Status of Radio Frequency Interference (RFI) in the 1400–1427 MHz passive band based on six years of SMOS mission

Oliva, Roger; Daganzo, E.; Richaume, Philippe; Kerr, Yann H.; Cabot, François; Soldo, Yan; Anterrieu, Éric; Reul, Nicolás; Gutierrez, Antonio P.; Barbosa, José; Lopes, Goncalo

doi:10.1016/j.rse.2016.01.013

Cited by 105 publications

(52 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This work has shown that the relatively short SMOS data record allows providing insight into the dominant modes of temporal variability in the Earth's surface soil moisture. Also, although previous studies have shown some weaknesses of SMOS retrievals (e.g., [11,27,55]), the good correlation obtained with ERA5 modern reanalysis and GLDAS-Noah indicates that an L-band climatology, such as the one proposed in this study, is a reasonable reference to be used for a climate data record exclusively based on remote sensing data. The presented SMOS-based climatology offers a unique view of recent processes governing freshwater fluxes in the water cycle, and allows observing specific phenomena, as the different variability regimes present within the Amazon and Congo basins and the dominance of the interannual variability in wide regions within Europe, United States, Eastern Australia and South America.…”

Section: Discussion and Final Remarksmentioning

confidence: 61%

“…Although L-band is an internationally protected band for radio astronomy, it was soon clear after the SMOS launch that anthropogenic RFI exceeded expected levels in many regions worldwide [26]. The situation has now improved, but the presence of RFI still masks SMOS observations, severely limiting its coverage in some regions [27]. The impact of RFI is considerably reduced in SMAP, since a number of hardware and software measures were implemented to detect and where possible mitigate its effects [28].…”

Section: Smos Soil Moisturementioning

confidence: 99%

“…SMOS's wide swath (1000 km) and polar orbit allow for a 3-day global revisit period. However, there is an important amount of missing data due to the presence of radio frequency interferences masking L-band measurements, particularly in South-East Asia [27]. In addition, no retrievals are attempted in areas of high topography (e.g., Himalaya) and in soils covered by snow.…”

Section: Temporal Averaging and Filtering Of Smos Datamentioning

confidence: 99%

“…It is interesting to note that subseasonal variability is predominant in regions where the SMOS signal has already a relatively low variance ( Figure 10) and is most likely influenced by noise such as the Sahara desert, the Arabian Peninsula and Western Australia, i.e., where the noise is at least of the same magnitude that the annual variance. Indeed, despite having carefully filtered the data, some of the SMOS retrievals in Asia and Europe may still be affected by undetected RFI contamination [27]. Also, results may be affected by the intrinsic uncertainty of microwave satellite SM retrievals, which is higher in presence of dense vegetation canopies, heterogeneous landscapes, and high topography [6,11,55].…”

Section: Analysis Of the Dominant Features Of Global Soil Moisture Vamentioning

confidence: 99%

See 3 more Smart Citations

Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite

2019

View full text Add to dashboard Cite

Soil moisture observations are expected to play an important role in monitoring global climate trends. However, measuring soil moisture is challenging because of its high spatial and temporal variability. Point-scale in-situ measurements are scarce and, excluding model-based estimates, remote sensing remains the only practical way to observe soil moisture at a global scale. The ESA-led Soil Moisture and Ocean Salinity (SMOS) mission, launched in 2009, measures the Earth's surface natural emissivity at L-band and provides highly accurate soil moisture information with a 3-day revisiting time. Using the first six full annual cycles of SMOS measurements (June 2010-June 2016), this study investigates the temporal variability of global surface soil moisture. The soil moisture time series are decomposed into a linear trend, interannual, seasonal, and high-frequency residual (i.e., subseasonal) components. The relative distribution of soil moisture variance among its temporal components is first illustrated at selected target sites representative of terrestrial biomes with distinct vegetation type and seasonality. A comparison with GLDAS-Noah and ERA5 modeled soil moisture at these sites shows general agreement in terms of temporal phase except in areas with limited temporal coverage in winter season due to snow. A comparison with ground-based estimates at one of the sites shows good agreement of both temporal phase and absolute magnitude. A global assessment of the dominant features and spatial distribution of soil moisture variability is then provided. Results show that, despite still being a relatively short data set, SMOS data provides coherent and reliable variability patterns at both seasonal and interannual scales. Subseasonal components are characterized as white noise. The observed linear trends, based upon one strong El Niño event in 2016, are consistent with the known El Niño Southern Oscillation (ENSO) teleconnections. This work provides new insight into recent changes in surface soil moisture and can help further our understanding of the terrestrial branch of the water cycle and of global patterns of climate anomalies. Also, it is an important support to multi-decadal soil moisture observational data records, hydrological studies and land data assimilation projects using remotely sensed observations.

