佳文赏析 | 卫星重力与水文学2020年1月文章合集
List
1、A Framework for Deriving Drought Indicators from the Gravity Recovery and Climate Experiment (GRACE)
By: Helena Gerdener, Olga Engels, Jürgen Kusche.
Journal: Hydrology and Earth System Sciences
Abstract:
Identifying and quantifying drought in retrospective is a necessity for better understanding drought conditions and the propagation of drought through the hydrological cycle and eventually for developing forecast systems. Hydrological droughts refer to water deficits in surface and subsurface storage, and since these are difficult to monitor at larger scales, several studies have suggested exploiting total water storage data from the GRACE (Gravity Recovery and Climate Experiment) satellite gravity mission to analyze them. This has led to the development of GRACE-based drought indicators. However, it is unclear how the ubiquitous presence of climate-related or anthropogenic water storage trends found within GRACE analyses masks drought signals. Thus, this study aims to better understand how drought signals propagate through GRACE drought indicators in the presence of linear trends, constant accelerations, and GRACE-specific spatial noise. Synthetic data are constructed and existing indicators are modified to possibly improve drought detection. Our results indicate that while the choice of the indicator should be application-dependent, large differences in robustness can be observed. We found a modified, temporally accumulated version of the Zhao et al. (2017) indicator particularly robust under realistic simulations. We show that linear trends and constant accelerations seen in GRACE data tend to mask drought signals in indicators and that different spatial averaging methods required to suppress the spatially correlated GRACE noise affect the outcome. Finally, we identify and analyze two droughts in South Africa using real GRACE data and the modified indicators.
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2、Can We Resolve the Basin‐Scale Sea Level Trend Budget from GRACE Ocean Mass?
By: Sam Royston, Bramha Dutt Vishwakarma, Richard Westaway, et al.
Journal: Journal of Geophysical Research:Oceans
Abstract:
Understanding sea level changes at a regional scale is important for improving local sea level projections and coastal management planning. Sea level budget (SLB) estimates derived from the sum of observation of each component close for the global mean. The sum of steric and Gravity Recovery and Climate Experiment (GRACE) ocean mass contributions to sea level calculated from measurements does not match the spatial patterns of sea surface height trends from satellite altimetry at 1° grid resolution over the period 2005–2015. We investigate potential drivers of this mismatch aggregating to subbasin regions and find that the steric plus GRACE ocean mass observations do not represent the small-scale features seen in the satellite altimetry. In addition, there are discrepancies with large variance apparent at the global and hemispheric scale. Thus, the SLB closure on the global scale to some extent represents a cancelation of errors. The SLB is also sensitive to the glacial isostatic adjustment correction for GRACE and to altimery orbital altitude. Discrepancies in the SLB are largest for the Indian-South Pacific Ocean region. Taking the spread of plausible sea level trends, the SLB closes at the ocean-basin scale (2σ) but with large spread of magnitude, one third or more of the trend signal. Using the most up-to-date observation products, our ocean-region SLB does not close everywhere, and consideration of systematic uncertainties diminishes what information can be gained from the SLB about sea level processes, quantifying contributions, and validating Earth observation systems.
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3、Contributions to Arctic Sea Level from 2003 to 2015
By: Carsten A. Ludwigsen, Ole B. Andersen.
Journal: Advances in Space Research
Abstract:
As one of the most remote and inaccessible regions in the world, the sea level in the Arctic is still today in large parts uncertain. Sea level estimates from GRACE and satellite altimetry show disagreements in areas of the Arctic while only few in-situ measurements are present to validate satellite products. By using an independent in-situ based dataset of hydrographic data (DTUSteric), this study compares different available datasets from GRACE and altimetry. The best agreement (R = 0.76) is reached between the combination of DTUSteric and the JPL Mascon solution and the altimetry product from Centre of Polar Observation and Modelling (CPOM). A large residual signal is found in the East Siberian Sea, an area with no in-situ observations and in general uncertain satellite observations. The spatial correlation coefficients ranging from 0.32 to 0.76 reflects a large number of unknowns and uncertainties, with coarse GRACE resolution, extensive interpolation and lack of in-situ data in parts of the Arctic Ocean and uncertainty of the altimetric products being the largest sources of error. In general, we recommended that satellite observations are used carefully in the Arctic. Even this study shows that steric estimates from in-situ observations to some extent can explain the gap between GRACE and altimetry, the observed sea level trend in significant regions of the Arctic cannot be validated with in-situ hydrographic data.
