High‐resolution CSR GRACE RL05 mascons

Save, Himanshu; Bettadpur, Srinivas; Tapley, Byron D

doi:10.1002/2016jb013007

Cited by 794 publications

(581 citation statements)

References 47 publications

(136 reference statements)

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“…The available global mascon solutions discussed in this study are the products released by JPL (Watkins et al 2015), GSFC (Luthcke et al 2013) and CSR (Save et al 2016). Note that these mascon solutions are estimated from GRACE KBR data, while the method developed in this study uses GRACE SHCs.…”

Section: Comparison With Greenland Mass Anomalies From Other Studiesmentioning

confidence: 99%

“…96 for CSR (the Center of Space Research of the University of Texas at Austin) RL05 solutions (Bettadpur 2012) and 90 for GFZ (GeoForschungsZentrum) RL05 solutions (Dahle et al 2012). Alternatively, gravity solutions in terms of mass anomalies per mass concentration block ("mascon") have also been released by Jet Propulsion Laboratory (JPL) (Watkins et al 2015;Wiese 2015;Wiese et al 2016), Goddard Space Flight Center (GSFC) (Luthcke et al 2013) and CSR (Save et al 2016). To clean KBR data from the contribution of high-frequency mass variations, an ocean tide model [e.g.…”

Section: Introductionmentioning

confidence: 99%

“…This helps in reducing distortions in the estimated mass anomalies. Luthcke et al (2006) were the first to use the mascon representation to derive mass anomalies over Greenland from GRACE level-1b data, followed by Luthcke et al (2013), Watkins et al (2015) and Save et al (2016). To reduce the numerical complexity, variants of the mascon approach have been suggested, which use monthly sets of SHCs as input, e.g.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

Ran

Ditmar

Klees

et al. 2017

J Geod

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We present an improved mascon approach to transform monthly spherical harmonic solutions based on GRACE satellite data into mass anomaly estimates in Greenland. The GRACE-based spherical harmonic coefficients are used to synthesize gravity anomalies at satellite altitude, which are then inverted into mass anomalies per mascon. The limited spectral content of the gravity anomalies is properly accounted for by applying a low-pass filter as part of the inversion procedure to make the functional model spectrally consistent with the data. The full error covariance matrices of the monthly GRACE solutions are properly propagated using the law of covariance propagation. Using numerical experiments, we demonstrate the importance of a proper data weighting and of the spectral consistency between functional model and data. The developed methodology is applied to process real GRACE level-2 data (CSR RL05). The obtained mass anomaly estimates are integrated over five drainage systems, as well as over entire Greenland. We find that the statistically optimal data weighting reduces random noise by 35-69%, depending on the drainage system. The obtained mass anomaly time-series are de-trended to eliminate the contribution of ice discharge and are compared with detrended surface mass balance (SMB) time-series computed with the Regional Atmospheric Climate Model (RACMO 2.3). We show that when using a statistically optimal data weighting in GRACE data processing, the discrepancies between GRACE-based estimates of SMB and modelled SMB are reduced by 24-47%.B J. Ran

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Section: Comparison With Greenland Mass Anomalies From Other Studiesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

Ran

Ditmar

Klees

et al. 2017

J Geod

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“…GRACE satellite data allow derivation of monthly time series of total water storage anomalies (TWSA) over all continents. In our study CSR GRACE RL05 mascon solutions (Save et al, 2016;10 http://www2.csr.utexas.edu/grace/RL05_mascons.html, last accessed: 17 Jul. 2018) were used.…”

Section: Watergapmentioning

confidence: 99%

Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in-situ data for calibrating a hydrological model

