Abstract This paper describes improvements to geophysical retrievals from NASA's Advanced Microwave Precipitation Radiometer (AMPR) during the Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). The retrieved products are validated using independent data sets, and example applications in addressing science questions about the maritime tropics are provided. Multi‐linear regression equations previously developed to retrieve cloud liquid water path (CLW), total precipitable water vapor (WV), and 10‐m wind speed (WS) from AMPR brightness temperatures in the midlatitudes were examined. Initial testing revealed that the CLW methods required modification for the maritime tropics, likely due to the stark environmental differences. Minor WS adjustments were also needed to account for the presence of a new AMPR radome. Compared with numerical simulations, the updated CLW equation performed nearly an order of magnitude better than its predecessor. Validating AMPR CLW with airborne polarimeter‐derived CLW throughout CAMP2Ex yielded a median absolute deviation that is less than the predecessor CLW equation's uncertainty and comparable to CLW precisions observed in past studies. In situ WV and WS validation using dropsondes was promising, with mean deviations that are less than their target uncertainties. Correlating AMPR CLW with polarimeter‐derived cloud‐top height (CTH) indicated an expected CLW ∝ CTH2 relation for CTH < 4 km, but reduced CLW for CTH > 4 km may have been associated with cloud droplet removal via accretion and/or mixed‐phase onset. These results demonstrate the power of airborne radiometer geophysical retrievals as standalone metrics and the insight they provide when used alongside other data sets.

Atmospheric cold pools are transient sub-mesoscale to mesoscale weather phenomena generated by convective precipitation. They are characterized by cool, dense air spreading laterally, which strongly alters near-surface atmospheric conditions and the thermohaline properties of the ocean skin layer (< 1 mm) and near-surface layer (NSL: < 1 m). The spatial extent and thermodynamic intensity of atmospheric cold pools are moderated by mixing within the moist marine boundary layer (MBL), the lowest ~0.5–1 km of air above the ocean. Despite this moderation, accompanying wind surges and intense precipitation drive short-lived intensifications of atmosphere–ocean fluxes that can abruptly restructure upper-ocean thermohaline structure, an aspect that remains poorly constrained by in situ measurements and is underrepresented in coupled atmosphere–ocean models.Here we present observations of atmospheric cold pool passages over the tropical Atlantic Ocean, combining ship-based meteorological measurements, aerial drones, weather balloon profiles, and high-resolution observations from the autonomous surface vehicle HALOBATES. Equipped with meteorological and oceanographic sensors sampling at high-resolution (1 Hz), HALOBATES resolves the ocean skin layer and the NSL dynamics, allowing us to identify and characterize cold pools as they passed over the study area during the R/V METEOR M211 field campaign (14 June–27 July 2025).Between 13 and 18 July 2025, cold pool passages were identified by rapid air-temperature drops of 0.6–1.8 °C and, during rainy events, rainfall rates of up to 37 mm h⁻¹. All cold pools induced transient ocean surface cooling, leading to sea surface temperature anomalies (Tskin-TNSL) of 0.02 – 0.35 °C, and amplified cooling in the skin layer relative to the NSL. To quantify the cooling and recovery of the ocean skin layer following the cold pool passage, we consider two different skin-layer depths: the infrared (IR) skin layer observed by thermal cameras and the skin layer measured in situ by HALOBATES. This comparison shows that skin-temperature responses evolve on timescales of only a few minutes and therefore require high temporal resolution in situ measurements to be adequately resolved.Salinity responses depended critically on precipitation: cold pools that passed the study area without measurable rainfall produced negligible changes, whereas intense-rain events freshened the skin by up to 1.3 g kg-1 and the NSL by 0.4 g kg-1, forming shallow freshwater lenses that re-stratified the upper meter within approximately 15 minutes. Pronounced cold pool passages were accompanied by enhanced latent and sensible heat fluxes, with maximum increases of −140 W m⁻² and −30 W m⁻², respectively, driven primarily by increased wind speeds and indicating intensified ocean-to-atmosphere heat exchange. These observations demonstrate that cold pools strongly affect short-term variability in upper-ocean thermohaline structure through short-lived intense peaks in atmosphere–ocean fluxes, emphasizing the need to include these transient events in future coupled atmosphere–ocean models.