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4、Drift of the Earth’s Principal Axes of Inertia from GRACE and Satellite Laser Ranging Data
By: José M. Ferrándiz, Sadegh Modiri, Santiago Belda, et al.
Journal: Remote Sensing
Abstract:
The location of the Earth’s principal axes of inertia is a foundation for all the theories and solutions of its rotation, and thus has a broad effect on many fields, including astronomy, geodesy, and satellite-based positioning and navigation systems. That location is determined by the second-degree Stokes coefficients of the geopotential. Accurate solutions for those coefficients were limited to the stationary case for many years, but the situation improved with the accomplishment of Gravity Recovery and Climate Experiment (GRACE), and nowadays several solutions for the time-varying geopotential have been derived based on gravity and satellite laser ranging data, with time resolutions reaching one month or one week. Although those solutions are already accurate enough to compute the evolution of the Earth’s axes of inertia along more than a decade, such an analysis has never been performed. In this paper, we present the first analysis of this problem, taking advantage of previous analytical derivations to simplify the computations and the estimation of the uncertainty of solutions. The results are rather striking, since the axes of inertia do not move around some mean position fixed to a given terrestrial reference frame in this period, but drift away from their initial location in a slow but clear and not negligible manner.
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5.GRACE Satellite Monitoring and Driving Factors Analysis of Groundwater Storage Under High-Intensity Coal Mining Conditions: A Case Study of Ordos, Northern Shaanxi and Shanxi, China
By: Xuhui Chen, Jinbao Jiang, Tianjie Lei, et al.
Journal: Hydrogeology Journal
Abstract:
Coal mining in northwestern China is an important industry. For the traditional monitoring of water resources in coal-rich regions, a single monitoring well or remote-sensing image is often used to obtain the groundwater level or water body area. The process is restricted by the spatial distribution of monitoring wells and the quality of remote sensing images. The regions of Ordos, Northern Shaanxi (including Yan’an and Yulin cities), herein collectively referred to as OYY, and Shanxi (SX) were studied. Here, groundwater storage anomalies (GWSA) were derived using the gravity recovery and climate experiment (GRACE) satellite data and WaterGAP global hydrology model, and the change trend of groundwater storage (GWS) was explored. Using time series analysis and grey slope relational analysis, the potential driving factors of regional GWSA were derived and considered independent variables. In combination with GWSA, the quantitative relationship between the variables was established by partial least squares regression. Results showed that: (1) the decreasing rate of GWS in OYY and SX reached –0.65 and –1.16 cm/year, respectively, from 2003 to 2014; (2) the main driving factors leading to the reduction of GWS included coal-mining water consumption for OYY and water consumption by coal mining and agricultural irrigation for SX, and the weights of water consumption by coal mining and agricultural irrigation for SX were both 50%. Therefore, GRACE satellite data show good application in groundwater monitoring of coal-mining concentrated areas, providing an important basis for the formulation of water resource management measures.
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6.Greening Trends of Southern China Confirmed by GRACE
By: Le Chang, Wenke Sun.
Journal: Remote Sensing
Abstract:
As reported by the National Aeronautics and Space Administration (NASA), the world has been greening over the last two decades, with the highest greening occurring in China and India. The increasing vegetation will increase plant tissue accumulation and water storage capacity, and all of these variations will cause mass change. In this study, we found that the mass change related to greening in Southern China could be confirmed by Gravity Recovery and Climate Experiment (GRACE) observations. The mean mass change rate detected by GRACE is 6.7±0.8 mm/yr in equivalent water height during 2003–2016 in our study region. This is consistent with the sum of vegetation tissue, soil water and groundwater change calculated using multi-source data. The vegetation accumulation is approximately 3.8±1.3 mm/yr, which is the major contribution to region mass change. We also found that the change of water storage capacity related to vegetation can be detected by GRACE.
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7.High Resolution Mapping of Ice Mass Loss in the Gulf of Alaska from Constrained Forward Modeling of GRACE Data
By: Cheick Doumbia, Pascal Castellazzi, Alain N Rousseau, et al.
