Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data
Multivariate Prediction of Total Water Storage Changes Over West Africa from Multi-Satellite Data
复制标题
利用多卫星数据对西非总水储量变化进行多变量预测
DOI：
10.1007/s10712-014-9292-0
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发表时间：
--
影响因子：
4.6
通讯作者：
C.K. Shum
中科院分区：
文献类型：
--
作者：
E. Forootan;J. Kusche;I. Loth;W-D. Schuh;A. Eicker;J. Awange;L. Longuevergne;B. Diekkrueger;M. Schmidt;C.K. Shum
西非国家在过去几十年里经历了降雨模式的变化，包括明显的负趋势。这对该区域的水资源造成不利影响，例如，淡水供应减少。由于西非的环境、社会和经济影响，评估和预测大规模总储水量（TWS）变化是必要的。然而，由于数据缺乏，水文模型在西非可能表现不佳。本研究描述了一种新的统计数据驱动方法，通过重力恢复和气候实验（GRACE）获得的（过去）重力数据、热带降雨测量任务（TRMM）的（同期）降雨数据和大西洋、太平洋和印度洋的海表温度（SST）数据来预测西非TWS的变化。因此，建议的方法利用遥感观测的可用性来预测每月的TWS， TWS在实地很难观测到，但对测量区域能量平衡以及农业和水资源管理很重要。使用独立成分分析确定这些数据集中的主要遥相关，并通过低程度自回归模型建立预测框架。经过72个月的学习阶段，我们的方法仅从降雨量和海温数据预测TWS，这比从全球水文模型预测的TWS更符合观测到的GRACE-TWS。我们的结果表明，TWS变化的两种主要年际模式的第一年预测拟合度分别为79%和67%。这一拟合度在预测第二年分别降至62%和57%。因此，建议的方法具有预测西非长达2年的TWS的强大潜力。它也有可能弥合目前GRACE每162天1个月的数据差距，以及GRACE与西非后续任务之间的（希望有限的）差距。所提出的方法也可用于对表现出强遥连的区域产生近实时的GRACE预报。
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.
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影响因子：
4.4
作者：
Forootan, E.;Kusche, J.
通讯作者：
Kusche, J.
影响因子：
56.9
作者：
Koster, RD;Dirmeyer, PA;Yamada, T
通讯作者：
Yamada, T
来自 GRACE、GPS 和海洋模型的每周分辨率的总海洋质量变化
影响因子：
--
作者：
Rietbroek R;Brunnabend SE;Dahle C;Flechtner F;Kusche J;Schröter J;Timmermann R
通讯作者：
Timmermann R
GRACE 同化至 WGHM 的协方差分析和敏感性研究
影响因子：
5.4
作者：
M. Schumacher;A. Eicker;J. Kusche;H. Schmied;P. Döll
通讯作者：
P. Döll
影响因子：
8
作者：
Rodell, M;Houser, PR;Toll, D
通讯作者：
Toll, D