L. Caporaso

Study of atmospheric aerosols and mixing layer by LIDAR

The LIDAR (laser radar) is an active remote sensing technique, which allows for the altitude-resolved observation of several atmospheric constituents. A typical application is the measurement of the vertically resolved aerosol optical properties. By using aerosol particles as a marker, continuous determination of the mixing layer height (MLH) can also be obtained by LIDAR. Some examples of aerosol extinction coefficient profiles and MLH extracted from a 1-year LIDAR data set collected in Milan (Italy) are discussed and validated against in situ data (from a balloon-borne optical particle counter). Finally a comparison of the observation-based MLH with relevant numerical simulations (mesoscale model MM5) is provided.

Inferring soil moisture variability in the Mediterrean Sea area using infrared and passive microwave observations

The objective of this study was to infer soil moisture variability from a combination of passive microwave and infrared satellite observations. The proposed approach is mainly based on the concept of apparent thermal inertia (ATI) and makes use of the daily gradient in brightness temperature from MODIS AQUA to infer soil moisture at moderate spatial resolution. Soil moisture retrievals from optical polar orbiting satellites are affected by discontinuities due to the presence of clouds and spurious fluctuations because of low temporal sampling, which is not sufficient for a reliable daily cycle sampling. To mitigate these limitations, we propose using soil moisture temporal trend derived from passive microwave based product, namely the NASA AMSR-E soil moisture product, to filter estimates from MODIS observations. Passive microwave-based soil moisture products exhibit less fluctuation because of their coarse resolution and lower sensitivity to atmosphere. They can therefore be considered as natural “low pass filters” thus reducing the effect of noise in the infrared based estimates. A sensitivity test was conducted to identify to determine the contribution of various factors to the inferred soil moisture from ATI and the error that they may introduce in the estimates. The ATI-based approach was then applied to qualitatively describe the spatial distribution of soil moisture. The algorithm was validated over two different test areas in Italy and France where reference measurements are available. For the test site in Italy, the obtained ATI values were clustered around four different values corresponding to different levels of wetness. The determined four classes of soil moisture (low, medium, medium-high, and high) were compared to available in situ observations. An agreement with in situ observations of 81% was obtained. In densely vegetated areas, only three classes of soil moisture were instead distinguishable. The obtained agreement between observed and inferred soil moisture values was 88%. Also, in the second study area in France, where vegetation is more dominant, only three classes of soil moisture were determined with a lower agreement of 73%. In addition, the ATI trends are in agreement with thermal inertia values determined from physics-based formulation. This study showed that a combination of infrared and passive microwave observation may lead to a better mapping of soil moisture at the regional scale.

Relating Mean Radiosounding Profiles to Surface Fluxes for the Very Stable Boundary Layer

A dataset collected during a measurement campaign in the middle of the Po Valley, Italy, is used to investigate the boundary-layer structure in stable conditions. Empirical formulations for temperature and wind profiles derived from Monin–Obukhov similarity theory are used as regression curves to fit radiosounding profiles in the lower half of the boundary-layer. The best fitting parameters of the regression are then compared to the surface turbulent fluxes as measured by a co-located sonic anemometer. This comparison shows significant discrepancies and supports earlier results showing that surface fluxes, in the limit of high stability, are not adequate scalings for mean profiles. The most evident differences are found for cases for which the bulk Richardson number turns out to be quite large. One of the practical consequences is that boundary-layer height diagnostic formulations that mainly rely on surface fluxes are in disagreement with those obtained by inspecting the thermodynamic profiles recorded during the radiosounding ascent. Moreover the incorrect scaling of similarity profiles in stable conditions leads to the erroneous diagnosis of 2-m air temperatures used in numerical weather prediction validation.