State Key Laboratory of Satellite Ocean Environment Dynamics

Hangzhou, China

State Key Laboratory of Satellite Ocean Environment Dynamics

Hangzhou, China
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Wang G.,State Key Laboratory of Satellite Ocean Environment Dynamics | Wang C.,National Oceanic and Atmospheric Administration | Huang R.X.,Woods Hole Oceanographic Institution
Journal of Climate | Year: 2010

Based on the Simple Ocean Data Assimilation (SODA) dataset and three types of Sverdrup stream function, an interdecadal variability of the eastward current in the middle South China Sea (SCS) during summer is identified. Both the pattern and strength of the summer Asian monsoon wind stress curl over the SCS contribute to the interdecadal variability of this current. From 1960 to 1979, the monsoon intensified and the zero wind stress curl line shifted southward. Both the core of positive wind stress curl in the northern SCS and the negative curl in the southern SCS moved southward and thus induced a southward shift of both the southern anticyclonic and northern cyclonic gyres, resulting in a southward displacement of the eastward current associated with these two gyres. In the meantime, the southern (northern) SCS anticyclonic (cyclonic) ocean gyre weakened (strengthened) and therefore also induced the southward shift of the eastward current near the intergyre boundary. In contrast, the eastward current shifted northward from 1980 to 1998 because the monsoon relaxed and the zero wind stress curl line shifted northward. After 1998, the eastward jet moved southward again as the zero wind stress curl line shifted southward and the SCS monsoon strengthened. The eastward current identified from the baroclinic streamfunction moved about 1.7° more southward than that from the barotropic streamfunction, indicating that the meridional position of the eastward current is depth dependent. © 2010 American Meteorological Society.


Wu Q.,State Key Laboratory of Satellite Ocean Environment Dynamics | Ruan Z.,Xiamen University
Quarterly Journal of the Royal Meteorological Society | Year: 2016

Diurnal variations of the areas and temperatures in tropical cyclone convective cloud systems in the western North Pacific were estimated using pixel-resolution infrared (IR) brightness temperature (BT) and best-track data for 2000-2013. The mean areal extent of very cold cloud cover (IR BTs < 208 K) reached a maximum in the early morning (0000-0300 local solar time (LST)), then decreased after sunrise. This was followed by increasing cloud cover between 208 and 240 K, reaching its maximum areal extent in the afternoon (1500-1800 LST). The time at which cloud cover reached a maximum was sensitive to the temperature thresholds used over the ocean. IR BTs < 240 K reached minima in the morning (0300-0600 LST), and IR BTs > 240 K reached minima in the afternoon (1500-1800 LST). The out-of-phase relationships between IR BTs < 240 K and IR BTs > 240 K, and between the maximum coverage times of IR BTs < 208 K and 208 K < IR BTs < 240 K, can both lead to the radius-averaged IR temperature having two minima per day. The different diurnal evolutions under different cloud conditions suggest tropical cyclone convective cloud systems are best described in terms of both areal extent and cloud-top temperature. Maximum occurrence of clouds with IR BTs < 208 K in the morning and maximum occurrence of clouds with 208 K < IR BTs < 240 K in the afternoon suggest that two different mechanisms might be involved in causing diurnal variations under these two types of tropical cyclone cloud conditions. © 2016 Royal Meteorological Society.


Tang Y.,State Key Laboratory of Satellite Ocean Environment Dynamics | Tang Y.,University of Northern British Columbia | Chen D.,State Key Laboratory of Satellite Ocean Environment Dynamics | Yan X.,University of Northern British Columbia | Yan X.,George Mason University
Journal of Climate | Year: 2014

In this study, the potential predictability of the North American (NA) surface air temperature was explored using information-based predictability framework and Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) multiple model ensembles. Emphasis was put on the comparison of predictability measured by information-based metrics and by the conventional signal-to-noise ratio (SNR)-based metrics. Furthermore, the potential predictability was optimally decomposed into different modes by maximizing the predictable information (equivalent to the maximum of SNR), from which the most predictable structure was extracted and analyzed. It was found that the conventional SNR-based metrics underestimate the potential predictability, in particular in these areas where the predictable signals are relatively weak. The most predictable components of the NA surface air temperature can be characterized by the interannual variability mode and the long-term trend mode. The former is inherent to tropical Pacific sea surface temperature (SST) forcing such as El Niño-Southern Oscillation (ENSO), whereas the latter is closely associated with the global warming. The amplitude of the two modes has geographical variations in different seasons. On this basis, the possible physical mechanisms responsible for the predictable mode of interannual variability and its potential benefits to the improvement of seasonal climate prediction were discussed. © 2014 American Meteorological Society.


