Accurate characterization of Raindrop Size Distribution (RDSD) is essential for precipitation estimation, rainfall microphysics, and model parameterizations. This study compares four years of continuous RDSD measurements from a Two-Dimensional Video Disdrometer (2DVD) and a Joss-Waldvogel Disdrometer (JWD) at Tuljapur, India, to assess how spectral differences affect rain integral parameters, gamma DSD parameters, Radar Reflctivity Factor (Z, mm(6)m(-3))-Rainfall Intensity (R, mm h(-1)), i.e., Z-R relationships, and microphysical regimes. Half-hourly rainfall accumulations from both instruments agreed well with an Automatic Rain Gauge, with 2DVD showing lower bias and RMSE. The 2DVD captured a broader spectrum (0.2-10 mm), detecting more large (5-10 mm) and small (D < 1 mm) drops, whereas the JWD, limited to 0.3-5.3 mm, underestimated small drops for rain rates > 5 mm h(-1) and overestimated mid-sized drops (2-3 mm). These differences impacted rain integral parameters, with JWD-derived total raindrop concentration (N-T,m(-3)), Liquid Water Content (LWC, gm(-3)), R, and Z deviating significantly at intensities above 20 mmh(-1). Correspondingly, 2DVD-derived gamma shape (& micro;) and slope (lambda, mm(-1)) were lower, indicating a broader distribution. Z-R relationships (Z = aR(b)) were similar for 0.1 < R <= 20 mmh(-1) but diverged at higher intensities. For 50 < R <= 100 mmh(-1), 2DVD coefficients were 58% larger. Principal Component Analysis (PCA)-based microphysical regime analysis showed JWD underrepresented convective events and overrepresented stratiform rain relative to 2DVD. These results demonstrate that differences in RDSD sampling between 2DVD and JWD strongly affect microphysical parameters and Z-R relationships, with implications for rainfall retrievals and cloud-precipitation modeling over the Indian monsoon region.

Unique observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX Phase-IV) revealed the complex multi-layer structure of monsoon clouds, offering key insights into their microphysical and thermodynamic processes. This study investigates the influence of vertically layered aerosol distributions on cloud microphysical properties over the rain-shadow region of India, focusing on three distinct cloud layers: a highly polluted boundary layer cloud, a cleaner mid-layer cloud, and a polluted upper-level cloud. Results show that aerosol layering significantly influences warm cloud microphysics of the layer clouds, including cloud drop radius, liquid water content, spectral width, and cloud droplet number concentration. The drop size distribution (DSD) and particle size distribution (PSD) across the three cloud layers indicated that the middle cloud layer developing under extremely clean conditions exhibited a significantly broader DSD and PSD compared to the other two layers, which formed in environments with slightly higher aerosol loading. Such extremely clean conditions, characterized by cloud droplet number concentrations below 20 cm-3, are rare over continental regions. The upper portion of the top stratiform cloud was characterized by a high concentration of dendritic ice particles, with sizes ranging from 300 to 3000 mu m. Just below this dendritic layer, numerous supercooled drizzle drops were observed, with significant aircraft icing. The microphysical characteristics of both the dendritic ice zone and the underlying icing layer containing supercooled drizzle drops were investigated. This study presents observational evidence of the complex vertical structure of monsoon clouds and highlights the role of layered aerosol distributions in modulating cloud microphysical properties, providing constraints for the improvement of cloud process representations in weather and climate models.

