L-band Microwave Research Articles

Impact of Soil Permittivity and Temperature Profile on L-Band Microwave Emission of Frozen Soil

An unexplored aspect of L-band microwave emission is the impact of soil moisture and soil temperature (SMST) profile dynamics on diurnal brightness temperature ( T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> ) signatures of frozen soil. This study investigates this effect by comparing the T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> simulations of layered ( T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,l</sub> ) and uniform ( T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,u</sub> ) soils using a newly developed integrated land emission model. The multilayer Wilheit model and the single-layer Fresnel model are adopted to compute the smooth soil reflectivity for the layered and uniform soils, respectively. A four-phase dielectric mixing model is used to calculate the soil permittivity ( ε <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ). A data set of concurrent ELBARA-III T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> and SMST profile measurements performed in a seasonally frozen Tibetan meadow ecosystem is used for the analysis. The simulated T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,l</sub> considering SMST profile information captures well the ELBARA-III measurements with low biases (≤6 K) and high correlations ( R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ≥ 0.88). T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,u</sub> produced based on the Fresnel model using the soil moisture of 2.5 cm is more consistent with the T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,l</sub> . The sensitivity test of averaging SMST profile below 2.5 cm leads to maximum differences of 2 K in T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,l</sub> simulations, indicating that the T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> variations are primary dominated by the SMST dynamics at the surface layer. A sensitivity test of the Wilheit model to different ε <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> parameterizations shows that the dielectric model of Zhang et al. is comparable to the four-phase dielectric model in simulating T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B,l</sub> , while the Mironov et al. 's model demonstrates larger biases for frozen soil with, on average, 2.2% clay content, 49.7% sand content, and a bulk density of 1 g·cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> .

Evaluation of GEOS-Simulated L-Band Microwave Brightness Temperature Using Aquarius Observations over Non-Frozen Land across North America

L-band brightness temperature (Tb) is one of the key remotely-sensed variables that provides information regarding surface soil moisture conditions. In order to harness the information in Tb observations, a radiative transfer model (RTM) is investigated for eventual inclusion into a data assimilation framework. In this study, Tb estimates from the RTM implemented in the NASA Goddard Earth Observing System (GEOS) were evaluated against the nearly four-year record of daily Tb observations collected by L-band radiometers onboard the Aquarius satellite. Statistics between the modeled and observed Tb were computed over North America as a function of soil hydraulic properties and vegetation types. Overall, statistics showed good agreement between the modeled and observed Tb with a relatively low, domain-average bias (0.79 K (ascending) and −2.79 K (descending)), root mean squared error (11.0 K (ascending) and 11.7 K (descending)), and unbiased root mean squared error (8.14 K (ascending) and 8.28 K (descending)). In terms of soil hydraulic parameters, large porosity and large wilting point both lead to high uncertainty in modeled Tb due to the large variability in dielectric constant and surface roughness used by the RTM. The performance of the RTM as a function of vegetation type suggests better agreement in regions with broadleaf deciduous and needleleaf forests while grassland regions exhibited the worst accuracy amongst the five different vegetation types.

Soil moisture retrievals using ALOS2-ScanSAR and MODIS synergy over Tibetan Plateau

This paper investigates the soil moisture retrievals over Tibetan Plateau using multi-temporal ALOS2-PALSAR2 data acquired in ScanSAR mode, in contrary to the commonly used StripMap SAR imaging mode. Considering the dual-polarimetry with limited observables, the surface roughness parameters such as the RMS height and auto-correlation length are first estimated by optimizing the semi-empirical Oh2004 model applied to the ALOS2 data acquired under bare soil condition. The vegetation water content corresponding to each ALOS2 acquisition time is derived from an empirical model applied to the temporally interpolated MODIS NDVI data. Then, the obtained roughness and vegetation optical depth are substituted into the Water Cloud Model which we modified by adding a double-bounce component according to the L-band scattering processes to retrieve the effective scattering albedo and soil moisture. The results show that the optimized surface RMS height and the associated slope are negatively related to a dual-angular radar index ΔHH, indicating the feasibility to optimize the relatively stable surface roughness parameters before retrieving the soil moisture dynamics. The obtained vegetation optical depth which is cross-validated against a normalized cross-polarized radar descriptor indicates a significant increase from May to August, in response to the vegetation phenological growth. Furthermore, the time-variable scattering albedo is less than 0.08, and slightly increases with the vegetation development. By accounting for the double-bounce component, the retrieved soil moisture better agrees with the ground measurements with R = 0.89 and RMSE = 0.058 m3/m3, but exhibits an overestimation issue for the soil moisture higher than 0.35 m3/m3 due to the saturation of SAR signal and the relatively strong vegetation cover. A positive correspondence (R = 0.81) between the retrieved soil moisture and the interpolated NDVI was found, verifying their close coupling in the soil-vegetation system. This study deepens the insights in the potential integration between the optical and L-band microwave observations to retrieve soil moisture over vegetated area.

