including exponential, gamma, lognormal, and Weibull distributions. However, there is no satisfying theoretical explanation as to why certain distribution forms preferentially occur instead of others. Intuitively, the analytical form of a PSD can be derived by directly solving the general dynamic equation, but no analytical solutions have been found yet. Instead of a process-level approach, the use of the principle of maximum entropy (MaxEnt) for determining the theoretical form of PSDs from the perspective of system is examined here. MaxEnt theory states that the probability density function with the largest information entropy among a group satisfying the given properties of the variable should be chosen. Here, the issue of variability under coordinate transformations that arises using the Gibbs–Shannon definition of entropy is identified, and the use of the concept of relative entropy to avoid these problems is discussed. Focusing on cloud physics, the four-parameter generalized gamma distribution is proposed as the analytical form of a PSD using the principle of maximum (relative) entropy with assumptions on power-law relations among state variables, scale invariance, and a further constraint on the expectation of one state variable (e.g., bulk water mass). The four-parameter generalized gamma distribution is very flexible to accommodate various type of constraints that could be assumed for cloud PSDs.

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Wei Wu, Zhiping Wen, Renguang Wu, and Tongmei Wang

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In the present study, monthly mean objectively analyzed air–sea fluxes (OAFlux) and NCEP–Department of Energy (DOE) reanalysis datasets are employed to investigate air–sea interaction over the subtropical North Pacific during the El Niño–Southern Oscillation (ENSO) transition phase. A coupled low-frequency mode is identified, for which surface net heat flux and atmospheric circulation changes are strongly coupled during the ENSO transition phase. This mode features anomalous cooling (warming) and low-level anomalous cyclonic (anticyclonic) circulation over the subtropical North Pacific. When this mode is prominent, the atmospheric circulation anomalies lead to SST cooling (warming) through surface heat flux anomalies associated with increases (decreases) in the sea–air temperature and humidity differences induced by anomalous cold (warm) advection. In turn, positive heat flux anomalies induce more surface heating, and the SST cooling (warming) causes less (more) deep convective heating. The anomalous surface heating and deep convective heating contribute significantly to anomalous circulation through the thermal adaptation mechanism (adaptation of atmospheric circulation to vertical differential heating). This positive feedback favors the maintenance of these anomalous winds over the subtropical North Pacific.

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Marvin A. Geller, Weixing Shen, Minghua Zhang, and Wei-Wu Tan

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One-dimensional calculations are carried out for the time evolution of the equatorial lower stratospheric mean zonal wind forced by time-varying equatorial Kelvin and mixed Rossby–gravity waves. If the time variation of the wave momentum forcing is given by a steady forcing plus a sinusoidal modulation, a tendency toward phase locking between the period of the wave forcing’s modulation and the period of the resulting mean wind oscillation is found in some cases, depending on the period and magnitude of the wave forcing as well as the phase difference between variations of the easterly and westerly momentum fluxes. Regime diagrams are shown to make these dependences clearer. If the wave forcings are irregularly modulated, the resulting time variation of the wind oscillation shows no resemblance to the imposed time variation of the wave forcing. These simple calculations are used to indicate that for nonlinear phenomena, such as the quasi-biennial oscillation (QBO), one cannot conclude that a lack of correlation between two data records means that these are physically unrelated. When the equatorial wave momentum fluxes are modulated according to the eastern Pacific sea surface temperatures, the simulated time variation of the QBO period sometimes (depending on the phase relation between the easterly and westerly time-varying fluxes) shows a great resemblance to the observations. This suggests that easterly and westerly momentum fluxes into the equatorial lower stratosphere are related to SST variations.

