Precipitation Systems Research Articles

A Rootless Duckweed-Inspired Flexible Artificial Leaf from Plasmonic Photocatalysts.

The naturally existing leaves are ubiquitous two-dimensional flexible solar-to-chemical conversion systems that can run continuously in a sustainable manner. However, the current artificial photocatalytic systems are unable to achieve this due to the grand challenge in integrating existing photocatalysts in a flexible layout with high conversion efficiency and the ability to function independently. Here, we report on a rootless duckweed-inspired artificial leaf based on a lightweight, flexible, Janus plasmonic nanosheet-integrated sponge. The Janus plasmonic catalytically active nanosheet was made from self-assembled gold nanocube nanoassemblies grown on the porous sponges, which were further coated with an ultrathin palladium layer on one side via a ligand symmetry-breaking method. This sponge-based photocatalytic system is lightweight yet able to float on a water surface and conducts the gas-liquid reaction without auxiliary pumping and mixing devices. In a model reaction of 4-nitrophenol reduction, this floating leaf could achieve 2.5-fold and 65-fold higher efficiency than the corresponding dispersion and precipitation systems, respectively. The film theory is used to explain the sponge-based lightweight solar-to-chemical conversion system in a detailed kinetic and thermodynamic analysis, including the reaction rate constant, activation energy, enthalpy, entropy, Gibbs energy, and equilibrium constant.

Rift Gaps in Chemical-Wave Network Systems.

We carry out experiments in diffusion-precipitation systems in a framework with multiple diffusion sources. The advancing precipitation fronts reach a point where they stop, leaving a rift or gap between the precipitate zones. In a similar setting, fractal metal deposits emerging from various reduction centers were synthesized. They were shown to meander in the medium, but fail to meet or overlap, thus also leaving a gap or rift just like in the precipitation system. The obtained patterns were analyzed by calculating entropy and front velocity for the former system, and fractal dimension for the latter. The observed structures represent chemical analogs of Voronoi diagrams.

The Changing Morphology of Global Precipitation Systems during the Last Two Decades

Abstract The morphology of global precipitation systems can enhance our comprehension of precipitation patterns and the underlying physical processes. However, several unresolved issues remain in the existing studies of precipitation system morphology. This study employs Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG)-derived precipitation system dataset to investigate the climatological and changing characteristics of global precipitation system morphology from 2001 to 2022. The results show that precipitation systems with larger scales tend to be more flattened in morphology, while no clear differences in morphological characteristics are observed across systems with different intensities. In terms of geographic distributions, a notable land–sea contrast is observed, with land systems more circular than those over oceans. Due to the impact of the Coriolis force, the orientation distribution of precipitation systems shows obvious hemispherical contrast. Precipitation systems over tropical regions are more regular in shape and more likely to be organized convective systems. During the period of 2001–22, there is a significant trend of global precipitation systems becoming more flattened and are more likely to manifest as organized convective systems. Our results also indicate that the precipitation system morphology is under combined influence of subtropical highs, lateral stretching influences of wind, and the organizing effects of moisture transport and convergence. Moreover, the increasing flattening of precipitation systems could be attributed to enhanced atmospheric stability which constrains vertical expansion and increased moisture availability which favors wider horizontal extension. This study could provide new insights into precipitation changes under global warming.

Ice Formation, Exsolution, and Multiphase Equilibria in the Methane–Ethane–Nitrogen System at Titan Surface Conditions