Cheng Y.,University of Northern British Columbia | Cheng Y.,National Climate Center | Tang Y.,University of Northern British Columbia | Chen D.,Lamont Doherty Earth Observatory | Chen D.,State Key Laboratory of Satellite Ocean Environment Dynamics
Journal of Geophysical Research: Oceans | Year: 2011

Ensemble predictions are performed using the LDEO5 model for the period from 1856 to 2003 based on a well developed El Nio-Southern Oscillation (ENSO) ensemble system. Information-based and ensemble-based potential predictability measures of ENSO are explored using ensemble predictions and the recently developed framework of predictability. Relationships of these potential predictability measures and actual predictability measures are investigated on multiple time scales from interannual to decadal. Results show that among three information-based potential predictability measures, relative entropy (RE) is better than predictive information (PI) and predictive power (PP) in quantifying correlation-based prediction skill, whereas PI and PP are better indicators in estimating mean square error (MSE)-based prediction skill. The primary reason for these relationships is analyzed and the control factors of the potential predictability measures are identified. It is found that RE is dominated by the signal component, but the dispersion component has a comparable contribution during weak ENSO periods. Copyright 2011 by the American Geophysical Union.


Song D.,Key Laboratory of Physical Oceanography | Song D.,University of New South Wales | Wang X.H.,University of New South Wales | Wang X.H.,State Key Laboratory of Satellite Ocean Environment Dynamics
Journal of Geophysical Research: Oceans | Year: 2013

A three-dimensional wave-current-sediment coupled numerical model with wetting and drying process is developed to understand hydrodynamics and sediment transport dynamics in the Deepwater Navigation Channel (DNC), the North Passage of the Yangtze River Estuary (YRE), China. The model results are in good agreement with observed data, and statistics show good model skill scores and correlation coefficients. The model well reproduces the spring-neap variation between a well-mixed estuary and a highly stratified estuary. Model results indicate that the estuarine gravitational circulation plays the most important role in the estuarine turbidity maximum (ETM) formation in the DNC. The upstream nonlocal sediment intrusion through the spillover mechanism is a major source of sediment trapping in the North Passage after the morphological changes. Numerical studies are conducted to show scenarios in the YRE under the effects of different forcings (river discharges, waves, and winds). Between these study cases, surface-wave-breaking relieves the sediment trapping and bottom-wave-current-interaction aggravates the bed erosion and elevates the SSC in the ETM; the former and the latter have the least and largest influence on the suspended sediment transport in the DNC. The wind effects have a greater influence on sediment trapping than the river discharges, and the steady northwesterly wind condition favors the siltation in the DNC most. The significance of density-driven turbidity current is also assessed, which can enhance the saline-water intrusion and suppress the turbulent mixing in the bottom boundary layer. © 2013. American Geophysical Union. All Rights Reserved.


Zhou L.,Lamont Doherty Earth Observatory | Zhou L.,State Key Laboratory of Satellite Ocean Environment Dynamics | Sobel A.H.,Lamont Doherty Earth Observatory | Sobel A.H.,University of Applied and Environmental Sciences | Murtugudde R.,University of Maryland College Park
Journal of Climate | Year: 2012

Akinetic energy budget for the Madden-Julian oscillation (MJO) is established in a three-scale framework. The three scales are the zonal mean, the MJO scale with wavenumbers 1-4, and the small scale with wavenumbers larger than 4. In the composite budget, the dominant balance at the MJOscale is between conversion from potential energy and work done by the pressure gradient force (PGF). This balance is consistent with the view that the MJO wind perturbations can be viewed as a quasi-linear response to a slowly varying heat source. A large residual in the upper troposphere suggests that much kinetic energy dissipates there by cumulus friction. Kinetic energy exchange between different scales is not a large component of the composite budget. There is a transfer of kinetic energy from the MJO scale to the small scale; that is, this multiscale interaction appears to damp rather than strengthen the MJO. There is some variation in the relative importance of different terms from one event to the next. In particular, conversion from mean kinetic energy can be important in some events. In a few other events, the influence from the extratropics is pronounced. © 2012 American Meteorological Society.


Cheng Y.,University of Northern British Columbia | Tang Y.,University of Northern British Columbia | Jackson P.,University of Northern British Columbia | Chen D.,Lamont Doherty Earth Observatory | And 2 more authors.
Journal of Climate | Year: 2010

El Niño-Southern Oscillation (ENSO) retrospective ensemble-based probabilistic predictions were performed for the period of 1856-2003 using the Lamont-Doherty Earth Observatory, version 5 (LDEO5), model. To obtain more reliable and skillful ENSO probabilistic predictions, first, four ensemble construction strategies were investigated: (i) the optimal initial perturbation with singular vector of sea surface temperature anomaly (SSTA), (ii) the realistic high-frequency anomalous winds, (iii) the stochastic optimal pattern of anomalous winds, and (iv) a combination of the first and the third strategy. Second, verifications were conducted to examine the reliability and resolution of the probabilistic forecasts provided by the four methods. Results suggest that reliability of ENSO probabilistic forecast is more sensitive to the choice of ensemble construction strategy than the resolution, and a reliable and skillful ENSO probabilistic prediction system may not necessarily have the best deterministic prediction skills. Among these ensemble construction methods, the fourth strategy produces the most reliable and skillful ENSO probabilistic prediction, benefiting from the joint contributions of the stochastic optimal winds and the singular vector of SSTA. In particular, the stochastic optimal winds play an important role in improving the ENSO probabilistic predictability for the LDEO5 model. © 2010 American Meteorological Society.


