The Tibetan Plateau (TP) region contains maximal alpine grassland ecology at the mid-latitudes. This region is also recognized as an ecologically fragile and sensitive area under the effects of global warming. Regional climate modeling and ecosystem research depend on accurate land cover (LC) information. In order to obtain accurate LC information over the TP, the reliability and precision of five moderate/high-resolution LC products (MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 in 2020) were analyzed and evaluated in this study. The different LC products were compared with each other in terms of areal/spatial consistency and assessed with four reference sample datasets (Geo-Wiki, GLCVSS, GOFC-GOLD, and USGS) using the confusion matrix method for accuracy evaluation over the TP. Based on the paired comparison of these five LC datasets, all five LC products show that grass is the major land cover type on the TP, but the range of grass coverage identified by the different products varies noticeably, from 43.35% to 65.49%. The fully consistent spatial regions account for 43.72% of the entire region of the TP, while, in the transition area between grass and bare soil, there is still a large area of medium-to-low consistency. In addition, a comparison of LC datasets using integrated reference datasets shows that the overall accuracies of MCD12Q1, C3S-LC, GlobeLand30, GLC_FCS30, and ESA2020 are 54.29%, 49.32%, 53.03%, 53.73%, and 60.11%, respectively. The producer accuracy of the five products is highest for grass, while glaciers have the most reliable and accurate characteristics among all LC products for users. These findings provide valuable insights for the selection of rational and appropriate LC datasets for studying land-atmosphere interactions and promoting ecological preservation in the TP.

The Haihe River basin of North China is characterized by extremely low per capita water resources and a consistently long-term decreasing trend of precipitation and runoff over the last few decades. This study analyzes the climatological features of rainy season (May–September) precipitation in the Haihe River basin and its branch systems based on a high-density hourly observational dataset during 2007–2017. We show that there are two high-rainfall zones in the basin, with one along the south of the Yanshan Mountains to Taihang Mountains and another along the Tuma River in the south. Rainstorm centers exist amidst the two zones. July generally sees the highest precipitation, followed by August, and May has the lowest precipitation. The major flood season is reached between the third pentad of July and the fourth pentad of August. The precipitation is high at night but low in the daytime. In the pre-flood season before early July, rainfalls mostly arrive at 16:00–21:00 h. After entering the major flood season, the diurnal precipitation has two peaks, one at 17:00–22:00 h and the other at 0:00–7:00 h. In the post-flood season after mid-August, the most rain occurs at night, with the peak appearing at 0:00–8:00 h. The short-duration precipitation is mainly distributed in the mountainous areas, and the long-duration precipitation that contributes most to seasonal rainfalls appears in the plain areas, and the continuous precipitation mostly occurs in the windward slopes of the Taihang Mountains and the Yanshan Mountains. In addition, urbanization process around large city stations may have affected the rainy season precipitation to a certain extent in the Haihe River basin, with large and medium city stations experiencing around 10% higher precipitation than small city stations. However, this issue needs to be investigated exclusively.

Using solar observation and meteorological data of the Sino-Singapore Tianjin Eco-city from August 14^th 2014 to August 12^th 2015, characteristics of solar radiation of the eco-city and characteristics of solar radiation on a tilted surface under different weather conditions were analyzed and assessed. And the accuracy and error sources of isotropic and anisotropic calculation model for solar radiation on a tilted surface were studied. The results show that observed radiation on a horizontal and tilted surface is quite different at monthly, seasonal and annual time scales, so the estimated photovoltaic power generation based on the solar radiation on a horizontal surface is not accurate. Diurnal cycle of solar radiation is affected by different weather conditions and the power stations need to adjust generation strategies according to weather conditions. Accuracy of the two kinds of tilted radiation calculation models is similar and the overall calculation effect is reasonable. The uncertainty of the direct portion segment calculation function is the main cause of calculated errors.