Titan is unique among the icy satellites in that it has a thick atmosphere, stable surficial bodies of liquid, and a precipitation system that promotes interactions between the two. Although Titan’s surface conditions are typically assumed to be above the freezing point temperatures of the major constituent species of the climate system (methane, ethane, and nitrogen), conditions may be sufficiently cool across parts of Titan to allow for ice formation alongside known liquid-vapor phases. In this study, we used Raman spectroscopy, visual inspection, and the CRYOCHEM 2.0 equation of state to map the appearance of first ice and to quantify the amount of nitrogen dissolution into liquid in the methane–ethane–nitrogen system along a 1.5 bar isobaric cooling path in the temperature range 80–95 K. This was with the intent of (1) determining the effects nitrogen has on the phase behaviors of the methane–ethane binary system, and (2) establishing the temperatures and ternary mixing ratios needed for ice formation on Titan’s surface. We found that ethane-rich mixtures enter a three-phase solid–liquid–vapor equilibrium and are characterized by nitrogen-rich exsolution upon freezing and ice that form at the bottom of the sample. With sufficient methane content, the mixtures cross a univariant four-phase solid–liquid–liquid–vapor boundary, which contributes to a distinct isothermal freezing point profile and ice that forms starting at the liquid–liquid interface. Our results generally agree with findings from previous studies of the methane–ethane–nitrogen system and are intended to add to our current understanding of Titan’s geochemical processes.

Projected changes of thermal, rainfall and drought indices in Morocco from high resolution climate models

Abstract Over the past decade, global changes in temperature, average and extreme precipitation have been observed many times. The increase in temperature or even the change in precipitation systems is directly affect extreme weather events, for example, heat waves, heavy rainfall, storms, and droughts are becoming more frequent and more powerful worldwide due to climate change caused by several factors including human activity. This is why there is a necessity to monitor future changes in climate extremes. The objective of this paper is to evaluate the future changes in thermal and rainfall extremes projected by the four climate models over time horizon 2041-2060 relative to the 1981-2010 reference period, based on the 5 climate indices, including Tmm, Tx90p, WSDI, PRCPTOT and SPI. The projections are given under the RCP 4.5 medium scenario. The analysis in thermal aspect shows that Morocco could experience by 2041-2060, a significant warming, has manifested by an increase in average temperature. Future changes in rainfall indices show that the spatial distribution of rainfall in Morocco could change significantly by 2041-2060 compared to the reference period 1971-2010. The four climate models agree on a decrease in annual precipitation that could affect most of the Kingdom. In the same way to dryness, the future changes of the SPI index that characterizes the drought, indicates a move to a dry climate.

Initiation and evolution of urban-induced precipitation under different background wind speeds: Roles of urban breeze circulation and cold pool

Urban-enhanced precipitation is often observed far downwind of cities, suggesting important roles of background wind. This study examines the impacts of background wind on the initiation and evolution of urban-induced precipitation through idealized ensemble large-eddy simulations with different initial background wind speeds of 0, 1, 2, 3, 4, and 5 m s−1. Without background wind, a strong urban breeze circulation (UBC) initiates a relatively large number of cumulus clouds in the urban area, which exhibit greater cloud top heights than those in the rural area. The early-initiated clouds do not produce precipitation but moisten the middle troposphere, assisting later-initiated clouds to develop into deep convective clouds and produce concentrated precipitation in the urban area. As the background wind speed increases, the UBC weakens. Also, the high-humidity area generated by early-initiated clouds is continuously advected away from the urban area. Consequently, the precipitation initiation is delayed as the background wind speed increases. Precipitating clouds are advected downwind and generate a cold pool, and updrafts are repeatedly produced at the downwind boundary of the cold pool. The downwind-advected clouds are fed by the newly produced updrafts, being a long-lived organized precipitation system that produces a considerable amount of precipitation in the downwind area. This feeding effect is most prominent for a moderate background wind (3 m s−1), causing the precipitation amount and duration to be maximized. For stronger background winds, precipitation is initiated by the mechanical lifting of the warm air of the urban boundary layer over the cool rural boundary layer around sunset.