Building on the hypothesis of wall and jet structural modes proposed in Part 1 (Choudhary et al. 2024), this study reports coherent patterns and vortical structures associated with the jet mode by further analysing our experimental particle image velocimetry datasets. Instantaneous velocity fields are binned based on dominant streamwise Fourier modes, focusing on submodes with wavelengths $\lambda _x\approx 5{z_{T}}$ (submode 1) and $\lambda _x\approx 2.5{z_{T}}$ (submode 2); $z_{T}$ is outer length scale of the flow. Two-point correlations of streamwise velocity fluctuations for the total and modal fields reveal near-periodic coherent patterns inclined backwards (similar to $14<^>{\circ }$ ) in the outer region and forwards (similar to $9<^>{\circ }$ ) in the inner region. Vortical structures in conditionally averaged velocity fluctuation vector fields are examined using linear stochastic estimation (LSE) with anticlockwise vorticity (prograde) at the outer energy site as the condition. The vortical structure of submode 1 is a three-vortex system with (i) a robust clockwise vortex in the inner region and (ii) a saddle-point topology in the outer region. The vortical structure of submode 2 is a backward-leaning vortex packet. The LSE fields indicate Q1-Q3 events in the inner region contributed by 'non-local' eddies through the interaction of outer and inner submode 1 vortices. Quadrant analysis reveals that Q1-Q3 events due to 'non-local' eddies outweigh Q2-Q4 contributions of 'local' eddies, producing counter-gradient momentum diffusion below mean velocity maximum. These findings further substantiate the hypothesis of wall and jet structural modes and indicate that the region below mean velocity maximum in wall jets significantly differs from a turbulent boundary layer.

Ice-nucleating particles (INPs) play a critical role in cloud microphysics, influencing precipitation efficiency and cloud lifetime. This study presents measurements of immersion-freezing INPs over the rain-shadow region of India, with immersion freezing and condensation freezing considered as a single mode. INP concentrations ranged from 2 to 12 L-1 between -15 degrees C to -35 degrees C. At -40 degrees C, which is representative of homogeneous freezing conditions, the ice crystal concentration reaches similar to 800 L-1. Ice nucleation activity was further characterized through parameters such as ice fraction and active surface site density. These parameters, as functions of temperature and ice supersaturation, provide valuable constraints for representing mixed-phase cloud processes in weather and climate models. Observed INP concentrations showed weak sensitivity to coarse-mode aerosol number concentrations, in which positive correlations with aerosols are emerging only below -25 degrees C. An empirical INP-temperature parameterization was developed from observations and evaluated within the Weather Research & Forecasting model, alongside two commonly used immersion-freezing schemes. Simulations of mixed-phase monsoon clouds demonstrated that cloud properties such as cloud top temperature, supercooled liquid water content, ice content, and water paths are sensitive to the chosen INP parameterization, particularly in the absence of secondary ice production (SIP). Inclusion of SIP mechanisms reduced this sensitivity, as SIP-generated ice particles compensated for variations induced by heterogeneous nucleation. Minimal changes in surface precipitation were observed, likely due to dominant homogeneous freezing at upper cloud levels.

Accurate characterization of Raindrop Size Distribution (RDSD) is essential for precipitation estimation, rainfall microphysics, and model parameterizations. This study compares four years of continuous RDSD measurements from a Two-Dimensional Video Disdrometer (2DVD) and a Joss–Waldvogel Disdrometer (JWD) at Tuljapur, India, to assess how spectral differences affect rain integral parameters, gamma DSD parameters, Z–R relationships, and microphysical regimes. Half-hourly rainfall accumulations from both instruments agreed well with an Automatic Rain Gauge, with 2DVD showing lower bias and RMSE. The 2DVD captured a broader spectrum (0.2–10 mm), detecting more large (5–10mm) and small (D<1mm) drops, whereas the JWD, limited to 0.3–5.3 mm, underestimated small drops for rain rates >5mm h−1 and overestimated mid-sized drops (2–3 mm). These differences impacted rain integral parameters, with JWD-derived NT, LWC, R, and Z deviating significantly at intensities above 20 mmh−1. Correspondingly, 2DVD-derived gamma shape (μ) and slope (λ, mm−1) were lower, indicating a broader distribution. Z–R relationships (Z=aRb) were similar for 0.1

Heatwaves are among the deadliest natural hazards in India, and their frequency and duration have intensified in recent decades due to anthropogenic climate change. While heatwave characteristics and future projections are well-studied, there remains limited understanding at the city level of how urban populations are exposed to extreme heat. In urban areas, climate-induced warming is further amplified by the urban heat island effect, increasing population exposure to extreme heat. Using the Global High-Resolution Daily Extreme Urban Heat Exposure dataset, we assess changes in urban population exposure to extreme heat across India from 1983 to 2016. At the national scale, exposure increased by 157 %, with two-thirds of the increase driven by population growth and the remaining increase attributed to urban warming. The frequency of very high-risk days increased by 44%, while extreme-risk days more than doubled, adding nearly an extra month of dangerously hot conditions each year. A key contribution of this study is the first systematic ranking of India's major cities based on heat exposure. Delhi ranks highest, with total exposure trends primarily driven by population growth (74%), followed by Kolkata (≅47%) and Mumbai (≅54%), where both urban warming and population growth contribute substantially. In contrast, southern coastal cities exhibit warming-dominated exposure, with over 90% attributed to urban warming. These findings provide a foundation for policymakers to design future adaptation strategies across diverse urban contexts. It also highlights the urgent need for continuous monitoring and region-specific measures to reduce heat stress in densely populated areas.

