Quanan Zheng

Bio: Quanan Zheng is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Sea surface temperature & Internal wave. The author has an hindex of 34, co-authored 163 publications receiving 20319 citations. Previous affiliations of Quanan Zheng include National Science Foundation & University of Delaware.

A study of radar backscattering from water surface in response to rainfall

Abstract: In this paper, radar backscattering from a water surface in response to rainfall was studied. The paper consists of two parts. First, the spatial characteristics of raindrops in rain fields were analyzed based on published data and the response of a water surface to rainfall was experimentally studied in the laboratory. Rain-generated surface features including stalks, crowns, ring waves, and secondary drops were measured. It was found that stalks and crowns are dominant in terms of their height and energy. Second, the radar signatures of a rainfall event simultaneously observed by C band ENVISAT (European satellite), ASAR (Advanced Synthetic Aperture Radar), and ground-based weather radar in the Northwest Pacific were investigated. The relationship between the radar return intensity extracted from the C band ASAR image and the reflectivity factor (rain rate) obtained from ground-based weather radar was analyzed. For light/moderate rain (with low reflectivity factors), the radar backscattering intensity increases as the reflectivity factor increases. For heavy rain (with high reflectivity factors), the radar backscattering intensity decreases as the reflectivity factor increases. The maximum radar backscattering intensity occurs at a reflectivity factor of 45 dBZ (with rain rate of 24 mm/h). It was found that the spaceborne radar backscattering intensity strongly correlates with the average distance between the stalks on the water surface in the rain field in a nonlinear manner. The physics of the radar signatures of the rain event are explored.

Variability of Kuroshio Surface Axis Northeast of Taiwan Island Derived from Satellite Altimeter Data

Abstract: The spatial and temporal variability of the Kuroshio surface axis northeast of Taiwan Island is investigated using 24 years of surface geostrophic currents derived from satellite altimeter data from 1993 to 2016. The Kuroshio surface axis is derived by an extraction method with three selected parameters, including the length of the subsidiary line, the intervals between two adjacent points, and the distance between the two adjacent subsidiary lines. The empirical mode decomposition analysis on the 24-year Kuroshio axes reveals that the mean periods of intra-seasonal and inter-annual variability, which are the two dominant components, are about 3.2 months and 1.3 years, respectively. The self-organizing map analysis reveals that the variation of Kuroshio axis northeast of Taiwan Island has four best matching unit (BMU) patterns: straight-path (BMUS), meandering-path (BMUM) and two transition stages (BMUT1 and BMUT2). The straight-path pattern shows strong seasonality: more likely occurring in summer. The meandering-path pattern is less frequent than straight-path pattern. During a typical period from November 26, 2012 to January 27, 2013, which is chosen as an independent example, the analysis on the satellite altimeter and sea surface temperature data shows that the patterns of the Kuroshio axis change successively in order of BMUT1→BMUM→BMUT2→BMUS, i.e., the Kuroshio axis migrates from the meandering-path to the straight-path pattern. During the typical period the warm water intrusion and a mesoscale eddy occur at the second stage corresponding to BMUM and migrate northwestward gradually at the last two stages corresponding to BMUT2 and BMUS. The transient order appears only during this typical period but it is not common for the whole study period. The monthly mean relatively vorticity is calculated and analyzed to evaluate the impact of the eddies on the Kuroshio surface axis variability, the results show that the anticyclonic (cyclonic) eddies can promote the Kuroshio surface axis to present the meandering-path (straight-path) pattern because of the potential vorticity conservation. The impacts of the anticyclonic eddies and the cyclonic eddies on the variability of the Kuroshio surface axis are opposite. The long-term day-to-day detection contributes to improving understanding the variability of Kuroshio surface axis northeast of Taiwan Island.

Interannual variability of cold domes northeast of Taiwan

Abstract: Multi-sensor data from different satellites were analysed to study the interannual variability of the cold domes northeast of Taiwan. From the empirical orthogonal function analysis of along-track ...

The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis

Abstract: A new method for analysing nonlinear and non-stationary data has been developed. The key part of the method is the empirical mode decomposition method with which any complicated data set can be dec...

Ensemble empirical mode decomposition: a noise-assisted data analysis method

Abstract: A new Ensemble Empirical Mode Decomposition (EEMD) is presented. This new approach consists of sifting an ensemble of white noise-added signal (data) and treats the mean as the final true result. Finite, not infinitesimal, amplitude white noise is necessary to force the ensemble to exhaust all possible solutions in the sifting process, thus making the different scale signals to collate in the proper intrinsic mode functions (IMF) dictated by the dyadic filter banks. As EEMD is a time–space analysis method, the added white noise is averaged out with sufficient number of trials; the only persistent part that survives the averaging process is the component of the signal (original data), which is then treated as the true and more physical meaningful answer. The effect of the added white noise is to provide a uniform reference frame in the time–frequency space; therefore, the added noise collates the portion of the signal of comparable scale in one IMF. With this ensemble mean, one can separate scales naturall...

Variational Mode Decomposition

Abstract: During the late 1990s, Huang introduced the algorithm called Empirical Mode Decomposition, which is widely used today to recursively decompose a signal into different modes of unknown but separate spectral bands. EMD is known for limitations like sensitivity to noise and sampling. These limitations could only partially be addressed by more mathematical attempts to this decomposition problem, like synchrosqueezing, empirical wavelets or recursive variational decomposition. Here, we propose an entirely non-recursive variational mode decomposition model, where the modes are extracted concurrently. The model looks for an ensemble of modes and their respective center frequencies, such that the modes collectively reproduce the input signal, while each being smooth after demodulation into baseband. In Fourier domain, this corresponds to a narrow-band prior. We show important relations to Wiener filter denoising. Indeed, the proposed method is a generalization of the classic Wiener filter into multiple, adaptive bands. Our model provides a solution to the decomposition problem that is theoretically well founded and still easy to understand. The variational model is efficiently optimized using an alternating direction method of multipliers approach. Preliminary results show attractive performance with respect to existing mode decomposition models. In particular, our proposed model is much more robust to sampling and noise. Finally, we show promising practical decomposition results on a series of artificial and real data.

Accumulation and fragmentation of plastic debris in global environments.

Abstract: One of the most ubiquitous and long-lasting recent changes to the surface of our planet is the accumulation and fragmentation of plastics. Within just a few decades since mass production of plastic...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Abstract: Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...