Hydrometeor categorization in stratiform and convective precipitation systems over a tropical coastal region

Hydrometeor categorization in stratiform and convective precipitation systems over a tropical coastal region

Dissolved ammonia catalyzes proto-dolomite precipitation at Earth surface temperature

Marine carbonate rocks are the major reservoir of carbon through CaCO3 and CaMg(CO3)2 precipitation extracting CO2/HCO3- from the atmosphere/oceans; hence dolomite is one of the major sinks in the global carbon cycle. Most ancient dolomite has been considered as mainly precipitated under Earth surface conditions. Previous studies have demonstrated that microbes can mediate dolomite formation. However, the “microbial dolomite” model is not sufficient to explain the dolomite that shows no or little evidence of a microbial origin. Although attempted for decades, the synthesis of inorganically-produced dolomite at normal temperatures (<50 °C) has been relatively unsuccessful. Hence, this "dolomite enigma" has been one principal research focus this century. Here we demonstrate that NH3 catalyzes proto-dolomite precipitation inorganically with higher Mg/Ca molar ratios and CO32- activity at normal temperatures of 30 °C and 40 °C. NH3 dissolution increases the alkalinity of the solution and transformes into NH4+ ions, which prefer to bond with H2O on Mg[(H2O)6]2+ rather than free H2O, thus releasing Mg2+ to facilitate proto-dolomite nucleation. Furthermore, the low dielectric constant and low dipole moment allow NH4+ absorbed on crystal surfaces to lower the energy barrier of Mg[(H2O)6]2+ dehydration, promoting proto-dolomite nucleis growth. The system for proto-dolomite precipitation in our experiments closely simulates the natural aqueous environment. This study brings new insights to understanding the mechanisms of dolomite precipitation in natural waters.

A Multi-Scale Analysis of the Extreme Precipitation in Southern Brazil in April/May 2024

Since 2020, southern Brazil’s Rio Grande do Sul (RS) State has been affected by extreme precipitation episodes caused by different atmospheric systems. However, the most extreme was registered between the end of April and the beginning of May 2024. This extreme precipitation caused floods in most parts of the state, affecting 2,398,255 people and leading to 183 deaths and 27 missing persons. Due to the severity of this episode, we need to understand its drivers. In this context, the main objective of this study is a multi-scale analysis of the extreme precipitation between 26 April and 5 May, i.e., an analysis of the large-scale patterns of the atmosphere, a description of the synoptic environment, and an analysis of the mesoscale viewpoint (cloud-top features and lightning). Data from different sources (reanalysis, satellite, radar, and pluviometers) were used in this study, and different methods were applied. The National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN) registered accumulated rainfall above 400 mm between 26 April and 5 May using 27 pluviometers located in the central-northern part of RS. The monthly volumes reached 667 mm and 803 mm, respectively, for April and May 2024, against a climatological average of 151 mm and 137 mm for these months. The maximum precipitation recorded was 300 mm in a single day on 30 April 2024. From a large-scale point of view, an anomalous heat source in the western Indian Ocean triggered a Rossby wave that contributed to a barotropic anticyclonic anomalous circulation over mid-southeastern Brazil. While the precipitant systems were inhibited over this region (the synoptic view), the anomalous stronger subtropical jet southward of the anticyclonic circulation caused uplift over RS State and, consequently, conditions leading to mesoscale convective system (MCS) development. In addition, the low-level jet east of the Andes transported warm and moist air to southern Brazil, which also interacted with two cold fronts that reached RS during the 10-day period, helping to establish the precipitation. Severe deep MCSs (with a cloud-top temperature lower than −80 °C) were responsible for a high lightning rate (above 10 flashes km−2 in 10 days) and accumulated precipitation (above 600 mm in 10 days), as observed by satellite measurements. This high volume of rainfall caused an increase in soil moisture, which exceeded a volume fraction of 0.55, making water infiltration into the soil difficult and, consequently, favoring flood occurrence.