The present study examines the ozone concentration and surface energy budget over Delhi during the pre-monsoon season, with a specific emphasis on non-heatwave (NHW), moist heatwave (Moist HW), and dry heatwave (Dry HW) conditions using observations, reanalysis data, and numerical simulations. The results indicate that surface ozone peaked during Moist HW (similar to 92 ppbv), followed by Dry HW and NHW periods. The elevated ozone during Moist HWs is associated with weak winds (0.2-2.5 ms(-1)), high humidity (>60%), increased CO (similar to 200 ppbv), decreased NOx (congruent to 0.8 ppbv), and dust loading, a shallow boundary layer (similar to 2223 m), which collectively enhanced ozone in the boundary layer. A key contributor to the enhanced ozone during Moist HWs is the influence of the residual layer, which retained elevated ozone levels overnight (similar to 1800 m) that subsequently mixed with daytime emissions, amplifying surface ozone concentrations, and is supported by the vertical ozone flux diagnostics. In contrast, Dry HW periods, despite stronger radiative forcing, higher sensible heat flux, deeper boundary layers, and stronger winds, exhibited lower ozone concentrations due to reduced CO, NOx, and dust levels, which suppressed photochemical ozone production. Surface energy budget analysis revealed that although Dry HWs were more thermally intense, Moist HWs posed greater heat stress due to higher humidity and ozone levels, with the Heat Index during Moist HWs exceeding that of Dry HWs by 0.7 degrees C. These findings emphasize the distinction between Dry and Moist HWs in managing heat stress in urban environments, highlighting the critical influence of atmospheric mixing, boundary layer dynamics, and inversion layers in ozone accumulation.

Abstract. The Southern Ocean plays a critical role in Earth's climate system, acting as a major sink for heat and carbon dioxide. Clouds over this region strongly influence the regional radiation budget, yet their formation remains poorly understood and represented in climate models. This is partially driven by the lack of in-situ observations, particularly over the undersampled Indian sector. In this study, we report on the latitudinal variability of cloud condensation nuclei (CCN) and examine the meteorological and biological factors that can influence their distribution across this region. CCN concentrations were measured during the 12th Indian Scientific Expedition to the Southern Ocean during February and March 2025 aboard a research vessel traversing from 20° S to 68° S. CCN concentrations varied across supersaturation levels, with the highest values approximately 500 cm-3 observed at S = 1.0 % in the polar band (60–70° S) and lower concentrations at lower S levels. CCN concentrations showed a poor correlation with coarse-mode aerosols, suggesting that wind-driven sea spray does not play a major role in controlling the CCN variability in this region. Chlorophyll a, used as a proxy for biological productivity, showed a positive relationship with CCN concentrations. Air masses passing over biologically productive waters during the preceding 24–48 h were associated with higher CCN concentrations, with the strongest relationship observed within the 30–50° S latitude band encompassing the subtropical and subantarctic fronts. This suggests a closer association between marine biological activity and CCN variability in this region. In contrast, the weaker relationship outside this latitude band indicates that physical processes and non-biological sources may exert a greater influence on CCN concentrations in other regions.

