Yupeng Liu

Dr. Yupeng Liu

South China Sea Institute of Oceanology, Chinese Academy of Sciences

Research Focus & Metrics

Academic Career Length

8Years (2019-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
4 August 2019 in Remote Sensing
Verified
Journal Article
Open access
PDF file
YLYupeng Liu
Yupeng Liu
DTDanling Tang
Danling Tang
EMEvgeny Aleksandrovich Morozov
Evgeny Aleksandrovich Morozov
The typhoon Wind-Pump induced upwelling and cold eddy often promote the significant growth of phytoplankton after the typhoon. However, the importance of eddy-pumping and wind-driven upwelling on the sea surface chlorophyll a concentration (Chl-a) during the typhoon are still not clearly distinguished. In addition, the air–sea heat flux exchange is closely related to the upper ocean processes, but few studies have discussed its role in the sea surface Chl-a variations under typhoon conditions. Based on the cruise data, remote sensing data, and model data, this paper analyzes the contribution of the vertical motion caused by the eddy-pumping upwelling and Ekman pumping upwelling on the surface Chl-a, and quantitatively analyzes the influence of air–sea heat exchange on the surface Chl-a after the typhoon Linfa over the northeastern South China Sea (NSCS) in 2009. The results reveal the Wind Pump impacts on upper ocean processes: (1) The euphotic layer-integrated Chl-a increased after the typhoon, and the increasing of the surface Chl-a was not only the uplift of the deeper waters with high Chl-a but also the growth of the phytoplankton; (2) The Net Heat Flux (air–sea heat exchange) played a major role in controlling the upper ocean physical processes through cooling the SST and indirectly increased the surface Chl-a until two weeks after the typhoon; (3) the typhoon-induced cyclonic eddy was the most important physical process in increasing the surface Chl-a rather than the Ekman pumping and wind-stirring mixing after typhoon; (4) the spatial shift between the surface Chl-a blooms and the typhoon-induced cyclonic eddy could be due to the Ekman transport; (5) nutrients uplifting and adequate light were two major biochemical elements supplying for the growth of surface phytoplankton.

1 November 2020 in Science of The Total Environment
Verified
Journal Article
Open access
YLYupeng Liu
Yupeng Liu
DTDanling Tang
Danling Tang
STShilin Tang
Shilin Tang
EMEvgeny Aleksandrovich Morozov
Evgeny Aleksandrovich Morozov
WLWenzhao Liang
Wenzhao Liang
YSYi Sui
Yi Sui
New evidences provided that the tropical cyclone (TC) Linfa in 2015 induced looping path of Kuroshio invasion into the northeastern South China Sea (NESCS) through the northwestern Luzon Strait (LS), based on the in-situ measurements, satellite data and model output data. This TC-enhanced Kuroshio invasion with low nutrients and denser waters suppressed the TC "Wind Pump" induced upwelling and nutrients uptake, and therefore inhibited the Chlorophyll a concentration (Chl-a) increase from surface to ~50 m in the open ocean of the NESCS. The TC-induced Kuroshio invasion promoted the generation of the strong cyclonic eddy to its left side where weak Ekman Pumping Velocity was observed. This enhancing cyclonic eddy then dominated the nutrients uplift and increased the surface and subsurface (0-50 m) Chl-a through eddy pumping rather than Ekman Pumping. The TC-declined anti-cyclonic eddy, which shoaled the Mixed Layer Depth (MLD), benefited to the nutrient uptake through TC-induced upwelling and thereby increased the surface Chl-a and raised the Chl-a Maximum Layer (CML) to ~20 m over the southwestern LS. The temporal Chl-a variations were also influenced by TC intensities and biochemical processes. The air-sea heat budget analysis indicated that, the air-sea heat exchange contributed to nearly 80% of the sea surface cooling (SST cooling) over the northwestern LS with Kuroshio invasion, while eddy-induced upwelling dominated the SST cooling over the western LS, and the wind-driven upwelling (and mixing) controlled the SST cooling over the southwestern LS. These different formations of SST cooling then played important role in Chl-a variations. This study is the first case of TC "Wind Pump" induced Chl-a variations considering air-sea heat exchange, Kuroshio invasion and mesoscale eddies over LS, which would help to evaluate the influence of TCs over the other major heat transport arteries of the world ocean: The Gulf Stream area.

1 May 2023 in IEEE Transactions on Geoscience and Remote Sensing
Verified
Journal Article
Closed access
YHYuye Huang
Yuye Huang
HYHongqiang Yang
Hongqiang Yang
STShilin Tang
Shilin Tang
YLYongming Liu
Yongming Liu
YLYupeng Liu
Yupeng Liu
Bathymetric inversions constitute a key preliminary step when characterizing coral topography. The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) is poised to provide true values for satellite-derived bathymetry (SDB) in the absence of measured data. Nevertheless, the influences of the different available algorithms and atmospheric correction (AC) processes applied to construct SDB over coral reef waters are still poorly understood. In this research, three empirical-based bathymetric algorithms (the linear ratio model (LRM), polynomial ratio model (PRM), and exponential ratio model (ERM)) and three ACs (ACOLITE, SeaDAS, and Sen2Cor) are evaluated with Sentinel-2A/B multispectral imagery to achieve fine-spatial-resolution bathymetric information. The bathymetry estimates produced by fusing the Sentinel-2A/B and ICESat-2 datasets using the three models exhibit sufficient accuracies, with low percent errors and mean absolute errors (MAEs) between 0.44 and 0.74 m and root mean square errors (RMSEs) between 0.61 and 0.96 m. In all cases, the PRM outperforms the ERM and LRM. The AC method comparisons show that the performance of ACOLITE is better than those of Sen2Cor and SeaDAS. The obtained depth estimates are less sensitive to the impacts of the AC methods in relatively shallow waters than in relatively deep waters, and ACOLITE performs more stably. Overall, the PRM coupled with the ACOLITE method performs best. With depths extracted from ICESat-2, high-spatial-resolution SDB data capable of supporting the long-range goal of coral topography analyses are attainable even without in situ datasets.