Characteristics of Precipitation and Mesoscale Convective Systems Over the Peruvian Central Andes in Multi 5‐Year Convection‐Permitting Simulations

AbstractUsing the Weather Research and Forecasting model with two planetary boundary layer schemes, ACM2 and MYNN, convection‐permitting model (CPM) regional climate simulations were conducted for a 6‐year period, including a one‐year spin‐up period, at a 15‐km grid spacing covering entire South America and a nested convection‐permitting 3‐km grid spacing covering the Peruvian central Andes region. These two CPM simulations along with a 4‐km simulation covering South America produced by National Center for Atmospheric Research (NCAR), three gridded precipitation products, and rain gauge data in Peru and Brazil, are used to document the characteristics of precipitation and mesoscale convective systems (MCSs) in the Peruvian central Andes region. Results show that all km‐scale simulations generally capture the spatiotemporal patterns of precipitation and MCSs at both seasonal and diurnal scales, although biases exist in aspects such as precipitation intensity and MCS frequency, size, propagation speed, and associated precipitation intensity. The 3‐km simulation using MYNN scheme generally outperforms the other simulations in capturing seasonal and diurnal precipitation over the mountain, while both it and the 4‐km simulation demonstrate superior performance in the western Amazon Basin, based on the comparison to the gridded precipitation products and gauge data. Dynamic factors, primarily low‐level jet and terrain‐induced uplift, are the key drivers for precipitation and MCS genesis along the east slope of the Andes, while thermodynamic factors control the precipitation and MCS activity in the western Amazon Basin and over elevated mountainous regions. The study suggests model improvements and better model configurations for future regional climate projections.

β-Lactoglobulin Separation from Whey Protein: A Comprehensive Review of Isolation and Purification Techniques and Future Perspectives

Cow milk, although rich in essential nutrients, is a well-known allergic food that can cause allergic reactions in infants and young children. β-Lactoglobulin accounts for 10% of the total protein in milk and 50% of the whey protein, which has high nutritional value and excellent functional properties but is also the main allergen leading to milk protein allergy. Exploring the mechanism of milk allergy and selecting suitable separation and purification methods to obtain high-purity β-Lactoglobulin is the premise of research on reducing allergenicity. In this review, the research progress in membrane technology, gel filtration chromatography, ion exchange chromatography, affinity chromatography, precipitation and aqueous 2-phase system separation for the separation and purification of milk β-Lactoglobulin is reviewed in detail to promote the further development of milk β-Lactoglobulin separation and purification methods and provide a new method for the development of hypoallergenic dairy products in the future. Among these methods, ion exchange chromatography and gel chromatography are widely used, precipitation is generally used as a crude purification step, and high-performance liquid chromatography and membrane technology are used for further purification to improve the purity of allergens.

Differences in Thunderstorms' Ice Microphysics Between the Amazon and Central Africa Inferred From Spaceborne Passive Microwave and Radar Observations

AbstractThis study examines the differences related to microphysical properties of ice in thunderstorms over the Amazon and Congo Basin using the Precipitation Feature (PF) data sets derived from passive microwave and radar observations from the Tropical Rainfall Measuring Mission and Global Precipitation Mission Core Satellites. Analysis reveals that Amazon thunderstorms are likely composed of ice crystals smaller but more numerous than those in the Congo Basin, resulting in half as many flashes per PF on average in the Amazon, for similar Ice Water Content (IWC) or Area of 30 dBZ at −10°C (Acharge). The increase of the flash count following an increase of the IWC (Acharge) is only 72% (61%) as effective in the Amazon as it would be in the Congo Basin area. PFs with similar 30 dBZ radar echo top heights exhibit lower Brightness Temperatures (TBs) in the 85/89, 165, and 183 GHz frequencies over the Amazon, indicating more numerous smaller ice particles compared to those over the Congo Basin, which tend to show colder TBs at 37 GHz, possibly due to more numerous large graupel or hail particles. Comparisons of TBs in PFs with similar 30 dBZ echo top temperature between the Amazon and 3 × 3º global grids show that the median TB in Amazon is higher than that in most oceanic areas but is comparable to areas having high oceanic lightning activity (e.g., South Pacific Convergence Zone). It suggests that systems in the Amazon have similarities with maritime precipitation systems, yet with distinct characteristics indicative of land systems.