show abstract

Section: Discussion and Final Remarksmentioning

confidence: 61%

Section: Smos Soil Moisturementioning

confidence: 99%

Section: Temporal Averaging and Filtering Of Smos Datamentioning

confidence: 99%

Section: Analysis Of the Dominant Features Of Global Soil Moisture Vamentioning

confidence: 99%

See 2 more Smart Citations

Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite

2019

View full text Add to dashboard Cite

show abstract

“…Even though the SMOS, Aquarius, and SMAP radiometer bandwidths fall within a protected band (1400-1427 MHz), significant levels of radio-frequency interference (RFI) caused by anthropogenic sources of radiation are commonly observed in satellite L-band measurements (Oliva et al, 2016;Le Vine et al, 2014;Piepmeier et al, 2014;Aksoy and Johnson, 2013). The United Nations provision 5.340 of Radio Regulations of the International Telecommunication Union Radiocommunication Sector (ITU-R) has regulated that the frequency allocation of 1400-1427 MHz be dedicated to passive remote sensing from space and radio-astronomy research and that all other emissions within this band be prohibited or limited to maximum permitted emission power levels (ITU, 2012).…”

Section: Introductionmentioning

confidence: 99%

Radio-frequency interference mitigating hyperspectral L-band radiometer

Toose

Roy

Solheim³

et al. 2017

Geosci. Instrum. Method. Data Syst.

View full text Add to dashboard Cite

Abstract. Radio-frequency interference (RFI) can significantly contaminate the measured radiometric signal of current spaceborne L-band passive microwave radiometers. These spaceborne radiometers operate within the protected passive remote sensing and radio-astronomy frequency allocation of 1400-1427 MHz but nonetheless are still subjected to frequent RFI intrusions. We present a unique surfacebased and airborne hyperspectral 385 channel, dual polarization, L-band Fourier transform, RFI-detecting radiometer designed with a frequency range from 1400 through ≈ 1550 MHz. The extended frequency range was intended to increase the likelihood of detecting adjacent RFI-free channels to increase the signal, and therefore the thermal resolution, of the radiometer instrument. The external instrument calibration uses three targets (sky, ambient, and warm), and validation from independent stability measurements shows a mean absolute error (MAE) of 1.0 K for ambient and warm targets and 1.5 K for sky. A simple but effective RFI removal method which exploits the large number of frequency channels is also described. This method separates the desired thermal emission from RFI intrusions and was evaluated with synthetic microwave spectra generated using a Monte Carlo approach and validated with surface-based and airborne experimental measurements.

show abstract

Satellite-based Time-Series of Sea Surface Salinity designed for Ocean and Climate Studies

Boutin¹,

Reul²,

Kohler³

et al. 2021

Preprint

View full text Add to dashboard Cite

Status of Radio Frequency Interference (RFI) in the 1400–1427 MHz passive band based on six years of SMOS mission

Cited by 105 publications

References 13 publications

Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite

Dominant Features of Global Surface Soil Moisture Variability Observed by the SMOS Satellite

Radio-frequency interference mitigating hyperspectral L-band radiometer

Satellite-based Time-Series of Sea Surface Salinity designed for Ocean and Climate Studies

Contact Info

Product

Resources

About