European Space Agency Soil Moisture And Ocean Salinity Research Articles

Modeling Influence of Soil Properties in Different Gradients of Soil Moisture: The Case of the Valencia Anchor Station Validation Site, Spain

The prediction of spatial and temporal variation of soil water content brings numerous benefits in the studies of soil. However, it requires a considerable number of covariates to be included in the study, complicating the analysis. Integrated nested Laplace approximations (INLA) with stochastic partial differential equation (SPDE) methodology is a possible approach that allows the inclusion of covariates in an easy way. The current study has been conducted using INLA-SPDE to study soil moisture in the area of the Valencia Anchor Station (VAS), soil moisture validation site for the European Space Agency SMOS (Soil Moisture and Ocean Salinity). The data used were collected in a typical ecosystem of the semiarid Mediterranean conditions, subdivided into physio-hydrological units (SMOS units) which presents a certain degree of internal uniformity with respect to hydrological parameters and capture the spatial and temporal variation of soil moisture at the local fine scale. The paper advances the knowledge of the influence of hydrodynamic properties on VAS soil moisture (texture, porosity/bulk density and soil organic matter and land use). With the goal of understanding the factors that affect the variability of soil moisture in the SMOS pixel (50 km × 50 km), five states of soil moisture are proposed. We observed that the model with all covariates and spatial effect has the lowest DIC value. In addition, the correlation coefficient was close to 1 for the relationship between observed and predicted values. The methodology applied presents the possibility to analyze the significance of different covariates having spatial and temporal effects. This process is substantially faster and more effective than traditional kriging. The findings of this study demonstrate an advancement in that framework, demonstrating that it is faster than previous methodologies, provides significance of individual covariates, is reproducible, and is easy to compare with models.

Study of a Strong L-Band RFI Source

CN006 is the name given by the European Space Agency (ESA) in their reports on radio frequency interference (RFI) to an instance of RFI in the L-band spectral window at 1.413 GHz protected for passive use only. The source of the interference is located east of the Chinese city of Hangzhou in an area with radar installations. Its effect was initially indistinguishable from that of many such RFI sources observed by the ESA's SMOS and NASA's Soil Moisture Active Passive (SMAP) radiometers over China. However, in July 2020, the level of radiation increased dramatically reaching levels exceeding 1700000 K as reported by Soil Moisture and Ocean Salinity (SMOS) becoming the strongest source observed by SMOS. This article describes an analysis of this very strong source (a radar). It provides information to provide insight into an example of a well-defined source of RFI and illustrates the powerful capability of the SMAP radiometer receiver and RFI processing incorporated in it for identifying and understanding interference.

Spaceborne High Precision Sea Surface Salinity Remote Sensing by Interferometric Radiometry

The global sea surface salinity (SSS) can be accomplished by means of the L-band microwave radiometers from space, such as European Space Agency's SMOS (soil moisture and ocean salinity) and NASA's Aquarius/SAC-D. However, the microwave imaging radiometer using aperture synthesis in SMOS mission suffers from various errors and unexpected in-orbit phenomena, which degrade SSS accuracy. To further improve SSS accuracy, a full polarization aperture synthesis microwave radiometer (FPASMR) has been proposed for China's next-generation Haiyang satellite program with two important improvements, which is composed by an L- and X-band aperture synthesis radiometer (ASR) with two dimensions. One important improvement is that the sea surface roughness and sea surface temperature are simultaneously measured by the full polarization X-band ASR, and another important improvement is that the microwave-optical receiving technology and in-orbit thermal control subsystem are employed to improve the stability of the FPASMR for reducing visibility phase errors. The system of the FPASMR is introduced in terms of L-band subsystem, X-band subsystem, and the calibration subsystem. The main specifications of the FPASMR are analyzed in terms of field of view, angular resolution, and radiometric sensitivity. In addition, the FPASMR calibration is also introduced. The FPASMR demonstrator has also been developed and a series of experiments is performed to assess the performance of the FPASMR demonstrator and the improvements in the FPASMR.

Toward an Enhanced SMOS Level-2 Ocean Salinity Product

The quality of the Soil Moisture and Ocean Salinity (SMOS) sea surface salinity (SSS) measurements has been noticeably improved in the past years. However, for some applications, there are still some limitations in the use of the Level-2 ocean salinity product. First, the SSS measurements are still affected by a latitudinal and seasonal bias. Second, the high standard deviation of the SSS error could significantly degrade part of the SSS signal. Finally, the coverage of the Level-2 salinity measurements is significantly reduced after applying filtering criteria to discard the poor-quality retrievals. In this work, we apply nodal sampling to the SMOS brightness temperatures (TBs), which effectively reduces the standard deviation of the TB error; then, we use debiased non-Bayesian retrieval for the mitigation of systematic biases on SSS and the statistical filtering criteria of the degraded salinity retrievals; and finally, we comprehensively characterize the residual latitudinal and seasonal biases and derive a correction for the retrieved SSS. We generate three years of an enhanced SMOS Level-2 Ocean Salinity product and we compare its performances with the ones corresponding to the European Space Agency SMOS Level-2 Ocean Salinity product (v662).

