Philippe Waldteufel

Soil moisture retrieval from space: the Soil Moisture and Ocean Salinity (SMOS) mission

Microwave radiometry at low frequencies (L-band: 1.4 GHz, 21 cm) is an established technique for estimating surface soil moisture and sea surface salinity with a suitable sensitivity. However, from space, large antennas (several meters) are required to achieve an adequate spatial resolution at L-band. So as to reduce the problem of putting into orbit a large filled antenna, the possibility of using antenna synthesis methods has been investigated. Such a system, relying on a deployable structure, has now proved to be feasible and has led to the Soil Moisture and Ocean Salinity (SMOS) mission, which is described. The main objective of the SMOS mission is to deliver key variables of the land surfaces (soil moisture fields), and of ocean surfaces (sea surface salinity fields). The SMOS mission is based on a dual polarized L-band radiometer using aperture synthesis (two-dimensional [2D] interferometer) so as to achieve a ground resolution of 50 km at the swath edges coupled with multiangular acquisitions. The radiometer will enable frequent and global coverage of the globe and deliver surface soil moisture fields over land and sea surface salinity over the oceans. The SMOS mission was proposed to the European Space Agency (ESA) in the framework of the Earth Explorer Opportunity Missions. It was selected for a tentative launch in 2005. The goal of this paper is to present the main aspects of the baseline mission and describe how soil moisture will be retrieved from SMOS data.

Two-dimensional microwave interferometer retrieval capabilities over land surfaces (SMOS Mission).

Abstract This paper discusses the potential of an L-band 2-D microwave interferometric radiometer for monitoring surface variables over land surfaces. The instrument is the payload of the Soil Moisture and Ocean Salinity (SMOS) Mission recently selected for phase A studies by the European Space Agency (ESA) as the second Earth Explorer Opportunity Mission. The L-band radiometer is based on an innovative two-dimensional aperture synthesis concept. This sensor has new and significant capabilities, especially in terms of multiangular viewing configurations. The main aspects of the retrieval capabilities of SMOS for monitoring soil moisture, vegetation biomass, and surface temperature are presented in this paper. The analysis is based on model inversion. The standard errors of estimate of the surface variables are computed for various configurations as a function of both the uncertainties associated with the space measurements and those associated with the ancillary information used in the retrievals. The potential of SMOS and the possibility to retrieve one, two, or three surface variables are investigated, depending on the view angle configuration. These questions are key issues to optimize the SMOS mission scenario, to meet both the scientific requirements and the technical constraints of the mission.

Overview of the SMOS Sea Surface Salinity Prototype Processor

The L-band interferometric radiometer onboard the Soil Moisture and Ocean Salinity mission will measure polarized brightness temperatures (Tb). The measurements are affected by strong radiometric noise. However, during a satellite overpass, numerous measurements are acquired at various incidence angles at the same location on the Earths surface. The sea surface salinity (SSS) retrieval algorithm implemented in the Level 2 Salinity Prototype Processor (L2SPP) is based on an iterative inversion method that minimizes the differences between Tb measured at different incidence angles and Tb simulated by a full forward model. The iterative method is initialized with a first-guess surface salinity that is iteratively modified until an optimal fit between the forward model and the measurements is obtained. The forward model takes into account atmospheric emission and absorption, ionospheric effects (Faraday rotation), scattering of celestial radiation by the rough ocean surface, and rough sea surface emission as approximated by one of three models. Potential degradation of the retrieval results is indicated through a flagging strategy. We present results of tests of the L2SPP involving horizontally uniform scenes with no disturbing factors (such as sun glint or land proximity) other than wind-induced surface roughness. Regardless of the roughness model used, the error on the retrieved SSS depends on the location within the swath and ranges from 0.5 psu at the center of the swath to 1.7 psu at the edge, at 35 psu and 15degC. Dual-polarization (DP) mode provides a better correction for wind-speed (WS) biases than pseudofirst Stokes mode (ST1). For a WS bias of -1 mmiddots-1, the corresponding SSS bias at the center of the swath is equal to -0.3 psu in DP mode and to -0.5 psu in ST1 mode. The inversion methodology implicitly assumes that WS errors follow a Gaussian distribution, even though these errors should follow more closely a Rayleigh distribution. For this reason, the use of wind components, which typically exhibit Gaussian error distributions, may be preferred in the retrieval. However, the use of noisy wind components creates WS and SSS biases at low WSs (0.1 psu at 3 mmiddots-1). At a sea surface temperature (SST) of 15degC, the retrieved SSS is weakly sensitive to the SST biases, with the SSS bias always lower than 0.3 psu for SST biases ranging from -0.5degC to -2degC. In DP mode, biases in the vertical total electron content (TEC) of the atmosphere result in SSS biases smaller than 0.2 psu. The pseudofirst Stokes mode is insensitive to TEC. Failure to fully account for sea surface roughness scattering effects in the computation of sky radiation contribution leads to a maximum SSS bias of 0.2 psu in the selected configuration, i.e., a descending orbit over the Northern Pacific in February. To achieve SSS biases that are smaller than 0.2 psu, special care must be taken to correct for biases at low WS and to ensure that the bias on the mean WS (averaged over 200 km times 200 km and ten days) remains smaller than 0.5 mmiddots-1.

Characterizing the dependence of vegetation model parameters on crop structure, incidence angle, and polarization at L-band

To retrieve soil moisture over vegetation-covered areas from microwave radiometry, it is necessary to account for vegetation effects. At L-band, many retrieval approaches are based on a simple model that relies on two vegetation parameters: the optical depth (/spl tau/) and the single-scattering albedo (/spl omega/). When the retrievals are based on multiconfiguration measurements, it is necessary to take into account the dependence of /spl tau/ and /spl omega/ on the system configuration, in terms of incidence angle and polarization. In this paper, this dependence was investigated for several crop types (corn, soybean, wheat, grass, and alfalfa) based on L-band experimental datasets. The results should be useful for developing more accurate forward modeling and retrieval methods over mixed pixels including a variety of vegetation types.

