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

Abstract

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.

Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain

“…The Advanced Research core of the WRF model (WRF-ARW) [20,21], version 3.6.1 (Boulder, CO, USA), was used to simulate the selected forecasting period: 6 to 11 July 2011. The model setup is based on that used in previous studies [6,28] conducted over the study area. WRF was set up using the Dudhia shortwave radiation [35] and the rapid radiative transfer model (RRTM) longwave radiation [36] as radiation options, whereas the YSU scheme [37] was used as the PBL parameterization.…”

“…Accurate and reliable information of surface energy fluxes and atmospheric variables is of critical importance for different application fields, not only for atmospheric and climate modeling but also for agricultural, ecological, and hydrological purposes, among others. One of the efforts focused on improving the simulation of surface energy fluxes and atmospheric variables has been dedicated to an accurate simulation of land surface and atmosphere interactions [1][2][3][4][5][6][7]. All these studies have shown essential synergies between the land surface and the atmosphere.…”

“…The interaction between the land surface and the atmosphere, comparing the SVA feedbacks, are modeled by the corresponding LSM models implemented within the WRF modeling system. Both Noah and Noah-MP coupled to the Weather Research and Forecast model have been used by atmospheric and hydrological researchers for different purposes [5,6,15,16,24,[27][28][29]. In addition, these LSMs have been compared to each other for a wide range of applications.…”

“…In addition, these LSMs have been compared to each other for a wide range of applications. For instance, LSMs, and particularly Noah/Noah-MP LSMs, have been used to simulate energy fluxes in response to near-surface atmospheric forcing based on their representation of the land surface processes [5,6,[28][29][30][31][32][33][34]. As such, it is of significant importance to accurately document the model's performance for the simulation of surface energy fluxes [15].…”

Effects of Surface Coupling Strength in WRF/Noah-MP Model on Regional Climate Simulations Over China

“…For example, the difference of summer ΔT in North China between the Czil-h and default M-O schemes is 1.48 °C, in which the mean bias for Ts is 1.28 °C (the contribution of 86.49%) and for Ta is -0.20 °C. These demonstrate the important role of Ch in controlling Ts, andYang et al (2011) indicated that Ch is the most important factor of modeling Ts, thus, considerable efforts by the LSMs modelers have been spent to improve the performance of model in reproducing Ts through the Ch parameterization(Chen et al 2011;Gomez et al 2020).Discussions 4.1 Sensitivities of surface flux and precipitation simulations to the Czil-h scheme and the uncertainties of applying the Czil-h scheme…”