Mean flow and eddy summer moisture transport over East Asia in reanalysis data and a regional climate simulation

Understanding the impact of atmospheric variability on climatological mean moisture transport is crucial because moisture transport determines continental water availability as well as convective organization and resulting precipitation. Here, we analyze the mean flow and eddy components of summer moisture transport in the downwind of the Tibetan Plateau (TP), a region that is characterized by interactions between monsoon systems, extratropical circulation, and mountainous weather systems. Using 40 years of ERA5 reanalysis data and a regional WRF simulation, we determine the absolute and relative contributions of mean flow and eddy moisture transport from multi-daily to sub-daily scales. We also link these components to large-scale circulation indices, precipitation, evaporation, and mesoscale convective systems (MCSs). The results show that the largest contributions of eddies to the climatological mean moisture transport are found in the immediate downwind region of the TP. Half of the total eddy transport downwind of the TP is due to multi-daily eddy transport and the other half is due to daily to sub-daily eddy transport. Regional precipitation anomalies are dominated by the mean flow component of southerly moisture influxes which in turn are positively correlated with different South Asian summer monsoon indices and negatively correlated with the West Northern Pacific monsoon index. The eddy transport from the south is positively correlated with a lower jet latitude but does not show any significant correlations with precipitation or MCS activity, likely due to the dominant role of the mean flow moisture transport. While the relative contributions of eddies to the climatological mean moisture transport are similar in ERA5 and WRF, the correlations between moisture transport components and large-scale circulation indices are generally weaker in WRF. This suggests that the dynamical downscaling does not significantly change the role of eddy moisture transport averaged for the region, but it resolves processes that decouple the moisture transport from its large-scale forcing.

Downstream and upstream effects of urban chains on precipitation in Beijing

A summer convective rainfall event in Beijing on June 26, 2018 was investigated though a series of numerical simulations. The system moved from northwest to southeast, passing through Yanqing (YQ), Changping (CP), and the central urban area (CUA) of Beijing. The combined influences of the multiple urban areas and the mechanisms of the mutual impacts of upstream and downstream cities on precipitation were investigated. Results showed that the urban surfaces led to an increase in near-surface temperature, a decrease in lower-level wind speed, and airflow triggered convergence and updrafts. The resulting upward moisture transport and latent heat release in the cloud were promoted during the subsequent precipitation. The thermal and dynamic impacts of CUA and CP urban areas propagated downstream along the low-level southeasterly flow, resulting in increased temperatures, strengthened updrafts, and latent heat release in the cloud along YQ-CP-CUA region. The urban effects propagated downstream under the southeasterly wind, leading to enhanced precipitation over YQ and CP. The YQ also, however, contributed to the increased precipitation in CUA. The “city chain” comprised of YQ, CP, and CUA thus promoted the progression and advancement of the precipitation system. This study highlights the importance of the correct identification of the “upwind” and “downwind” directions when studying urban impacts on precipitation.

Classifying Microwave Radiometer Observations over the Netherlands into Dry, Shallow, and Nonshallow Precipitation Using a Random Forest Model

Abstract Spaceborne microwave radiometers represent an important component of the Global Precipitation Measurement (GPM) mission due to their frequent sampling of rain systems. Microwave radiometers measure microwave radiation (brightness temperatures Tb), which can be converted into precipitation estimates with appropriate assumptions. However, detecting shallow precipitation systems using spaceborne radiometers is challenging, especially over land, as their weak signals are hard to differentiate from those associated with dry conditions. This study uses a random forest (RF) model to classify microwave radiometer observations as dry, shallow, or nonshallow over the Netherlands—a region with varying surface conditions and frequent occurrence of shallow precipitation. The RF model is trained on five years of data (2016–20) and tested with two independent years (2015 and 2021). The observations are classified using ground-based weather radar echo top heights. Various RF models are assessed, such as using only GPM Microwave Imager (GMI) Tb values as input features or including spatially aligned ERA5 2-m temperature and freezing level reanalysis and/or Dual-Frequency Precipitation Radar (DPR) observations. Independent of the input features, the model performs best in summer and worst in winter. The model classifies observations from high-frequency channels (≥85 GHz) with lower Tb values as nonshallow, higher values as dry, and those in between as shallow. Misclassified footprints exhibit radiometric characteristics corresponding to their assigned class. Case studies reveal dry observations misclassified as shallow are associated with lower Tb values, likely resulting from the presence of ice particles in nonprecipitating clouds. Shallow footprints misclassified as dry are likely related to the absence of ice particles. Significance Statement Published research concerning rainfall retrieval algorithms from microwave radiometers is often focused on the accuracy of these algorithms. While shallow precipitation over land is often characterized as problematic in these studies, little progress has been made with these systems. In particular, precipitation formed by shallow clouds, where shallow refers to the clouds being close to Earth’s surface, is often missed. This study is focused on detecting shallow precipitation and its physical characteristics to further improve its detection from spaceborne sensors. As such, it contributes to understanding which shallow precipitation scenes are challenging to detect from microwave radiometers, suggesting possible ways for algorithm improvement.