18 December 2020 in Sensors
Verified
Journal Article
Open access
PDF file
XLXiangyu Li
Xiangyu Li
Yangong ZhengYangong Zheng
Yangong Zheng
XKXiangyan KONG
Xiangyan KONG
YLYupeng Liu
Yupeng Liu
DTDanling Tang
Danling Tang
High-precision microelectromechanical system (MEMS) accelerometers have wide application in the military and civil fields. The closed-loop microaccelerometer interface circuit with switched capacitor topology has a high signal-to-noise ratio, wide bandwidth, good linearity, and easy implementation in complementary metal oxide semiconductor (CMOS) process. Aiming at the urgent need for high-precision MEMS accelerometers in geophones, we carried out relevant research on high-performance closed-loop application specific integrated circuit (ASIC) chips. According to the characteristics of the performance parameters and output signal of MEMS accelerometers used in geophones, a high-precision closed-loop interface ASIC chip based on electrostatic time-multiplexing feedback technology and proportion integration differentiation (PID) feedback control technology was designed and implemented. The interface circuit consisted of a low-noise charge-sensitive amplifier (CSA), a sampling and holding circuit, and a PID feedback circuit. We analyzed and optimized the noise characteristics of the interface circuit and used a capacitance compensation array method to eliminate misalignment of the sensitive element. The correlated double sampling (CDS) technology was used to eliminate low-frequency noise and offset of the interface circuit. The layout design and engineering batch chip were fabricated by a standard 0.35 μm CMOS process. The active area of the chip was 3.2 mm × 3 mm. We tested the performance of the accelerometer system with the following conditions: power dissipation of 7.7 mW with a 5 V power supply and noise density less than 0.5 μg/Hz1/2. The accelerometers had a sensitivity of 1.2 V/g and an input range of ±1.2 g. The nonlinearity was 0.15%, and the bias instability was about 50 μg.

23 October 2020 in Water
Verified
Journal Article
Open access
PDF file
HXHuabing Xu
Huabing Xu
RYRongzhen Yu
Rongzhen Yu
DTDanling Tang
Danling Tang
YLYupeng Liu
Yupeng Liu
SWSufen Wang
Sufen Wang
DFDongyang Fu
Dongyang Fu
This paper uses the Argo sea surface salinity (SSSArgo) before and after the passage of 25 tropical cyclones (TCs) in the Bay of Bengal from 2015 to 2019 to evaluate the sea surface salinity (SSS) of the Soil Moisture Active Passive (SMAP) remote sensing satellite (SSSSMAP). First, SSSArgo data were used to evaluate the accuracy of the 8-day SMAP SSS data, and the correlations and biases between SSSSMAP and SSSArgo were calculated. The results show good correlations between SSSSMAP and SSSArgo before and after TCs (before: SSSSMAP = 1.09SSSArgo−3.08 (R2 = 0.69); after: SSSSMAP = 1.11SSSArgo−3.61 (R2 = 0.65)). A stronger negative bias (−0.23) and larger root-mean-square error (RMSE, 0.95) between the SSSSMAP and SSSArgo were observed before the passage of 25 TCs, which were compared to the bias (−0.13) and RMSE (0.75) after the passage of 25 TCs. Then, two specific TCs were selected from 25 TCs to analyze the impact of TCs on the SSS. The results show the significant SSS increase up to the maximum 5.92 psu after TC Kyant (2016), which was mainly owing to vertical mixing and strong Ekman pumping caused by TC and high-salinity waters in the deep layer that were transported to the sea surface. The SSSSMAP agreed well with SSSArgo in both coastal and offshore waters before and after TC Roanu (2016) and TC Kyant (2016) in the Bay of Bengal.

7 February 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
BLBo Li
Bo Li
Junmin LiJunmin Li
Junmin Li
JLJunliang Liu
Junliang Liu
STShilin Tang
Shilin Tang
武陈武阳 陈
武阳 陈
YLYupeng Liu
Yupeng Liu
The wave data measured by CFOSAT (China France Oceanography Satellite) have been validated mainly based on numerical model outputs and altimetry products on a global scale. It is still necessary to further calibrate the data for specific regions, e.g., the southern South China Sea. This study analyses the practicability of calibrating the dominant wavelength by using artificial neural networks and mean impact value analysis based on two sets of buoy data with a 2-year observation period and contemporaneous ERA5 reanalysis data. The artificial neural network modeling experiments are repeated 1000 times randomly by Monte Carlo methods to avoid sampling uncertainty. Both experimental results based on the random sampling method and chronological sampling method are performed. Independent buoy observations are used to validate the calibration model. The results show that although there are obvious differences between the CFOSAT wavelength data and the field observations, the parameters observed by the satellite itself can effectively calibrate the data. In addition to the wavelength, nadir significant wave height, nadir wind speed, and the distance between the calibration point and satellite observation point are the most important parameters for the calibration. Accurate data from other sources, such as ERA5, would be helpful to further improve the calibration results. The variable contributing the most to the calibration effect is the mean wave period, which virtually provides relatively accurate wavelength information for the calibration network. These results verify the possibility of synchronous self-calibration for the CFOSAT wavelength data and provide a reference for the further calibration of the satellite products in other regions.