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In recent years, extreme weather events caused by global climate change have occurred frequently, intensifying the frequency of flood disasters. For flood hazard analysis, high-quality data and a reasonable weight assignment of the relevant factors are critical. This study conducts four rainfall fusion methods, to fuse the Tropical Rainfall Measuring Mission (TRMM) 3B42 and the observations in Dazhou City, China. Then, the random forest was applied to obtain the weights of various factors to facilitate a comprehensive flood hazard analysis under four rainfall durations. The results show that (1) the linear regression performs best out of the four fusion methods, with a correlation coefficient of 0.56; (2) the Digital Elevation Model (DEM) is the most impact factor with a weight of more than 0.2; and (3) the proposed flood analysis system performs well, as 70% of historical flood points are distributed in high and sub-high hazard areas and more than 93% of historical flood points are distributed in medium hazard areas. This study identified the flood hazard grade and distribution in Dazhou City, which could provide a valuable methodology to contribute to flood hazard analysis and disaster management with satellite rainfall. Furthermore, the results of this paper are profound for future work on the high-resolution flood risk assessment and management in Dazhou City. [ABSTRACT FROM AUTHOR]

Aboveground net primary productivity (ANPP) and rain-use efficiency (RUE) are important indicators in assessing the response of ecosystems to climate change. In this paper, the Changtang Plateau in the Tibetan Autonomous Region was selected as the study area to analyze the spatial and temporal changes of ANPP and RUE in grassland communities and their response to climate change. The results showed the following:(1) The spatial pattern of ANPP was closely related to rainfall on the Changtang Plateau. The average ANPP over the past 15 years increased gradually from the arid west to the humid east. A consistent pattern was exhibited in different grassland types and climate zones. (2) The RUE was higher at the east and west edges of the Changtang Plateau, especially in the arid west, but was lower in the center. From the perspective of different climatic zones, the average RUE in the southern Tibetan semiarid climate zone and the Ngari arid climate zone was significantly higher than that in other climate zones. However, the average RUE in different grassland types only varied from 0.07 to 0.09 g·m−2·mm−1. The spatial variation in RUE was more distinct in different climatic zones than in different grassland types. (3) Climate change influenced the interannual variation of ANPP and RUE, but the response of ANPP to rainfall showed a significant lag. The interannual change in RUE was negatively correlated with changes in precipitation. (4) In general, a greater area showed a significant increase rather than a decrease in ANPP on the Changtang Plateau, which meant that the grassland condition is improving. The temporal variation patterns of ANPP and RUE in different climate zones were consistent with the overall patterns on the Changtang Plateau, while the variation was not significant in different grassland types. [ABSTRACT FROM AUTHOR]

In this paper, we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near real-time (3 h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (<3 mm h − 1 ). [ABSTRACT FROM AUTHOR]