Deployment mechanism for a L-band helix antenna in 1-Unit Cubesat

Recently, there is a renewed interest in Earth Observation (EO) of the cryosphere as a proxy of global warming, soil moisture for agriculture and desertification studies, and biomass for carbon storage. Global Navigation Satellite System-Reflectometry (GNSS-R) and L-band microwave Radiometry have been used to perform these measurements. However, it is expected that the combination of both can largely improve current observations.3Cat-4 mission aims at addressing this technology challenge by integrating a combined GNSS-R and Microwave Radiometer payload into a 1-Unit CubeSat. One of the greatest challenges is the design of an antenna that respects the envelope and stowage requirements of 1-Unit CubeSat, being able to work in the different frequency bands: Global Positioning System (GPS) L1-band (1575 MHz), GPS L2-band (1227 MHz), and microwave radiometry at 1400–1427 MHz. After a trade-off analysis, a helix antenna was found to be the most suitable option. This antenna has 11 turns equally distributed with 68.1 mm of diameter. This design generates an antenna with 506 mm of axial length, providing the maximum radiation gain in the endfire direction. Additionally, a counterweight is added at the tip of the antenna to enhance the directivity, and it is used as gravity gradient technique. The deployment of this antenna in vacuum and extreme temperature conditions is the greatest mechanical challenge that needs to be addressed for the success of the mission.This work presents a mechanical solution that enables to deploy the helix antenna from 25.5 mm (stowed configuration) to the final 506 mm (deployed configuration). By sequentially deploying different parts of the antenna, the final configuration is reached without impacting the attitude pointing of the CubeSat. This is accomplished using dyneema lines that are melted sequentially by commands. In addition, the deployment velocity, acceleration, and waving are presented as part of its characterization. The current test results in a Thermal Vacuum Chamber indicate also that the deployment can be achieved in −35 °C. The 3Cat-4 CubeSat, with the L-band helix antenna, will be launched in Q4 2020 as part of the “Fly Your Satellite!” program of the European Space Agency (ESA).

Seasonal evolution of L-band SAR backscatter over landfast Arctic sea ice

We construct and present the first baseline, time series evolution of L-band SAR microwave backscatter (σ0HH) for landfast Arctic first-year (FYI) and multi-year (MYI) sea ice from ALOS PALSAR. We compare the winter to freeze-up seasonal L-band σ0HH signatures with C-band RADARSAT-2 SAR imagery and Ku-band QuikSCAT scatterometer data. We also explored the utility of L-band σ0HH to detect FYI and MYI melt onset dates. For both ice types, L-band exhibited a similar σ0HH evolution to C- and Ku-bands. A rise in L-band σ0HH was observed from winter to melt onset, however, with a lower magnitude attributed to the larger penetration of L-band microwaves through the snow-covered sea ice medium. Over FYI, L-band σ0HH exhibited the most robust response and greater diversity in melt onset signature, compared to C- and Ku-bands. Over MYI, L-band σ0HH declined during the winter to melt onset transition contrasting the C- and Ku-band evolution of σ0HH during melt onset. Although, a distinct L-band σ0HH response was not found during pond onset, a very strong σ0HH response was found during sea ice break-up, which could operationally be utilized to identify sea ice break-up timing. During freeze-up, L-band σ0HH showed greater diversity compared to C- and Ku-bands. Our study also found that, L-band detected melt onset dates were up to 6 days later than C- and Ku-band detected dates, for both ice types. The melt response was the strongest at L-band for FYI, where C-band detected a robust melt onset date for MYI. Therefore, for operational sea ice monitoring, L-band suits better for FYI, whereas C-band is still a better choice for MYI. In the warming Arctic, where FYI has become the dominant ice type, L-band demonstrates promise to be the optimal choice for sea ice operational monitoring with high spatiotemporal data acquisition from existing, upcoming and proposed L-band SAR missions.

