The Tibetan Plateau (TP) is the highest land in the world and has a very complex topography. However, the influence of topography on TP snow cover simulations has not been adequately addressed in most land surface models. The analysis of satellite observations indicates that snow cover fraction (SCF) simulation biases increase with the topography complexity, and this increasing trend slows down when the standard deviation of topography is greater than 200 m. The result also shows that using the SCF schemes without consideration of topography leads to a consistent overestimation in winter. To account for the topographic effects, we introduce a modified topographic factor to the SCF schemes. Then we conduct regional simulations using the Simplified Simple Biosphere Model version 3 (SSiB3) and evaluate the results at the location of observation sites to reduce the uncertainty induced by forcing data. Compared with the default SCF scheme, the mean winter SCF bias is reduced from 3.83% to −0.10%. The optimization of SCF simulations further improves the winter surface albedo and land surface temperature (LST) simulations. The winter surface albedo bias over the TP is reduced from 0.020 to 0.007, with a maximum reduction by −0.133. The winter LST bias is reduced from −3.33 to −3.04 K, with a maximum reduction by 3.60 K. This study highlights the importance of topographic effects in simulating snow cover distribution and land surface energy budget for reducing the “cold bias” in winter climate simulations over the TP.

For integrated pest management (IPM), we propose a generalized stage-structured plant-pest-natural enemy system with impulsive spraying pesticide and releasing natural enemies at different fixed moment. By the stroboscopic maps, we obtain two types of periodic solutions: the plant-pest-extinction and the pest-extinction. The sufficient conditions for the global attractivity of a pest-extinction periodic solution and permanence of the system are obtained by comparison theorem and stroboscopic technique. Moreover, numerical simulations are inserted to verify the effectiveness and feasibility of the theoretical results, which show that the impulsive control plays a key role on the permanence of the system.

In this study, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China based on two commonly used aircraft icing diagnostic methods (hereinafter referred to as the IC index method and the TF empirical method, respectively) and ERA5 reanalysis data as the atmospheric environmental field for icing occurrence. The spatial and temporal distribution characteristics of aircraft icing accumulation occurrence over typical cities at different latitudes in China are calculated separately, and the spatial and temporal distribution of icing accumulation areas over Xinchang, Zhejiang Province in China during one case of cold air activity is simulated. Accordingly, several application scenarios for the application of methods to forecast aircraft icing accumulation are proposed. The results indicate that among the selected icing cases, the diagnosis accuracy of the IC index method and the TF empirical method is 80% and 92%, respectively. The TF empirical method takes into account the effects of aircraft flight speed and dynamic warming, and shows better correlation with ice water particle concentration and cloud cover in medium and low clouds. However, the predicted icing accumulation intensity predicted by the TF empirical method is not accurate enough without the real flight speed of the aircraft, and there are more empty forecasts above 400 hPa. In practical applications, both the IC index method and the TF empirical method can effectively identify the icing-prone pressure levels and time periods and forecast the distribution of icing accumulation intensity at high pressure levels for a given station.

In this study, an aircraft icing diagnosis and forecasting method is constructed and hindcast for 25 collected spring icing cases over Eastern China based on two commonly used aircraft icing diagnostic methods (hereinafter referred to as the IC index method and the TF empirical method respectively) and ERA5 reanalysis data as the atmospheric environmental field for icing occurrence. The spatial and temporal distribution characteristics of aircraft icing accumulation occurrence over typical cities at different latitudes in China are calculated separately, and the spatial and temporal distribution of icing accumulation areas over Xinchang, Zhejiang Province in China during one cold air activity case is simulated. Accordingly, several application scenarios of aircraft icing accumulation forecasting methods are proposed. The results indicate that among the selected icing cases, the diagnosis accuracy of the IC index method is 80%, while the TF empirical method is 92%. The effects of aircraft flight speed and dynamic warming are taken into account by TF empirical method, which has better correlation with ice water particle concentration and cloud cover in medium and low clouds. However, the predicted icing accumulation intensity predicted by TF empirical method is not accurate enough without the real flight speed of the aircraft, and there are more empty forecasts above 400-hPa. In practical applications, both the IC index method and the TF empirical method can better diagnose the icing-prone pressure level and the icing-prone time period, and can effectively forecast the distributions of high pressure levels icing accumulation intensity at a certain station.