P. de Rosnay

AMMA Land Surface Model Intercomparison Experiment coupled to the Community Microwave Emission Model: ALMIP-MEM

This paper presents the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Models Intercomparison Project (ALMIP) for Microwave Emission Models (ALMIP-MEM). ALMIP-MEM comprises an ensemble of simulations of C-band brightness temperatures over West Africa for 2006. Simulations have been performed for an incidence angle of 55°, and results are evaluated against C-band satellite data from the Advanced Microwave Scanning Radiometer on Earth Observing System (AMSR-E). The ensemble encompasses 96 simulations, for 8 Land Surface Models (LSMs) coupled to 12 configurations of the Community Microwave Emission Model (CMEM). CMEM has a modular structure which permits combination of several parameterizations with different vegetation opacity and soil dielectric models. ALMIP-MEM provides the first intercomparison of state-of-the-art land surface and microwave emission models at regional scale. Quantitative estimates of the relative importance of land surface modeling and radiative transfer modeling for the monitoring of low-frequency passive microwave emission on land surfaces are obtained. This is of high interest for the various users of coupled land surface microwave emission models. Results show that both LSMs and microwave model components strongly influence the simulated top of atmosphere (TOA) brightness temperatures. For most of the LSMs, the Kirdyashev opacity model is the most suitable to simulate TOA brightness temperature in best agreement with the AMSR-E data. When this best microwave modeling configuration is used, all the LSMs are able to reproduce the main temporal and spatial variability of measured brightness temperature. Averaged among the LSMs, correlation is 0.67 and averaged normalized standard deviation is 0.98.

Skill and global trend analysis of soil moisture from reanalysis and microwave remote sensing

AbstractIn situ soil moisture measurements from 2007 to 2010 for 196 stations from five networks across the world (United States, France, Spain, China, and Australia) are used to determine the reliability of three soil moisture products: (i) a revised version of the ECMWF Interim Re-Analysis (ERA-Interim; ERA-Land); (ii) a revised version of the Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis from NASA (MERRA-Land); and (iii) a new, microwave-based multisatellite surface soil moisture dataset (SM-MW). Evaluation of the time series and anomalies from a moving monthly mean shows a good performance of the three products in capturing the annual cycle of surface soil moisture and its short-term variability. On average, correlations (95% confidence interval) are 0.66 (±0.038), 0.69 (±0.038), and 0.60 (±0.061) for ERA-Land, MERRA-Land, and SM-MW. The two reanalysis products also capture the root-zone soil moisture well; on average, correlations are 0.68 (±0.035) and 0.73 (±0.03...

A Simple Model of the Bare Soil Microwave Emission at L-Band

A simple reflectivity model of a bare soil at L-band is developed to account for the effects of soil roughness at different angles and polarizations. This model was developed using a long-term dataset acquired over the bare soil in the framework of the Surface Monitoring Of the Soil Reservoir EXperiment (SMOSREX). It is shown that the roughness effects are different depending on the measurement configuration, in terms of incidence angle and polarization. However, in this paper, a simple parameterization that is based on a single roughness parameter was calibrated in order to account for this angular and polarization dependencies. This parameter was found to be dependent on soil moisture: drier conditions were associated to higher ldquoroughnessrdquo conditions. The root-mean-square error between the measured and modeled reflectivities on days when no precipitation events were detected at vertical polarization (V-pol) is 0.0275, and at horizontal polarization (H-pol), the rmse is 0.0237; all incidence angles were considered. When all data are considered, the rmsd for V-pol is 0.0350, and for H-pol, the rmse is 0.0373. This new simple model is suitable for soil moisture retrieval from Soil Moisture and Ocean Salinity data. By means of this simple parameterization, almost two years of soil moisture data were retrieved with a good accuracy. The SMOSREX dataset allowed to ensure a long-term suitability of the proposed parameterization.

Evaluating an Improved Parameterization of the Soil Emission in L-MEB

In the forward model [L-band microwave emission of the biosphere (L-MEB)] used in the Soil Moisture and Ocean Salinity level-2 retrieval algorithm, modeling of the roughness effects is based on a simple semiempirical approach using three main “roughness” model parameters: HR, QR, and NR. In many studies, the two parameters QR and NR are set to zero. However, recent results in the literature showed that this is too approximate to accurately simulate the microwave emission of the rough soil surfaces at L-band. To investigate this, a reanalysis of the PORTOS-93 data set was carried out in this paper, considering a large range of roughness conditions. First, the results confirmed that QR could be set to zero. Second, a refinement of the L-MEB soil model, considering values of NR for both polarizations (namely, NRV and NRH), improved the model accuracy. Furthermore, simple calibrations relating the retrieved values of the roughness model parameters HR and (NRH - NRV) to the standard deviation of the surface height were developed. This new calibration of L-MEB provided a good accuracy (better than 5 K) over a large range of soil roughness and moisture conditions of the PORTOS-93 data set. Conversely, the calibrations of the roughness effects based on the Choudhury approach, which is still widely used, provided unrealistic values of surface emissivities for medium or large roughness conditions.

Evaluation of AMSR-E soil moisture product based on ground measurements over temperate and semi-arid regions

Soil moisture (SM) products provided by remote sensing approaches at continental scale are of great importance for land surface modeling and numerical weather prediction. Before using remotely sensed SM products it is crucial to validate them. This paper presents an evaluation of AMSR-E (Advanced Microwave Scanning Radiometer - Earth Observing System) SM products over two sites. They are located in the south-west of France and in the Sahelian part of Mali in West Africa, in the framework of the SMOSREX (Surface Monitoring Of Soil Reservoir Experiment) and AMMA (African Monsoon Multidisciplinary Analysis) projects respectively. The most representative station of the four stations of each site is used for the comparison of AMSR-E derived and in-situ SM measurements in absolute and normalized values. Results suggest that, although AMSR-E SM product is not able to capture absolute SM values, it provides reliable information on surface SM temporal variability, at seasonal and rainy event scale. It is shown, however, that the use of radiometric products, such as polarization ratio, provides better agreement with ground stations than the derived SM products.

