Potential and limitations of multidecadal satellite soil moisture observations for climate model evaluation studies

Abstract. Soil moisture is an essential climate variable of major importance for land-atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observational based soil moisture data set has become available that provides information on soil moisture dynamics from satellite observations (ECVSM). The present study investigates the potential and limitations of this new dataset for several applications for climate model evaluation. We compare soil moisture data from satellite observations, reanalysis data and simulation results from a state-of-the-art climate model and analyze relationships between soil moisture and precipitation anomalies in the different datasets. In a detailed regional study, we show that ECVSM is capable to capture well interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

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Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies

Hydrology and Earth System Sciences ◽

10.5194/hess-17-3523-2013 ◽

2013 ◽

Vol 17 (9) ◽

pp. 3523-3542 ◽

Cited By ~ 77

Author(s):

A. Loew ◽

T. Stacke ◽

W. Dorigo ◽

R. de Jeu ◽

S. Hagemann

Keyword(s):

Soil Moisture ◽

Model Evaluation ◽

Climate Model ◽

Global Climate Models ◽

Satellite Observations ◽

Surface Model ◽

Climate Variable ◽

Soil Moisture Dynamics ◽

Climate Model Evaluation ◽

Moisture Dynamics

Abstract. Soil moisture is an essential climate variable (ECV) of major importance for land–atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observation-based soil moisture dataset has become available that provides information on soil moisture dynamics from satellite observations (ECVSM, essential climate variable soil moisture). The present study investigates the potential and limitations of this new dataset for several applications in climate model evaluation. We compare soil moisture data from satellite observations, reanalysis and simulations from a state-of-the-art land surface model and analyze relationships between soil moisture and precipitation anomalies in the different dataset. Other potential applications like model parameter optimization or model initialization are not investigated in the present study. In a detailed regional study, we show that ECVSM is capable to capture well the interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

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A dense network of cosmic-ray neutron sensors for soil moisture observation in a pre-alpine headwater catchment in Germany

10.5194/essd-2020-48 ◽

2020 ◽

Author(s):

Benjamin Fersch ◽

Till Francke ◽

Maik Heistermann ◽

Martin Schrön ◽

Veronika Döpper ◽

...

Keyword(s):

Soil Moisture ◽

Hydrological Modeling ◽

Root Zone ◽

Spatial Scales ◽

Cosmic Ray ◽

Dense Network ◽

Data Set ◽

Soil Moisture Dynamics ◽

Moisture Dynamics ◽

Headwater Catchment

Abstract. Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while well established sensors typically suffer from a small spatial support. With a sensor footprint up to several hectares, Cosmic-Ray Neutron Sensing (CRNS) is an emerging technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-alpine Rott headwater catchment in Southern Germany which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, that network was designed to study root zone soil moisture dynamics at the catchment-scale. The observations of the dense CRNS network were complemented by extensive measurements that allow to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from Unmanned Areal Systems (UAS), permanent and temporary wireless sensor networks, profile probes as well as comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive dataset to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatio-temporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land – atmosphere exchange processes. The data set is available through EUDAT, splitted into the two subsets https://doi.org/10.23728/b2share.85fe0f9dac0f48df9215c17e65d1f1e1 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.93ed99e486904d48a8a6a68083066198 (Fersch et al., 2020b).

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A dense network of cosmic-ray neutron sensors for soil moisture observation in a highly instrumented pre-Alpine headwater catchment in Germany

Earth System Science Data ◽

10.5194/essd-12-2289-2020 ◽

2020 ◽

Vol 12 (3) ◽

pp. 2289-2309

Author(s):

Benjamin Fersch ◽

Till Francke ◽

Maik Heistermann ◽

Martin Schrön ◽

Veronika Döpper ◽

...

Keyword(s):

Soil Moisture ◽

Hydrological Modeling ◽

Root Zone ◽

Spatial Scales ◽

Cosmic Ray ◽

Dense Network ◽

Data Set ◽

Soil Moisture Dynamics ◽

Moisture Dynamics ◽

Headwater Catchment

Abstract. Monitoring soil moisture is still a challenge: it varies strongly in space and time and at various scales while conventional sensors typically suffer from small spatial support. With a sensor footprint up to several hectares, cosmic-ray neutron sensing (CRNS) is a modern technology to address that challenge. So far, the CRNS method has typically been applied with single sensors or in sparse national-scale networks. This study presents, for the first time, a dense network of 24 CRNS stations that covered, from May to July 2019, an area of just 1 km2: the pre-Alpine Rott headwater catchment in Southern Germany, which is characterized by strong soil moisture gradients in a heterogeneous landscape with forests and grasslands. With substantially overlapping sensor footprints, this network was designed to study root-zone soil moisture dynamics at the catchment scale. The observations of the dense CRNS network were complemented by extensive measurements that allow users to study soil moisture variability at various spatial scales: roving (mobile) CRNS units, remotely sensed thermal images from unmanned areal systems (UASs), permanent and temporary wireless sensor networks, profile probes, and comprehensive manual soil sampling. Since neutron counts are also affected by hydrogen pools other than soil moisture, vegetation biomass was monitored in forest and grassland patches, as well as meteorological variables; discharge and groundwater tables were recorded to support hydrological modeling experiments. As a result, we provide a unique and comprehensive data set to several research communities: to those who investigate the retrieval of soil moisture from cosmic-ray neutron sensing, to those who study the variability of soil moisture at different spatiotemporal scales, and to those who intend to better understand the role of root-zone soil moisture dynamics in the context of catchment and groundwater hydrology, as well as land–atmosphere exchange processes. The data set is available through the EUDAT Collaborative Data Infrastructure and is split into two subsets: https://doi.org/10.23728/b2share.282675586fb94f44ab2fd09da0856883 (Fersch et al., 2020a) and https://doi.org/10.23728/b2share.bd89f066c26a4507ad654e994153358b (Fersch et al., 2020b).

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