Fusion of Active and Passive Microwave Observations to Create an Essential Climate Variable Data Record on Soil Moisture

Wagner, Wolfgang; Dorigo, Wouter; Jeu, R. A. M. de; Fernández, Diego; Benvéniste, Jérôme; Haas, Eva; Ertl, Martin

doi:10.5194/isprsannals-i-7-315-2012

Cited by 218 publications

(81 citation statements)

References 33 publications

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“…The SMOS-IC product provides daily SSM at 25 km resolution (Fernandez-Moran et al, 2017). The SMOS-IC soil moistures are derived from the SMOS satellite data, based on the algorithm presented by Wigneron et al (2007). This method uses the new calibrated values of the soil roughness and effective scattering albedo parameters presented by Li et al (2020).…”

Section: Discussionmentioning

confidence: 99%

“…Estimation of the root-zone soil moisture from intermittent remotely sensed surface data has focused on the assimilation of such data into land surface models. Many studies now also suggest that constraining those land surface models using various types of earth observations, including vegetation-related earth observations, may lead to a better representation of the root-zone soil moisture (Bolten et al, 2009;Pezij et al, 2019;Wagner et al, 2012). In addition, simplified approaches (e.g., Soil Water Index) have also been developed for obtaining root-zone soil moisture.…”

Section: Introductionmentioning

confidence: 99%

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A multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood model

Eeckman

Roux

Douinot

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. The MARINE (Model of Anticipation of Runoff and INundations for Extreme events) hydrological model is a distributed model dedicated to flash flood simulation. Recent developments of the MARINE model are explored in this work. On one hand, transfers of water through the subsurface, formerly relying on water height, now take place in a homogeneous soil column based on the soil saturation degree (SSF model). On the other hand, the soil column is divided into two layers, which represent, respectively, the upper soil layer and the deep weathered rocks (SSF–DWF model). The aim of the present work is to assess the accuracy of these new representations for the simulation of soil moisture during flash flood events. An exploration of the various products available in the literature for soil moisture estimation is performed. The efficiency of the models for soil saturation degree simulation is estimated with respect to several products either at the local scale or spatially distributed: (i) the gridded soil moisture product provided by the operational modeling chain SAFRAN-ISBA-MODCOU; (ii) the gridded soil moisture product provided by the LDAS-Monde assimilation chain, which is based on the ISBA-A-gs land surface model and assimilating satellite derived data; (iii) the upper soil water content hourly measurements taken from the SMOSMANIA observation network; and (iv) the Soil Water Index provided by the Copernicus Global Land Service (CGLS), which is derived from Sentinel-1 C-SAR and ASCAT satellite data. The case study is performed over two French Mediterranean catchments impacted by flash flood events over the 2017–2019 period. The local comparison of the MARINE outputs with the SMOSMANIA measurements, as well as the comparison at the basin scale of the MARINE outputs with the gridded LDAS-Monde and CGLS data, lead to the following conclusion: both the dynamics and the amplitudes of the soil saturation degree simulated with the SSF and SSF–DWF models are better correlated with both the SMOSMANIA measurements and the LDAS-Monde data than the outputs of the base model. Finally, the soil saturation degree simulated by the two-layers model for the deep layer is compared to the soil saturation degree provided by the LDAS-Monde product at corresponding depths. In conclusion, the developments presented for the representation of subsurface flow in the MARINE model enhance the soil saturation degree simulation during flash floods with respect to both gridded data and local soil moisture measurements.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood model

Eeckman

Roux

Douinot

et al. 2021

Hydrol. Earth Syst. Sci.

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“…A long-term global surface soil moisture (SSM) data record based on satellite mounted active and passive microwave sensors is provided by the European Space Agency Climate Initiative (ESA-CCI) (Liu et al, 2012(Liu et al, , 2011Wagner et al, 2012;ESA-CCI soil moisture, 2015). We use the COM-BINED data set which covers a time period up to and including the year 2013.…”

Section: Soil Moisturementioning

confidence: 99%

“…In addition, it introduces a merged AOD product, combining retrievals from the Deep Blue and Dark Target algorithms to produce a consistent data set covering a multitude of surface types ranging from oceans to bright deserts. A crucial aspect is the problem of spurious AOD trends due to instrumental drift found in earlier MODIS collections (Wang et al, 2012;Zhang and Reid, 2010;Levy et al, 2010), which has been addressed recently (Levy et al, 2013). Another difference to previous studies is the extended time period considered: to verify the persistence of the AOD increase, we take MODIS data up to 2015 into account.…”

