Global expansion of tropical cyclone precipitation footprint.

Precipitation from tropical cyclones (TCs) can cause massive damage from inland floods and is becoming more intense under a warming climate. However, knowledge gaps still exist in changes of spatial patterns in heavy TC precipitation. Here we define a metric, DIST30, as the mean radial distance from centers of clustered heavy rainfall cells (> 30 mm/3 h) to TC center, representing the footprint of heavy TC precipitation. There is significant global increase in DIST30 at a rate of 0.34 km/year. Increases of DIST30 cover 59.87% of total TC impact areas, with growth especially strong in the Western North Pacific, Northern Atlantic, and Southern Pacific. The XGBoost machine learning model showed that monthly DIST30 variability is majorly controlled by TC maximum wind speed, location, sea surface temperature, vertical wind shear, and total water column vapor. TC poleward migration in the Northern Hemisphere contributes substantially to the DIST30 upward trend globally.

A Dark Target Detection Method Based on the Adjacency Effect: A Case Study on Crack Detection.

Dark target detection is important for engineering applications but the existing methods do not consider the imaging environment of dark targets, such as the adjacency effect. The adjacency effect will affect the quantitative applications of remote sensing, especially for high contrast images and images with ever-increasing resolution. Further, most studies have focused on how to eliminate the adjacency effect and there is almost no research about the application of the adjacency effect. However, the adjacency effect leads to some unique characteristics for the dark target surrounded by a bright background. This paper utilizes these characteristics to assist in the detection of the dark object, and the low-high threshold detection strategy and the adaptive threshold selection method under the assumption of Gaussian distribution are designed. Meanwhile, preliminary case experiments are carried out on the crack detection of concrete slope protection. Finally, the experiment results show that it is feasible to utilize the adjacency effect for dark target detection.

Global exposure to rainstorms and the contribution rates of climate change and population change.

Quantifying global population exposure to rainstorms is a key component of population risk assessments for rainstorms and induced floods. Based on daily precipitation data from the NEX-GDDP dataset, rainfall from rainstorms is first calculated by a multi-model ensemble method for four periods from 1986 to 2100. Combined with population data from the SSP2 scenario, the global population exposure to rainstorms is then calculated and analyzed. Finally, the contribution rates of climate change effect, population change effect, and joint change effect on exposure change are quantitatively assessed. The results showed that (1) Population exposure to rainstorms shows a linear upward trend from base period to the late 21st century period in most regions, and the mid-21st century period compared with base period has the fastest rate of increase. (2) The spatial patterns of population exposure to rainstorms are very similar for the four periods and the areas with high exposure are mainly distributed in Asia, population exposure of Africa is gradually increasing. The countries with high exposure show little volatility, especially the top eight countries. (3) The change in total exposure is mainly due to population change. Based on the composition of the total exposure change for each country, the number of countries whose climate change effect is greater than that of population change is gradually increasing, and this number reaches more than a quarter of the total when the late 21st century period is compared with the mid-21st century period.

Assessment of the Casualty Risk of Multiple Meteorological Hazards in China.

A study of the frequency, intensity, and risk of extreme climatic events or natural hazards is important for assessing the impacts of climate change. Many models have been developed to assess the risk of multiple hazards, however, most of the existing approaches can only model the relative levels of risk. This paper reports the development of a method for the quantitative assessment of the risk of multiple hazards based on information diffusion. This method was used to assess the risks of loss of human lives from 11 types of meteorological hazards in China at the prefectural and provincial levels. Risk curves of multiple hazards were obtained for each province and the risks of 10-year, 20-year, 50-year, and 100-year return periods were mapped. The results show that the provinces (municipalities, autonomous regions) in southeastern China are at higher risk of multiple meteorological hazards as a result of their geographical location and topography. The results of this study can be used as references for the management of meteorological disasters in China. The model can be used to quantitatively calculate the risks of casualty, direct economic losses, building collapse, and agricultural losses for any hazards at different spatial scales.