Ghislain Picard

Multitemporal C-band radar measurements on wheat fields

This paper investigates the relationship between C-band backscatter measurements and wheat biomass and the underlying soil moisture content. It aims to define strategies for retrieval algorithms with a view to using satellite C-band synthetic aperture radar (SAR) data to monitor wheat growth. The study is based on a ground-based scatterometer experiment conducted on a wheat field at the Matera site in Italy during the 2001 growing season. From March to June 2001, eight C-band scatterometer acquisitions at horizontal-horizontal and vertical-vertical polarization, with incidence angles ranging from 23/spl deg/ to 60/spl deg/, were taken. At the same time, soil moisture, wheat biomass, and canopy structure were collected. The paper describes the experiment and investigates the radar sensitivity to biophysical parameters at different polarizations and incidence angles, and at different wheat phenological stages. Based on the experimental results, the retrieval of wheat biomass and soil moisture content using Advanced Synthetic Aperture Radar data is discussed.

Measurement of vertical profiles of snow specific surface area with a 1 cm resolution using infrared reflectance: instrument description and validation

The specific surface area (SSA), defined as the surface area of ice per unit mass, is an important variable characterizing the complex microstructure of snow. Its application range covers the physical evolution of snow (metamorphism), photochemistry and optical and microwave remote sensing. This paper presents a new device, POSSSUM (Profiler Of Snow Specific Surface area Using SWIR reflectance Measurement), designed to allow the rapid acquisition of SSA profiles down to ∼20 m depth and with an effective vertical resolution of 10―20 mm. POSSSUM is based on the infrared (IR) reflectance technique: A laser diode operating at 1310 nm illuminates the snow at nadir incidence angle along the face of a drilled hole. The reflected radiance is measured at three zenith angles (20°, 40° and 60°) each for two azimuth angles (0° and 180°). A second laser operating at a shorter wavelength (635 nm), which is almost insensitive to SSA, allows the distance to the snow face to be estimated. The reflected IR radiance and the distance are combined to estimate bidirectional reflectances. These reflectances are converted into hemispherical reflectances and in turn into SSA using a theoretical formulation based on an asymptotic solution of the radiative transfer equation. The evaluation and validation of POSSSUMs SSA measurements took place in spring 2009 in the French Alps. The new method was compared with the methane adsorption technique and DUFISSS, another well-validated instrument based on the IR technique. The overall measurement error is in the range 10―15%.

The Concordiasi Project in Antarctica

The Concordiasi project is making innovative observations of the atmosphere above Antarctica. The most important goals of the Concordiasi are as follows: To enhance the accuracy of weather prediction and climate records in Antarctica through the assimilation of in situ and satellite data, with an emphasis on data provided by hyperspectral infrared sounders. The focus is on clouds, precipitation, and the mass budget of the ice sheets. The improvements in dynamical model analyses and forecasts will be used in chemical-transport models that describe the links between the polar vortex dynamics and ozone depletion, and to advance the under understanding of the Earth system by examining the interactions between Antarctica and lower latitudes. To improve our understanding of microphysical and dynamical processes controlling the polar ozone, by providing the first quasi-Lagrangian observations of stratospheric ozone and particles, in addition to an improved characterization of the 3D polar vortex dynamics. Techni...

Understanding C-band radar backscatter from wheat canopy using a multiple-scattering coherent model

This paper describes a modeling approach to interpret the C-band synthetic aperture radar (SAR) data from wheat canopies as provided by European Remote Sensing (ERS) satellites, RADARSAT, and the forthcoming Environmental Satellite/Advanced Synthetic Aperture Radar (ENVISAT/ASAR) satellite. At a first step, the results of a first-order modeling were compared to ERS data and scatterometer data over the growing season at two different test sites. The prediction by first-order approach was in disagreement with the data from stem extension stage to soft ripening stage. The first-order approach was found to overestimate the attenuation at vertical (V) polarization, resulting in a predicted backscattering coefficient one order of magnitude lower than that observed by the SAR system. To improve the prediction, a multiple-scattering modeling based on numerical solution of multiple-scattering Foldy-Lax equation was used. The multiple-scattering modeling provides better backscatter estimates at vertical-vertical (VV) polarization for both test sites. Then, the model is used to derive the prevailing interactions mechanisms at horizontal-horizontal (HH) and VV polarizations and 23/spl deg/ and 40/spl deg/ of incidence angle. Finally, the retrieval of crop parameters from C-band SAR data is addressed.