Estimating the Effective Soil Temperature at L-Band as a Function of Soil Properties

To retrieve soil moisture from L-band microwave radiometry, it is necessary to account for the effects of temperature within both vegetation and soil media. To compute the effective soil temperature TG, several simple formulations accounting for soil temperatures at the surface and at depth and surface soil moisture have been developed. However, the effects of the soil physical properties in terms of texture, density, or structure, which all may be important variables in the modeling of TG, have never been investigated. In this paper, several simple formulations of TG at L-band, accounting for or ignoring the effects of soil texture and density, were developed and compared based on a very large simulated data set. The best configurations and parameterizations of these simple formulations were computed and could be directly used for operational applications in future soil moisture retrieval studies. For instance, we showed that the use of the surface temperature in the estimation of TG can be significantly improved by using additional information on the soil temperature at depth (the average error in the estimation of TG decreased from ~ 4 to ~ 1.8 K). On the contrary, almost no improvement was obtained if air temperature was used instead of surface temperature. Also, it is shown that the use of additional information on the soil properties, mainly the soil clay content and density, led to improved results by about 0.2 K in the estimation of TG. The improvement was found to be larger for sandy and dry soils: simplified formulations accounting for soil properties are able to represent the fact that TG is closer to the soil temperature at depth for these soil conditions.

Soil moisture retrievals from biangular L-band passive microwave observations

A simple approach for correcting the effect of vegetation in the estimation of soil moisture (w/sub S/) from L-band passive microwave observations is presented in this study. The approach is based on statistical relationships, calibrated from simulated datasets, which requires only two observations made at distinct incidence angles (/spl theta//sub 1/,/spl theta//sub 2/). A sensitivity study was carried out, and best retrieval remote sensing configurations, in terms of polarization and couple of incidence angles (/spl theta//sub 1/,/spl theta//sub 2/), were investigated. Best estimations of w/sub S/ could be made at H polarization, for /spl theta//sub 1/ varying between 15/spl deg/ and 30/spl deg/, and with a difference (/spl theta//sub 2/-/spl theta//sub 1/) larger than 30/spl deg/. The method was tested against two experimental datasets acquired over crop fields (soybean and wheat). The average accuracy in the soil moisture retrievals during the whole crop cycle was found to be about 0.05 m/sup 3//m/sup 3/ for both crops.

Sensitivity of surface fluxes to the number of layers in the soil model used in GCMs.

Many GCM land surface schemes were recently developed in order to take into account the physical processes of soil water flow by resolving Darcy equation. But numerical resolution of the Darcy equation requires care because of its high degree of non-linearity. This paper presents a sensitivity experiment of the numerically computed surface fluxes to the vertical soil resolution. It is shown that too coarse resolutions drastically affects the ability of the scheme to give physically based representations of moisture and energy fluxes.

Evaluating the L-MEB Model From Long-Term Microwave Measurements Over a Rough Field, SMOSREX 2006

The present paper analyzes the effects of roughness on the surface emission at L-band based on observations acquired during a long-term experiment. At the Surface Monitoring of the Soil Reservoir Experiment site near Toulouse, France, a bare soil was plowed and monitored over more than a year by means of an L-band radiometer, profile soil moisture and temperature sensors, and a local weather station, accompanied by 12 roughness campaigns. The aims of this paper are the following: 1) to present this unique database and 2) to use this data set to investigate the semiempirical parameters for the roughness in L-band Microwave Emission of the Biosphere, which is the forward model used in the Soil Moisture and Ocean Salinity soil moisture retrieval algorithm. In particular, we studied the link between these semiempirical parameters and the soil roughness characteristics expressed in terms of standard deviation of surface height (σ) and the correlation length (LC). The data set verifies that roughness effects decrease the sensitivity of surface emission to soil moisture, an effect which is most pronounced at high incidence angles and soil moisture and at horizontal polarization. Contradictory to previous studies, the semiempirical parameter Qr was not found to be equal to 0 for rough conditions. A linear relationship between the semiempirical parameters N and σ was established, while NH and NV appeared to be lower for a rough (NH ~ 0.59 and NV ~ -0.3) than for a quasi-smooth surface. This paper reveals the complexity of roughness effects and demonstrates the great value of a sound long-term data set of rough L-band surface emissions to improve our understanding on the matter.

Radar Signatures of Sahelian Surfaces in Mali Using ENVISAT-ASAR Data

This paper presents an analysis of ENSIVAT advanced synthetic aperture radar data acquired over a Sahelian region located in Mali, West Africa. The considered period is 2004-2005 and includes two rainy seasons. Emphasis is put on two ScanSAR modes, namely, the global monitoring (GM) and the wide swath (WS) modes characterized by spatial resolutions of about 1 km and 150 m, respectively. Results show that the WS mode offers better performance in terms of radiometric resolution, radiometric stability, and speckle reduction than the GM mode. The latter is more appropriate for studies at large scale (> 10 times 10 km). In both modes, pronounced angular and temporal signatures are observed for most soil surfaces, and azimuthal effects are observed on markedly orientated rocky surfaces. In contrast, polarization differences (VV/HH) are small during the dry season except on flat loamy soil surfaces. Finally, a relationship is observed between the normalized WS backscattering signal at HH polarization and the surface soil moisture of sandy soils.