We report results of new pair creation experiments using ~100 Joule pulses of the Texas Petawatt Laser to irradiate solid gold and platinum targets, with intensities up to ~1.9 × 1021 W.cm−2 and pulse durations as short as ~130 fs. Positron to electron (e+/e−) ratios >15% were observed for many thick disk and rod targets, with the highest e+/e− ratio reaching ~50% for a Pt rod. The inferred pair yield was ~ few ×1010 with emerging pair density reaching ~1015/cm3 so that the pair skin depth becomes < pair jet transverse size. These results represent major milestones towards the goal of creating a significant quantity of dense pair-dominated plasmas with e+/e− approaching 100% and pair skin depth ≪ pair plasma size, which will have wide-ranging applications to astrophysics and fundamental physics.

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Automatic modulation classification (AMC) is a core technique in noncooperative communication systems. In particular, feature-based (FB) AMC algorithms have been widely studied. Current FB AMC methods are commonly designed for a limited set of modulation and lack of generalization ability; to tackle this challenge, a robust AMC method using convolutional neural networks (CNN) is proposed in this paper. In total, 15 different modulation types are considered. The proposed method can classify the received signal directly without feature extracion, and it can automatically learn features from the received signals. The features learned by the CNN are presented and analyzed. The robust features of the received signals in a specific SNR range are studied. The accuracy of classification using CNN is shown to be remarkable, particularly for low SNRs. The generalization ability of robust features is also proven to be excellent using the support vector machine (SVM). Finally, to help us better understand the process of feature learning, some outputs of intermediate layers of the CNN are visualized.

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Unmanned aerial vehicle (UAV) experiments, multiple datasets from ground-based stations and satellite remote sensing platforms, and backward trajectory models were combined to investigate the characteristics and influential mechanisms of the air pollution episode that occurred in Nanjing during 3–4 December 2017. Before the experiments, the position of the detector mounted on a UAV that was minimally disturbed by the rotation of the rotors was analyzed based on computational fluid dynamics (CFD) simulations. The combined analysis indicated that the surface meteorological conditions—high relative humidity, low wind speed, and low temperature—were conducive to the accumulation of PM2.5. Strongly intense temperature inversion layers and the low thickness of the atmospheric mixed layer could have resulted in elevated PM2.5 mass concentrations. In the early stage, air pollution was affected by the synoptic circulation of the homogenous pressure field and low wind speeds, and the pollutants mainly originated from emissions from surrounding areas. The aggravated pollution was mainly attributed to the cold front and strong northwesterly winds above 850 hPa, and the pollutants mostly originated from the long-distance transport of emissions with northwesterly winds, mainly from the Beijing‒Tianjin‒Hebei (BTH) region and its surrounding areas. This long-distance transport predominated during this event. The air pollution level and aerosol optical depth (AOD) were positively correlated with respect to their spatial distributions; they could reflect shifts in areas of serious pollution. Pollution was concentrated in Anhui Province when it was alleviated in Nanjing. Polluted dust, polluted continental and smoke aerosols were primarily observed during this process. In particular, polluted dust aerosols accounted for a major part of the transport stage, and existed between the surface and 4 km. Moreover, the average extinction coefficient at lower altitudes (<1 km) was higher for aerosol deposition.

The trend in the atmospheric heat source over the central and eastern Tibetan Plateau (CE-TP) is quantitatively estimated using historical observations at 71 meteorological stations, three reanalysis datasets from 1980-2008, and two satellite radiation datasets from . Results show that a weakening of sensible heat (SH) flux over the CE-TP continues. The most significant trend occurs in spring, induced mainly by decelerated surface wind speeds. The ground-air temperature difference shows a notable increasing trend over the last 5 years. Trends in net radiation flux of the atmospheric column over the CE-TP, evaluated by two satellite radiation datasets, are clearly different. Trends in the atmospheric heat source calculated by the three reanalysis datasets are not completely consistent, and even show opposite signals. Results from the two datasets both show a weakening of the heat source but the magnitude of one is significantly stronger, whereas an increase is indicated by the other data. Therefore, it is challenging to accurately calculate the trend in the atmospheric heat source over the CE-TP, particularly from the estimates of the reanalysis datasets. The Tibetan Plateau (TP) is situated on the subtropical eastcentral Eurasian continent. It is the highest (average elevation > 4000 m) plateau in the world, with complex topography and surface conditions. As a strong heat source, the plateau directly heats the middle troposphere [1][2][3]. In spring, sensible heat (SH) dominates the atmospheric heat source over the TP and works efficiently as a huge air pump [4], for not only the onset and maintenance of the Asian summer monsoon [5], but also for the development of weather systems over east China [6] and even the boreal summer climate pattern [6,7]. Changes in the thermal condition of the TP and the atmospheric circulation in East Asia are closely related [8]. Zhao and Chen [9] investigated the atmospheric heat source over the TP and its relationship with rainfall in China, and concluded that this heat source in spring may be regarded as a good indicator of a summer precipitation anomaly in east China. They also showed that it had a clear positive correlation with summer precipitation in the middle and lower reaches of the Yangtze River. Bai et al.[10] confirmed these results. Duan and Wu [11] pointed out that it is not adequate to study the influence of TP thermal forcing on the climate with an area-averaged heating index, because of the large area and various climate types of the TP. Under a global warming scenario, TP warming is powerful, and the warming trend is much greater than surrounding regions at the same latitudes [12][13][14][15]. The thermal condition of the TP is an important influence on atmospheric circulation, climate change and long-term weather processes. The relationship between TP heating and variability

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The spring sensible heating (SH) over the Tibetan Plateau (TP) serves as a huge 'air pump', significantly influencing the Asian summer monsoon, has experienced a decreasing trend. However, it remains unclear whether this decline will continue. Therefore, we here examine the long-term trends of spring SH over the central and eastern TP (CETP) based on a meteorological station-based calculated SH dataset, and CMIP6 multi-model simulations. These two sources confirmed the previous finding that the SH peaks in May. Further, we find that the declining SH was replaced by a fast recovery after approximate 2000 in the station-based SH. This is to some extent verified by the historical simulations of CMIP6 models. Importantly, CMIP6 future projections suggest that this increasing trend will continue, and get stronger with higher radiative forcing from SSP126 to SSP585. Mechanism analysis indicates that the previous decreasing trend in SH was mainly caused by the decline of 10 m wind speed, while the recent and future increasing trend results from the rising ground-air temperature difference. We suggest that this increasing trend of spring SH over the CETP may serve as an alternative driver for the enhancement of the East Asian summer monsoon in the future.