Soils containing gravel (particle size ≥2 mm) are widely distributed over the Qinghai–Tibet Plateau (QTP). Soil mixed with gravel has different thermal and hydrological properties compared with fine soil (particle size <2 mm) and thus has marked impacts on soil water and heat transfer. However, the most commonly used land models do not consider the effects of gravel. This paper reports the development of a new scheme that simulates the thermal and hydrological processes in soil containing gravel and its application in the QTP. The new scheme was implemented in version 4 of the Community Land Model, and experiments were conducted for two typical sites in the QTP. The results showed that (1) soil with gravel tends to reduce the water holding capacity and enhance the hydraulic conductivity and drainage; (2) the thermal conductivity increases with soil gravel content, and the response of the temperature of soil mixed with gravel to air temperature change is rapid; (3) the new scheme performs well in simulating the soil temperature and moisture—the mean biases of soil moisture between the simulation and observation reduced by 25–48 %, and the mean biases of soil temperature reduced by 9–25 %. Therefore, this scheme can successfully simulate the thermal and hydrological processes in soil with different levels of gravel content and is potentially applicable in land surface models.
This study explored the impact of coastal radar observability on the forecast of the track and rainfall of Typhoon Morakot(2009)using a WRF-based ensemble Kalman filter(EnKF)data assimilation(DA)system.The results showed that the performance of radar EnKF DA was quite sensitive to the number of radars being assimilated and the DA timing relative to the landfall of the tropical cyclone(TC).It was found that assimilating radial velocity(Vr)data from all the four operational radars during the 6 h immediately before TC landfall was quite important for the track and rainfall forecasts after the TC made landfall.The TC track forecast error could be decreased by about 43% and the 24-h rainfall forecast skill could be almost tripled.Assimilating Vr data from a single radar outperformed the experiment without DA, though with less improvement compared to the multiple-radar DA experiment.Different forecast performances were obtained by assimilating different radars, which was closely related to the first-time wind analysis increment, the location of moisture transport, the quasi-stationary rainband, and the local convergence line.However, only assimilating Vr data when the TC was farther away from making landfall might worsen TC track and rainfall forecasts.Besides, this work also demonstrated that Vr data from multiple radars, instead of a single radar, should be used for verification to obtain a more reliable assessment of the EnKF performance. 相似文献
IntroductionSince Steketee introduced the elastic dislocation theory into geophysics in 1958, it has become an important part of seismology. Because the fracture of fault can be treated as a displacement bound, the elastic displacement field (forward problem) can be studied by the static elastic dislocation theory under some given condition. Vice versa, if the static displacement field is known, the cause (inverse problem) can be inferred by the dislocation theory. In the last 40 years, many … 相似文献