Atmospheric aerosols play a vital role in offsetting warming caused by greenhouse gases. However, the light-absorbing fractions of carbonaceous aerosols, such as black carbon (BC) and brown carbon (BrC), introduce significant uncertainties into climate models. A significant reason for this uncertainty is that the properties of carbonaceous aerosols are poorly constrained by existing observations. This lack of clarity needs to be addressed to understand their accurate and precise impact on climate and air quality. This study investigated the mass and absorption characteristics of various carbonaceous aerosol species using in-situ observations with a multi-wavelength Aethalometer during a cruise expedition across the Bay of Bengal transect from 2 degrees N to 18 degrees N in April-May 2024. The results showed increased BC mass at higher (northern) latitudes. Air mass back trajectory analysis indicated that the elevated BC levels in the northern latitudes were largely due to long-range transport of carbonaceous aerosols from the Indian subcontinent. Interestingly, the contribution of BrC was relatively large (17%) at southern latitudes compared to the northern latitudes (10%), where air masses originated from remote oceanic regions. Evidence showed a strong positive correlation between NO2 emissions and BrC absorption at lower (southern) latitudes in proximity to the Indo-Pacific trade route, suggesting that NOx emissions from ship traffic may enhance the production of nitrogen-containing BrC chromophores, which are more light-absorbing.

Refractory black carbon (rBC) plays an important role in aerosol-cloud-radiation interactions, yet in situ observations of rBC incorporation into cloud droplets within deep convective monsoon clouds remain limited. Aircraft-based measurements of ambient and in-cloud rBC were conducted during Cloud Aerosol Interaction and Precipitation Enhancement EXperiment (CAIPEEX Phase-IV) over the rain-shadow region of peninsular India. Ambient aerosols were sampled using an isokinetic inlet, while cloud droplet residuals were sampled using a counterflow virtual impactor (CVI) inlet. Ambient rBC concentrations peaked below cloud base (similar to 60-200 cm(-3)) and decreased with altitude, with values typically below 5 cm(-3) above 5 km. In contrast, in-cloud rBC concentrations remained low (<10 cm(-3)) and declined from cloud base to similar to 0.1 cm(-3) at cloud top. Size-resolved in-cloud rBC residuals showed unimodal distributions peaking at similar to 0.18-0.22 mu m, with concentrations 1-2 orders of magnitude lower than ambient rBC, indicating limited rBC incorporation into cloud droplets. Estimated coagulation fractions of rBC remained below 1% and our estimations showed that coagulation alone is insufficient to explain the observed in-cloud rBC concentrations. The estimated ratio of in-cloud rBC to cloud droplet number concentration (CDNC) indicated that less than 3% of cloud droplets contained rBC particles. Clustering-based analysis further showed that the relationship between in-cloud rBC and CDNC varied with cloud dynamical and microphysical conditions. No significant correlation was observed in cloud-core parcels, whereas a weak positive correlation was evident within entrainment regions. These observations provide new constraints on rBC behavior within deep convective monsoon clouds.

Aerosols modulate the microphysical evolution of deep convective clouds by altering cloud condensation nuclei (CCN) and ice-nucleating particle (INP) concentrations, yet their role over oceanic regions remains poorly constrained due to limited in situ observations. This study investigates the influence of aerosol loading on the microphysical properties of deep convective clouds with active mixed-phase processes over the Bay of Bengal (BoB) using unique airborne microphysical observations and high-resolution simulations.In the observed case, the polluted marine boundary layer was characterized by CCN concentrations exceeding 1000 cm−3, attributed to the nonlocal transport of continental aerosols. The elevated CCN concentrations led to high cloud droplet number concentrations (up to ∼800 cm−3) and small droplet effective radii (<12 μm) throughout much of the cloud depth. These microphysical conditions suppressed collision–coalescence processes and delayed the formation of warm rain. Observations indicate that most precipitation-sized particles occurred as graupel, highlighting the important role of mixed-phase microphysical processes in rain formation. Ice particle concentrations (10–100 L−1) exceeded estimated INP concentrations by 2 orders of magnitude, suggesting strong secondary ice production (SIP).Numerical Simulations were conducted to investigate microphysical processes under clean and polluted conditions, defined based on variations in cloud droplet number concentration. The control simulation successfully reproduced the vertical distributions of liquid water content, ice water content, and ice number concentrations. Simulated polluted clouds exhibit approximately 20% higher liquid water content and ∼43% greater ice water content than clean clouds, accompanied by enhanced depositional growth, aggregation, riming, and snow production. Overall, simulated polluted clouds exhibit stronger ice enhancement due to more active SIP and glaciation at warmer temperatures compared with clean clouds. Additionally, the simulation with polluted conditions shows higher ice and liquid water paths, accompanied by reduced rain production. The findings suggest that high aerosol loading in polluted maritime convection suppresses warm-rain processes while strengthening mixed-phase and ice-phase pathways. This study presents rare observations from BoB, making it a special case for aerosol–cloud interactions. More observations and simulations are needed to generalize the results.