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Xinrong Wu, Wei Li, Guijun Han, Shaoqing Zhang, and Xidong Wang

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While fixed covariance localization can greatly increase the reliability of the background error covariance in filtering by suppressing the long-distance spurious correlations evaluated by a finite ensemble, it may degrade the assimilation quality in an ensemble Kalman filter (EnKF) as a result of restricted longwave information. Tuning an optimal cutoff distance is usually very expensive and time consuming, especially for a general circulation model (GCM). Here the authors present an approach to compensate the demerit in fixed localization. At each analysis step, after the standard EnKF is done, a multiple-scale analysis technique is used to extract longwave information from the observational residual (referred to the EnKF ensemble mean). Within a biased twin-experiment framework consisting of a global barotropical spectral model and an idealized observing system, the performance of the new method is examined. Compared to a standard EnKF, the hybrid method is superior when an overly small/large cutoff distance is used, and it has less dependence on cutoff distance. The new scheme is also able to improve short-term weather forecasts, especially when an overly large cutoff distance is used. Sensitivity studies show that caution should be taken when the new scheme is applied to a dense observing system with an overly small cutoff distance in filtering. In addition, the new scheme has a nearly equivalent computational cost to the standard EnKF; thus, it is particularly suitable for GCM applications.

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Qigang Wu, Jing Zhang, Xiangdong Zhang, and Wei Tao

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The Beaufort Sea high (BSH) plays an important role in forcing Arctic sea ice and the Beaufort Gyre. This study examines the variability and long-term trends of atmospheric circulation over the Chukchi and Beaufort Seas using the ECMWF Interim Re-Analysis (ERA-Interim) for the period 1979–2012. Because of the mobility of the BSH through the year, EOF analysis is applied to the sea level pressure (SLP) field in order to investigate the principal patterns of BSH variability. In each season, the three leading EOF modes explain nearly 90% of the total variance and reflect a strengthened or weakened BSH centered over the western Arctic Ocean (EOF1), a north–south dipole-like SLP anomaly (EOF2), and a west–east dipole-like SLP anomaly (EOF3), respectively. These three EOF modes offer distinct influences on local climate in each season and have different connections with the large-scale climate variability modes in winter. In particular, the second principal component (PC2) associated with EOF2 in the autumn exhibits a tendency toward high-index polarity significant at the 5% level, and is related to strongly reduced sea ice extent.

Further, the authors have detected significant anticyclonic trends among surface wind fields associated with a strengthened BSH during summer and autumn, but significant cyclonic trends associated with a weakened BSH during early midwinter, consistent with significant trends in SLP gradients between western Arctic Ocean and the adjoining landmass. Comparison with forced trends of surface winds from various simulations from the IPCC Fifth Assessement Report (AR5) indicates that summertime changes in atmospheric circulation cannot be explained by natural external forcing or lower boundary forcings and may instead be attributable to external anthropogenic forcing.

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Guijun Han, Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, and Wei Li

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Coupled data assimilation uses a coupled model consisting of multiple time-scale media to extract information from observations that are available in one or more media. Because of the instantaneous exchanges of information among the coupled media, coupled data assimilation is expected to produce self-consistent and physically balanced coupled state estimates and optimal initialization for coupled model predictions. It is also expected that applying coupling error covariance between two media into observational adjustments in these media can provide direct observational impacts crossing the media and thereby improve the assimilation quality. However, because of the different time scales of variability in different media, accurately evaluating the error covariance between two variables residing in different media is usually very difficult. Using an ensemble filter together with a simple coupled model consisting of a Lorenz atmosphere and a pycnocline ocean model, which characterizes the interaction of multiple time-scale media in the climate system, the impact of the accuracy of coupling error covariance on the quality of coupled data assimilation is studied. Results show that it requires a large ensemble size to improve the assimilation quality by applying coupling error covariance in an ensemble coupled data assimilation system, and the poorly estimated coupling error covariance may otherwise degrade the assimilation quality. It is also found that a fast-varying medium has more difficulty being improved using observations in slow-varying media by applying coupling error covariance because the linear regression from the observational increment in slow-varying media has difficulty representing the high-frequency information of the fast-varying medium.

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