Variations in the Ice Phenology and Water Level of Ayakekumu Lake, Tibetan Plateau, Derived from MODIS and Satellite Altimetry Data

2018 ◽  
Vol 46 (10) ◽  
pp. 1689-1699 ◽  
Author(s):  
Jun Chen ◽  
YongFeng Wang ◽  
LiGuo Cao ◽  
Jiajia Zheng
Keyword(s):  
Tibetan Plateau ◽  
Water Level ◽  
Satellite Altimetry ◽  
Altimetry Data ◽  
Satellite Altimetry Data ◽  
Ice Phenology

scholarly journals Long-Term Discharge Estimation for the Lower Mississippi River Using Satellite Altimetry and Remote Sensing Images

2020 ◽  
Vol 12 (17) ◽  
pp. 2693
Author(s):  
Daniel Scherer ◽  
Christian Schwatke ◽  
Denise Dettmering ◽  
Florian Seitz
Keyword(s):  
Remote Sensing ◽  
Water Level ◽  
Cross Sections ◽  
Mississippi River ◽  
Satellite Altimetry ◽  
Altimetry Data ◽  
Virtual Station ◽  
Lower Mississippi River ◽  
Satellite Altimetry Data

Despite increasing interest in monitoring the global water cycle, the availability of in situ gauging and discharge time series is decreasing. However, this lack of ground data can partly be compensated for by using remote sensing techniques to observe river stages and discharge. In this paper, a new approach for estimating discharge by combining water levels from multi-mission satellite altimetry and surface area extents from optical imagery with physical flow equations at a single cross-section is presented and tested at the Lower Mississippi River. The datasets are combined by fitting a hypsometric curve, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is derived from the differences between virtual station elevations, which are computed in a least square adjustment from the height differences of all multi-mission satellite altimetry data that are close in time. Using the virtual station elevations, satellite altimetry data from multiple virtual stations and missions are combined to one long-term water level time series. All required parameters are estimated purely based on remote sensing data, without using any ground data or calibration. The validation at three gauging stations of the Lower Mississippi River shows large deviations primarily caused by the below average width of the predefined cross-sections. At 13 additional cross-sections situated in wide, uniform, and straight river sections nearby the gauges the Normalized Root Mean Square Error (NRMSE) varies between 10.95% and 28.43%. The Nash-Sutcliffe Efficiency (NSE) for these targets is in a range from 0.658 to 0.946.

scholarly journals Relationships between pacific and atlantic ocean sea surface temperatures and water levels from satellite altimetry data in the Amazon rivers

RBRH ◽  
2018 ◽  
Vol 23 (0) ◽  
Author(s):  
Mylena Vieira Silva ◽  
Adrien Paris ◽  
Stéphane Calmant ◽  
Luiz Antonio Cândido ◽  
Joecila Santos da Silva
Keyword(s):  
Water Level ◽  
Satellite Altimetry ◽  
Amazon Basin ◽  
Strong Relationship ◽  
Water Levels ◽  
Sea Surface ◽  
Altimetry Data ◽  
Negro River ◽  
Hydrological Extremes ◽  
Satellite Altimetry Data

ABSTRACT The influence of SST (Sea Surface Temperature) of adjacent oceans on the variability of water levels in the Amazon basin was investigated by using radar altimetry from the ENVISAT and Jason-2 missions. Data from the in situ network was used to compare the correlations of water level and SST anomalies in the sub-basins of the Amazonas-Peru, Solimões, Negro and Madeira Rivers. The analysis was made on the monthly and annual scales between 2003 and 2015. The correlations with anomalies of levels from altimetry presented higher accuracy indices than those from the conventional network. In general, ATN and PAC are better correlated with the entire basin. During the flood months, most of the sub-basins presented negative associations with ATN. In the months of ebb, the response to the indexes varies according to the region. The satellite altimetry data permitted to reach regions non-monitored by the conventional network. We also analyzed the impacts of hydrological extremes in all these sub-regions in the last 13 years. In Western Amazon, the drought of 2010 stands out, associated with the warming of the Tropical Atlantic and the El Niño. In the Negro River, the water level anomalies were the lowest in the basin during the 2005 drought. In the Purus River, the effects of the 2010 drought that affected the entire Amazon, were higher in 2011 due to its strong relationship with the Atlântic and Pacific oceans. In general, hydrological extremes are stronger or highlighted when SST increases simultaneously in both oceans.