A New Optical Instrument for Simultaneous Measurement of Raindrop Diameter and Fall Speed Distributions

Abstract This paper presents a recently developed optical spectro-pluviometer. The principle of the device is based upon the optical occultation of an infrared light beam by falling drops. This allows the retrieval of raindrop-size and velocity distributions. The characteristics of the instrument are described in detail. Possible errors resulting either from instrumental limitations or from environment conditions of measurement are reviewed. Preliminary results regarding a 20 min rainshower observed near Paris in September 1980 are presented and discussed. The deduced total precipitation amount is in good agreement with other independent measurements. The results reveal small but significant differences between the deduced fall velocities and Gunn and Kinzers observations. The relationship between rainfall bulk parameters (rainfall rate, water content, reflectivity factor and mean fall velocity) are obtained with small relative dispersion.

Two-year global simulation of L-band brightness temperatures over land

This letter presents a synthetic L-band (1.4 GHz) multiangular brightness temperature dataset over land surfaces that was simulated at a half-degree resolution and at the global scale. The microwave emission of various land-covers (herbaceous and woody vegetation, frozen and unfrozen bare soil, snow, etc.) was computed using a simple model [L-band Microwave Emission of the Biosphere (L-MEB)] based on radiative transfer equations. The soil and vegetation characteristics needed to initialize the L-MEB model were derived from existing land-cover maps. Continuous simulations from a land-surface scheme for 1987 and 1988 provided time series of the main variables driving the L-MEB model: soil temperature at the surface and at depth, surface soil moisture, proportion of frozen surface soil moisture, and snow cover characteristics. The obtained global maps constitute a useful dataset for a first evaluation of the sensitivity of future satellite-based L-band radiometry data to soil moisture.

SMOS first data analysis for sea surface salinity determination

Soil Moisture and Ocean Salinity (SMOS), launched on 2 November 2009, is the first satellite mission addressing sea surface salinity (SSS) measurement from space. Its unique payload is the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS), a new two-dimensional interferometer designed by the European Space Agency (ESA) and operating at the L-band frequency. This article presents a summary of SSS retrieval from SMOS observations and shows initial results obtained one year after launch. These results are encouraging, but also indicate that further improvements at various data processing levels are needed and hence are currently under investigation.

Apodization functions for 2-D hexagonally sampled synthetic aperture imaging radiometers

It is now well established that synthetic aperture imaging radiometers promise to be powerful sensors for high-resolution observations of the Earth at low microwave frequencies. Within this context, the European Space Agency is currently developing the Soil Moisture and Ocean Salinity (SMOS) mission. The Y-shaped array selected for SMOS is fitted with equally spaced antennae and leads to a natural hexagonal sampling of the Fourier plane. This paper deals with the choice of the apodization function to be applied to the complex visibilities. The aim of this function is to reduce the Gibbs phenomenon produced by the finite extent of the star-shaped frequency coverage and the resulting sharp frequency cut-off. A large number of windows are introduced. A comparison of these in terms of their spatial domain properties is given, according to criteria relevant for remote sensing of the Earths surface. This paper also describes how discrete Fourier transform calculations over hexagonal grids can be performed using a simple algorithm. Actually, standard fast Fourier transform algorithms designed for Cartesian grids and which have a long track record of optimization can be reused. Finally, an interpolation formula is given for resampling data from hexagonal grids without introducing any aliasing artifacts in the resampled data.

About off-axis radiometric polarimetric measurements

Polarization changes for off-axis rays, while a minor effect for narrow-beam antennas, become a significant issue for wide-beam antennas required by synthetic aperture radiometry. This note provides the angle-dependent relationship between upwelling fields and collected signals; results are illustrated by the case of the Surface Moisture and Ocean Salinity (SMOS) mission.

Surface Salinity Retrieved from SMOS Measurements over the Global Ocean: Imprecisions Due to Sea Surface Roughness and Temperature Uncertainties

The Soil Moisture and Ocean Salinity (SMOS) mission recently led by the European Space Agency (ESA) intends to monitor soil moisture and sea surface salinity (SSS). Since the sensitivity of radiometric L-band signal to SSS is weak, measuring SSS with an acceptable accuracy is challenging: it requires both a very stable instrument and very precise corrections of other geophysical signals than the SSS affecting the L-band signal. Concentration is on the sea surface roughness and temperature (SST) effects and the extent to which they need to be corrected to optimize both SSS precision and retrieval complexity. In addition to uncertainties regarding SST and wind speed (W), realistic noise on the SMOS brightness temperatures (Tb’s) are considered and possible consequences of Tb biases are examined. In most oceanic regions, random noise in W, SST, and Tb should not hamper the SMOS SSS retrieval within the Global Ocean Data Assimilation Experiment (GODAE) requirements (a precision better than 0.1 pss over 200 km 3 200 km and 10 days). However, minimizing systematic bias errors over the time scale at which the SSS products will be averaged is critical: the GODAE requirement will not be met if Tb’s or W is biased in warm waters (258C) by 0.07 K and 0.3 m s21, respectively, and in cold waters (58C) by 0.03 K and 0.15 m s21, respectively, or if no a priori information on W is available. In order to minimize errors coming from the W natural variability, it is essential to use high-temporal-resolution wind data. The use of the first Stokes parameter instead of bipolarized Tb degrades the SSS precision by less than 10% in most regions, showing that Faraday rotation should not hamper SMOS SSS retrieval.