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Understanding the underlying processes causing large-scale dust storms and their transport in North Africa is essential for their accurate prediction. Different atmospheric mechanisms have been identified to govern the emission of dust and its transport, ranging in scale and season, from Rossby wave breaking to local, low-level cold and dry jets. Connecting these features in a Lagrangian sense is a coherent airflow from the midlatitude upper troposphere to the surface where dust concentrations peak. Such dry intrusions (DIs) are linked to reduced static stability and strong, dry winds and indeed have been recently shown to play a central role in four of the largest dust storm in the region. Yet, the climatological link between DIs and dust storms over a long time period has not been studied yet. The aim of this paper is to identify objectively dust events that co-occur with DIs, and understand their spatio-temporal characteristics and underlying dynamical drivers. Combining Lagrangian-based DI identification in ERA-Interim and dust optical depth data in CAMS reanalyses, 325 events during 2003–2018 are identified. The events occur mostly in late winter and spring, when they are also larger in size and last longer, compared to summer events. When occurring with DIs, dust optical depth is generally higher, compared to events that are not accompanied by DIs. We focus on March events, and find coherent large-scale precursors and atmospheric conditions of dust-DI events: a northward jet shift over the North Atlantic with anticyclonic Rossby wave breaking occurs on average 4–5 days prior to the events. The lower troposphere responds with dry and cold conditions in northwest Africa, coinciding with the outflow of the DI airstream that is initially guided by the upper trough. Finally, elevated near-surface dust concentrations prevail on the leading edge of the DI in tropical west Africa, and in northeast Africa, where dust is exported to the Mediterranean in association with a Mediterranean cyclone. • 325 dust storms related to DIs in North Africa were compiled using objective identification and a matching algorithm. • The largest, longest and most frequent events occur in February and March. They are more intense compared to non-DIs events. • Large-scale precursor jet anomalies related to anticyclonic Rossby wave breaking exist 4–5 days prior to the events. • DIs descend from upper-tropospheric anomalies towards the surface in Africa where the highest dust concentrations prevail. [ABSTRACT FROM AUTHOR]

• Long-term air temperature prediction is carried out by a novel two-phased approach. • eXplainable Artificial Intelligence models are applied to better analyse the results. • The approach is applied to the Southern part of the Iberian Peninsula from ERA5 data. • A comprehensive comparison against state-of-the-art techniques has been carried out. • XAI models outperform the compared techniques and benefit from being interpretable. In this paper we have tackled the problem of long-term air temperature prediction with eXplainable Artificial Intelligence (XAI) models. Specifically, we have evaluated the performance of an Artificial Neural Network (ANN) architecture with sigmoidal neurons in the hidden layer, trained by means of an evolutionary algorithm (Evolutionary ANNs, EANNs). This XAI model architecture (XAI-EANN) has been applied to the long-term air temperature prediction at different sub-regions of the South of the Iberian Peninsula. In this case, the average August air temperature has been predicted from ERA5 Reanalysis data variables, obtaining good predictions skills and explainable models in terms of the input climatological variables considered. A cluster analysis has been first carried out in terms of the average air temperature in the zone, in such a way that a number of sub-regions with different air temperature behaviour have been defined. The proposed XAI-EANN model architecture has been applied to each of the defined sub-regions, in order to find significant differences among them, which can be explained with the XAI-EANN models obtained. Finally, a comprehensive comparison against some state-of-the-art techniques has also been carried out, concluding that there are statistically significant differences in terms of accuracy in favour of the proposed XAI-EANN model, which also benefits from being an XAI model. [ABSTRACT FROM AUTHOR]

Based on the 18 realizations of three state-of-the-art climate models participated in the Coupled Model Intercomparison Project phase 6 (CMIP6), this paper examines the changes in climatology and trends of winter diurnal temperature range (DTR) over East Asia in response to natural and anthropogenic forcings. In the observation, the climatology of DTR during 1979–2014 displays a horizontal tile from southwest to northeast over East Asia. In addition, the observed DTR also presents an obviously declining trend in recent decades, with the magnitude of roughly −0.10 °C decade−1. The historical all-forcing simulations well reproduce the geographical distributions and magnitude of climatology and trends of winter DTR over East Asia in 1979–2014. Furthermore, the winter DTR exhibits a continuous declining trend from the historical scenario to the future SSP245 scenario over East Asia, with the most significant declining during the first half of twenty-first century (i.e., 2021–2060). Based on the individual forcing experiments, it suggests that the greenhouse gases forcing plays a primary role in driving the climatology and trends of DTR over East Asia, especially for the SSP245 scenario. Further analysis indicates that the increasing precipitation under greenhouse gases forcing largely explain the declining DTR trends over East Asia, especially over the northern East Asia both in historical and SSP245 scenarios. • The observed decreasing DTR trends are reasonably captured in the all-forcing historical simulations in CMIP6 models. • The greenhouse gas forcing plays a primary role in driving the declining DTR trends over East Asia • The declining of DTR is partly attributed to the increasing precipitation over East Asia in the greenhouse gas forcing. [ABSTRACT FROM AUTHOR]

Understanding the lightning climatological distribution is of great significance but remains challenging which is in part due to the lack of continuous and uniform lightning observations. In this paper, for the first time, an 11-year ground-based cloud-to-cloud lightning dataset of China National Lightning Detection Network from 2010 to 2020 is used to investigate the lightning climatology over China's land area in terms of spatial distribution, seasonal, monthly and diurnal variations. Lightning activity in China's land area generally decreases from south to north and from east to west. The mean cloud-to-ground lightning density of China's land area is 0.9 fl km−2 yr−1, with the average maximums (exceeding 10 fl km−2 yr−1) are found in the south and east coastal provinces, such as Guangdong, Hainan, Fujian and Zhejiang Province. The lightning activity in spring, summer and autumn seems consistent throughout the daytime cycle, with the lightning activity is rather weak in the morning and most active in the afternoon, while winter lightning appears to be more active in the nighttime and in the very early morning produced from nocturnal thunderstorms. The cloud-to-ground lightning activity in the tropical and subtropical areas within 15–25°N is mainly concentrated in the late spring and early summer, with two weak peaks in May and August, while lightning in mid latitudes within 25–55°N mainly occurs in the summer (June–July-August). The percentage of positive cloud-to-ground lightning flashes with peak current higher than 75 kA is more than 3 times than that of negative cloud-to-ground lightning flashes. Meanwhile, the mean peak current of cloud-to-ground lightning flashes shows an inverse diurnal pattern to the cloud-to-ground lightning activity. • Cloud-to-ground lightning climatology over Chinese continent is first investigated. • Lightning activity generally decreases from south to north and from east to west. • More lightning occurs in the summer in mid latitudes within 25–55°N. • Winter lightning is unique, usually produced from nocturnal thunderstorms. [ABSTRACT FROM AUTHOR]