scholarly journals An improved perspective in the spatial representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution “all weather” product

2019 ◽  
Vol 23 (1) ◽  
pp. 255-275 ◽  
Author(s):  
Samiro Khodayar ◽  
Amparo Coll ◽  
Ernesto Lopez-Baeza
Keyword(s):  
Soil Moisture ◽  
Initial Conditions ◽  
Temporal Distribution ◽  
Added Value ◽  
Point Scale ◽  
Spatio Temporal ◽  
Analysis System ◽  
June July ◽  
Svat Model

Abstract. This study uses the synergy of multi-resolution soil moisture (SM) satellite estimates from the Soil Moisture Ocean Salinity (SMOS) mission, a dense network of ground-based SM measurements, and a soil–vegetation–atmosphere transfer (SVAT) model, SURFEX (externalized surface), module ISBA (interactions between soil, biosphere and atmosphere), to examine the benefits of the SMOS level 4 (SMOS-L4) version 3.0, or “all weather” high-resolution soil moisture disaggregated product (SMOS-L43.0; ∼1 km). The added value compared to SMOS level 3 (SMOS-L3; ∼25 km) and SMOS level 2 (SMOS-L2; ∼15 km) is investigated. In situ SM observations over the Valencia anchor station (VAS; SMOS calibration and validation – Cal/Val – site in Europe) are used for comparison. The SURFEX (ISBA) model is used to simulate point-scale surface SM (SSM) and, in combination with high-quality atmospheric information data, namely from the European Centre for Medium-Range Weather Forecasts (ECMWF) and the Système d'analyse fournissant des renseignements atmosphériques à la neige (SAFRAN) meteorological analysis system, to obtain a representative SSM mapping over the VAS. The sensitivity to realistic initialization with SMOS-L43.0 is assessed to simulate the spatial and temporal distribution of SSM. Results demonstrate the following: (a) All SMOS products correctly capture the temporal patterns, but the spatial patterns are not accurately reproduced by the coarser resolutions, probably in relation to the contrast with point-scale in situ measurements. (b) The potential of the SMOS-L43.0 product is pointed out to adequately characterize SM spatio-temporal variability, reflecting patterns consistent with intensive point-scale SSM samples on a daily timescale. The restricted temporal availability of this product dictated by the revisit period of the SMOS satellite compromises the averaged SSM representation for longer periods than a day. (c) A seasonal analysis points out improved consistency during December–January–February and September–October–November, in contrast to significantly worse correlations in March–April–May (in relation to the growing vegetation) and June–July–August (in relation to low SSM values < 0.1 m3 m−3 and low spatial variability). (d) The combined use of the SURFEX (ISBA) SVAT model with the SAFRAN system, initialized with SMOS-L43.0 1 km disaggregated data, is proven to be a suitable tool for producing regional SM maps with high accuracy, which could be used as initial conditions for model simulations, flood forecasting, crop monitoring and crop development strategies, among others.

scholarly journals An improved perspective in the representation of soil moisture: potential added value of SMOS disaggregated 1 km resolution product

2018 ◽  
Author(s):  
Samiro Khodayar ◽  
Amparo Coll ◽  
Ernesto Lopez-Baeza
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Temporal Distribution ◽  
Added Value ◽  
Point Scale ◽  
Spatio Temporal ◽  
Analysis System ◽  
June July ◽  
Realistic Information

Abstract. This study uses the synergy of multiresolution soil moisture (SM) satellite estimates from the Soil Moisture Ocean Salinity (SMOS) mission, a dense network of ground-based SM measurements, and a Soil Vegetation Atmosphere Transfer (SVAT) model, SURFEX (Externalized Surface) – module ISBA (Interactions between Soil-Biosphere-Atmosphere), to examine, i) the comparison and suitability of different operational SMOS SM products to provide realistic information on the water content of the soil as well as the added value of the newly released SMOS Level 4 3.0 all weather disaggregated ~ 1 km SM (SMOS_L43.0), and ii) its potential impact for improving uncertainty associated to SM initialization in land surface modelling. Three different data products from SMOS-L3 (~ 25 km), L2 (~ 15 km), and disaggregated L4 3.0 (~ 1 km) are investigated. In situ SM observations over the Valencia Anchor Station (VAS; SMOS Calibration/Validation (Cal/Val) site in Europe) are used for comparison. The SURFEX-ISBA model is used to simulate point-scale surface SM (SSM) and, in combination with high-quality atmospheric information data, namely ECMWF and the SAFRAN meteorological analysis system, to obtain a representative SSM mapping over the VAS. The sensitivity to SSM initialization, particularly to realistic initialization with SMOS_L43.0 to simulate the spatial and temporal distribution of SSM is assessed. Results demonstrate: (a) all SMOS products correctly capture the temporal patterns, but, the spatial patterns are not accurately reproduced by the coarser resolutions probably in relation to the contrast with point-scale in situ measurements. (b) The potential of SMOS-L43.0 product is pointed out to adequately characterize SM spatio-temporal variability reflecting patterns consistent with intensive point scale SSM samples on a daily time scale. The restricted temporal availability of this product dictated by the revisit period of the SMOS satellite compromises the averaged SSM representation for longer periods than a day. (c) A seasonal analysis points out improved consistency during December-January-February and September-October-November in contrast to significantly worse correlations in March-April-May (in relation to the growing vegetation) and June-July-August (in relation to low SSM values

