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Forootan E.,University of Bonn | Kusche J.,University of Bonn | Loth I.,University of Bonn | Schuh W.-D.,University of Bonn | And 7 more authors.
Surveys in Geophysics | Year: 2014

West African countries have been exposed to changes in rainfall patterns over the last decades, including a significant negative trend. This causes adverse effects on water resources of the region, for instance, reduced freshwater availability. Assessing and predicting large-scale total water storage (TWS) variations are necessary for West Africa, due to its environmental, social, and economical impacts. Hydrological models, however, may perform poorly over West Africa due to data scarcity. This study describes a new statistical, data-driven approach for predicting West African TWS changes from (past) gravity data obtained from the gravity recovery and climate experiment (GRACE), and (concurrent) rainfall data from the tropical rainfall measuring mission (TRMM) and sea surface temperature (SST) data over the Atlantic, Pacific, and Indian Oceans. The proposed method, therefore, capitalizes on the availability of remotely sensed observations for predicting monthly TWS, a quantity which is hard to observe in the field but important for measuring regional energy balance, as well as for agricultural, and water resource management. Major teleconnections within these data sets were identified using independent component analysis and linked via low-degree autoregressive models to build a predictive framework. After a learning phase of 72 months, our approach predicted TWS from rainfall and SST data alone that fitted to the observed GRACE-TWS better than that from a global hydrological model. Our results indicated a fit of 79 % and 67 % for the first-year prediction of the two dominant annual and inter-annual modes of TWS variations. This fit reduces to 62 % and 57 % for the second year of projection. The proposed approach, therefore, represents strong potential to predict the TWS over West Africa up to 2 years. It also has the potential to bridge the present GRACE data gaps of 1 month about each 162 days as well as a-hopefully-limited gap between GRACE and the GRACE follow-on mission over West Africa. The method presented could also be used to generate a near-real-time GRACE forecast over the regions that exhibit strong teleconnections. © 2014 Springer Science+Business Media Dordrecht. Source


Forootan E.,University of Bonn | Rietbroek R.,University of Bonn | Kusche J.,University of Bonn | Sharifi M.A.,University of Tehran | And 4 more authors.
Remote Sensing of Environment | Year: 2014

Extracting large scale water storage (WS) patterns is essential for understanding the hydrological cycle and improving the water resource management of Iran, a country that is facing challenges of limited water resources. The Gravity Recovery and Climate Experiment (GRACE) mission offers a unique possibility of monitoring total water storage (TWS) changes. An accurate estimation of terrestrial and surface WS changes from GRACE-TWS products, however, requires a proper signal separation procedure. To perform this separation, this study proposes a statistical approach that uses a priori spatial patterns of terrestrial and surface WS changes from a hydrological model and altimetry data. The patterns are then adjusted to GRACE-TWS products using a least squares adjustment (LSA) procedure, thereby making the best use of the available data. For the period of October 2002 to March 2011, monthly GRACE-TWS changes were derived over a broad region encompassing Iran. A priori patterns were derived by decomposing the following auxiliary data into statistically independent components: (i) terrestrial WS change outputs of the Global Land Data Assimilation System (GLDAS); (ii) steric-corrected surface WS changes of the Caspian Sea; (iii) that of the Persian and Oman Gulfs; (iv) WS changes of the Aral Sea; and (v) that of small lakes of the selected region. Finally, the patterns of (i) to (v) were adjusted to GRACE-TWS maps so that their contributions were estimated and GRACE-TWS signals separated. After separation, our results indicated that the annual amplitude of WS changes over the Caspian Sea was 152. mm, 101. mm over both the Persian and Oman Gulfs, and 71. mm for the Aral Sea. Since January 2005, terrestrial WS in most parts of Iran, specifically over the center and northwestern parts, exhibited a mass decrease with an average linear rate of ~. 15. mm/yr. The estimated linear trends of groundwater storage for the drought period of 2005 to March 2011, corresponding to the six main basins of Iran: Khazar, Persian and Oman Gulfs, Urmia, Markazi, Hamoon, and Srakhs were -6.7, -6.1, -11.2, -9.1, -3.1, and -4.2. mm/yr, respectively. The estimated results after separation agree fairly well with 256 in-situ piezometric observations. © 2013 Elsevier Inc. Source


Schmeer M.,Helmholtz Center Potsdam | Schmidt M.,German Geodetic Research Institute DGFI | Bosch W.,German Geodetic Research Institute DGFI | Seitz F.,TU Munich
Journal of Geodynamics | Year: 2012

Since 2002 the two GRACE satellites observe the time varying gravity signal mainly caused by the sum of mass variations within the Earth subsystems ocean, atmosphere, and continental hydrosphere. It is a challenging problem to separate the integral GRACE signal and to identify and quantify the mass variations of the individual subsystems. This work proves first by a closed loop simulation that such a decomposition is successful by means of empirical orthogonal functions (EOF) derived from geophysical models and a least-squares adjustment with a multivariate Gauss-Markov model with time coefficients parameterized. The geophysical models are used to synthesize GRACE observations which are subsequently separated leading to time coefficients coinciding with those of the predefined models. In a second step the separation is performed with real, unfiltered time series of 5. years of monthly GRACE gravity field models (with atmospheric and oceanic background models reconstructed) and a limited number of EOFs. The reconstructed time coefficients are in good agreement with the original ones and exhibit high correlations (0.70 for ocean, 0.91 for atmosphere and 0.93 for continental hydrosphere). Analysis of GRACE residuals and the correlation among the time coefficients substantiate a successful identification. © 2012 Elsevier Ltd. Source

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