A Sensitivity Study on High Resolution NWP ICON—LAM Model over Italy

Abstract

In this work, the results of a sensitivity study based on ICON-LAM simulations at 2.5 km of spatial resolution over the Italian area, driven by ECMWF IFS global data, are presented. The main aim is to provide a contribution to the selection of suitable parameterization schemes that result in more effective for a proper representation of the Italian climate features. Model evaluation was conducted in terms of the air temperature and precipitation for three subregions, comparing a set of 13 simulations against SCIA and E-OBS standard datasets. In addition, evaluation was also conducted against selected data stations scattered over the Italian area. We found that the ICON-LAM model was able to provide a good representation of the temperature over Italy, whereas non-negligible biases were observed for precipitation in certain regions. The model proved to be sensitive to changes in physical parameterization schemes. In particular, we found that the explicit treatment of deep convection and the “clouds as in turbulence” scheme for cloud cover allowed for a better representation of precipitation in the summer over the Alpine region. The single moment scheme is currently the best option for cloud microphysics.

A Metamodel-Based Optimization of Physical Parameters of High Resolution NWP ICON-LAM over Southern Italy

“…The optimization process performed in the present work starts from a configuration name list (here referred to as baseline), inherited from the work described in [10], where a suitable configuration for the whole Italian peninsula was defined, based on a reference defined at DWD (Germany) with some modifications suggested by the Israeli Meteorological Service (IMS, Israel). This reference configuration assumes that the shallow convection parameterization is active, whereas the parts treating deep-and mid-level convection are switched off.…”

“…Specifically, over the domain considered, data from 28 stations are available for temperature and 48 for precipitation (Figure 2). Grid data (obtained through an interpolation process, already considered in a previous work [10]) are available over the whole domain on a regular grid at 5 km resolution for temperature and 10 km for precipitation. Furthermore, the outputs of ICON simulations were also compared with the results obtained with COSMO on a similar domain.…”

“…Several studies have shown that the configuration of an NWP LAM model (developed for a specific area) cannot be directly transferred to other geographical areas [10]. The definition of a suitable model configuration for ICON-LAM over Italy is only at an early stage, so that deep analyses are still required in order to consider the particular orography of the Italian peninsula and its strong interaction with the sea.…”

“…The computational budget for the off-line stage involved a test matrix of thirty-six ICON simulations, plus the baseline set of ICON runs with the configuration of physical variables inherited from [10]. In the adaptive stage, the two metamodels drove the opti-mization, each suggesting its own candidate name list that ICON simulated, and, then, updated the metamodel once the results were post-processed.…”

“…A first sensitivity analysis was performed with respect to the domain size, considering a reference domain and two additional domains that were respectively 50% and 100% larger (in both directions) than the original one. Then, an automatic calibration of four critical physical parameters was carried out starting from a model configuration previously defined by the authors (in a joint effort with the CMCC Foundation, Italy) for the whole Italian area, employing a different resolution (R2B10, about 2.5 km) [10]. The tuning was performed over the following parameters that were previously shown to play a significant role in determining model response: tkhmin (minimal diffusion coefficient for heat and moisture), tkmmin (minimal diffusion coefficient for momentum), rlam_heat (factor for laminar resistance for heat) and v0snow (factor for vertical velocity of snow).…”