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

Land Surface Models (LSM) have shown some difficulties to properly simulate day-time 2-m air and surface skin temperatures. This kind of models are coupled to atmospheric models in mesoscale modelling, such as the Regional Atmospheric Modeling System (RAMS) and the Weather Research and Forecasting (WRF) Model. This model coupling is used within Numerical Weather Prediction Systems (NWP) in order to forecast key physical processes for agricultural meteorology and forestry as well as in ecological modelling. The current study first evaluates the surface energy fluxes and temperatures simulated by these two state-of-the-art NWP models over two distinct vegetated covers, one corresponding to a poor and sparsely vegetated area and the other one corresponding to the tall and well-vegetated area of a forest. On the other hand, the importance of parameterizing the thermal roughness length within the LSM coupled to the corresponding atmospheric model is also evaluated. The LEAF-3 LSM is used within the RAMS modelling environment while the Noah-MP LSM is applied within WRF. Results indicate that the original version of the models underestimates the temperature during the day, more remarkably in the forested area, whereas modifications in the thermal roughness length successfully simulates the temperature and sensible heat flux forecasts over this area. This study highlights the key role of the surface exchange processes when coupling land and atmosphere models. In this regard, incorporating an extra resistance in the surface-layer parameterization through the thermal roughness length is essential to simulate well both temperatures and sensible heat fluxes, which becomes more relevant over tall and well-vegetated areas, such as a forest. This extra resistance for heat exchange prevents effective molecular diffusion in the layer between the momentum roughness length and the thermal roughness length. Additionally, an appropriate description of the canopy height permits to apply an improved surface-layer formulation over different land and vegetation covers

Spatio-temporal variability of fog-water collection in the eastern Iberian Peninsula: 2003-2012

Among the different inputs involved in the hydrological system, fog water measured by man-made passive devices is one of the most unknown components, although it could be an additional water resource for specific environmental applications (forest restoration, forest firefighting, etc.). Focusing on the Mediterranean Iberian Peninsula, the aim of this work is to quantify fog-water collected by a 24-fog-stations network spread across three latitudinal sectors with different locations (coastal, pre-littoral and inland), and to determine the most productive sites. Measurements from the network show that distance-to-sea, latitude or elevation differences between stations are factors affecting fog-water collection potential. The network, based on passive cylindrical omnidirectional fog-water collectors, was active during the period 2003-2012. In addition to fog collection, other environmental variables such as rainfall, wind speed and wind direction, air temperature and relative humidity were measured. These ancillary data were used in a specific data reduction technique to eliminate the simultaneous rainwater component from the fog water measurements, and in the retrieval of the optimum mean wind directions to harvest fog-water efficiently. It was concluded that (i) positive differences in elevation allow greater collection rates, even under 100m differences; (ii) optimum harvesting wind directions for inland locations are in line with the orientation of the existent valley coupled with the shortest path to the coastline, their collected fog-water volumes being generally smaller than those near the coast; (iii) fog-water collection at coastal locations present more dispersed optimal wind directions, ranging from north to the direction of the most immediate coastline; and (iv) there is a practically null dependence of the optimum mean wind direction on seasonality, but a strong dependence of fog-water captured volumes, however

Improved meteorology and surface fluxes in mesoscale modelling using adjusted initial vertical soil moisture profiles

The Regional Atmospheric Modeling System (RAMS) is being used for different and diverse purposes, ranging from atmospheric and dispersion of pollutants forecasting to agricultural meteorology and ecological modelling as well as for hydrological purposes, among others. The current paper presents a comprehensive assessment of the RAMS forecasts, comparing the results not only with observed standard surface meteorological variables, measured at FLUXNET stations and other portable and permanent weather stations located over the region of study, but also with non-standard observed variables, such as the surface energy fluxes, with the aim of evaluating the surface energy budget and its relation with a proper representation of standard observations and key physical processes for a wide range of applications. In this regard, RAMS is assessed against in-situ surface observations during a selected period within July 2011 over Eastern Spain. In addition, the simulation results are also compared with different surface remote sensing data derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) (MSG-SEVIRI) as well as the uncoupled Land Surface Models (LSM) Global Land Data Assimilation System (GLDAS). Both datasets complement the available in-situ observations and are used in the current study as the reference or ground truth when no observations are available on a selected location. Several sensitivity tests have been performed involving the initial soil moisture content, by adjusting this parameter in the vertical soil profile ranging from the most superficial soil layers to those located deeper underground. A refined adjustment of this parameter in the initialization of the model has shown to better represent the observed surface energy fluxes. The results obtained also show an improvement in the model forecasts found in previous studies in relation to standard observations, such as the air temperature and the moisture fields. Therefore, the application of a drier or wetter soil in distinct soil layers within the whole vertical soil profile has been found to be crucial in order to produce a better agreement between the simulation and the observations, thus reiterating the determining role of the initial soil moisture field in mesoscale modelling, but in this case considering the variation of this parameter vertically