Despite advancements in science and technology, flood prediction and preparedness remain challenging due to uncertainties in forecasting atmospheric and hydrologic processes, limited real-time data, and communication barriers. The Integrating Prediction of Precipitation and Hydrology for Early Actions (InPRHA) project, a 5-yr initiative under the WMO's World Weather Research Programme, is the first to bring together meteorology, hydrology, and social sciences within a steering committee to address these challenges. Building on knowledge from the High Impact Weather (HiWeather) project, InPRHA focuses on multihazard flood forecasting across the entire warning value chain from minutes to days, in a rapidly changing world. A key emphasis is understanding flood predictability and how uncertainties cascade through forecasting systems and are perceived, communicated, and acted upon by diverse stakeholders. This includes bridging research and operations, examining socioeconomic, cultural, and environmental challenges that influence risk perception and response. We propose key scientific questions across seven themes that address critical gaps in integrating predictions along the flood warning value chain. Addressing these gaps requires collaboration across disciplines and agencies. The project is structured into four work packages: DEFINE (identifying challenges), CONSTRUCT (gathering case studies), EXPERIMENT (scientific evaluations), and ENGAGE (community collaboration). Research will span rural, urban, and underdeveloped regions as well as countries with established warning systems, ensuring broad applicability. We invite scientists and practitioners from meteorology, hydrology, hydraulics, impacts, communication, human behavior, and economics to collaborate. By integrating disciplines and fostering transdisciplinary research, InPRHA aims to advance the science and practice of flood forecasting and early warnings to better protect vulnerable communities at risk. SIGNIFICANCE STATEMENT: InPHRA is a 5-yr project aimed at promoting international cooperation and advancing research to enhance flood hazard forecasting systems and warnings. By integrating precipitation and hydrologic predictions with social sciences, it seeks to improve early warning for communities in a rapidly changing world. InPRHA aims to reenvision the warning process by addressing flood multihazard interdependencies, local vulnerability, and climate change impacts on precipitation and hydrology forecasts. InPRHA calls on the broader research and operational community to collaborate on addressing key scientific questions and fostering transdisciplinary research across academia, research institutions, policymakers, and operational forecasting centers.

Statistical and fractal properties of the scalar interface in a plane turbulent wall jet of air are investigated experimentally. Seeding is introduced for only the jet flow. These seed particles do not diffuse or evaporate quickly, in contrast to smoke that is commonly used in air flows. Three cameras are placed one above the other and operated in a single-frame mode to image the instantaneous scalar interface between the seeded jet and unseeded ambient fluid with sub-Kolmogorov spatial resolution and an unprecedented dynamic range (large-to-small scale ratio) of 2450. The interface in each image is marked by a simple thresholding technique. A well-converged probability density function (p.d.f.) of the interface height from the wall is obtained from an ensemble of 2945 usable images. The p.d.f. is found to be Gaussian to an excellent approximation, with the most probable location at 1.57 times the outer length scale of the wall jet (marking half the maximum velocity). Fractal dimension of the interface in each usable image is computed using the box counting algorithm and compensated plots for an objective determination. The mean fractal dimension over all usable images is 1.361 ± 0.002, which agrees very well with the near-universal value reported by Sreenivasan and coworkers for a variety of turbulent flows.

This study investigates aerosol impacts in the primary and secondary convective cells and their associated cold pools resulting from the convective outflow over the dry and arid regions of the Indian peninsula. A convective event observed with C-band polarimetric radar is analysed through several numerical simulations, focusing on the impact of aerosol on rainfall and cold pool characteristics. Control simulations were conducted with low, moderate and high cloud condensation nuclei (CCN). Additional sensitivity experiments introduced more ice nuclei particles (INP) in both the primary and secondary convection areas with supercooled liquid water content. The introduction of more INP in all experiments resulted in more ice crystals, snow, hail, as well as an enhancement of high-intensity rainfall. In the primary convection area, the addition of INP led to enhanced mass flux, snow, hail, and melting of hail, which contributed to enhanced area averaged rainfall (>1 mm) and an increase in the cold pool area. However, no significant change was observed in the speed and depth of the primary cold pool depending on the low/high INP simulation. Addition of INP in the secondary convection area did not notably affect the strength or area of the cold pool. Overall, the study highlights that the spatial features of convection and cold pools are modified by the introduction of additional ice forming aerosols.