An Improved Conversion Relationship between Tropical Cyclone Intensity Index and Maximum Wind Speed for the Advanced Dvorak Technique in the Northwestern Pacific Ocean Using SMAP Data

The Advanced Dvorak Technique (ADT) uses geostationary satellite data to estimate tropical cyclone (TC) intensity owing to the difficulty in directly observing a TC’s internal structure. This study presents a new relationship (Hong and Ryu scale) between the current intensity (CI) number and estimated maximum wind speed (MWS) of TCs over the northwestern Pacific region; the CI number is the TC intensity index retrieved from the ADT. The Soil Moisture Active Passive (SMAP) with the L-band (1.4 GHz) microwave radiometer, is used to calibrate and produce the new Hong and Ryu scale for the ADT algorithm. Japan Meteorological Agency (JMA) best track MWS data, SMAP sea surface wind speed estimates, and ADT’s TC intensity data between 2015–2018 are spatiotemporally collocated for the calibration process. The CI number is derived from the Korea Meteorological Administration (KMA) operational ADT which uses the Koba scale to convert to the MWS for validation against the MWS of the best track. The conversion relationships between CI number and SMAP MWS, and between SMAP MWS and MWS of the best track a derived, and the MWS of two ADTs with the Koba and Hong and Ryu scales are then estimated using the same CI numbers with TC intensity data between 2015–2018. Finally, the MWS of the ADT with the Koba scale and the new ADT with the proposed Hong and Ryu scale are independently validated on best track data from 2013–2014. The MWS root mean square error (RMSE) is 4.39 m/s for the new ADT using the Hong and Ryu scale, which is lower than 4.77 m/s RMSE of the ADT using the Koba scale. Hence, the ADT using the Hong and Ryu scale can modestly improve the accuracy of TC intensity analysis in the northwestern Pacific region.

Surface Roughness Effect on L-Band Multiangular Brightness Temperature Modeling and Soil Liquid Water Retrieval of Frozen Soil

A less explored aspect of L-band microwave emission is the surface roughness effect on the multiangular brightness temperature (T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sup> ) modeling and retrieval of liquid water content (θ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">liq</sub> ) in frozen soil. This letter investigates this effect based on a data set of multiangular ETH L-band radiometer (ELBARA-III) T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sup> measurements performed in a seasonally frozen Tibetan meadow ecosystem. The surface roughness effect is first investigated via comparing the performance of the HQN model and Shi's parameterization of the integral equation model in simulating the measured T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sup> signatures. Overestimations are noted for the two model simulations at the vertical polarization in comparison to the ELBARA-III measurements, and Shi's model with Gaussian autocorrelation function shows better performance especially for the vertical polarization at large incidence angles. The HQN model is then calibrated with the multiangular T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sup> measurements, which leads to h = 0 and Q > 0 that depends on the polarization. As such, the noncoherent emission contribution to cross-polarization mixing can be accounted for by the HQN model. Furthermore, θ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">liq</sub> retrievals are derived from the multiangular T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sup> measurements using the default and optimized HQN model and Shi's model and compared to the in situ θ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">liq</sub> . Unbiased root-mean-square errors of less than 0.025 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> are obtained for these retrievals, which are well within the satellite mission requirements. This study demonstrates that the multiangular T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">p</sup> modeling can be enhanced with site-specific calibration of the HQN model that also leads to the improvement of the θ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">liq</sub> retrievals, and consideration of polarization mixing is necessary for L-band emission modeling.

