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Atmospheric rivers (ARs) are known to produce both beneficial and extreme rainfall, leading to natural hazards in Chile. Motivated to understand moisture transport during AR events, this study performs a moisture budget analysis along 50 zonally elongated ARs reaching the western coast of South America. We identify the convergence of moist air masses of tropical/subtropical origin along the AR as the primary source of vertically integrated water vapor (IWV). Over the open ocean, moisture convergence is nearly balanced by precipitation. The advection of moisture along the AR, although smaller compared to mass convergence, significantly increases toward the landfalling region. The near conservation of IWV over the open ocean, observed by tracking a Lagrangian atmospheric column along the ARs, is the explanation behind the seemingly tropical origin of ARs in time‐lapse visualizations of IWV. Plain Language Summary Imagine atmospheric rivers (ARs) as massive, flowing rivers in the sky, but instead of water, they carry vapor from the ocean. When these “sky rivers” travel and hit the Andes Mountains in South America, they can cause a lot of rain and snow to fall. This precipitation is often good because it helps fill reservoirs and water crops. However, sometimes there’s too much rain, leading to floods and landslides, which can be dangerous. Over the ocean, the amount of water vapor these atmospheric rivers pick up is almost exactly balanced by the rain that falls from them. As these atmospheric rivers get closer to South America, the movement of moisture along the river, though generally less significant than the gathering of moist air, becomes more pronounced. This means that as the atmospheric river approaches the land, it starts carrying more moisture toward its destination. We were able to see this process in action by following a moving “slice” of the atmosphere (a Lagrangian atmospheric column) as it travels along the path of the atmospheric river. This helped us understand how atmospheric rivers maintain their water content as they move. It also shows why atmospheric rivers seem to originate from tropical areas when we look at them in time‐lapse images of water vapor. Key Points We calculate the moisture transport budget of 50 events of zonal atmospheric rivers over the Pacific that reach South America Horizontal convergence of tropical and subtropical air masses act to maintain atmospheric rivers over the ocean while advection dominates near the coast Following a Lagrangian column, precipitable water is roughly conserved along atmospheric rivers, except near landfalling

Four years of Indian Institute of Tropical Meteorology lightning location network lightning observation data are used to determine the seasonal and spatial (over different geographical locations) distribution of the ratio of intra‐cloud (IC) lightning to cloud‐to‐ground (CG) lightning in thunderstorms over the Indian subcontinent. The ratio is high (6–10) in the northwestern parts and low (0.5–3.5) in the northeastern parts. No prominent latitudinal variation of the IC to CG ratio exists, but a climatological seasonal variability exists over all regions. In the pre‐monsoon season (March–May), the mean ratio is observed to be 3.81 with a standard deviation of 0.79, and during the monsoon season (June–September), a value of 3.04 with a standard deviation of 0.50. Although convective available potential energy is the regulating factor, little dependency has been found between the ratio of IC to CG lightning (IC:CG ratio) and the total flash rate (f), as well as with cold cloud depths. The ratio is observed to be proportional to the total flash rate as f0.61. The cold cloud depth is most prominently linked with the regional and seasonal IC:CG ratio. The implication of these observed results has the importance of separating CG lightning flash from total and can be used in numerical models to give a proper prediction of CG lightning in hazard mitigation. Plain Language Summary Pre‐monsoon thunderstorms exhibit more intra‐cloud (IC) discharge than monsoonal thunderstorms; hence, the IC:cloud‐to‐ground (CG) ratio is also high in pre‐monsoon. In this paper, we have shown that CG lightning is approximately 20% of total lightning in pre‐monsoon whereas 25% of total lightning in monsoon all over the Indian region. A stronger vertical updraft associated with high convective available potential energy enhances the cold cloud depth. It may expand the mixed phase region, which can broaden and uplift the size of the upper positive charge center inside a thunderstorm. In contrast, the middle negative charge center remains at the same temperature level. Therefore, this process may enhance IC discharge between the upper positive charge center and the middle negative charge center, increasing the IC:CG ratio of a thunderstorm. Key Points The mean intra‐cloud:cloud‐to‐ground (IC:CG) ratio remains high in the Pre‐monsoon season compared to the Monsoon season over the Indian land mass The high cold cloud depth associated with stronger updrafts expand the mixed‐phase region and increases the IC flash rate and IC:CG ratio High flash rate associated with high IC flash occurrences is also responsible for a high IC:CG ratio

The extratropical Andes, a hotspot for landfalling atmospheric rivers (ARs), are prone to extreme precipitation and related hydrological hazards, including floods and landslides. An improved understanding of the drivers of precipitation intensification during AR landfall is critical for hazard preparedness. Focusing on 50 zonally elongated ARs (ZARs), we demonstrate that precipitation amplification over the Andes is largely associated with strong ascent produced by orographic lifting of ZAR flow and further strengthened by the release of atmospheric instabilities. The efficient realization of these instabilities is linked to large surface relative humidity, RHsfc$\\mathrm{R}{\\mathrm{H}}_{\\text{sfc}}$ , particularly over regions with steep elevation gradients. We further demonstrate that ZAR‐related moisture convergence and terrain‐modulated heat advection in these regions lead to an increase in RHsfc$\\mathrm{R}{\\mathrm{H}}_{\\text{sfc}}$over the steep Andean terrain. This study emphasizes that accurately estimating precipitation intensification and its spatial distribution during ZAR landfall requires an improved understanding of both moisture and heat transport to the extratropical Andes.

