Comparative assessment of RAMS and WRF short-term forecasts over Eastern Iberian Peninsula using various in-situ observations, remote sensing products and uncoupled land surface model datasets

Abstract

The Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) mesoscale models are being used for weather and air quality studies as well as forecasting tools in Numerical Weather Prediction (NWP) systems. In the current study, we perform a comparative assessment of these models under distinct typical atmospheric conditions, classified according to the dominant wind flow and cloudiness, over Eastern Iberian Peninsula. This study is focused on the model representation of key physical processes in terms of meteorology and surface variables during a 7-days period in summer 2011. The hourly outputs produced by these two models are compared not only with observed standard surface variables, measured at different permanent weather stations located over the region of study, but also with different surface remote sensing products and uncoupled Land Surface Models (LSM) datasets. Confronting RAMS and WRF, the current study highlights relevant differences over areas near the coast when mesoscale circulations or Eastern synoptic advections are developed over the region of study. A higher moisture content is observed under these atmospheric conditions, due to the moisture transport by the sea breeze inland. In this regard, it has been found that the Eastern wind field simulated by WRF reaches inland areas and comprises a larger sea breeze extension than RAMS. This sea breeze development impacts meteorology and surface variables in locations not too close to the coast, but still affected by land-sea winds. Additionally, WRF remains more windy and moister than RAMS at night-time, while alike results are found under Western synoptic advections. The results obtained in the current paper show differences under distinct dominant atmospheric conditions, which outline further research in this field in order to achieve more general conclusions.

3D-VAR Data Assimilation of SEVIRI Radiances for the Prediction of Solar Irradiance in Italy Using WRF Solar Mesoscale Model—Preliminary Results

“…Indeed, the value of the MBE one hour after the assimilation time passes from 49 W/m 2 to 20 W/m 2 for ASSIM and from 54 W/m 2 to 42 W/m 2 for CNTRL, using only the water grid points and the behavior is similar for the remaining indexes. The statistical scores obtained are comparable or slightly better than the values obtained from similar works, where a NWP is used to estimate the GHI [13][14][15][16][17][18]. The results from these preliminary tests show that the assimilation of geostationary satellite data increase the performances of the WRF-Solar model especially in the short-term range of the forecasts.…”

“…A similar evaluation has been performed for the WRF/RAMS models over a region in Eastern Spain under distinct atmospheric conditions using in-situ observations and remote sensing data derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the Meteosat Second Generation (MSG) and the uncoupled Land Surface Model (LSM) Global Land Data Assimilation System (GLDAS) during a 7-day period in summer 2011. Both the models show difficulties to forecast clouds with values of Mean Bias Error (MBE) and RMSE in overcast conditions ranging, respectively, from −70 to −80 W/m 2 and from 140 to 190 W/m 2 for WRF and from −80 to −110 W/m 2 and from 200 to 400 W/m 2 for RAMS [18].…”

Improving RAMS and WRF mesoscale forecasts over two distinct vegetation covers using an appropriate thermal roughness length parameterization

“…However, it is accompanied with some persistence cloudiness around the study area starting around noon, even though no significant cloudiness is specifically observed over BON and ALM. As it will be seen later, both RAMS and WRF simulate cloudiness over these two locations, reflecting the difficulty of mesoscale models regarding cloud forecasting (Gómez et al, 2018b), thus producing higher errors than those obtained for instance on 6 or 7 July. RAMS and WRF have been used to perform a daily simulation with a forecast horizon of 36 h and a temporal resolution of 1 h, starting at 12 UTC the previous day.…”

“…It seems that the surface-layer parameterizations used in the current study produces indeed the same effect no matter the specific LSM formulation implemented within RAMS and WRF. However, the same surface-layer formulation for these models produces higher 2-m air temperatures using RAMS than those simulated using WRF (Gómez et al, 2018b). This result is obtained no matter whether z 0h =z 0 or an alternative definition for z 0h is used.…”

“…On the other hand, the Land Surface Temperature (LST; Caselles et al, 1997;Trigo et al, 2008) generated by the Land Surface Analysis Satellite Applications Facility (LSA SAF) from satellite data, obtained from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) (MSG-SEVIRI), is used as well for the models' assessment in the current study (Gómez et al, 2016b(Gómez et al, , 2018b.…”