Assimilating SMOS Brightness Temperature for Hydrologic Model Parameters and Soil Moisture Estimation with an Immune Evolutionary Strategy

Hydrological models play an essential role in data assimilation (DA) systems. However, it is a challenging task to acquire the distributed hydrological model parameters that affect the accuracy of the simulations at a grid scale. Remote sensing data provide an ideal observation for DA to estimate parameters and state variables. In this study, a special assimilation scheme was proposed to jointly estimate parameters and soil moisture (SM) by assimilating brightness temperature (TB) from the Soil Moisture and Ocean Salinity (SMOS) mission. Variable infiltration capacity (VIC) hydrological model and L-band microwave emission of the biosphere model (L-MEB) are coupled as model and observation operators, respectively. The scheme combines two stages of estimators, one for the static model parameters and the other for the dynamic state variables. The estimators approximate the posterior probability distribution of an unknown target through sequential Monte Carlo (SMC) sampling. Markov chain Monte Carlo (MCMC) and immune evolution strategy are embedded in both stages to solve particle impoverishment problems. To evaluate the effectiveness of the scheme, the estimated SM sets are compared with in-situ observations and SMOS products in Maqu on the Tibetan Plateau. Specifically, the root mean square error decreased from 0.126 to 0.087 m3m−3 for surface SM, with a slight impact on the root zone. The temporal correlation between DA results and in-situ measurements increased to 0.808 and 0.755 for surface SM (+0.057) and root zone SM (+0.040), respectively. The results demonstrate that assimilating TB has tremendous potential as an approach to improve the estimation of distributed model parameters and SMs of surface and root zone at a grid scale, and the immune evolution strategy is effective for increasing the accuracy of approximation in sampling.

The Potential of Space-Based Sea Surface Salinity on Monitoring the Hudson Bay Freshwater Cycle

Hudson Bay (HB) is the largest semi-inland sea in the Northern Hemisphere, connecting with the Arctic Ocean through the Foxe Basin and the northern Atlantic Ocean through the Hudson Strait. HB is covered by ice and snow in winter, which completely melts in summer. For about six months each year, satellite remote sensing of sea surface salinity (SSS) is possible over open water. SSS links freshwater contributions from river discharge, sea ice melt/freeze, and surface precipitation/evaporation. Given the strategic importance of HB, SSS has great potential in monitoring the HB freshwater cycle and studying its relationship with climate change. However, SSS retrieved in polar regions (poleward of 50°) from currently operational space-based L-band microwave instruments has large uncertainty (~ 1 psu) mainly due to sensitivity degradation in cold water (&lt;5°C) and sea ice contamination. This study analyzes SSS from NASA Soil Moisture Active and Passive (SMAP) and European Space Agency (ESA) Soil Moisture and Ocean Salinity(SMOS) missions in the context of HB freshwater contents. We found that the main source of the year-to-year SSS variability is sea ice melting, in particular, the onset time and places of ice melt in the first couple of months of open water season. The freshwater contribution from surface forcing P-E is smaller in magnitude comparing with sea ice contribution but lasts on longer time scale through the whole open water season. River discharge is comparable with P-E in magnitude but peaks before ice melt. The spatial and temporal variations of freshwater contents largely exceed the remote sensed SSS uncertainty. This fact justifies the use of remote sensed SSS for monitoring the HB freshwater cycle.

Internal solitary waves from L-band SAR over the Argentine inner Patagonian shelf

ABSTRACTInternal waves represent an important mechanism of energy exchange influencing primary production through the turbulent transport of nutrients and changes in the intensity of light available for photosynthesis. Internal solitary waves (internal solitons) appear in packages and retain their shape and speed even after interacting with other internal waves. We detected solitons in the inner Patagonian shelf with the active L-band microwave satellite sensor (ALOS-PALSAR). Packages found in the satellite images were digitized. Generation mechanisms and propagation speeds were assessed using historical CTD profiles near the detected waves, assuming linear theory and atwo-layer vertical structure. The estimated propagation speeds of the waves ranged from 0.5 to 0.7m s−1. The generation regimes of waves originated at asill near the coast were classified as subcritical or near-critical according to the Froude number. We hypothesize that at this site, the generation mechanism starts leeward from the sill (lee wave mechanism), after the relaxation of the tidal current. Generation mechanisms of waves detected elsewhere over the shelf are not so obvious. More images are necessary to better determine the wave generation site. We will continue the analysis with L-band images aboard the SAOCOM 1A (CONAE), put in orbit in October 2018.