Improving Forecasts of the “21⋅7” Henan Extreme Rainfall Event Using a Radar Assimilation Scheme that Considers Hydrometeor Background Error Covariance

Abstract On 20–21 July 2021, a record-breaking rainfall event occurred in Henan Province, China, and a maximum hourly accumulated precipitation of 201.9 mm was recorded at Zhengzhou Meteorological Station. To improve the prediction of such extreme rainfall and to better understand the impacts of the radar reflectivity assimilation on forecasting, we assimilated radar reflectivity data using the hydrometeor background error covariance (HBEC) that includes vertical and multivariate correlations and then diagnosed the dynamic, thermal, and microphysical forecasts of this event. The results show that the radar reflectivity assimilation based on the HBEC properly transferred the observed radar reflectivity to the analysis of hydrometeors and other model states, and clearly improved the heavy rainfall forecast. The diagnosis of the dynamic and thermal forecasts indicated that the reflectivity assimilation based on the HBEC improved the convective environments of the precipitation systems, with stronger cold pools near the surface and deeper and wetter updrafts near Zhengzhou station, when compared with the experiment that did not assimilate radar reflectivity and the experiment that assimilated radar reflectivity without using the HBEC. The diagnosis of the microphysical forecasts further shows that assimilating reflectivity data using HBEC contributed to higher conversion rates of water vapor and cloud water to graupel and higher conversion rates of graupel and cloud water to rainwater, when compared with the other experiments. These improvements of both convective environments and microphysical processes within the convections ultimately enhanced the forecasts of this extreme rainfall event.

Evaluation of Precipitation Forecast by the Operational China Meteorological Administration Mesoscale Model During the 2020 Meiyu Period

AbstractThis study evaluated the precipitation forecast produced by the operational China Meteorological Administration Mesoscale model (CMA‐MESO) during the “super violent” Meiyu season of 2020. Generally, CMA‐MESO, which runs with ∼3‐km‐grid resolution, is able to reproduce the distribution and diurnal variation of precipitation. However, the precipitation amount is greatly overestimated, especially in eastern coastal areas of China. Precipitation in that region usually occurs with two peaks: one in the morning that mostly reflects organized precipitation systems, and the other in the afternoon generated mostly by local convection. Analyses showed that overestimation of low‐level wind speed is the main reason for the overestimation of precipitation. CMA‐MESO produces low‐level winds that are overly strong, which greatly enhance the predicted convergence at night, leading to overestimation of precipitation. Additionally, the stronger wind speed increases the estimated transport of water vapor to the eastern coastal area, producing fake convection near the coastal mountains as the perturbed wind direction turns toward the mountain area in the afternoon. In comparison with ERA5, CMA‐MESO tends to overestimate (underestimate) the temperature in the northwest (southeast), and the larger temperature gradient increases the pressure gradient, resulting in the stronger low‐level wind speed.