An unresolved problem of the current Global Climate Models (GCM) is the unrealistic distribution of rainfall over the Indian Summer Monsoon (ISM) region, which is also related to the persistent dry bias over the Indian landmass. Therefore, quantitative prediction of the intensity of rainfall events has remained a challenge for state-of-the-art GCMs. Based on observations, it is hypothesized that the insufficient growth of cloud droplets and the processes responsible for the cloud-to-rainwater conversion are the key components in distinguishing between shallow and convective clouds. The Eulerian–Lagrangian particle-by-particle-based small-scale model provides a path for reassessing the ‘autoconversion’ parameterization schemes and suggests the relative dispersion-based ‘autoconversion’ parameterization scheme for the climate model. The realistic information on cloud drop size distribution is incorporated into the microphysical parameterization scheme of the climate model. Two sensitivity simulations are conducted using the climate forecast system (CFSv2) model. The coupled climate model incorporates a relative dispersion-based Liu–Daum-type autoconversion parameterization scheme in place of the traditional Sundqvist-type autoconversion, which, based on small-scale model analysis, makes the model more accurate in simulating the probability distribution (PDF) of rainfall with accompanying specific humidity, liquid water content, and outgoing long-wave radiation (OLR). The improved simulation of rainfall PDF appears to have been aided by a significantly improved simulation of OLR, which led to a more accurate simulation of the ISM rainfall.

Electro-crystallization, the freezing of water droplet induced by an electric field has been investigated by many investigators previously. But disagreements regarding the cause of freezing still persist in the literature. A cloud chamber of the internal dimension of 1 ft × 1 ft has been designed to study electro-crystallization of ‘mm’ size pure water drops. More than 150 experiments have been performed in the chamber in the absence and presence of an electric field. Preliminary results suggest that in normal conditions, maximum drops freeze in the temperature ranging from −10° to –15°C, consistent with the previous laboratory studies. When the drops are subjected to an electric field of magnitude 2–5 kV cm −1 , the drops are observed to freeze in a much warmer temperature ranging from –6° to –10°C indicating an electric field induced crystallization. No movement of the drops is observed during the freezing, which suggests that the freezing may be initiated by absorption of the latent heat of fusion by the Nylon wire where the drops are kept suspended. The implication of the electrically induced freezing from the perspective of cloud physics also has been discussed.

An unresolved problem of present generation coupled climate models is the realistic distribution of rainfall over Indian monsoon region, which is also related to the persistent dry bias over Indian land mass. Therefore, quantitative prediction of the intensity of rainfall events has remained a challenge for the state-of-the-art global coupled models. Guided by the observation, it is hypothesized that insufficient growth of cloud droplets and processes responsible for the cloud to rain water conversion are key components to distinguish between shallow to convective clouds. The new diffusional growth rates and relative dispersion based autoconversion from the Eulerian-Lagrangian particleby-particle based small-scale model provide a pathway to revisit the parameterizations in climate models for monsoon clouds. The realistic information of cloud drop size distribution is incorporated in the microphysical parameterization scheme of climate model. Two sensitivity simulations are conducted using coupled forecast system (CFSv2) model. When our physically based small-scale derived modified parameterization is used, a coupled climate model simulates the probability distribution (PDF) of rainfall and accompanying specific humidity, liquid water content, and outgoing long-wave radiation (OLR) with increasing accuracy. The improved simulation of rainfall PDF appears to have been aided by much improved simulation of OLR and resulted better simulation of the ISM rainfall.

Lightning strikes are a well-known danger, and are a leading cause of accidental fatality worldwide. Unfortunately, lightning hazards seldom make headlines in international media coverage because of their infrequency and the low number of casualties each incidence. According to readings from the TRMM LIS lightning sensor, thunderstorms are more common in the tropics while being extremely rare in the polar regions. To improve the precision of lightning forecasts, we develop a technique similar to LightNet's, with one key modification. We didn't just base our model off the results of preliminary numerical simulations; we also factored in the observed fields' time-dependent development. The effectiveness of the lightning forecast rose dramatically once this adjustment was made. The model was tested in a case study during a thunderstorm. Using lightning parameterization in the WRF model simulation, we compared the simulated fields. As the first of its type, this research has the potential to set the bar for how regional lightning predictions are conducted in the future because of its data-driven approach. In addition, we have built a cloud-based lightning forecast system based on Google Earth Engine. With this setup, lightning forecasts over West India may be made in real time, giving critically important information for the area.

In the backdrop of a revolution in weather prediction by Numerical Weather Prediction (NWP) models, quantitative prediction of intensity of heavy rainfall events and associated disasters has remained a challenge. Encouraged by compelling evidence of electrical influences on cloud/rain microphysical processes, here we propose a hypothesis that modification of raindrop size distribution (RDSD) towards larger drop sizes through enhanced collision-coalescence facilitated by cloud electric fields could be one of the factors responsible for intensity errors in weather/climate models. The robustness of the hypothesis is confirmed through a series of simulations of strongly electrified (SE) rain events and weakly electrified (WE) events with a convection-permitting weather prediction model incorporating the electrically modified RDSD parameters in the model physics. Our results indicate a possible roadmap for improving hazard prediction associated with extreme rainfall events in weather prediction models and climatological dry bias of precipitation simulation in many climate models.