Journal: Frontiers in Earth Science
Abstract:
The resolution of Gravity Recovery And Climate Experiment (GRACE) Terrestrial Water Storage (TWS) change data is too low to discriminate mass variations at the scale of glaciers, small ensemble of glaciers, or icefields. In this paper, we apply an iterative constraint modeling strategy over the Gulf Of Alaska (GOA) to improve the resolution of ice loss estimates derived from GRACE. We assess the effect of the most influential parameters such as the type of GRACE solution and the degree of heterogeneity of the distribution map over which the GRACE data is focused. Three GRACE solutions from the most common processing strategies and three ice distribution maps of resolutions ranging from 55,000 to 20,000 km2 are used. First, we present results from a series of simulations with synthetic data and a mix of synthetic/modeled data to validate the focusing strategy and we point out how inaccuracies arise while increasing the spatial resolution of GRACE data. Second, we present the recovery of the total GRACE-derived mass change anomaly at the scale of the GOA. At this scale, all solutions and distribution maps agree, showing ∼40 Gt/year of mean ice mass loss over the period 2002–2017. This result is similar to studies using GRACE solutions from the latest releases and time-series of more than 8 years. The first studies using GRACE data published during the 2005–2008 era generally overestimated the long-term ice mass loss. Third, we show results of the three resolutions tested to focus the mass anomaly. Using focusing units (mascon) of ∼30,000 km2 or larger, the focusing procedure provides reliable results with errors below 15%. Below this threshold, errors of up to 56% are observed.
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8.Improving the Predictive Skill of a Distributed Hydrological Model by Calibration on Spatial Patterns with Multiple Satellite Data Sets
By: Moctar Dembélé, Markus Hrachowitz, Hubert H.G. Savenije, et al.
Journal: Water Resources Research
Abstract:
Hydrological model calibration combining Earth observations and in situ measurements is a promising solution to overcome the limitations of the traditional streamflow-only calibration. However, combining multiple data sources in model calibration requires a meaningful integration of the data sets, which should harness their most reliable contents to avoid accumulation of their uncertainties and mislead the parameter estimation procedure. This study analyzes the improvement of model parameter selection by using only the spatial patterns of satellite remote sensing data, thereby ignoring their absolute values. Although satellite products are characterized by uncertainties, their most reliable key feature is the representation of spatial patterns, which is a unique and relevant source of information for distributed hydrological models. We propose a novel multivariate calibration framework exploiting spatial patterns and simultaneously incorporating streamflow and three satellite products (i.e., Global Land Evaporation Amsterdam Model [GLEAM] evaporation, European Space Agency Climate Change Initiative [ESA CCI] soil moisture, and Gravity Recovery and Climate Experiment [GRACE] terrestrial water storage). The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature data set is used for model evaluation. A bias-insensitive and multicomponent spatial pattern matching metric is developed to formulate a multiobjective function. The proposed multivariate calibration framework is tested with the mesoscale Hydrologic Model (mHM) and applied to the poorly gauged Volta River basin located in a predominantly semiarid climate in West Africa. Results of the multivariate calibration show that the decrease in performance for streamflow (−7%) and terrestrial water storage (−6%) is counterbalanced with an increase in performance for soil moisture (+105%) and evaporation (+26%). These results demonstrate that there are benefits in using satellite data sets, when suitably integrated in a robust model parametrization scheme.
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9.Many Commonly Used Rainfall‐Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections
By: Keirnan Fowler, Wouter Knoben, Murray Peel, et al.
Journal: Water Resources Research
Abstract:
Evidence suggests that catchment state variables such as groundwater can exhibit multi-year trends. This means their state may reflect not only recent climatic conditions, but also climatic conditions in past years or even decades. Here we demonstrate that five commonly used conceptual “bucket” rainfall-runoff models are unable to replicate multi-year trends exhibited by natural systems during the “Millennium Drought” in South East Australia. This causes an inability to extrapolate to different climatic conditions, leading to poor performance in split sample tests. Simulations are examined from five models applied in 38 catchments, then compared with groundwater data from 19 bores and Gravity Recovery and Climate Experiment (GRACE) data for two geographic regions. Whereas the groundwater and GRACE data decrease from high to low values gradually over the duration of the 13-year drought, the model storages go from high to low values in a typical seasonal cycle. This is particularly the case in the drier, flatter catchments. Once the drought begins, there is little room for decline in the simulated storage, because the model “buckets” are already “emptying” on a seasonal basis. Since the effects of sustained dry conditions cannot accumulate within these models, we argue they should not be used for runoff projections in a drying climate. Further research is required to (a) improve conceptual rainfall-runoff models; (b) better understand circumstances in which multi-year trends in state variables occur; and (c) investigate links between these multi-year trends and changes in rainfall-runoff relationships in the context of a changing climate.