Multirotor drones (part of the category of small Uncrewed Aerial Systems [sUAS] or small Uncrewed Aerial Vehicles [sUAV]) are used in atmospheric research to make measurements of the lower atmosphere, and their use is poised to increase in the future. New drone atmospheric sensing opportunities, such as ride-along applications and drone swarms, are emerging. These opportunities, which may not allow room for specialized shielding or aspiration equipment, together with increased drone usage, necessitate the characterization of the performance of unshielded sensors mounted to drones if the accuracy of such observations is to be understood. In this work, we characterize the accuracy of thermodynamic measurements, specifically temperature and water vapor mixing ratio, based on the sensor mounting position onboard multirotor drones. To assess the influence of the drone mechanics on the measurements, ninety-eight individual drone flights with eight distinct thermodynamic sensor positions were performed next to an instrumented flux tower and a tethersonde carrying identical sensors, where the tower and tethersonde measurements are assumed as truth. The flights were at least nine minutes in length, and nine of the flights were conducted at night. At the best position, absolute daytime temperature errors were between −0.83 and +0.61 K at the 95 % confidence interval, while nighttime temperature errors were smaller, ranging from −0.28 and +0.48 K. Water vapor mixing ratio errors are within −0.22 and +0.66 g kg−1. We conclude that measurements in field campaigns are more accurate when sensors are placed away from the main body of the drone and are sufficiently aspirated, such as a position near, but not directly under, a spinning propeller.

Aerosol modulation of atmospheric convection remains an important topic in ongoing research. A key challenge in evaluating aerosol impacts on cumulus convection is isolating their effects from environmental influences. This work investigates aerosol effects on maritime tropical convection using airborne observations from NASA's Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). Eight environmental parameters with known physical connections to cloud and storm formation were identified from dropsonde data, and 92 dropsondes were matched with corresponding CAMP2Ex flight "scenes." To constrain environmental conditions, scenes were binned based on their association with "low," "medium," or "high" values for each dropsonde-derived parameter. In each scene and environmental bin, eight radar- and radiometer-based parameters with physical implications for convective intensity and/or prevalence were correlated with lidar-derived aerosol concentrations to examine trends in convective characteristics under different aerosol conditions. Threshold values used to stratify the environments were varied across four sensitivity tests to examine how the convective-aerosol correlations within each environmental bin responded. The results were generally inconclusive, with relatively weak correlations observed with limited statistical significance in many cases. Some interesting and potentially impactful comparisons identified in the convective-aerosol analyses support the idea of warm-phase convective invigoration trends and suggest that higher aerosol concentrations were correlated with stronger and/or more-prevalent convection in some cases, while other cases saw a "Goldilocks" zone of medium aerosol concentration favoring enhanced convection. Our results also stress the importance of considering environmental conditions when evaluating aerosol impacts.

There are many unknowns surrounding why convective storms occur exactly when and where they do, including environmental impacts on storm morphology and processes. One of primary science objectives of NASA's upcoming INvestigation of Convective UpdraftS (INCUS) satellite mission is to quantify relationships between a storm's environment and its convective mass flux. To do this, we seek to distill the somewhat nebulous concept of a “convective environment” into a small number of scalar variables. In this study, as a first step towards those goals, we leverage 25 years of spaceborne radar observations from TRMM and GPM to evaluate how the depth and width of precipitating convective storms are related to large-scale environmental variables obtained from ERA5 reanalysis. Using random forests, we identify eight variables that are useful for distinguishing between global convective storm modes. We then show that principal component analysis can collapse most of the information in these variables into just two dimensions. The top two principal components effectively separate the environments of the deepest convective features from the environments of other convective features (Fig. 1).

Abstract. Multirotor drones (also known as small Uncrewed Aerial Systems [sUAS] or small Uncrewed Aerial Vehicles [sUAV]) are being increasingly used in atmospheric research to make measurements of the lower atmosphere, and their use is poised to increase in the future. New opportunities are now emerging for drone atmospheric sensing around smaller instrument footprints and lower sensor weights, such as ride-along applications and drone swarms, which necessitate characterizing the performance of unshielded sensors mounted to drones. In this work, we characterize the accuracy of thermodynamic measurements, specifically temperature and water vapor mixing ratio, based on the sensor position onboard multirotor drones. To assess the influence of the drone mechanics on the measurements, ninety-eight drone flights with eight distinct thermodynamic sensor positions were performed next to an instrumented flux tower and a tethersonde carrying identical sensors, where the tower and tethersonde measurements are assumed as truth. The flights were at least nine minutes in length, and nine of the flights were conducted at night. At the best position, absolute daytime temperature errors were between -0.83 K and +0.61 K at the 95 % confidence interval, while nighttime temperature errors were smaller, ranging from -0.28 K and +0.48 K. Water vapor mixing ratio errors are within -0.22 g kg-1 and +0.66 g kg-1. We conclude that measurements in field campaigns are more accurate when sensors are placed away from the main body of the drone and are sufficiently aspirated, such as a position near, but not directly under, a spinning propeller.

