Concurrent Linking of Soil Moisture and Sea Surface Salinity to the Earth's Water Cycle
Doubkova, Marcela; Fernández-Prieto, Diego; Klockmann, Marlene; Sabia, Roberto
ESA ESRIN, ITALY

An increasing number of water cycle parameters is being retrieved using the Earth Observation (EO) data. These include, for instance, precipitation, soil moisture, water vapour, or snow. Only recently, ocean salinity became available from satellites, e.g. from the ESA's Soil Moisture and Ocean Salinity (SMOS) mission. The objective of the SMOS mission is a provision of ocean salinity and soil moisture datasets. The synchronized acquisitions of both parameters offer a great opportunity to study their interactions as well as their links to the Earth's Water Cycle.

This study investigates the spatio-temporal interaction between the oceans and land components in the global water cycle through the analysis of surface soil moisture, ocean salinity and additional existing records of different variables characterising the global water cycle (e.g. evapotranspiration (E) and precipitation (P)) during the full SMOS live time.

The core of the hydrological cycle consists of two complementary processes - the evaporation (E) of moisture/seawater and its precipitation (P). These two processes can occur over an identical region (regions with high moisture/seawater recycling) or over two separate regions (regions with low moisture/seawater recycling). The E - P indicates the difference in moisture in atmosphere and acts as one of the triggers of the moisture movement around the planet. To fulfil the Earth's water balance the difference I_L = P_L - E_L over land must be directly related to I_O = E_O - P_O over ocean. In addition, in the open ocean away from polar regions, surface salinity distribution is closely tied to I_O patterns [1]. Likewise, soil moisture is expected to be a proxy for I_L especially over arid and semiarid regions [2].

This study employs the state-of-the-art datasets of SSM, SSS, E and P to a) evaluate their quality based on common assumptions and results from existing model studies and b) study the interactions between parameters and between their changes in time (ΔSSM, ΔSSS, ΔI_L and ΔI_O). The data employed in the study include the monthly averages of MERRA evapotranspiration, GPCP precipitation, SMOS and combined WACMOS soil moisture products over land and SSM/I precipitation, OAFluxes evaporation and SMOS salinity over the oceans. Many of the used products are merged combinations of several independent products that were combined to decrease the uncertainty and increase the data coverage.

First, the quality of the E and P will be assessed by studying if these follow common expectations such as that P_L > E_L over land and E_O > P_O over the ocean on a global scale. Next, correlations between separate parameters and their changes in time (ΔI_L, ΔI_O, ΔSSM and ΔSSS) will be computed for the SMOS live time years. The assessments is expected to be hampered by the fact that several of the major water discharge areas are masked out in the soil moisture data. Over oceans, in turn, major features determining SSS variability and therefore hindering this study are river run off, freezing and melting of ice, advection and entrainment. Also, the common variability of ΔSSM and ΔSSS will be assessed over areas that are known to demonstrate close interaction between land and ocean; e.g. East Africa and the Indian Ocean or eastern Australia and the equatorial Pacific.

This study investigates the possible links of SSS and SSM to the major components of water cycle as well as between SSS and SSM themselves. It is not the aim of this study to assess water budget closure but to improve the understanding of the dynamical links between separate parameters that is expected to support future water budget studies.

[1] M. E. McCulloch, P. Spurgeon, and A. Chuprin, "Have mid-latitude ocean rain lenses been seen by the SMOS satellite?," vol. 43-44, pp. 108 - 111, 2012.
[2] P. A. Dirmeyer, C. A. Schlosser, and K. L. Brubaker, "Precipitation, Recycling, and Land Memory: An integrated Analysis," Journal of Hydrometeorology, vol. 10, pp. 278 - 288, 2009.
[3] K. E. Trenberth, J. T. Fasullo, and J. Mackaro, "Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses," Journal of Climate, vol. 24, no. 18, pp.
4907-4924, 2011.