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

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.

Design of an ultra-thin magnetic radar absorber embedded with double period frequency selective surface for entire L-band microwave absorption

In this paper, a thin, broadband and low frequency with high absorption (more than 90% absorption) radar absorber (RA) consisting of magnetic-type material substrate and double period frequency selective surface (FSS) is demonstrated. The geometric parameters were investigated for its contribution towards absorption by the finite-difference time domain (FDTD) method. The effects of incidence angles of electromagnetic radiation were also discussed. The simulation indicates that the use of the double period FSS makes a remarkable increase of operational bandwidth and moves the resonant frequency to the lower frequency comparison with single magnetic radar absorption materials (SMRA). Due to the excellent symmetric nature of the proposed structure, the reflectivity is insensitive to incident angle from 0° to 30°. The reflectance of RA lower than -10 dB (over 90% absorption) is obtained in the whole frequency range of L-band which is 1.5 times wider than the bandwidth of the same thickness SMRA when the structure thickness is only 2.62 mm. The simulation method is verified by comparison with the experiment in the literature. Thus, the presented RA breaks the limitation of the thickness (λ/4) for the traditional low-frequency band absorbing material and has wide application prospect in electromagnetic shielding and low-frequency stealth.

Effect of Rainfall Events on SMAP Radiometer-Based Soil Moisture Accuracy Using Core Validation Sites

AbstractSoil moisture retrieval is particularly challenging during and immediately after precipitation events because of the transient movement of water in the shallow subsurface. Conventional L-band microwave radiometer–based soil moisture products use algorithms that assume a static state and a constant vertical soil moisture distribution. This study assessed the retrieval performance of a SMAP radiometer-based soil moisture product during and immediately after rain events. The removal of the rain event samples systematically improved the unbiased root-mean-square error (ubRMSE) from 0.037 (all measurements) to 0.028 m3 m−3 (transitory measurements screened out), while the magnitude of the bias became larger (from −0.005 to −0.014 m3 m−3); RMSE improved from 0.047 to 0.042 m3 m−3, and the Pearson correlation saw a minor positive change from 0.813 to 0.824. The results indicate that removing samples during the transitional period causes the comparison to improve, but also suggests that the true bias may be larger than the one estimated using all the samples. Furthermore, the results revealed that the effect was stronger for areas with high clay content. An assessment of the performance of the product during the rain events (overpass within 3 h from the start of the rain) showed that the ubRMSE degraded from the benchmarked 0.036 m3 m−3 (during no rain events at all) to 0.043 m3 m−3 (during rain). The results also showed that the bias became wetter, which is expected because SMAP sensed the water on the surface before propagating to the in situ sensors. SMAP maintains its soil moisture sensitivity even during rain events and screening of rain events may not be necessary to ensure sufficient soil moisture retrieval quality.

Soil moisture experiment in the Luan River supporting new satellite mission opportunities