This study evaluates a popular density current propagation speed equation using a large, novel set of radiosonde and dropsonde observations. Data from pairs of sondes launched inside and outside of cold pools along with the theoretical density current propagation speed equation are used to calculate sonde-based propagation speeds. Radar/satellite-based propagation speeds, assumed to be the truth, are calculated by manually tracking the propagation of cold pools and correcting for advection due to the background wind. Several results arise from the comparisons of the theoretical sonde-based speeds with the radar/satellite-based speeds. First, sonde-based and radar-based propagation speeds are strongly correlated for US High Plains cold pools, suggesting the density current propagation speed equation is appropriate for use in midlatitude continental environments. Second, cold pool Froude numbers found in this study are in agreement with previous studies. Third, sonde-based propagation speeds are insensitive to how cold pool depth is defined, since the preponderance of negative buoyancy is near the surface in cold pools. Fourth, assuming an infinite channel depth and assuming an incompressible atmosphere when deriving the density current propagation speed equation can increase sonde-based propagation speeds by up to 20% and 11%, respectively. Finally, sonde-based propagation speeds can vary by ~300% based on where and when the sondes were launched, suggesting sub-mesoscale variability could be a major influence on cold pool propagation.

© 2024 American Meteorological Society. This published article is licensed under the terms of the default AMS reuse license. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Corresponding author: Sean W. Freeman, sean.freeman@uah.edu *These authors contributed equally.

We have quantified the impacts of varying thermodynamic environments on tropical congestus and cumulonimbus clouds (CCCs) within maritime tropical regions. To elucidate this relationship, we employed the Regional Atmospheric Modeling System (RAMS) to conduct high-resolution (1 km) simulations of convection over the Philippine Archipelago for a month-long period in 2019. We subsequently performed a cloud-object-based analysis, identifying and tracking hundreds of thousands of individual CCCs using the Tracking and Object-Based Analysis of Clouds ( tobac ) tracking library. Using this object-oriented dataset of tracked cells, we examined differences in individual storm strength, organization, and morphology due to the storm's initial environment. We found that storm strength, defined here as maximum midlevel updraft velocity, was controlled primarily by convective available potential energy (CAPE) and precipitable water (PW); high CAPE (>2500 J kg21) and high (approximately 63 mm) PW were both required for midlevel CCC updraft velocities to reach at least 10 ms21. Of the CCCs with the most vigorous updrafts, 80.9% were also in the upper tercile of precipitation rates, with the strongest precipitation rates requiring even higher PW. Further, we found that vertical wind shear was the primary differentiator between organized and isolated convective storms. Within the set of organized storms, linearly oriented CCC systems have significantly weaker vertical wind shear than nonlinear CCCs in low- (0-1, 0-3 km) and midlevels (0-5, 2-7 km). Overall, these results provide new insights into the environmental conditions determining the CCC properties in maritime tropical regions.

There is a continuously increasing need for reliable feature detection and tracking tools based on objective analysis principles for use with meteorological data. Many tools have been developed over the previous 2 decades that attempt to address this need but most have limitations on the type of data they can be used with, feature computational and/or memory expenses that make them unwieldy with larger datasets, or require some form of data reduction prior to use that limits the tool's utility. The Tracking and Object-Based Analysis of Clouds (tobac) Python package is a modular, open-source tool that improves on the overall generality and utility of past tools. A number of scientific improvements (three spatial dimensions, splits and mergers of features, an internal spectral filtering tool) and procedural enhancements (increased computational efficiency, internal regridding of data, and treatments for periodic boundary conditions) have been included in tobac as a part of the tobac v1.5 update. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field to date and expand its potential use in other fields. Future plans for tobac v2 are also discussed.

