L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields

Wigneron, Jean‐Pierre; Kerr, Yann H.; Waldteufel, Philippe; Saleh, Khaldoun; Escorihuela, María José; Richaume, Philippe; Ferrazzoli, P.; Rosnay, Patricia de; Gurney, R. J.; Calvet, Jean‐Christophe; Grant, Jennifer; Guglielmetti, Massimo; Hornbuckle, B. K.; Mätzler, Christian; Pellarin, Thierry; Schwank, Mike

doi:10.1016/j.rse.2006.10.014

Cited by 593 publications

(438 citation statements)

References 69 publications

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“…where R p is the rough soil surface reflectivity and R p * is the specular reflectivity, q is the opposite polarization of p, Q R is the polarization mixing parameter (Q R = 0 as polarization crosstalk is assumed to be negligible [11,27]), N R expresses the angular dependence of roughness (N R = −1 as proposed in [11,27,28]), and H R accounts for the intensity of the roughness effect. The soil surface roughness was considered as constant during the experiment.…”

Section: Radiative Transfer Modelmentioning

confidence: 99%

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

et al. 2018

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Organic soils play a key role in global warming because they store large amount of soil carbon which might be degraded with changing soil temperatures or soil water contents. There is thus a strong need to monitor these soils and, in particular, their hydrological characteristics using, for instance, space-borne L-band brightness temperature observations. However, there are still open issues with respect to soil moisture retrieval techniques over organic soils. In view of this, organic soil blocks with their vegetation cover were collected from a heathland in the Skjern River catchment in western Denmark and then transported to a remote sensing field laboratory in Germany where their structure was reconstituted. The controlled conditions at this field laboratory made it possible to perform tower-based L-band radiometer measurements of the soils over a period of two months. Brightness temperature data were inverted using a radiative transfer (RT) model for estimating the time variations in the soil dielectric permittivity and the vegetation optical depth. In addition, the effective vegetation scattering albedo parameter of the RT model was retrieved based on a two-step inversion approach. The remote estimations of the dielectric permittivity were compared to in situ measurements. The results indicated that the radiometer-derived dielectric permittivities were significantly correlated with the in situ measurements, but their values were systematically lower compared to the in situ ones. This could be explained by the difference between the operating frequency of the L-band radiometer (1.4 GHz) and that of the in situ sensors (70 MHz). The effective vegetation scattering albedo parameter was found to be polarization dependent. While the scattering effect within the vegetation could be neglected at horizontal polarization, it was found to be important at vertical polarization. The vegetation optical depth estimated values over time oscillated between 0.10 and 0.19 with a mean value of 0.13. This study provides further insights into the characterization of the L-band brightness temperature signatures of organic soil surface layers and, in particular, into the parametrization of the RT model for these specific soils. Therefore, the results of this study are expected to improve the performance of space-borne remote sensing soil moisture products over areas dominated by organic soils.

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Section: Radiative Transfer Modelmentioning

confidence: 99%

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

et al. 2018

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“…CMEM consists of the physics and parameterizations used in the Land Surface Microwave Emission Model (LSMEM; Drusch et al, 2001) and the L-band Microwave Emission of the Biosphere (L-MEB; Wigneron et al, 2007). For polarization (p), the brightness temperatures over snow-free areas at the top of the atmosphere (TOA) T Btoa,p , which result from the contributions of three dielectric layers (soil, vegetation, and atmosphere), can be expressed as follows: CMEM includes a modular choice regarding the physical parameterizations for the soil, vegetation, and atmosphere dielectric layers.…”

Section: Cmemmentioning

confidence: 99%

“…Several RTMs (Dobson et al, 1985;Weng et al, 2001;Drusch et al, 2001;Chen et al, 2003;Shi et al, 2005;Wigneron et al, 2007) have been proposed to simulate microwave brightness temperatures over various surface conditions. The Community Microwave Emission Model (CMEM) was developed by the European Centre for Medium-Range Weather Forecasts (ECMWF) as the forward operator for low frequency passive microwave brightness temperatures (from 1 GHz to 20 GHz) of the surface (Holmes et al, 2008;Drusch et al, 2009).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Community Microwave Emission Model Coupled with the Community Land Model over East Asia

Jia¹,

Xie

2011

Atmospheric and Oceanic Science Letters

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“…This approach is based on L1-band GPS signal strength changes due to changes in the permittivity of the soil, which are highly correlated with changes in the water content within the soil. As the GPS signals are broadcasted via L-band, the physical processes are comparable to passive L-band microwave remote sensing, e.g., with the SMOS mission [36]. To be independent of vegetation influences on the GPS signals, this approach was tested on a bare soil field.…”

Section: Introductionmentioning

confidence: 99%

Soil Moisture Retrieval Based on GPS Signal Strength Attenuation

Koch

Schlenz

Prasch

et al. 2016

Water

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Soil moisture (SM) is a highly relevant variable for agriculture, the emergence of floods and a key variable in the global energy and water cycle. In the last years, several satellite missions have been launched especially to derive large-scale products of the SM dynamics on the Earth. However, in situ validation data are often scarce. We developed a new method to retrieve SM of bare soil from measurements of low-cost GPS (Global Positioning System) sensors that receive the freely available GPS L1-band signals. The experimental setup of three GPS sensors was installed at a bare soil field at the German Weather Service (DWD) in Munich for almost 1.5 years. Two GPS antennas were installed within the soil column at a depth of 10 cm and one above the soil. SM was successfully retrieved based on GPS signal strength losses through the integral soil volume. The results show high agreement with measured and modelled SM validation data. Due to its non-destructive, cheap and low power setup, GPS sensor networks could also be used for potential applications in remote areas, aiming to serve as satellite validation data and to support the fields of agriculture, water supply, flood forecasting and climate change.

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L-band Microwave Emission of the Biosphere (L-MEB) Model: Description and calibration against experimental data sets over crop fields

Cited by 593 publications

References 69 publications

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

Passive L-Band Microwave Remote Sensing of Organic Soil Surface Layers: A Tower-Based Experiment

Evaluation of the Community Microwave Emission Model Coupled with the Community Land Model over East Asia

Soil Moisture Retrieval Based on GPS Signal Strength Attenuation

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