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10.Prograde and Retrograde Terms of Gravimetric Polar Motion Excitation Estimates from the GRACE Monthly Gravity Field Models
By: Jolanta Nastula, Justyna Śliwińska.
Journal: Remote Sensing
Abstract:
From 2002 to 2017, the Gravity Recovery and Climate Experiment (GRACE) mission’s twin satellites measured variations in the mass redistribution of Earth’s superficial fluids, which disturb polar motion (PM). In this study, the PM excitation estimates were computed from two recent releases of GRACE monthly gravity field models, RL05 and RL06, and converted into prograde and retrograde circular terms by applying the complex Fourier transform. This is the first such analysis of circular parts in GRACE-based excitations. The obtained series were validated by comparison with the residuals of observed polar motion excitation (geodetic angular momentum (GAM)–atmospheric angular momentum (AAM)–oceanic angular momentum (OAM) (GAO)) determined from precise geodetic measurements of the pole coordinates. We examined temporal variations of hydrological excitation function series (or hydrological angular momentum, HAM) in four spectral bands: seasonal, non-seasonal, non-seasonal short-term, and non-seasonal long-term. The general conclusions arising from the conducted analyses of prograde and retrograde terms were consistent with the findings from the equatorial components of PM excitation studies drawn in previous research. In particular, we showed that the new GRACE RL06 data increased the consistency between different solutions and improved the agreement between GRACE-based excitation series and reference data. The level of agreement between HAM and GAO was dependent on the oscillation considered and was higher for long-term than short-term variations. For most of the oscillations considered, the highest agreement with GAO was obtained for CSR RL06 and ITSG-Grace2018 solutions. This study revealed that both prograde and retrograde circular terms of PM excitation can be determined by GRACE with similar levels of accuracy. The findings from this study may help in choosing the most appropriate GRACE solution for PM investigations and can be useful in future improvements to GRACE data processing.
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11.Replacing GRACE/GRACE‐FO C30 with Satellite Laser Ranging Impacts on Antarctic Ice Sheet Mass Change
By: Bryant D. Loomis, Kenneth E. Rachlin, David N. Wiese, et al.
Journal: Geophysical Research Letters
Abstract:
Satellite laser ranging (SLR) observations have long been relied upon for measuring changes in Earth's dynamic oblateness, C20. This major component of Earth's time-variable gravity field is not well-observed by the GRACE and GRACE-FO missions, leading to the common practice of replacing their values with those obtained by SLR. The C30 coefficient, which has a large impact on the recovered Antarctic Ice Sheet mass changes, is shown here to be poorly observed by GRACE/GRACE-FO when either mission is operating without two fully functional accelerometers. The GRACE spacecraft pair operated nominally until October 2016 when one accelerometer was powered off due to battery limitations, while GRACE-FO is currently excluding one accelerometer from the data processing due to elevated noise levels. Beginning with the launch of LARES in 2012, SLR-derived C30 values are suitable for replacing any problematic GRACE/GRACE-FO estimates, enabling the accurate recovery of Antarctic Ice Sheet mass changes, among others.
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12.Satellite Detection of Varying Seasonal Water Supply Restrictions on Grassland Productivity in the Missouri Basin, USA
By: Geruo A, Isabella Velicogna, Meng Zhao, et al.