&lt;p&gt;Moisture convergence, latent heat, upper-level divergence all contribute to the genesis and growth of convective updrafts. In order to characterize the morphology of this evolution, and identify its constituent modes, we analyzed a large data set of synthetic updrafts simulated using a convection-resolving differential-equation solver run at high spatial and temporal resolutions (respectively 100 meters and 10 seconds). The analysis started by fitting each simulated updraft with a 6-parameter analytic representation, so that the joint statistics of the 6 parameters and of their evolution in time can be quantified. The first result is that an effective 6-parameter representation does exist and approximates the vertical profiles with a residual relative error whose r.m.s. value is smaller than 10% for 59% of all cases, and smaller than 20% for 89% of all cases. The r.m.s value of the absolute error is smaller than 0.4 m/s for 97% of all cases. Having established the suitability of this approximation, the variability of the 6 parameters for the 2-minute average Wa of a profile W was quantified, as was the variability of the evolution of W &amp;#8211; Wa over a two-minute interval. The analysis reveals that 4 scalars suffice to capture the bulk of the variability of the evolution of convective updrafts. The modes (spanning the range of values of these 4 scalars) turn out to be related to the maximum amplitudes of w and to the heights at which they are achieved. This description paves the way toward the characterization of the environmental determinants of updraft evolution and, in turn, the determination of the effects of updraft characteristics on upper-level air density, divergence and the resulting anvil clouds.&lt;/p&gt;

The NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) employed the NASA P-3, Stratton Park Engineering Company (SPEC) Learjet 35, and a host of satellites and surface sensors to characterize the coupling of aerosol processes, cloud physics, and atmospheric radiation within the Maritime Continent's complex southwest monsoonal environment. Conducted in the late summer of 2019 from Luzon, Philippines, in conjunction with the Office of Naval Research Propagation of Intraseasonal Tropical Oscillations (PISTON) experiment with its R/V Sally Ride stationed in the northwestern tropical Pacific, CAMP2Ex documented diverse biomass burning, industrial and natural aerosol populations, and their interactions with small to congestus convection. The 2019 season exhibited El Nino conditions and associated drought, high biomass burning emissions, and an early monsoon transition allowing for observation of pristine to massively polluted environments as they advected through intricate diurnal mesoscale and radiative environments into the monsoonal trough. CAMP2Ex's preliminary results indicate 1) increasing aerosol loadings tend to invigorate congestus convection in height and increase liquid water paths; 2) lidar, polarimetry, and geostationary Advanced Himawari Imager remote sensing sensors have skill in quantifying diverse aerosol and cloud properties and their interaction; and 3) high-resolution remote sensing technologies are able to greatly improve our ability to evaluate the radiation budget in complex cloud systems. Through the development of innovative informatics technologies, CAMP2Ex provides a benchmark dataset of an environment of extremes for the study of aerosol, cloud, and radiation processes as well as a crucible for the design of future observing systems.

&lt;p&gt;Understanding how convective storms respond to changes in their environment on a local scale is critical to begin to elucidate how Earth&amp;#8217;s changing climate will affect storms globally. There is now a vast amount of storm-scale observational data, including from geostationary and low-earth orbiting satellites and ground-based observing systems. However, employing these datasets to build comprehensive databases of convective storms and the local environments that form them requires new analysis methodologies. Here, in preparation for the NASA INCUS satellite mission, we have used the &lt;em&gt;tobac&lt;/em&gt; tracking package to identify, track and analyze storms and their environments with these big datasets. Using &lt;em&gt;tobac &lt;/em&gt;to track storms with geostationary satellite and ground-based radar data, we have built a comprehensive, months-long database of convective storms over their entire lifetime. For each individual convective storm, the database contains their formation environments (including convective available potential energy, wind shear, etc.), evolution over time, and, where applicable, additional data, such as those from low earth orbiting satellites. In this presentation, we will employ this vast database of clouds and storms to quantify the relationship, on a storm scale, between thermodynamic and dynamic environments and storm properties, including lifetime, growth rate, and ice and liquid water paths.&amp;#160;&lt;/p&gt;

&lt;p&gt;The convective mass flux within tropical convection influences the large-scale circulation, drives cloud radiative forcing, has integral links to the production of fresh water, and impacts extreme weather. CMF forms the focus of the recently selected Investigation of Convective Updrafts (INCUS) mission to be launched in 2026. This NASA mission is comprised of 3 spacecraft, all of which will carry a Ka-band cloud radar. One spacecraft will also carry a passive microwave radiometer. The 3 smallsats are to be separated by time intervals of 30, 90 and 120 seconds, thus allowing for the rapid and systematic sampling of the same storm with all three spacecraft. These time intervals (delta-ts) also facilitate the investigation of the magnitude and evolution of CMF, which will be examined as a function of storm type, storm lifecycle and environmental properties. INCUS will therefore provide the first global systematic investigation into CMF and its evolution within deep tropical convection.&lt;/p&gt; &lt;p&gt;A wide range of research tasks have been conducted in preparation for the INCUS mission and the development of the INCUS algorithms including: (1) running and analyzing extensive suites of large-domain, high-resolution model simulations; (2) examining ground-based Doppler radar observations obtained using adaptive scanning techniques during several recent field campaigns; and (3) evaluating anvil characteristics using passive microwave radiometer and geoIR data. This talk will focus on three specific highlights arising from these modeling and observational analyses. First, we will examine the temporal scales of updraft variability. Second, we will analyze the relationship between ice water path cores and convective updrafts. Finally, we will demonstrate proof of the INCUS delta-t concept linking changes in reflectivity to CMF through the use of ground-based radar analyses.&lt;/p&gt;