The Soil Moisture Experiment in the Luan River (SMELR) was conducted from 2017 to 2018 in the semi-arid Luan River watershed located in the North of China. One of the objectives of SMELR is to serve as an assessment tool and demonstration for a new Terrestrial Water Resources Satellite (TWRS) concept with one-dimensional synthetic aperture microwave techniques, for which soil moisture retrieval under variable satellite observing configurations (mainly in terms of incidence angels) is the greatest challenge. This proposed mission is targeted to provide continuity for the current satellite L-band microwave observations, and further improve the accuracy and spatial resolution of soil moisture mapping through the synergistic use of active, passive and optical remote sensing data. Multi-resolution, multi-angle and multi-spectral airborne data were obtained four times over a 70 km by 12 km area in the Shandian River basin, and one time over a 165 km by 5 km area that includes the Xiaoluan River basin. The near surface soil moisture (0 cm–5 cm) was measured extensively on the ground in fifty 1 km by 2 km quadrats (targeted to compare with the airborne radiometer), and two hundred and fifty 200 m by 200 m quadrats corresponding to radar observations. Two networks were established for continuous measurement of the soil moisture and temperature profile (3 cm, 5 cm, 10 cm, 20 cm, 50 cm) and precipitation in the Shandian and Xiaoluan River basin, respectively. Supporting ground measurements also included ground temperature, vegetation water content, surface roughness, continuous measurement of microwave emission and backscatter at a pasture site, reflectance of various land cover types, evapotranspiration and aerosol observations. Preliminary results within the experimental area indicate that (1) the near surface soil moisture spatial variability at a 200 m scale was up to ~0.1 cm3/cm3 at an intermediate value of ~0.35 cm3/cm3. (2) The difference of soil and vegetation temperature in grass and croplands reach its maximum of 11 K around solar noon time, and the soil temperature gradient is largest at around 15 P.M. (3) Both the airborne and ground measurements cover a wide range of conditions. The L-band active and passive observations exhibit a large variation of ~30 dB and ~80 K, respectively, corresponding to soil moisture range from 0.1 cm3/cm3 to 0.5 cm3/cm3. The sensitivity of both active and passive data to soil moisture is compared at corresponding spatial resolutions and show high information complementarity for better accuracy and resolution soil moisture retrieval.

Tephra Mass Eruption Rate From Ground-Based X-Band and L-Band Microwave Radars During the November 23, 2013, Etna Paroxysm

The morning of November 23, 2013, a lava fountain formed from the New South-East Crater (NSEC) of Mt. Etna (Italy), one of the most active volcanoes in Europe. The explosive activity was observed from two ground-based radars, the X-band polarimetric scanning and the L-band Doppler fixed-pointing, as well as from a thermal-infrared camera. Taking advantage of the capability of the microwave radars to probe the volcanic plume and extending the volcanic ash radar retrieval (VARR) methodology, we estimate the mass eruption rate (MER) using three main techniques, namely surface-flux approach (SFA), mass continuity-based approach (MCA), and top-plume approach (TPA), as well as provide a quantitative evaluation of their uncertainty. Estimated exit velocities are between 160 and 230 m/s in the paroxysmal phase. The intercomparison between the SFA, MCA, and TPA methods, in terms of retrieved MER, shows a fairly good consistency with values up to $2.4\times 10^{6}$ kg/s. The estimated total erupted mass (TEM) is $3.8\times 10^{9}$ , $3.9\times 10^{9}$ , and $4.7\times 10^{9}$ kg for SFA with L-band, X-band, and thermal-infrared camera, respectively. Estimated TEM is between $1.7\times 10^{9}$ kg and $4.3\times 10^{9}$ for TPA methods and $3.9\times 10^{9}$ kg for the MCA technique. The SFA, MCA, and TPA results for TEM are in fairly good agreement with independent evaluations derived from ground collection of tephra deposit and estimated to be between $1.3\,\,\pm \,\,1.1\times 10^{9}$ and $5.7\times 10^{9}$ kg. This article shows that complementary strategies of ground-based remote sensing systems can provide an accurate real-time monitoring of a volcanic explosive activity.

Estimating Gravimetric Water Content of a Winter Wheat Field from L-Band Vegetation Optical Depth