Vertical structures and microphysical characteristics of summer precipitation in North China detected by GPM-DPR

The vertical structure and microphysical characteristics of stratiform precipitation (SP) and convective precipitation (CP) in North China are revealed based on the GPM-DPR product during boreal summer of 2014–2021 in this study. Additionally, the differences in precipitation features between the mountain and the plain are investigated. Under the combined influence of climatic factors and local topography, the precipitation amount is larger in the plain than in the mountain while precipitation frequency exhibits an opposite pattern. The proportions of the two precipitation types are similar in the mountain and the plain, with CP contributing to approximately a quarter of total precipitation frequency. In terms of mean intensity, both SP and CP are roughly 20 % more intense in the plain than in the mountain. The greater number of light SPs is a major contributor to higher precipitation frequency in the mountain, while more intense CPs result in larger precipitation amount in the plain. Compared to the mountain, the precipitation system is deeper in the plain, where higher storm top altitudes (STAs) and larger freezing level heights contribute to more intense CPs. Besides, it is observed that for the STA, more intense CPs occur in the plain compared to the mountain. In both the mountain and the plain, the coalescence process is dominant in the low-level layers for heavy (8–20 mm/h) to storm-level (>20 mm/h) CPs. Compared to the mountain, the low-level growth of hydrometeor size and radar reflectivity is more significant in the plain. These findings are important to quantitative precipitation estimation and precipitation prediction in the mountainous region, and can help understand the influence of local topography on precipitation.

Dynamical and Microphysical Aspects of Two Distinct Precipitation Systems in the Himalayas With 206.5 MHz Radar and WRF Model

AbstractThe dynamical and microphysical aspects of two different precipitating systems have been investigated using the ARIES Stratosphere‐Troposphere Radar (ASTRad) facility and further substantiated by Weather Research Forecasting (WRF) model over Manora Peak. The first event (Case‐I) is associated with the southwest Indian summer monsoon that occurred on 4 August 2020, with a vertical extension of 10–12 km and leads to liquid phase precipitation. The second event (Case‐II) linked to the winter western disturbance occurred on 5 February 2021. This precipitating system was developed with a vertical extension of 6–7 km, resulting in both liquid and solid phase precipitation. Such distinct vertical extension of the systems is found to be associated with the thermodynamical conditions and prevailed large‐scale circulations. By analyzing the vertical structure of these systems using three Doppler moments estimated from the ASTRad (equivalent Reflectivity dBZe, Doppler velocity, and Spectral width), maximum dBZe (∼60 dB) is observed in Case‐II, while higher spectral width (&gt;2 m s−1) is associated to Case‐I. The microphysical processes assessed by the WRF model pointed out that Case‐I involved snow accretion on supercooled droplets, leading to graupel and raindrop formation, while in Case–II, solid and liquid precipitation resulted from ice processes, including accretion or autoconversion. These findings highlight the significance of integrating radar and modeling data to understand the dynamical and microphysical evolution of precipitation under the influence of orography in the Himalayan region.

Self-clustered GAN for precipitation nowcasting

This paper proposes a novel GAN framework with self-clustering approach for precipitation nowcasting (ClusterCast). Previous studies have primarily captured the motion vector using only a single latent space, making the models difficult to adapt to disparate space-time distribution of precipitation. Environmental factors (e.g., regional characteristics and precipitation scale) have an impact on precipitation systems and can cause non-stationary distribution. To tackle this problem, our key idea is to train a generator network to predict future radar frames by learning a sub-network that automatically labels precipitation types from a generative model. The training process consists of (i) clustering the hierarchical features derived from the generator stem using a sub-network and (ii) predicting future radar frames according to the self-supervised labels, enabling heterogeneous latent representation. Additionally, we attempt an ensemble forecast that prescribes random perturbations to improve performance. With the flexibility of representation learning, ClusterCast enables the model to learn precipitation distribution more accurately. Results indicate that our method generates non-blurry future frames by preventing mode collapse, and the proposed method demonstrates robustness across various precipitation scenarios. Extensive experiments demonstrate that our method outperforms four benchmarks on a 2-h prediction basis with a mean squared error (MSE) of 8.9% on unseen datasets.