This study investigates how aerosol-induced changes tocloud properties subsequently influence the overall aerosol budget throughchanges to detrainment and rainout. We simulated an idealized field ofshallow maritime tropical clouds using the Regional Atmospheric ModelingSystem (RAMS) and varied the aerosol loading and type between 16simulations. The full aerosol budget was tracked over the course of the48 h simulation, showing that increasing the aerosol loading leads to anincrease in aerosol regeneration and detrainment aloft at the expense ofaerosol removal via rainout. Under increased aerosol loadings, clouddroplets are smaller and more likely to evaporate before they formprecipitation-sized hydrometeors. As a result, the aerosol particlescontained inside these droplets are released into the environment ratherthan being removed to the surface via rainout. However, the few raindropswhich do happen to form under increased aerosol loadings tend to be larger,since the cloud water available for collection is divided among fewerraindrops, and thus raindrops experience less evaporation. Thus, in contrastto previous work, we find that increases in aerosol loading lead to decreases inaerosol rainout efficiency, even without a decrease in the overallprecipitation efficiency. We further used tobac, a package for tracking andidentifying cloud objects, to identify shifts in the overall cloudpopulation as a function of aerosol loading and type, and we found contrastingaerosol effects in shallow cumulus and congestus clouds. Shallow cumulusclouds are more sensitive to the increase in cloud edge and/or top evaporation withincreased aerosol loading and thereby tend to rain less and remove feweraerosols via rainout. On the other hand, larger congestus clouds are moreprotected from evaporation and are thereby able to benefit from warm-phaseinvigoration. This leads to an increase in rain rates but not in domain-wideaerosol rainout, as the domain total rainfall becomes concentrated over asmaller horizontal area. Trends as a function of aerosol loading wereremarkably consistent between the different aerosol types tested. Theseresults represent a pathway by which a polluted environment not only hashigher aerosol loadings than a pristine one but is also less able toregulate those loadings by removal processes, instead transporting aerosolsto the free troposphere where they remain available for reactivation andfurther aerosol-cloud interactions.

T he interactions of updrafts and cold pools can play a pivotal role in determining convective storm characteristics.Convective updrafts are driven by latent heating, buoyancy, and vertical pressure gradients, and their velocities range from 5-10 m s -1 in tropical maritime convection to 50-70 m s -1 in midlatitude supercells.Cold pools, on the other hand, are formed through latent cooling due to evaporation and/or melting and are a surface manifestation of storm downdrafts.They range in depth from 100-200 m to nearly 5 km, and in horizontal extent from a few kilometers C 3 LOUD-Ex Raising the Curtain on Convection

A trimodal convective cloud distribution is commonly observed within the tropics due to the tropical-mean thermodynamic environment. The goal of this research has been to examine the integrated impacts of thermodynamic and aerosol properties on both the convective environment and the properties of the cloud modes themselves. This has been achieved by using LES experiments in which various thermodynamic and aerosol environments were independently and simultaneously perturbed. The key conclusions from this study are 1) large amounts of aerosol loading and low-level static stability suppress the bulk environment and the intensity and coverage of convective clouds; 2) cloud and environmental responses to aerosol loading tend to be stronger than those from static stability; 3) the effects of aerosol and stability perturbations modulate each other substantially; 4) the deepest convection and highest dynamical intensity occur at moderate aerosol loading, rather than at low or high loading; and 5) most of the strongest feedbacks due to aerosol and stability perturbations are seen in the boundary layer, though some are stronger above the freezing level. These results underscore the importance of considering the thermodynamic environment's impact on aerosol-induced convective invigoration while highlighting the dominance of aerosol impacts on the trimodal distribution and revealing synergies between thermodynamics and aerosols.

The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C3LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O(100) m through to O(1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.