The Hadley circulation is one of the most important atmospheric circulations. Widening of the Hadley circulation has drawn extensive studies in the past decade. The key concern is that widening of the Hadley circulation would cause poleward shift of the subtropical dry zone. Various metrics have been applied to measure the widening of the tropics. What are responsible for the observed widening trends of the Hadley circulation? How anthropogenic and natural forcings caused the widening? How the widening results in regional climatic effects? These are the major questions in studing the widening of the Hadley circulation. While both observations and simulations all show widening of the Hadley circulation in the past few decades, there are no general agreements of changes in the strength of the Hadley circulation. Although some reanalysis datasets show strengthening of the Hadley circulation, it was shown that the strengthening trend could be artificial, and simulations show weakening of the Hadley circulation for global greenhouse warming. In the present paper, we shall briefly review the major progresses of studies in trends in width and strength of the Hadley circulation. We address answers to these questions, clarify inconsistent results, and propose ideas for future studies.
Unmanned aerial vehicle (UAV) equipped with multispectral cameras for remote sensing (RS) has provided new opportunities for ecological and agricultural related applications for modelling, mapping, and monitoring. However, when the multispectral images are used for the quantitative study, they should be radiometrically calibrated, which accounts for atmospheric and solar conditions by converting the digital number into a unit of scene reflectance that can be directly used in quantitative remote sensing (QRS). Indeed, some of the present applications using multispectral images are processed without precise calibration or with coarse calibration. The radiometric calibration of images from the UAV platform is quite difficult to perform, as the imaging condition is different for every single image. Thus, a standard procedure is necessary for a systematical radiometric calibration method to generate multispectral images with unit reflectance. Further, these images can be used to calculate vegetation indices, which are useful in monitoring vegetation phenology. These vegetation indices are considered as a potential screening tool to know the plant status, such as nitrogen, chlorophyll content, green leaf biomass, etc. This study focuses on a series of radiometric calibrations for multispectral images acquired from different flight altitudes, time instants, and weather conditions. Radiometric calibration for multispectral images is performed using the linear regression method (LRM). The main contribution involves (1) affirming the optimal calibration targets and assessing the atmospheric effects of different flights using the single scene of images; (2) to evaluate the effects of mosaic images with the LRM; (3) to propose and validate a universal calibration equation for the Mini Multiple Camera Array (MCA) 6 camera. The obtained results show that the three calibration targets, such as the dark, moderate, and white, are better for the Mini MCA 6 camera. The atmospheric effects increase with the increase of flight altitudes for each band, and the camera effect is of a fixed number. However, the camera effect and atmospheric attenuation to reflectance from different altitudes were relatively low considering the accuracy assessment. The performance measures namely, mean absolute deviation (indicated as V) and root mean square error (RMSE) between single and mosaic images show that the mosaic will not influence too much reflectance. The LRM performs well in all weather conditions. The universal calibration equation is suitable to apply to the images acquired during a sunny day and even with a little cloud.
Drought disasters jeopardize agricultural production and are expected to become more serious in the context of global climate change. However, in China, little attention has been paid to evaluating agricultural drought risk in humid areas (such as in Southwest China), which have also been affected by severe drought in recent years. In this work, we used the Standardized Precipitation Evapotranspiration Index (SPEI), which was computed from high-quality monthly precipitation and temperature data from 92 rain-gauge stations across Southwest China, to study the drought characteristics (e.g., intensity, duration, and frequency) and their decadal variations from 1960 to 2017. Furthermore, we applied a widely accepted conceptual model that emphasizes the combined role of drought hazard (calculated by the intensity and frequency of drought) and agricultural drought vulnerability (integrated with high-resolution soil properties, climate, topography, irrigation, and gross domestic product) to conduct a spatial assessment of agricultural drought risk at a 1-km grid scale. The results revealed that drought has become more serious and frequent in Southwest China, especially since the 2000s. About 27.4% of the agricultural area has been exposed to an extremely high risk of drought, 33.5% to a high risk, 22.5% to a moderate risk, and 16.6% to a low risk. The extreme agricultural risk areas were located mainly in northeastern and southeastern Chongqing, southwestern Sichuan, northeastern and eastern Guizhou, and central and eastern Yunnan. Our findings highlighted that more attention should be paid to the agricultural drought risk in humid regions of China. Furthermore, this work could set the stage for policy makers and practitioners to take measures to reduce the agricultural drought risk in Southwest China.
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