scholarly journals Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

2010 ◽  
Vol 14 (5) ◽  
pp. 831-846 ◽  
Author(s):  
S. Juglea ◽  
Y. Kerr ◽  
A. Mialon ◽  
J.-P. Wigneron ◽  
E. Lopez-Baeza ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Soil ◽  
Temporal Distribution ◽  
Sea Surface Salinity ◽  
Surface Soil Moisture ◽  
Surface Salinity ◽  
Anchor Station ◽  
Svat Model

Abstract. The main goal of the SMOS (Soil Moisture and Ocean Salinity) mission is to deliver global fields of surface soil moisture and sea surface salinity using L-band (1.4 GHz) radiometry. Within the context of the Science preparation for SMOS, the Valencia Anchor Station (VAS) experimental site, in Spain, was chosen to be one of the main test sites in Europe for Calibration/Validation (Cal/Val) activities. In this framework, the paper presents an approach consisting in accurately simulating a whole SMOS pixel by representing the spatial and temporal heterogeneity of the soil moisture fields over the wide VAS surface (50×50 km2). Ground and meteorological measurements over the area are used as the input of a Soil-Vegetation-Atmosphere-Transfer (SVAT) model, SURFEX (Externalized Surface) - module ISBA (Interactions between Soil-Biosphere-Atmosphere) to simulate the spatial and temporal distribution of surface soil moisture. The calibration as well as the validation of the ISBA model are performed using in situ soil moisture measurements. It is shown that a good consistency is reached when point comparisons between simulated and in situ soil moisture measurements are made. Actually, an important challenge in remote sensing approaches concerns product validation. In order to obtain an representative soil moisture mapping over the Valencia Anchor Station (50×50 km2 area), a spatialization method is applied. For verification, a comparison between the simulated spatialized soil moisture and remote sensing data from the Advanced Microwave Scanning Radiometer on Earth observing System (AMSR-E) and from the European Remote Sensing Satellites (ERS-SCAT) is performed. Despite the fact that AMSR-E surface soil moisture product is not reproducing accurately the absolute values, it provides trustworthy information on surface soil moisture temporal variability. However, during the vegetation growing season the signal is perturbed. By using the polarization ratio a better agreement is obtained. ERS-SCAT soil moisture products are also used to be compared with the simulated spatialized soil moisture. However, the lack of soil moisture data from the ERS-SCAT sensor over the area (45 observations for one year) prevented capturing the soil moisture variability.

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

Geoderma ◽  
2012 ◽  
Vol 170 ◽  
pp. 195-205 ◽  
Author(s):  
Gary C. Heathman ◽  
Michael H. Cosh ◽  
Eunjin Han ◽  
Thomas J. Jackson ◽  
Lynn McKee ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Soil ◽  
Spatiotemporal Analysis ◽  
Surface Soil Moisture ◽  
Field Scale ◽  
Point Scale

scholarly journals Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring

2018 ◽  
Vol 10 (12) ◽  
pp. 1950 ◽  
Author(s):  
Luca Cenci ◽  
Luca Pulvirenti ◽  
Giorgio Boni ◽  
Nazzareno Pierdicca
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Added Value ◽  
Sar Images ◽  
Radar Images ◽  
Spatio Temporal ◽  
Set Up ◽  
The Impact ◽  
Hydrological Applications

The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provide a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations a day, with a spatial resolution of 100 m, maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the ones obtained by assimilating POLAR SAR-like SM maps.

scholarly journals Assessment of Multi-Scale SMOS and SMAP Soil Moisture Products across the Iberian Peninsula

2020 ◽  
Vol 12 (3) ◽  
pp. 570 ◽  
Author(s):  
Gerard Portal ◽  
Thomas Jagdhuber ◽  
Mercè Vall-llossera ◽  
Adriano Camps ◽  
Miriam Pablos ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Iberian Peninsula ◽  
Spatial Scale ◽  
Temporal Dynamics ◽  
Microwave Radiometer ◽  
Added Value ◽  
Optical Data ◽  
Enhanced Resolution ◽  
The Impact