Hosseini‐Moghari¹,

Araghinejad²,

Tourian³

et al. 2018

Preprint

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Abstract. During the last decades, the endorheic Lake Urmia basin in northwestern Iran has suffered from decreased precipitation, groundwater levels and a very strong reduction in the volume and more recently also in the extent of Lake Urmia.Human water use has exacerbated the desiccating impact of climatic variations. This study quantifies the contribution of human water use to the reduction of inflow into Lake Urmia, to the loss of lake water volume and to the loss of groundwater and total water storage in the entire Lake Urmia basin during [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013]. To this end, the WaterGAP Global Hydrology Model (WGHM) 15 was manually calibrated specifically for the basin against multiple in-situ and spaceborne data, and the best-performing calibration variant was run with or without taking into account water use. Observation data encompass remote-sensing based time series of annual irrigated area in the basin from MODIS, monthly total water storage anomaly (TWSA) from GRACE satellites and monthly lake volume. In-situ observations include time series of annual inflow into the lake and basin averages of groundwater level variations based on 284 wells. In addition, local estimates of sectoral water withdrawals in 2009 and 20 return flow fractions were utilized. Four calibration variants were set up in which the number of considered observation types was increased in a stepwise fashion. The best fit to each and all observations is achieved if the maximum amount of observations is used for calibration. Calibration against GRACE TWSA improves simulated inflow into Lake Urmia but still overestimates it by 90%; it results in an overestimation of lake volume loss, underestimation of groundwater loss and a shifted seasonality of groundwater storage. Lake and groundwater dynamics can only be simulated well if calibration against 25 groundwater levels leads to adjusting the fractions of human water use from groundwater and surface water. According to our study, human water use was the reason for 50% of the total basin water loss of about 10 km 3 during 2003-2013, for 40% of the Lake Urmia water loss of about 8 km 3 and for up to 90% of the groundwater loss. Lake inflow was 40% less than it would have been without human water use. We found that even without human water use, Lake Urmia would not have recovered from the significant loss of lake water volume caused by the drought year 2008. These findings may serve to support water 30 management in the basin and more specifically Lake Urmia restoration plans.Hydrol. Earth Syst. Sci. Discuss., https://doi

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“…Here the variation in GRACE liquid water equivalent thickness (LWET) was used to indicate the changes in surface and ground water due to irrigation activities. The GRACE data of version release-05 were retrieved based on the Mascon solutions from the Center for Space Research [23] spanning from 2002 to 2014 at a spatial resolution of 0.5 • × 0.5 • . Note that GRACE can only retrieve the anomaly of LWET instead of its absolute value.…”

Section: Gracementioning

confidence: 99%

Irrigation-Induced Environmental Changes around the Aral Sea: An Integrated View from Multiple Satellite Observations

et al. 2017

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Abstract:The Aral Sea basin (ASB) is one of the most environmentally vulnerable regions to climate change and human activities. During the past 60 years, irrigation has greatly changed the water distribution and caused severe environmental issues in the ASB. Using remote sensing data, this study investigated the environmental changes induced by irrigation activities in this region. The results show that, in the past decade, land water storage has significantly increased in the irrigated upstream regions (13 km 3 year −1 ) but decreased in the downstream regions (−27 km 3 year −1 ) of the Amu Darya River basin, causing a water storage decrease in the whole basin (−20 km 3 year −1 ). As a result, the water surface area of the Aral Sea has decreased from 32,000 in 2000 to 10,000 km 2 in 2015. The shrinking Aral Sea exposed a large portion of the lake bottom to the air, increasing (decreasing) the daytime (nighttime) temperatures by about 1 • C year −1 (0.5 • C year −1 ). Moreover, there were other potential environmental changes, including drier soil, less vegetation, decreasing cloud and precipitation, and more severe and frequent dust storms. Possible biases in the remote sensing data due to the neglect of the shrinking water surface area of the Aral Sea were identified. These findings highlight the severe environmental threats caused by irrigation in Central Asia and call attention to sustainable water use in such dryland regions.

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High‐resolution CSR GRACE RL05 mascons

Cited by 794 publications

References 47 publications

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

Statistically optimal estimation of Greenland Ice Sheet mass variations from GRACE monthly solutions using an improved mascon approach

Quantifying the impacts of human water use and climate variations on recent drying of Lake Urmia basin: the value of different sets of spaceborne and in-situ data for calibrating a hydrological model

Irrigation-Induced Environmental Changes around the Aral Sea: An Integrated View from Multiple Satellite Observations

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