Potential of Multi-mission Satellite Altimetry Observations and Hydrodynamic Model to Establish Virtual Gauging Network in Sparsely Gauged Basin

2021 ◽  
Author(s):  
Pankaj R Dhote ◽  
Joshal Bansal ◽  
Vaibhav Garg ◽  
Praveen Thakur ◽  
Ankit Agarwal
2021 ◽  
pp. 103887
Author(s):  
Alessio Domeneghetti ◽  
Giada Molari ◽  
Mohammad J. Tourian ◽  
Angelica Tarpanelli ◽  
Sajedeh Behnia ◽  
...  

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

2019 ◽  
Vol 63 (11) ◽  
pp. 3452-3472 ◽  
Author(s):  
Ami Hassan Md Din ◽  
Nur Adilla Zulkifli ◽  
Mohammad Hanif Hamden ◽  
Wan Anom Wan Aris

2018 ◽  
Author(s):  
Ludwig Schröder ◽  
Martin Horwath ◽  
Reinhard Dietrich ◽  
Veit Helm

Abstract. We developed an approach for a multi-mission satellite altimetry analysis over the Antarctic Ice Sheet which comprises Seasat, Geosat, ERS-1, ERS-2, Envisat, ICESat and CryoSat-2. In a first step we apply a consistent reprocessing of the radar alitmetry data which improves the measurement precision by up to 50 %. We then perform a joint repeat altimetry analysis of all missions. We estimate inter-mission offsets by approaches adapted to the temporal overlap or non-overlap and to the similarity or dissimilarity of involved altimetry techniques. Hence, we obtain monthly grids forming a combined surface elevation change time series. Owing to the early missions Seasat and Geosat, the time series span almost four decades from 07/1978 to 12/2017 over 25 % of the ice sheet area (coastal regions of East Antarctica and the Antarctic Peninsula). Since the launch of ERS-1 79 % of the ice sheet area is covered by observations. Over this area, we obtain a negative volume trend of −34 ± 5 km3 yr−1 for the more than 25-year period (04/1992–12/2017). These volume losses have significantly accelerated to a rate of −170 ± 11 km3 yr−1 for 2010–2017. Interannual variations significantly impact decadal volume rates which highlights the importance of the long-term time series. Our time series show a high coincidence with modeled cumulated precipitation anomalies and with satellite gravimetry. This supports the interpretation with respect to snowfall anomalies or dynamic thinning. Moreover, the correlation with cumulated precipitation anomalies back to the Seasat and Geosat periods highlights that the inter-mission offsets were successfully corrected and that the early missions add valuable information.


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