A considerable amount of water is stored in vegetation, especially in regions with high precipitation rates. Knowledge of the vegetation water status is essential to monitor changes in ecosystem health and to assess the vegetation influence on the water budget. In this study, we develop and validate an approach to estimate the gravimetric vegetation water content (mg), defined as the amount of water [kg] per wet biomass [kg], based on the attenuation of microwave radiation through vegetation. mg is expected to be more closely related to the actual water status of a plant than the area-based vegetation water content (VWC), which expresses the amount of water [kg] per unit area [m2]. We conducted the study at the field scale over an entire growth cycle of a winter wheat field. Tower-based L-band microwave measurements together with in situ measurements of vegetation properties (i.e., vegetation height, and mg for validation) were performed. The results indicated a strong agreement between the in situ measured and retrieved mg (R2 of 0.89), with mean and standard deviation (STD) values of 0.55 and 0.26 for the in situ measured mg and 0.57 and 0.19 for the retrieved mg, respectively. Phenological changes in crop water content were captured, with the highest values of mg obtained during the growth phase of the vegetation (i.e., when the water content of the plants and the biomass were increasing) and the lowest values when the vegetation turned fully senescent (i.e., when the water content of the plant was the lowest). Comparing in situ measured mg and VWC, we found their highest agreement with an R2 of 0.95 after flowering (i.e., when the vegetation started to lose water) and their main differences with an R2 of 0.21 during the vegetative growth of the wheat vegetation (i.e., where the mg was constant and VWC increased due to structural changes in vegetation). In addition, we performed a sensitivity analysis on the vegetation volume fraction (δ), an input parameter to the proposed approach which represents the volume percentage of solid plant material in air. This δ-parameter is shown to have a distinct impact on the thermal emission at L-band, but keeping δ constant during the growth cycle of the winter wheat appeared to be valid for these mg retrievals.

A Study on Oil Palm Remote Sensing at L-Band With Dense Medium Microwave Backscattering Model

Studies on the potential of using synthetic aperture radar (SAR) imaging data for remote sensing in oil palm growth needs to be done in depth. In this paper, we utilized a scattering model for oil palm to study and understand how L-band microwave interacts with the structure of the oil palm. The model is developed based on the radiative transfer theory and solved iteratively up to the second order. The knowledge obtained can likely be used to interpret the backscattering behavior of oil palm with respect to growth. The oil palm is modeled as a multilayer dense medium with leaflets as elliptical disk while the trunk and fronds as cylinders. The model takes into consideration of the close spacing effects of scattering in a dense medium with the use of phase correction theory. Furthermore, near-field interactions between closely spaced scatterers are also considered via the Fresnel phase and amplitude corrections. Ground truth data were measured from the oil palm fields and are used as input parameters in the model. Five different age groups of oil palm were chosen and their backscatter coefficient simulated at L-band frequency. L-band SAR data acquired were compared with the simulated results, and it was found that there was a good agreement between the simulated results and measured data. For further understanding, the model also simulated the breakdown of backscatter contribution by various components of oil palm which allows a better understanding of the interaction between microwave backscatter with specific components.

Spatio-Temporal Mapping of L-Band Microwave Emission on a Heterogeneous Area with ELBARA III Passive Radiometer

Water resources on Earth become one of the main concerns for society. Therefore, remote sensing methods are still under development in order to improve the picture of the global water cycle. In this context, the microwave bands are the most suitable to study land–water resources. The Soil Moisture and Ocean Salinity (SMOS), satellite mission of the European Space Agency (ESA), is dedicated for studies of the water in soil over land and salinity of oceans. The part of calibration/validation activities in order to improve soil moisture retrieval algorithms over land is done with ground-based passive radiometers. The European Space Agency L-band Microwave Radiometer (ELBARA III) located near the Bubnów wetland in Poland is capable of mapping microwave emissivity at the local scale, due to the azimuthal and vertical movement of the horn antenna. In this paper, we present results of the spatio-temporal mapping of the brightness temperatures on the heterogeneous area of the Bubnów test-site consisting of an area with variable organic matter (OM) content and different type of vegetation. The soil moisture (SM) was retrieved with the L-band microwave emission of the biosphere (L-MEB) model with simplified roughness parametrization (SRP) coupling roughness and optical depth parameters. Estimated soil moisture values were compared with in-situ data from the automatic agrometeorological station. The results show that on the areas with a relatively low OM content (4–6%—cultivated field) there was good agreement between measured and estimated SM values. Further increase in OM content, starting from approximately 6% (meadow wetland), caused an increase in bias, root mean square error (RMSE), and unbiased RMSE (ubRMSE) values and a general drop in correlation coefficient (R). Despite a span of obtained R values, we found that time-averaged estimated SM using the L-MEB SRP approach strongly correlated with OM contents.