Section: Introductionmentioning

confidence: 99%

Review on "Aerosol optical depth trend over the Middle East"

2016

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We use the combined Dark Target/Deep Blue aerosol optical depth (AOD) satellite product of the moderate-resolution imaging spectroradiometer (MODIS) collection 6 to study trends over the Middle East between 2000 and 2015. Our analysis corroborates a previously identified positive AOD trend over large parts of the Middle East during the period 2001 to 2012. We relate the annual AOD to precipitation, soil moisture and surface winds to identify regions where these attributes are directly related to the AOD over Saudi Arabia, Iraq and Iran. Regarding precipitation and soil moisture, a relatively small area in and surrounding Iraq turns out to be of prime importance for the AOD over these countries. Regarding surface wind speed, the African Red Sea coastal area is relevant for the Saudi Arabian AOD. Using multiple linear regression we show that AOD trends and interannual variability can be attributed to soil moisture, precipitation and surface winds, being the main factors controlling the dust cycle. Our results confirm the dust driven AOD trends and variability, supported by a decreasing MODIS-derived Ångström exponent and a decreasing AERONET-derived fine mode fraction that accompany the AOD increase over Saudi Arabia. The positive AOD trend relates to a negative soil moisture trend. As a lower soil moisture translates into enhanced dust emissions, it is not needed to assume growing anthropogenic aerosol and aerosol precursor emissions to explain the observations. Instead, our results suggest that increasing temperature and decreasing relative humidity in the last decade have promoted soil drying, leading to increased dust emissions and AOD; consequently an AOD increase is expected due to climate change.

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“…First, the variational estimation approach directly assimilates TB observations into a water-balanced constrained objective function; therefore, in addition to the ET and drainage function parameters, soil moisture estimates are also provided. Therefore, long-term harmonized soil moisture products and data sets such as the ESA Climate Change Initiative (CCI) (Dorigo et al, 2015;Wagner et al, 2012) are not inputs. Furthermore, to the best our knowledge, no harmonized SMAP-SMOS TB data products exists which can be leveraged.…”

Section: Introductionmentioning

confidence: 99%

Partitioning of Historical Precipitation Into Evaporation and Runoff Based on Hydrologic Dynamics Identified With Recent SMAP Satellite Measurements

Akbar

Gianotti

Salvucci

et al. 2020

Water Resources Research

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Microwave brightness temperature observations from the NASA Soil Moisture Active Passive (SMAP) mission and gauge-based precipitation data over the United States are used to reconstruct the soil water loss function and then historical (1979-2019) hydrological fluxes in the form of evapotranspiration (ET) and drainage (D) are quantified. Over the period of study, with the exception of snowy and hyper-arid regions, we observe a correlation of R 2 > 0.6 between SMAP-precipitation derived drainage estimates and streamflow measurements from the U.S. Geological Survey (USGS). There is a bias between estimated drainage and USGS streamflow with an underestimation of about 1 mm day −1 in southwest United States to 3 mm day −1 in parts of the eastern United States. SMAP-derived sensitivities of drainage and ET partitioning with respect to precipitation anomalies are also calculated. In parts of the Great Plains the drainage partitioning exhibits a near-linear response, while in the southeast United States, the response is nonlinear. Partitioning also is examined for 6 four-digit hydrologic unit basins wherein year-to-year variations in drainage partitioning are shown to be key mediators in translating precipitation anomalies into streamflow anomalies. Observation-driven drainage and ET estimates are obtained without relying on full hydrologic and Land Surface Models (LSMs). This independence (isolation from model parameterization assumptions) provides a path toward using satellite-derived landscape hydrological diagnostics to assess hydrologic models and LSMs as well as to guide their further development.

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Fusion of Active and Passive Microwave Observations to Create an Essential Climate Variable Data Record on Soil Moisture

Cited by 218 publications

References 33 publications

A multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood model

A multi-sourced assessment of the spatiotemporal dynamics of soil moisture in the MARINE flash flood model

Review on "Aerosol optical depth trend over the Middle East"

Partitioning of Historical Precipitation Into Evaporation and Runoff Based on Hydrologic Dynamics Identified With Recent SMAP Satellite Measurements

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