Eddy properties in the Pacific sector of the Southern Ocean from satellite altimetry data

2016 ◽  
Vol 35 (11) ◽  
pp. 28-34 ◽  
Author(s):  
Yongliang Duan ◽  
Hongwei Liu ◽  
Weidong Yu ◽  
Yijun Hou
Keyword(s):  
Southern Ocean ◽  
Satellite Altimetry ◽  
Altimetry Data ◽  
The Pacific ◽  
Satellite Altimetry Data

Kuroshio variations in the upstream region as seen by HF radar and satellite altimetry data

2008 ◽  
Vol 29 (21) ◽  
pp. 6417-6426 ◽  
Author(s):  
K. Ichikawa ◽  
R. Tokeshi ◽  
M. Kashima ◽  
K. Sato ◽  
T. Matsuoka ◽  
...  
Keyword(s):  
Satellite Altimetry ◽  
Hf Radar ◽  
Upstream Region ◽  
Altimetry Data ◽  
Satellite Altimetry Data

scholarly journals Evaluation of Marine Gravity Anomaly Calculation Accuracy by Multi-Source Satellite Altimetry Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Shanwei Liu ◽  
Yinlong Li ◽  
Qinting Sun ◽  
Jianhua Wan ◽  
Yue Jiao ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Gravity Anomaly ◽  
Mean Square Error ◽  
Spatial Resolution ◽  
Satellite Altimetry ◽  
Gravity Anomalies ◽  
Mean Square ◽  
Altimetry Data ◽  
Marine Gravity ◽  
Satellite Altimetry Data

The purpose of this paper is to analyze the influence of satellite altimetry data accuracy on the marine gravity anomaly accuracy. The data of 12 altimetry satellites in the research area (5°N–23°N, 105°E–118°E) were selected. These data were classified into three groups: A, B, and C, according to the track density, the accuracy of the altimetry satellites, and the differences of self-crossover. Group A contains CryoSat-2, group B includes Geosat, ERS-1, ERS-2, and Envisat, and group C comprises T/P, Jason-1/2/3, HY-2A, SARAL, and Sentinel-3A. In Experiment I, the 5′×5′ marine gravity anomalies were obtained based on the data of groups A, B, and C, respectively. Compared with the shipborne gravity data, the root mean square error (RMSE) of groups A, B, and C was 4.59 mGal, 4.61 mGal, and 4.51 mGal, respectively. The results show that high-precision satellite altimetry data can improve the calculation accuracy of gravity anomaly, and the single satellite CryoSat-2 enables achieving the same effect of multi-satellite joint processing. In Experiment II, the 2′×2′ marine gravity anomalies were acquired based on the data of groups A, A + B, and A + C, respectively. The root mean square error of the above three groups was, respectively, 4.29 mGal, 4.30 mGal, and 4.21 mGal, and the outcomes show that when the spatial resolution is satisfied, adding redundant low-precision altimetry data will add pressure to the calculation of marine gravity anomalies and will not improve the accuracy. An effective combination of multi-satellite data can improve the accuracy and spatial resolution of the marine gravity anomaly inversion.

scholarly journals Estimating bathymetry from multi-mission satellite altimetry data using Gravity-Geologic Method over Malaysian Seas

2021 ◽  
Vol 32 (5.2) ◽  
Author(s):  
Astina Tugi ◽  
Ami Hassan Md Din ◽  
Nornajihah Mohammad Yazid ◽  
Abdullah Hisam Omar ◽  
Amalina Izzati Abdul Hamid ◽  
...  
Keyword(s):  
Satellite Altimetry ◽  
Altimetry Data ◽  
Mission Satellite ◽  
Satellite Altimetry Data
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