In the last decade, technological advances led to the launch of two satellite missions dedicated to measure the Earth’s surface soil moisture (SSM): the ESA’s Soil Moisture and Ocean Salinity (SMOS) launched in 2009, and the NASA’s Soil Moisture Active Passive (SMAP) launched in 2015. The two satellites have an L-band microwave radiometer on-board to measure the Earth’s surface emission. These measurements (brightness temperatures TB) are then used to generate global maps of SSM every three days with a spatial resolution of about 30–40 km and a target accuracy of 0.04 m3/m3. To meet local applications needs, different approaches have been proposed to spatially disaggregate SMOS and SMAP TB or their SSM products. They rely on synergies between multi-sensor observations and are built upon different physical assumptions. In this study, temporal and spatial characteristics of six operational SSM products derived from SMOS and SMAP are assessed in order to diagnose their distinct features, and the rationale behind them. The study is focused on the Iberian Peninsula and covers the period from April 2015 to December 2017. A temporal inter-comparison analysis is carried out using in situ SSM data from the Soil Moisture Measurements Station Network of the University of Salamanca (REMEDHUS) to evaluate the impact of the spatial scale of the different products (1, 3, 9, 25, and 36 km), and their correspondence in terms of temporal dynamics. A spatial analysis is conducted for the whole Iberian Peninsula with emphasis on the added-value that the enhanced resolution products provide based on the microwave-optical (SMOS/ERA5/MODIS) or the active–passive microwave (SMAP/Sentinel-1) sensor fusion. Our results show overall agreement among time series of the products regardless their spatial scale when compared to in situ measurements. Still, higher spatial resolutions would be needed to capture local features such as small irrigated areas that are not dominant at the 1-km pixel scale. The degree to which spatial features are resolved by the enhanced resolution products depend on the multi-sensor synergies employed (at TB or soil moisture level), and on the nature of the fine-scale information used. The largest disparities between these products occur in forested areas, which may be related to the reduced sensitivity of high-resolution active microwave and optical data to soil properties under dense vegetation.

scholarly journals The AOTF-based NO<sub>2</sub> camera

2016 ◽  
Author(s):  
Emmanuel Dekemper ◽  
Jurgen Vanhamel ◽  
Bert Van Opstal ◽  
Didier Fussen
Keyword(s):  
Temporal Resolution ◽  
Temporal Distribution ◽  
Tunable Filter ◽  
Added Value ◽  
Dynamic Features ◽  
Emission Fluxes ◽  
New Type ◽  
Measurement Principle ◽  
Extended Sources ◽  
Spatio Temporal

Abstract. The abundance of NO2 in the boundary layer relates to air quality and pollution sources monitoring. Observing the spatio-temporal distribution of NO2 above well-delimited (flue gas stacks, volcanoes, ships) or more extended sources (cities) allows for several applications: monitoring emission fluxes or studying the plume dynamic chemistry and its transport. So far, most attempts to map the NO2 field from the ground have been made with visible-light scanning spectrometers. Benefiting from a high retrieval accuracy, they only achieve a relatively low temporal resolution that hampers the detection of dynamic features. We present a new type of passive remote sensing instrument aiming at the measurement of the 2-D distributions of NO2 slant column densities (SCD) with a high spatio-temporal resolution. The measurement principle has strong similarities with the popular filter-based SO2 camera as it relies on spectral images taken at wavelengths where the molecule absorption cross-section is different. Contrary to the SO2 camera, the spectral selection is performed by an acousto-optical tunable filter (AOTF) capable of resolving the target molecule's spectral features. The NO2 camera capabilities are demonstrated by imaging the NO2 abundance in the plume of a coal-fired power plant. During this experiment, the 2-D distribution of the NO2 SCD was retrieved with a temporal resolution of 3 minutes and a spatial sampling of 50 cm (over a 250 x 250 m2 area). The detection limit was close to 5 x 1016 molecules cm−2, with a maximum detected SCD of 4 x 1017 molecules cm−2. Illustrating the added-value of the NO2 camera measurements, the data reveal the dynamics of the NO to NO2 conversion in the early plume with an unprecedent resolution: from its release in the air, and for 100 m upwards, the observed NO2 plume concentration increased at a rate of 0.75–1.25 g s−1. In joint campaigns with SO2 cameras, the NO2 camera could also help in removing the bias introduced by the NO2 interference in the SO2 measurements.

scholarly journals Monitoring and Forecasting the Impact of the 2018 Summer Heatwave on Vegetation

2019 ◽  
Author(s):  
Clément Albergel ◽  
Emanuel Dutra ◽  
Bertrand Bonan ◽  
Yongjun Zheng ◽  
Simon Munier ◽  
...  
Keyword(s):  
Soil Moisture ◽  
High Resolution ◽  
Land Surface ◽  
Western Europe ◽  
Initial Conditions ◽  
Added Value ◽  
Area Index ◽  
Long Time ◽  
Land Data Assimilation System ◽  
The Impact