SMOS near-real-time soil moisture product: processor overview and first validation results

Abstract. Measurements of the surface soil moisture (SM) content are important for a wide range of applications. Among them, operational hydrology and numerical weather prediction, for instance, need SM information in near-real-time (NRT), typically not later than 3 h after sensing. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite is the first mission specifically designed to measure SM from space. The ESA Level 2 SM retrieval algorithm is based on a detailed geophysical modelling and cannot provide SM in NRT. This paper presents the new ESA SMOS NRT SM product. It uses a neural network (NN) to provide SM in NRT. The NN inputs are SMOS brightness temperatures for horizontal and vertical polarizations and incidence angles from 30 to 45°. In addition, the NN uses surface soil temperature from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS). The NN was trained on SMOS Level 2 (L2) SM. The swath of the NRT SM retrieval is somewhat narrower (∼ 915 km) than that of the L2 SM dataset (∼ 1150 km), which implies a slightly lower revisit time. The new SMOS NRT SM product was compared to the SMOS Level 2 SM product. The NRT SM data show a standard deviation of the difference with respect to the L2 data of < 0.05 m3 m−3 in most of the Earth and a Pearson correlation coefficient higher than 0.7 in large regions of the globe. The NRT SM dataset does not show a global bias with respect to the L2 dataset but can show local biases of up to 0.05 m3 m−3 in absolute value. The two SMOS SM products were evaluated against in situ measurements of SM from more than 120 sites of the SCAN (Soil Climate Analysis Network) and the USCRN (US Climate Reference Network) networks in North America. The NRT dataset obtains similar but slightly better results than the L2 data. In summary, the NN SMOS NRT SM product exhibits performances similar to those of the Level 2 SM product but it has the advantage of being available in less than 3.5 h after sensing, complying with NRT requirements. The new product is processed at ECMWF and it is distributed by ESA and via the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) multicast service (EUMETCast).

First Assessment of SMOS Data Over Open Ocean: Part II—Sea Surface Salinity

We validate Soil Moisture and Ocean Salinity (SMOS) sea surface salinity (SSS) retrieved during August 2010 from the European Space Agency SMOS processing. Biases appear close to land and ice and between ascending and descending orbits; they are linked to image reconstruction issues and instrument calibration and remain under study. We validate the SMOS SSS in conditions where these biases appear to be small. We compare SMOS and ARGO SSS over four regions far from land and ice using only ascending orbits. Four modelings of the impact of the wind on the sea surface emissivity have been tested. Results suggest that the L-band brightness temperature is not linearly related to the wind speed at high winds as expected in the presence of emissive foam, but that the foam effect is less than previously modeled. Given the large noise on individual SMOS measurements, a precision suitable for oceanographic studies can only be achieved after averaging SMOS SSS. Over selected regions and after mean bias removal, the precision on SSS retrieved from ascending orbits and averaged over 100 km <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$ \times$</tex></formula> 100 km and 10 days is between 0.3 and 0.5 pss far from land and sea ice borders. These results have been obtained with forward models not fitted to satellite L-band measurements, and image reconstruction and instrument calibration are expected to improve. Hence, we anticipate that deducing, from SMOS measurements, SSS maps at 200 km <formula formulatype="inline" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex Notation="TeX">$\times$</tex></formula> 200 km, 10 days resolution with an accuracy of 0.2 pss at a global scale is not out of reach.

First Assessment of SMOS Data Over Open Ocean: Part I—Pacific Ocean

The Soil Moisture and Ocean Salinity (SMOS) mission carries the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument. It is the first time that an interferometric radiometer is in orbit. The objective of this paper is to assess the quality of the brightness temperatures (TBs) derived from this novel instrument, as processed with the SMOS operational chain at the end of the SMOS commissioning phase. Extensive comparisons have been conducted between reconstructed TBs derived from MIRAS measurements (MIRAS TB) and TBs simulated using the default radiative transfer model implemented in the European Space Agency SMOS ocean salinity processor and the European Centre for Medium-Range Weather Forecast forcings. At first order, the North-South variability of MIRAS TB due to geophysical variations of temperature, salinity, and wind speed over the ocean is consistent with the simulated L-band signal, and the standard deviation of the MIRAS TB minus the model simulations is close to the theoretical radiometric resolution. On the other hand, biases of several Kelvins, that depend on the location in the field of view, are observed between averaged MIRAS TB and simulations. After these biases are removed, the North-South gradient of sea surface salinity is well sensed by MIRAS except at high wind speed.

The use of a semi-empirical emissivity model for a rough estimation of sea surface salinity from an airborne microwave radiometer

In preparation for the European Space Agency SMOS (Soil Moisture and Ocean Salinity) satellite mission, radiometric and oceanographic measurements were performed in December 2000 and January 2001 and in November 2001 from a fixed platform in the NW Mediterranean to improve the modelling of the sea surface emissivity at L-band and new semi-empirical models were derived. Now one of these models has been used to retrieve sea surface salinity from L-band radiometric data acquired with a different instrument and different location. These data were acquired in August 2003 over the continental shelf within the influence of the Rio de la Plata, from Argentina to Brazil, southern Atlantic ocean with the STARRS airborne radiometer. Results show that the radiometer is capable of realistically detecting natural variations in surface salinity even though the model was derived in very different oceanographic conditions and from data collected by a different instrument.

Helsinki University of Technology L-Band Airborne Synthetic Aperture Radiometer

An airborne L-band 2-D interferometric radiometer for Soil Moisture and Ocean Salinity (SMOS) measurements has been developed in the Helsinki University of Technology, Laboratory of Space Technology. The first successful flights were conducted in spring 2006. In this paper, the technical description, calibration, and image reconstruction philosophy and the latest results from the use of the instrument are discussed. One of the key goals of the instrument design has been to acquire L-band interferometric data to support the European Space Agency's SMOS mission that employs the L-band interferometric radiometer Microwave Interferometric Radiometer using Aperture Synthesis. Both instruments use aperture synthesis technology for the target image reconstruction in two dimensions.