Modeling time series of microwave brightness temperature at Dome C, Antarctica, using vertically resolved snow temperature and microstructure measurements

Time series of observed microwave brightness temperatures at Dome C, East Antarctic plateau, were modeled over 27 months with a multilayer microwave emission model based on dense-medium radiative transfer theory. The modeled time series of brightness temperature at 18.7 and 36.5 GHz were compared with Advanced Microwave Scanning Radiometer-EOS observations. The model uses in situ high-resolution vertical profiles of temperature, snow density and grain size. The snow grain-size profile was derived from near-infrared (NIR) reflectance photography of a snow pit wall in the range 850-1100 nm. To establish the snow grain-size profile, from the NIR reflectance and the specific surface area of snow, two empirical relationships and a theoretical relationship were considered. In all cases, the modeled brightness temperatures were overestimated, and the grain-size profile had to be scaled to increase the scattering by snow grains. Using a scaling factor and a constant snow grain size below 3 m depth (i.e. below the image-derived snow pit grain-size profile), brightness temperatures were explained with a root-mean-square error close to 1 K. Most of this error is due to an overestimation of the predicted brightness temperature in summer at 36.5 GHz.

Modeling time series of microwave brightness temperature in Antarctica

This paper aims to interpret the temporal variations of microwave brightness temperature (at 19 and 37 GHz and at vertical and horizontal polarizations) in Antarctica using a physically based snow dynamic and emission model (SDEM). SDEM predicts time series of top-of-atmosphere brightness temperature from widely available surface meteorological data (ERA-40 re-analysis). To do so, it successively computes the heat flux incoming the snowpack, the snow temperature profile, the microwaves emitted by the snow and, finally, the propagation of the microwaves through the atmosphere up to the satellite. Since the model contains several parameters whose value is variable and uncertain across the continent, the parameter values are optimized for every 50 km × 50 km pixel. Simulation results show that the model is inadequate in the melt zone (where surface melting occurs on at least a few days a year) because the snowpack structure and its temporal variations are too complex. In contrast, the accuracy is reasonably good in the dry zone and varies between 2 and 4 K depending on the frequency and polarization of observations and on the location. At the Antarctic scale, the error is larger where wind is usually stronger, suggesting either that meteorological data are less accurate in windy regions or that some neglected processes (e.g. windpumping, surface scouring) are important. At Dome C, in calm conditions, a detailed analysis shows that most of the error is due to inaccuracy of the ERA-40 air temperature (∼2 K). Finally, the paper discusses the values of the optimized parameters and their spatial variations across the Antarctic.

Improved Corrections of Forest Effects on Passive Microwave Satellite Remote Sensing of Snow Over Boreal and Subarctic Regions

Microwave radiometry has been extensively used in order to estimate snow water equivalent in northern regions. However, for boreal and taiga environments, the presence of forest causes important uncertainties in the estimates. Variations in snow cover and vegetation in northeastern Canada (north of the Québec province) were characterized in a transect from 50°N to 60 °N during the International Polar Year field campaign of February 2008. Forest properties show a strong latitudinal gradient in fraction and stem volume. A large database (>; 2000 points with a stem volume ranging between 0 and 700 m3 ·ha-1) showed that brightness temperatures (Tb) decrease as forest cover fraction decreases until a cover fraction of about 25% is reached. Furthermore, Tb values saturate at high stem volume, particularly at 37 GHz. We defined new relationships for the forest transmissivity as a function of stem volume and depending on the frequency/polarization. The proposed relationships give asymptotic transmissivity saturation levels of 0.51, 0.55, 0.53, and 0.53 for 19 GHz [vertical (V) polarization], 19 GHz [horizontal (H) polarization], 37 GHz (V polarization), and 37 GHz (H polarization), respectively. These relationships were used to estimate snow Tb from the Advanced Microwave Scanning Radiometer-Earth Observing System brightness temperatures at 18.7 and 36.5 GHz, and results show an estimated snow brightness temperature well correlated to the airborne snow brightness temperatures over vegetation-free areas.