This study aims to assess the potential of the LDAS-Monde a land data assimilation system developed by M&eacute;t&eacute;o-France to monitor the impact of the 2018 summer heatwave over western Europe vegetation state. The LDAS-Monde is forced by the ECMWF&rsquo;s (i) ERA5 reanalysis, and (ii) the Integrated Forecasting System High Resolution operational analysis (IFS-HRES), used in conjunction with the assimilation of Copernicus Global Land Service (CGLS) satellite derived products, namely the Surface Soil Moisture (SSM) and the Leaf Area Index (LAI). Analysis of long time series of satellite derived CGLS LAI (2000-2018) and SSM (2008-2018) highlights marked negative anomalies for July 2018 affecting large areas of North Western Europe and reflects the impact of the heatwave. Such large anomalies spreading over a large part of the considered domain have never been observed in the LAI product over this 18-yr period. The LDAS-Monde land surface reanalyses were produced at spatial resolutions of 0.25&deg;x0.25&deg; (January 2008 to October 2018) and 0.10&deg;x0.10&deg; (April 2016 to December 2018). Both configuration of the LDAS-Monde forced by either ERA5 or HRES capture well the vegetation state in general and for this specific event, with HRES configuration exhibiting better monitoring skills than ERA5 configuration. The consistency of ERA5 and IFS HRES driven simulations over the common period (April 2016 to October 2018) allowed to disentangle and appreciate the origin of improvements observed between the ERA5 and HRES. Another experiment, down-scaling ERA5 to HRES spatial resolutions, was performed. Results suggest that land surface spatial resolution is key (e.g. associated to a better representation of the land cover, topography) and using HRES forcing still enhance the skill. While there are advantages in using HRES, there is added value in down-scaling ERA5, which can provide consistent, long term, high resolution land reanalysis. If the improvement from LDAS-Monde analysis on control variables (soil moisture from layers 2 to 8 of the model representing the first meter of soil and LAI) from the assimilation of SSM and LAI was expected, other model variables benefit from the assimilation through biophysical processes and feedbacks in the model. Finally, we also found added value of initializing 8-day land surface HRES driven forecasts from LDAS-Monde analysis when compared with model only initial conditions.

Precipitation diurnal cycle and associated valley wind circulations over an Andean glacier region (Antizana, Ecuador)

2020 ◽  
Author(s):  
Clementine Junquas ◽  
Maria Belen Heredia ◽  
Thomas Condom ◽  
Jhan Carlo Espinoza ◽  
Jean Carlos Ruiz ◽  
...  
Keyword(s):  
Diurnal Cycle ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Regional Climate ◽  
Temporal Distribution ◽  
Tropical Andes ◽  
Time Step ◽  
Valley Wind ◽  
Spatio Temporal

&lt;p&gt;In the tropical Andes, the evolution of the mass balance of glaciers is strongly controlled by the variability of precipitation and humidity transport. It is therefore crucial to better understand the main patterns of precipitation in terms of spatio-temporal distribution at the local scale. In this study, we focus on the region of the Antizana ice cap, located in the Equatorial Andes about 50 km east of the city of Quito (Ecuador). In addition, the Antizana region is located in a very complex zonal climate gradient, with the Pacific Ocean to the west and the humid Amazonian plains to the east, including an area of &amp;#8203;&amp;#8203;maximum precipitation on the Amazonian slope, also called &quot;Precipitation hotspot&quot;.&lt;/p&gt;&lt;p&gt;In this study, we perform dynamical downscaling using a Regional Climate Model (RCM) to improve the understanding of the atmospheric processes controlling the spatio-temporal variability of precipitation. The WRF (Weather Research and Forecasting) model is used to perform a set of ten experiments with four one-way nesting domains (27km, 9km, 3km, 1km), with the highest resolution domain centered on the Antizana mountain, for the year 2005. For the model validation, we use the 3B42 satellite product of the Tropical Rainfall Measuring Mission (TRMM) at 3-hourly time step, the ORE Antizana meteorological station (SNO GLACIOCLIM, LMI GREATICE) at hourly time step, and 2 meteorological in-situ stations, installed by the Instituto Nacional de Metereolog&amp;#237;a e Hidrologia (INAMHI) in the Antizana region, with a complete chronology of daily precipitation (mm/day) during the 2005 year.&lt;/p&gt;&lt;p&gt;We test different forcings of DEM (Digital Elevation Model), microphysic schemes, Cumulus schemes and convection-permitting simulation, and radiation/slope dependent options. The analysis focuses in particular on how the different representation of thermally driven valley wind circulation can affect the diurnal cycle of precipitation at the ORE Antizana in-situ station. The influence of the diurnal cycle of the regional humidity flux on the mountain precipitation is also analyzed.&lt;/p&gt;

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