Preliminary results of an attempt to provide soil moisture datasets in order to verify numerical weather prediction models

In the recent years, there has been a significant growth in the recognition of the soil moisture importance in large-scale hydrology and climate modelling. Soil moisture is a lower boundary condition, which rules the partitioning of energy in terms of sensible and latent heat flux. Wrong estimations of soil moisture lead to wrong simulation of the surface layer evolution and hence precipitations and cloud cover forecasts could be consequently affected. This is true for largescale medium-range weather forecasts as well as for local-scale short-range weather forecasts, particularly in those situations in which local convection is well developed. Unfortunately, despite the importance of this physical parameter there are only few soilmoisture data sets sparse in time and in space around in the world. Due to this scarcity of soil moisture observations, we developed an alternative method to provide soilmoisture datasets in order to verify numericalw eather prediction models. In this paper are presented the preliminary results of an attempt to verify soil moisture fields predicted by a mesoscale model. The data for the comparison were provided by the simulations of the diagnostic land surface scheme LSPM (Land Surface Process Model), widely used at the Piedmont Regional Weather Service for agro-meteorological purposes. To this end, LSPM was initialized and driven by Synop observations, while the surface (vegetation and soil) parameter values were initialized by ECOCLIMAP global dataset at 1km2 resolution

Validation and sensitivity tests on improved paramerizations of a land surface process model (LSPM) in the Po Valley

The Land Surface Process Model (LSPM) has been improved with respect to the 1st version of 1994. The modifications have involved the parametrizations of the radiation terms and of turbulent heat fluxes. A parametrization of runoff has also been developed, in order to close the hydrologic balance. This 2nd version of LSPM has been validated against experimental data gathered at Mottarone (Verbania, Northern Italy) during a field experiment. The results of this validation show that this new version is able to apportionate the energy into sensible and latent heat fluxes. LSPM has also been submitted to a series of sensitivity tests in order to investigate the hydrological part of the model. The physical quantities selected in these sensitivity experiments have been the initial soil moisture content and the rainfall intensity. In each experiment, the model has been forced by using the observations carried out at the synoptic stations of San Pietro Capofiume (Po Valley, Italy). The observed characteristics of soil and vegetation (not involved in the sensitivity tests) have been used as initial and boundary conditions. The results of the simulation show that LSPM can reproduce well the energy, heat and water budgets and their behaviours with varying the selected parameters. A careful analysis of the LSPM output shows also the importance to identify the effective soil type

Validation of a method for the determination of the sensible-heat flux with Sodar data in free convection cases

A simple method to determine the value of the ground sensible-heat flux using Sodar data is presented and validated. The measurement of the variance of the wind velocity components gives us an estimate of the intensity of the atmospheric turbulence; the local value of variance of the vertical wind velocity s2w depends on the efficiency of thermal and mechanical turbulence production. The portion of the atmospheric boundary layer, where turbulent kinetic energy is prevalently produced by buoyancy forces, is characterised by profiles of s3w Oz and of (sensible-) heat flux which decrease linearly with height. The extrapolation to the ground of the former profile gives an estimate of the value of sensible-heat flux at the surface. The validation of the results is performed by comparison of the energy involved in the development of convective episodes calculated, over the same time interval, from sensible-heat flux at the surface with that derived from potential temperature profiles relative to two successive radio soundings. When perturbative processes like, for example, rise up of breezes, are absent, the estimates of energies are in excellent agreement, being the angular coefficient of regression line 1.01 and the linear correlation coefficient 0.93

Sensitivity tests on the criterion of potential vorticity index for discriminating the location of ozone sources and sinks over large continental areas

This paper presents the results of a sensitivity analysis of a statistical-dynamic model (ISOGASP, standing for Identification of SOurces of greenhouse GAS Plus), developed by our research group to reconstruct 3D concentration patterns of greenhouse gases in large and deep atmospheric regions over continental or oceanic areas and extending vertically from the lower troposphere to the lower stratosphere. The results of this analysis have shown the ability of the ISOGASP model to discriminate the locations of ozonesource s, according to the geographical distribution patterns of atmospheric O3 concentration inside a limited number of atmospheric layers at different heights above sea level, reconstructed through the method of backward trajectories simulating the travel of air parcels from each different layer to the receptor points at their own height. The potential vorticity index has been used to discriminate the sub-sets of trajectories belonging to stratosphere or troposphere