Younas W.,University of Northern British Columbia | Tang Y.,University of Northern British Columbia | Tang Y.,State Key Laboratory of Satellite Ocean Environment Dynamics
Journal of Climate | Year: 2013

In this study, the predictability of the Pacific-North American (PNA) pattern is evaluated on time scales from days to months using state-of-the-art dynamical multiple-model ensembles including the Canadian Historical Forecast Project (HFP2) ensemble, the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) ensemble, and the Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES). Some interesting findings in this study include (i) multiple-model ensemble (MME) skill was better than most of the individual models; (ii) both actual prediction skill and potential predictability increased as the averaging time scale increased from days to months; (iii) there is no significant difference in actual skill between coupled and uncoupled models, in contrast with the potential predictability where coupled models performed better than uncoupled models; (iv) relative entropy (REA) is an effective measure in characterizing the potential predictability of individual prediction, whereas the mutual information (MI) is a reliable indicator of overall prediction skill; and (v) compared with conventional potential predictability measures of the signal-to-noise ratio, the MI-based measures characterized more potential predictability when the ensemble spread varied over initial conditions. Further analysis found that the signal component dominated the dispersion component in REA for PNA potential predictability from days to seasons. Also, the PNA predictability is highly related to the signal of the tropical sea surface temperature (SST), and SST-PNA correlation patterns resemble the typical ENSO structure, suggesting that ENSO is the main source of PNA seasonal predictability. The predictable component analysis (PrCA) of atmospheric variability further confirmed the above conclusion; that is, PNA is one of the most predictable patterns in the climate variability over the Northern Hemisphere, which originates mainly from the ENSO forcing. © 2013 American Meteorological Society.


Yan X.,University of Northern British Columbia | Tang Y.,University of Northern British Columbia | Tang Y.,State Key Laboratory of Satellite Ocean Environment Dynamics
Quarterly Journal of the Royal Meteorological Society | Year: 2013

In this study, the superiorities of the super-ensemble for seasonal climate predictions are investigated based on the 500 mb geopotential height (GPH500) hindcasts produced by four Canadian atmospheric seasonal climate prediction models. The investigations are carried out mainly in two aspects: (i) a comprehensive evaluation of predictions for each grid point over the global domain by deterministic, probabilistic and potential prediction skill measures; (ii) the empirical orthogonal function (EOF) and the Maximum Signal-to-Noise (MSN) EOF analyses in the Northern Hemisphere. It is found that improvements of the super-ensemble are mainly due to the increase of ensemble size in the mid-high latitudes and the offsets of model uncertainties in the tropical regions. Measures of temporal correlation coefficient (CORR), Brier skill score (BSS) and reliability (REL) are more affected by the ensemble size; whereas the relative root-mean-square error (RRMSE) and resolution (RES) are sensitive to the offsets of model uncertainties. The first EOF mode of ensemble mean is similar to the most predictable pattern derived by the MSN EOF method, but the latter has the temporal evolutions more associated with the oceanic boundary forcing. The super-ensemble shows advantages in both EOF and MSN EOF analyses. © 2012 Royal Meteorological Society.


Liang X.S.,Central University of Finance and Economics | Liang X.S.,State Key Laboratory of Satellite Ocean Environment Dynamics | Liang X.S.,National University of Defense Technology
Dynamics of Atmospheres and Oceans | Year: 2011

How uncertainties are generated in deterministic geophysical fluid flows is an important but mostly overlooked subject in the atmospheric and oceanic research. In this study, it is shown that the generating mechanisms include local entropy generation (LEG) and cumulant information transfer, both of which are explicitly expressed with the aid of a theorem established herein. To a system the former is intrinsic, representing the evolutionary trend of a marginal entropy and bringing connections between the two physical notions namely uncertainty and instability. The latter results from the interaction between different locations through dynamic event synchronization, and appears only in the course of state evolution. Although in practice it is a notoriously difficult task to estimate entropy and entropy-related quantities for atmospheric and oceanic systems, which are in general of large dimensionality, estimation of the LEG can be accurately fulfilled with ensembles of limited size. If, furthermore, the processes of a system under consideration are quasi-ergodic and quasi-stationary, its LEG actually can be fairly satisfactorily estimated even without appealing to ensemble predictions. These assertions are illustrated and verified in an application with two simulated quasi-geostrophic jet streams with compact chaotic attractors, one global over the whole domain and another highly localized. The LEG study provides an objective way of rapid assessment for predictions, which is important in the practical fields such as adaptive sampling and adaptive modeling. © 2011 Elsevier B.V.

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