Accurate precipitation forecasting hinges on the representation of microphysical processes within numerical models. A key approach to understanding these processes is through the analysis of hydrometeor drop size distribution (DSD). The characteristics of DSD bulk parameters - Mass Weighted Mean Diameter (D-m) and the Normalized Intercept Parameter (N-w), are estimated from the double moment cloud microphysical scheme (CASIM: Cloud-Aerosol Interacting Microphysics) employed in the operational convection permitted model of National Centre for Medium-Range Weather Forecasting (NCUM-R). The observations from the Joss-Valdvogel Disdrometer (JWD) and the Global Precipitation Mission - Dual Frequency Precipitation Radar (GPM-DPR) are analyzed for providing essential validation. An algorithm for separating the monsoon precipitation into convective and stratiform types in NCUM-R and a new parameter estimation module to obtain DSD parameters from the CASIM are established in the study. The model exhibits agreement with the characteristics of the DSD of raindrops with D-m ranging from 0.5 to 2.5 mm marking the majority of the monsoon precipitation events. However, the underestimation when it comes to the larger drops (with D-m > 3.25 mm and Rainrate >= 8 mm h(-1)) demands a reassessment in microphysical parameterizations. The advanced autoconversion parameterization scheme applied in CASIM favored the growth of large drops compared to the existing scheme. The enhanced growth of larger drops is reflected in the increased accuracy in the prediction of extreme precipitation associated with a convective event. The current study underscores the importance of refining microphysical parameterizations to improve the accuracy of precipitation forecasts offering a pathway for enhanced model performance in future operational forecasting systems.

In this study, a spatial spectral analysis of turbulent plane wall jets is conducted using two-dimensional particle image velocimetry (2D-PIV) at three different nozzle Reynolds numbers: 10,244, 15,742, and 21,228. To accomplish this, four cameras are positioned side-by-side, capturing the longest field of view in the study of wall jets. The obtained PIV fields are utilized to construct spatial spectra, aiming to understand the model spectral contribution to the variance of velocity fluctuations and Reynolds shear stress. The study reveals that the jet mode exhibits wavelengths that scale with the jet length scale, denoted as z_T . This mode contains two dominant submodes with wavelengths of 5 z_T and 2.5 z_T respectively. In the region above, the velocity maximum, the presence of the jet mode is observed, while the region below it exhibits a robust bimodal behavior attributed to both the wall and jet modes.

Aerosol-cloud interactions are a persistent source of uncertainty in climate research. This study presents findings from a model intercomparison project examining the impact of aerosols on clouds and climate in convection-permitting radiative-convective equilibrium (RCE) simulations. Specifically, 11 different modeling teams conducted RCE simulations under varying aerosol concentrations, domain configurations, and sea surface temperatures (SSTs). We analyze the response of domain-mean cloud and radiative properties to imposed aerosol concentrations across different SSTs. Additionally, we explore the potential impact of aerosols on convective aggregation and large-scale circulation in large-domain simulations. The results reveal that the cloud and radiative responses to aerosols vary substantially across models. However, a common trend across models, SSTs, and domain configurations is that increased aerosol loading tends to suppress warm rain formation, enhance cloud water content in the mid-troposphere, and consequently increase mid-tropospheric humidity and upper-tropospheric temperature, thereby impacting static stability. The warming of the upper troposphere can be attributed to reduced lateral entrainment effects due to the higher environmental humidity in the mid-troposphere. However, models do not agree on aerosol impacts on convective updraft velocity based on the preliminary examination of high-percentiles of vertical velocity at a single mid-troposheric layer (500 hPa). In large-domain simulations, where convection tends to self-organize, aerosol loading does not consistently influence self-organization but tends to reduce the intensity of large-scale circulation forming between convective clusters and dry regions. This reduction in circulation intensity can be explained by the increase in static stability due to the upper tropospheric warming.