Search Results (2)

The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partitioning at the land surface in short-time scale simulations. Aside from in situ observations, we use the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor to assess the Land Surface Temperature (LST) field simulated by WRF. Regarding multiple options in Noah-MP, WRF has been configured using three distinct soil moisture factors to control stomatal resistance (β factor) available in Noah-MP (Noah, CLM, and SSiB-types), two canopy stomatal resistance (Ball–Berry and Jarvis), and two options for surface layer drag coefficients (Monin–Obukhov and Chen97 scheme). Considering the β factor schemes, CLM and SSiB-type β factors simulate very low values of the latent heat flux while increasing the sensible heat flux. This result has been obtained independently of the canopy stomatal resistance scheme used. Additionally, the surface skin temperature simulated by Noah-MP is colder than that obtained by the original Noah LSM. This result is also highlighted when the simulated surface skin temperature is compared to the MSG-SEVIRI LST product. The largest differences between the satellite data and the mesoscale simulations are produced using the Noah-MP configurations run with the Monin–Obukhov parameterization for surface layer drag coefficients. In contrast, the Chen97 scheme shows larger surface skin temperatures than Monin–Obukhov, but at the expense of a decrease in the simulated sensible heat fluxes. In this regard, the ground heat flux and the net radiation play a key role in the simulation results. Full article

In this paper, the coupled WRF/SSiB model, accompanied by a Karst Rocky Desertification (KRD) map of the Guizhou Karst Plateau (GKP) of China, was applied to detect how the changed vegetation and soil characteristics over the GKP modify the energy balance at the land surface. The results indicated that land degradation led to reduced net radiation by inducing more upward shortwave and longwave radiation, which were associated with increasing surface albedo and temperature, respectively. The KRD also resulted in changed surface energy partitioning into sensible and latent heat fluxes. The latent heat flux at land surface was reduced substantially due to the higher surface albedo and stomatal resistance, the lower Leaf Area Index (LAI) and roughness length in the degradation experiment, while the sensible heat flux increased, mainly because of the higher surface temperature. Furthermore, the moisture flux convergence was reduced, owing to the lower atmospheric heating and the relative subsidence. However, compared with the reduced evaporation, the decrease in moisture flux convergence contributed much less to the reduced precipitation. Precipitation strongly affects soil moisture, vegetation growth and phenology, and thus evaporation and convective latent heating, so when precipitation was changed, a feedback loop was created. Full article