Global Assessment of the SMAP Freeze/Thaw Data Record and Regional Applications for Detecting Spring Onset and Frost Events

More than half of the global land area undergoes seasonal frozen and thawed conditions that constrain eco-hydrological processes. The freeze-thaw (FT) retrieval from satellite microwave remote sensing detects landscape changes between frozen and non-frozen conditions due to the strong dependence of surface microwave emissions on liquid water abundance. We conducted an assessment of the latest version (R16) of the NASA Soil Moisture Active Passive (SMAP) Level 3 FT (L3_FT) global product. The L3_FT product provides a global FT classification with 3-day mean temporal fidelity derived using SMAP L-band (1.4 GHz) microwave brightness temperature (Tb) retrievals. The R16 product uses both normalized polarization ratio (NPR) and single channel vertically-polarized Tb (FT-SCV) algorithms to obtain FT retrievals over land areas where frozen temperatures are a significant ecological constraint. The L3_FT product is generated in a standard global grid with similar grid cell resolution (36-km) as the SMAP radiometer footprint. An enhanced 9-km global grid L3_FT product is also produced from optimally interpolated SMAP Tb retrievals. The resulting L3_FT products span a larger domain and longer period (2015–present) than earlier product releases. The L3_FT 36-km results showed a respective global mean annual FT classification accuracy of approximately 78 and 90 percent for descending (AM) and ascending (PM) orbit observations in relation to independent surface air temperature-based FT estimates from ~5000 global weather stations. The FT accuracy was lower in areas with greater terrain complexity, open water and vegetation cover; where the combined land cover factors explained 29–53% of the variability in the SMAP FT global accuracy. The L3_FT 9-km product showed an apparent enhancement of FT spatial patterns, but with ~4% lower accuracy than the 36-km product; the lower 9-km accuracy was attributed to stronger degradation from land cover heterogeneity, particularly in coastal areas, and artifact noise introduced from the spatial interpolation of SMAP Tb retrievals. Selected regional applications indicated product utility in capturing anomalous frost events over Australia and seasonal thaw and spring onset patterns over Alaska. Overall, the L3_FT global accuracy meets or exceeds the FT product science requirements established by the mission, while enabling studies of dynamic FT and water mobility constraints influencing hydrological and ecosystem processes, and global water-carbon-energy cycle linkages.

Calibration of SMOS Soil Moisture Retrieval Algorithm: A Case of Tropical Site in Malaysia

Soil Moisture and Ocean Salinity (SMOS) mission has successfully contributed to global soil moisture products since 2009. Validation and calibration activities were conducted worldwide, yet some of the validation results do not fulfill the targeted accuracy of ±0.04 $\text{m}^{3}\text{m}^{-3}$ . This paper presented the site-specific calibration of the V620 retrieval algorithm with in situ data collected at selected agricultural sites in the humid tropical regions, Malaysia. This set of data has been validated where low accuracy of SMOS soil moisture products was found. To improve the SMOS soil moisture retrieval, calibration of SMOS soil moisture retrieval algorithm based on the L-band Microwave Emission and Biosphere model and SMOS Level 1C $\text{T}_{\mathrm {B}}$ products, considering the local parameters was conducted. The calibration proves that these site-specific parameters improve the product’s accuracy. Validation of SMOS Level 2 product with in situ data showed bias, root-mean-square error (RMSE), and unbiased RMSE (ubRMSE) ranging from 0.050 to 0.118 $\text{m}^{3}\text{m}^{-3}$ , 0.068 to 0.142 $\text{m}^{3}\text{m}^{-3}$ , and 0.069 to 0.103 $\text{m}^{3}\text{m}^{-3}$ , respectively. The soil moisture retrieval based on the calibrated model showed an improved bias of 0.020–0.056 $\text{m}^{3}\text {m}^{-3}$ and RMSE of 0.026–0.065 $\text{m}^{3}\text{m}^{-3}$ . The ubRMSE ranges from 0.017 to 0.034 $\text{m}^{3}\text{m}^{-3}$ . Recently released SMOS-IC V105 product was also validated, where small improvements were noticed when compared to the accuracy of SMOS Level 2. This paper shows the importance of local parameters in retrieving soil moisture with higher accuracy compared to the use of global generalized parameters that are used in the original SMOS soil moisture retrieval algorithm.