Brightness Temperature Simulations of the Canadian Seasonal Snowpack Driven by Measurements of the Snow Specific Surface Area

Snow grain size is the snowpack parameter that most affects the microwave snow emission. The specific surface area (SSA) of snow is a metric that allows rapid and reproducible field measurements and that well represents the grain size. However, this metric cannot be used directly in microwave snow emission models (MSEMs). The aim of this paper is to evaluate the suitability and the adaptations required for using the SSA in two MSEMs, i.e., the Dense Media Radiative Theory-Multilayer model (DMRT-ML) and the Helsinki University of Technology model (HUT n-layer), based on in situ radiometric measurements. Measurements of the SSA, using snow reflectance in the short-wave infrared, were taken at 20 snowpits in various environments (e.g., grass, tundra, and dry fen). The results show that both models required a scaling factor for the SSA values to minimize the root-mean-square error between the measured and simulated brightness temperatures. For DMRT-ML, the need for a scaling factor is likely due to the oversimplified representation of snow as spheres of ice with a uniform radius. We hypothesize that the need for a scaling factor is related to the grain size distribution of snow and the stickiness between grains. For HUT n-layer, using the SSA underestimates the attenuation by snow, particularly for snowpacks with a significant amount of depth hoar. This paper provides a reliable description of the grain size for DMRT-ML, which is of particular interest for the assimilation of satellite passive microwave data in snow models.

Modeling the impact of snow drift on the decameter‐scale variability of snow properties on the Antarctic Plateau

The annual accumulation and the physical properties of snow close to the surface on the Antarctic Plateau are characterized by a large decameter-scale variability resulting from snow drift that is not simulated by one-dimensional snow evolution models. Here, the detailed snowpack model Crocus was adapted to Antarctic conditions and then modified to account for this drift-induced variability using a stochastic snow redistribution scheme. For this, 50 simulations were run in parallel and were allowed to exchange snow mass according to rules driven by wind speed. These simple rules were developed and calibrated based on in situ pictures of the snow surface recorded for two years. The simulation performed with this new model shows three substantial improvements with respect to standard Crocus simulations. First, significant and rapid variations of snow height observed in hourly measurements are well reproduced, highlighting the crucial role of snow drift in snow accumulation. Second, the statistics of annual accumulation is also simulated successfully, including the years with net ablation which are as frequent as 15% in the observations and 11% in the simulation. Last, the simulated vertical profiles of snow density and specific surface area down to 50 cm depth were compared to 98 profiles measured at Dome C during the summer 2012–2013. The observed spatial variability is partly reproduced by the new model, especially close to the surface. The erosion/deposition processes explain why layers with density lower than 250 kg m−3 or specific surface area larger than 30 m2 kg−1 can be found deeper than 10 cm.

Surface melting derived from microwave radiometers: a climatic indicator in Antarctica

Abstract This paper aims at presenting a new dataset including the melt events derived from microwave remote sensing occurring in Antarctica from summer 1979/80 to 2005/06. The method for detecting melt events and sources of error is presented, and then trends in melt duration for every pixel are extracted from the dataset, mapped and analyzed. The analysis focuses on two particular cases, and the main results show that: (1) the trends over the period 1980–2006 in the Antarctic Peninsula match with lengthening of the melt season on the ice shelves and, surprisingly, shortening of the melt season in the mountainous area of the peninsula; and (2) the trends over the period 1996–2006 on the entire continent show a dipolar pattern, with the western regions experiencing decreasing melt duration, whereas East Antarctica and the Ross Ice Shelf experience increasing melt duration. This pattern closely mirrors the temperature pattern expected when the Southern Annular Mode is in a decreasing trend, as it is over the period 1996–2006. For further analysis and validation, the dataset has been made available at http://www-lgge.obs.ujf-grenoble.fr/~picard/melting/.