Integrating multiple satellite observations into a coherent dataset to monitor the full water cycle – application to the Mediterranean region

Abstract

Abstract. The Mediterranean region is one of the climate hotspots where the climate change impacts are both pronounced and documented. The HyMeX (Hydrometeorological Mediterranean eXperiment) aims to improve our understanding of the water cycle from the meteorological to climate scales. However, monitoring the water cycle with Earth observations (EO) is still a challenge: EO products are multiple, and their utility is degraded by large uncertainties and incoherences among the products. Over the Mediterranean region, these difficulties are exacerbated by the coastal/mountainous regions and the small size of the hydrological basins. Therefore, merging/integration techniques have been developed to reduce these issues. We introduce here an improved methodology that closes not only the terrestrial but also the atmospheric and ocean budgets. The new scheme allows us to impose a spatial and temporal multi-scale budget closure constraint. A new approach is also proposed to downscale the results from the basin to pixel scales (at the resolution of 0.25∘). The provided Mediterranean WC budget is, for the first time, based mostly on observations such as the GRACE water storage or the netflow at the Gibraltar Strait. The integrated dataset is in better agreement with in situ measurements, and we are now able to estimate the Bosporus Strait annual mean netflow.

Assessing Water Balance Closure Using Multiple Data Assimilation and Remote Sensing-Based Datasets for Canada

“…Further studies are needed to identify the reasons for such inconsistencies and to examine their impacts on model calibration and analysis. Findings on water budget closure assessment and uncertainty from this study address the problems of physically inconsistent and uncertain water budget component products in large-scale modelling by providing a way to evaluate those datasets independent of a specific model (Pellet et al 2019). Such premodelling practice is important and is a useful tool in providing guidance to potential users regarding the reliability of different products, increasing the robustness of subsequent hydrological modelling and analyses.…”

Satellite Remote Sensing of Precipitation and the Terrestrial Water Cycle in a Changing Climate

“…Closure experiments have been attempted, and are starting to produce convincing results based on satellite data [49][50][51], although closure has not yet been attained using satellite data alone. Rodell et al [52] show that, in the majority of cases, the observed annual surface and atmospheric water budgets over the continents and oceans close with much less than a 10% residual, while observed residuals and optimized uncertainty estimates are considerably larger for monthly surface and atmospheric water budget closure, i.e., often ≥20% in North America, Eurasia, Australia and neighboring islands, and the Arctic and South Atlantic Oceans.…”

“…In depth studies would be beneficial for filling the gaps in our understanding of the common characteristics of Mediterranean-type climates around the world and their variability and change [56]. Specifically, observational datasets [49,50] are providing new insights on long-term changes in the Mediterranean basin, in support of model projections predicting increasing temperatures and decreasing evapotranspiration and precipitation over the region by the middle of this century [57,58]. The most recent datasets are contributing to addressing the contribution of the Mediterranean Sea to climatological precipitation on one side, and extreme precipitation on the other [59].…”

Reply on RC1

“…the ability to monitor the global water cycle and, hence, runoff. By taking advantage of satellite information, some studies tried to develop methodologies able to optimally produce multivariable datasets from the fusion of in situ and satellite-based observations (e.g., Rodell et al, 2015;Zhang et al, 2018;Pellet et al, 2019). Other studies exploited satellite observations of hydrological variables, e.g., precipitation (Hong et al, 2007), soil moisture (Massari et al, 2014), and geodetic variables (e.g., Tourian et al, 2018) to monitor single components of the water cycle in an independent way.…”