Influence of vegetation on SMOS mission retrievals

International audienceUsing the proposed Soil Moisture and Ocean Salinity (SMOS) mission as a case study, this paper investigates how the presence and nature of vegetation influence the values of geophysical variables retrieved from multi-angle microwave radiometer observations. Synthetic microwave brightness temperatures were generated using a model for the coherent propagation of electromagnetic radiation through a stratified medium applied to account simultaneously for the emission from both the soil and any vegetation canopy present. The synthetic data were calculated at the look-angles proposed for the SMOS mission for three different soil-moisture states (wet, medium wet and dry) and four different vegetation covers (nominally grass, crop, shrub and forest). A retrieval mimicking that proposed for SMOS was then used to retrieve soil moisture, vegetation water content and effective temperature for each set of synthetic observations. For the case of a bare soil with a uniform profile, the simpler Fresnel model proposed for use with SMOS gave identical estimates of brightness temperatures to the coherent model. However, to retrieve accurate geophysical parameters in the presence of vegetation, the opacity coefficient (one of two parameters used to describe the effect of vegetation on emission from the soil surface) used within the SMOS retrieval algorithm needed to be a function of look-angle, soil-moisture status, and vegetation cover. The effect of errors in the initial specification of the vegetation parameters within the coherent model was explored by imposing random errors in the values of these parameters before generating synthetic data and evaluating the errors in the geophysical parameters retrieved. Random errors of 10% result in systematic errors (up to 0.5°K, 3%, and ~0.2 kg m-2 for temperature, soil moisture, and vegetation content, respectively) and random errors (up to ~2°K, ~8%, and ~2 kg m-2 for temperature, soil moisture and vegetation content, respectively) that depend on vegetation cover and soil-moisture status. Keywords: passive microwave, soil moisture, vegetation, SMOS, retrieva

Application of a plane-stratified emission model to predict the effects of vegetation in passive microwave radiometry

This paper reports the application to vegetation canopies of a coherent model for the propagation of electromagnetic radiation through a stratified medium. The resulting multi-layer vegetation model is plausibly realistic in that it recognises the dielectric permittivity of the vegetation matter, the mixing of the dielectric permittivities for vegetation and air within the canopy and, in simplified terms, the overall vertical distribution of dielectric permittivity and temperature through the canopy. Any sharp changes in the dielectric profile of the canopy resulted in interference effects manifested as oscillations in the microwave brightness temperature as a function of canopy height or look angle. However, when Gaussian broadening of the top and bottom of the canopy (reflecting the natural variability between plants) was included within the model, these oscillations were eliminated. The model parameters required to specify the dielectric profile within the canopy, particularly the parameters that quantify the dielectric mixing between vegetation and air in the canopy, are not usually available in typical field experiments. Thus, the feasibility of specifying these parameters using an advanced single-criterion, multiple-parameter optimisation technique was investigated by automatically minimizing the difference between the modelled and measured brightness temperatures. The results imply that the mixing parameters can be so determined but only if other parameters that specify vegetation dry matter and water content are measured independently. The new model was then applied to investigate the sensitivity of microwave emission to specific vegetation parameters.</p> <p style='line-height: 20px;'><b>Keywords: </b>passive microwave, soil moisture, vegetation, SMOS, retrieva

Research Note:<br>Derivation of temperature lapse rates in semi-arid south-eastern Arizona

International audienceEcological and hydrological modelling at the regional scale requires distributed information on weather variables, and temperature is important among these. In an area of basin and range topography with a wide range of elevations, such as south-eastern Arizona, measurements are usually available only at a relatively small number of locations and elevations, and temperatures elsewhere must be estimated from atmospheric lapse rate. This paper derives the lapse rates to estimate maximum, minimum and mean daily temperatures from elevation. Lapse rates were calculated using air temperatures at 2 m collected during 2002 at 18 locations across south-eastern Arizona, with elevations from 779 to 2512 m. The lapse rate predicted for the minimum temperature was lower than the mean environmental lapse rate (MELR), i.e. 6 K km?1, whereas those predicted for the mean and maximum daily temperature were very similar to the MELR. Lapse rates were also derived from radiosonde data at 00 and 12 UTC (5 pm and 5 am local time, respectively). The lapse rates calculated from radiosonde data were greater than those from the 2 m measurements, presumably because the effect of the surface was less. Given temperatures measured at Tucson airport, temperatures at the other sites were predicted using the different estimates of lapse rates. The best predictions of temperatures used the locally predicted lapse rates. In the case of maximum and mean temperature, using the MELR also resulted in accurate predictions. Keywords: near surface lapse rates, semi-arid climate, mean minimum and maximum temperatures, basin and range topograph