Journal: Remote Sensing of Environment
Abstract:
Climate observations indicate more frequent drought in recent years, and model predictions suggest that drought occurrence will continue to rise with global warming. Understanding drought impacts on ecosystem functioning requires accurate quantification of vegetation sensitivity to changes in water supply condition. This is complicated by the seasonal variation in plant structural and physiological response to water stress, especially for semi-arid grasslands with characteristic strong spatial and temporal variability in carbon uptake. Here, we use complementary satellite soil moisture (SM) and total water storage (TWS) observations to delineate plant-accessible water supply variations for natural grasslands in the Missouri basin, USA. We evaluate how water supply influences the spatiotemporal variations in grassland productivity as a function of seasonal timing and climate condition. We identify a 128-day period from mid-June to early October when grassland growth is sensitive to soil moisture changes. We find the strongest SM sensitivity after the peak of the growing season associated with high temperature and VPD. SM limitation can extend to early and late growing season under warm conditions, while grassland sensitivity to SM is generally stronger in the late growth stage than in the green-up period given similar temperature and soil moisture. We find that complementary to the surface SM observations, TWS provides plant-available water storage information from the deeper soil, and both SM and TWS exert a lagged impact on grassland productivity. We find that the lag between the inter-annual variation of SM and associated plant response increases through the season, and overall there is a transition from SM-limitation to TWS-limitation on productivity during the late growing period when the TWS level is near the seasonal low. Future global change projections should account for a seasonally varying vegetation-moisture relationship to accurately assess the impact of the water supply constraint on plant productivity in a warming climate.
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13.Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa
By: Augusto Getirana, Hahn Chul Jung, Kristi Arsenault, et al.
Journal: Water Resources Research
Abstract:
West Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite-based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003-2016 and used to initialize six-month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE-DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE-DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast and water-related disaster warning systems for Africa.
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14.Stripe Mystery in GRACE Geopotential Models Revealed
By: Athina Peidou, Spiros Pagiatakis.
Journal: Geophysical Research Letters
Abstract:
The Gravity Recovery and Climate Experiment (GRACE) gravitational models suffer from a dominant systematic error, usually referred to as “longitudinal stripes”. These stripes contaminate useful geophysical signals and limit the spectrum of geoscience applications that can be benefited from GRACE and GRACE-Follow On. Analyses of the spatiotemporal structure of latitudinal stripe profiles show consistent spectral characteristics throughout three years of monthly solutions. Using an elegant combination of GRACE sampling characteristics and advanced moiré theory, we show that the GRACE stripes are sub-Nyquist (pseudo-moiré) artifacts arising from the oversampling of the Earth's low-frequency static disturbing potential (geoid) along the parallels. The low-frequency geoid modulates the total sampled gravitational signal with a frequency near m/n*fs, where fs is the sampling frequency of the GRACE ground track ‘bundles’ along the parallels of latitude, and m and n are mutually prime integers, with 2m≤n.
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15.Surface Deformation and Influence of Hydrological Mass over Himalaya and North India Revealed from a Decade of Continuous GPS and GRACE Observations
By: Ajish P. Saji, P.S. Sunil, K.M. Sreejith, et al.
Journal: Journal of Geophysical Research: Earth Surface
Abstract:
The India-Eurasia collision, driven by tectonic forcing, is modulated by nontectonic forcing allied to seasonal variations in the neighboring regions. To decipher the ground deformation in response to hydrological mass variations of the Himalaya and North India, we analyzed continuous Global Positioning System (cGPS) observations from 50 sites together with Gravity Recovery and Climate Experiment (GRACE) data for the period 2004-2015. Vertical components of surface deformation derived from GPS and GRACE show moderate to high-level amplitude correlation with a slope value of 0.76 and a level of phase delay from ±25° to ±30°. The average weighted root-mean-square reduction (WRMS) of 17.72% suggests the prominence of hydrological mass variations particularly over the sub-Himalaya and Indo-Gangetic Plain (IGP). GPS-derived vertical deformation after correcting the hydrological effects utilizing GRACE observations suggests that the sub-Himalaya and IGP are undergoing subsidence and the surrounding areas show uplift. In addition to the tectonic and nontectonic forcings, an unsustainable consumption of groundwater associated to irrigation and other anthropogenic uses influence the subsidence rate in the IGP and sub-Himalaya. Further, 2-D elastic dislocation modeling suggests that GRACE correction to the GPS vertical velocity causes a reduction in the subsurface slip rate estimation over the Main Himalayan Thrust (MHT) system by 12.06% and improves the chi-square misfit by 20.32%.
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转载自公众号:卫星重力与水文学
排版:张敏
责编:鲁嘉颐
审核:王波涛
终审:顾伟男 田巍 梁龙武
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