The proximity of the WMO station (locations P4 and T4) to the SPCFLUX93 site allowed us to implement and test an original method (named CREADB and described in Ruti et al., 1997 and in Cassardo et al., 1998) to derive from synoptic observations (which are wide-spread) the necessary data to drive SVAT (Soil Vegetation Atmosphere Transfer) schemes.
As know, a SVAT model needs boundary conditions: air pressure, temperature, humidity information (relative, specific, dew–point, etc.), wind vector, precipitation, solar radiation or cloudiness. CREADB method can use synoptic data to produce the necessary information for SVAT models.
We tested this procedure during SPCFLUX93. The results showed that air temperature and relative humidity data are reproduced in a good way, wind velocity in a satisfactory way, while precipitation is somehow smoothed, due to the fact that synoptic data only provided the information of cumulated precipitation in the last 6 hours. From these conclusions, we can state that CREADB can be safely used for climatological purposes.

Sensible, latent and ground-atmosphere heat fluxes, evaluated with the above mentioned procedures and the net radiation data measured in location T1B, were compared with the output coming from a simulation run with the biospheric model Land Surface Process Model (LSPM, version “2” of 1996) of Cassardo et al. (1995b). The assumed vegetation type was short grass. As initial soil temperatures, “climatological values”  for SPC site were used. Regarding initial values of soil moistures, we used a particular method in order to avoid the so-called “spin-up problem”: in fact, as known, the climatic system can require a few months before the initial values of the soil moisture fields are forgotten and this can be an estimate of the time needed by a climate model to adjust realistically to initial errors in the soil moisture distribution. Then, we used the values coming from the long time simulation (6 months from January to June 1993) carried out on SPC data and described in Ruti et al. (1997), where it was demonstrated that, after this long time simulation, LSPM reached its equilibrium state in June, and then the June values can be considered as unaffected by spin-up problems. Finally, the boundary conditions necessary for the above mentioned 6-months run (2 m temperature, 2 m relative humidity, 2 m wind, sea level pressure, precipitation and cloud coverage) were extracted and arranged from synop data by using CREADB algorithm (see § 6.3). The necessary radiation input (long and short wave) for the two models were simulated using the empirical package of LSPM, taken from Page (1986).
In Figures 23a are reported the time series of observations (points) and LSPM output (solid line) during the whole period of SPCFLUX93 campaign for net radiation. Generally speaking, the agreement between data and model predictions was good. Some overestimates and underestimates of midday values in clear and cloudy sky conditions were due to errors in the interpolation of cloudiness from synoptic observations (from which the radiation inputs are calculated) or to inaccuracy of the global radiation parameterisation in cloudy days.
Figures 23b and 23c show sensible and latent heat fluxes observations (points) and LSPM output (solid line). From these plots, we can infer that LSPM predictions of both heat fluxes were close to the observed data in their whole range. Only a few maximum values of the latent heat flux were underestimated, particularly in concurrence with large errors in the evaluation of net radiation or in cloudy sky conditions. For this reason, the Bowen ratio predicted by LSPM is larger than the observed one.
Figure 23d shows the heat flux G0 at the ground-atmosphere interface evaluated from observations using eq. 3 (points) compared with the LSPM calculations (solid line). The observations resulted in good agreement with the predictions, with the exception of a little overestimate during daytime around noon and the presence of strong negative minima (calculated) at sunrise.
 

Thermal wave propagation into soil
The data referring to temperature measurements at 7 levels in the first meter of soil allowed us to test different soil parameterisation schemes. In particular, we compared two widely used soil schemes: the (5-level)  multi-layer scheme, used for instance in the LSPM (Cassardo et al., 1995b), and the (3-level)  force-restore scheme, used for instance in the BATS (Dickinson et al., 1986). This comparison was performed running BATS and LSPM (driven with the same initial conditions) for a 6 months simulation (starting from 1st January 1993). Synoptic data arranged with CREADB method (see § 6.3) were used as initial and boundary conditions. In Ruti et al. (1997) we demonstrated that the multilayer scheme produced a more accurate estimate of the thermal wave propagation with respect to the results coming from the use of the classic force-restore method.