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NASA NTRS2022

Limitations of Separate Cloud and Rain Categories in Parameterizing Collision-Coalescence for Bulk Microphysics Schemes

Warm rain collision-coalescence has been persistently difficult to parameterize in bulk microphysics schemes. We use a flexible bulk microphysics scheme with bin scheme process parameterizations, called AMP, to investigate reasons for the difficulty. AMP is configured in a variety of ways to mimic bulk schemes and is compared to simulations with the bin scheme upon which AMP is built. We find that an important limitation in traditional bulk schemes is the use of separate cloud and rain categories. When the drop size distribution is instead represented by a continuous distribution, the simulation of cloud-to-rain conversion is substantially improved. We also find large sensitivity to the threshold size to distinguish cloud and rain in traditional schemes; substantial improvement is found by decreasing the threshold from 40 to 25 μm. Neither the use of an assumed functional form for the size distribution nor the choice of predicted distribution moments has a large impact on the ability of AMP to simulate rain production. When predicting four total moments of the liquid drop size distribution, either with a traditional two-category, two-moment scheme with a reduced size threshold, or a four-moment single-category scheme, errors in the evolution of mass and the cloud size distribution are similar, but the single-category scheme has a substantially better representation of the rain size distribution. Optimal moment combinations for the single-category approach are investigated and appear to be linked more to the information content they provide for constraining the size distributions than to their correlation with collision-coalescence rates.

autoconversion↗

DOE OSTI2025

Long-term measurements of ice nucleating particles at Atmospheric Radiation Measurement (ARM) sites worldwide

Ice nucleating particles (INPs) play a critical role in cloud microphysics and precipitation formation, yet long-term, spatially extensive observational datasets remain limited. Here, we present one of the most comprehensive publicly available datasets of immersion-mode INP concentrations using a single analytical method, generated through the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility. INP filter samples have been collected across a broad range of environments – including agricultural plains, Arctic coastlines, high-elevation mountain sites, marine regions, and urban areas – via fixed observatories, mobile facility deployments, and vertically-resolved tethered balloon system operations. We describe the standardized processing and quality assurance pipeline, from filter collection and processing using the Ice Nucleation Spectrometer to final data products archived on the ARM Data Discovery portal. The dataset includes both total INP concentrations and selectively treated samples, allowing for classification of biological, organic, and inorganic INP types. It features a continuous 5-year record of INP measurements from a central U.S. site, with data collection still ongoing. Seasonal and site-specific differences in INP concentrations are illustrated through intercomparisons at −10 and −20 °C, revealing distinct regional sources and atmospheric drivers. We also outline mechanisms for researchers to access existing data, request additional sample analyses, and propose future field campaigns involving ARM INP measurements. This dataset supports a wide range of scientific applications, from observational and mechanistic studies to model development, and provides critical constraints on aerosol-cloud interactions across diverse atmospheric regimes (Creamean et al., 2024, 2020b; https://doi.org/10.5439/1770816).

Creamean, Jessie M. [Colorado State Univ., Fort Co↗

NASA NTRS1990

Influence of anthropogenic CCN on stratus microphysics

Analysis of the airborne measurements of CCN from the FIRE marine stratocumulus project of 1987 shows that continental aerosol was pervasive in air immediately above widespread stratus decks more than 500 km from the coast of California. Indications are that a large portion of the CCN component of the continental aerosol is anthropogenic. An important issue concerning continental CCN production is the question of the ratio of manmade CCN to natural particle production processes. The measurements certainly indicate that southern California air pollution or at the least continental aerosol is manifested in the cloud and above cloud aerosol.

Hudson, James G.↗

NASA NTRS2011

Dynamical States of Low Temperature Cirrus

Low ice crystal concentration and sustained in-cloud supersaturation, commonly found in cloud observations at low temperature, challenge our understanding of cirrus formation. Heterogeneous freezing from effloresced ammonium sulfate, glassy aerosol, dust and black carbon are proposed to cause these phenomena; this requires low updrafts for cirrus characteristics to agree with observations and is at odds with the gravity wave spectrum in the upper troposphere. Background temperature fluctuations however can establish a dynamical equilibrium between ice production and sedimentation loss (as opposed to ice crystal formation during the first stages of cloud evolution and subsequent slow cloud decay) that explains low temperature cirrus properties. This newly-discovered state is favored at low temperatures and does not require heterogeneous nucleation to occur (the presence of ice nuclei can however facilitate its onset). Our understanding of cirrus clouds and their role in anthropogenic climate change is reshaped, as the type of dynamical forcing will set these clouds in one of two preferred microphysical regimes with very different susceptibility to aerosol.

Barahona, D.↗

NASA NTRSDate not supplied

Cubespark: A New Satellite-Based 3d Lightning Observing Concept

Legacy and current space-based optical lightning detectors are insensitive to small and dim pulses that make up much of the lightning activity produced by severe storms. Moreover, lightning flashes produced at low altitudes within optically thick clouds are severely under-detected by current optical detectors. Lastly, there is currently no capability to characterize the 3D structure of lightning both day and night at the global scale, yet this information is critical for identifying lightning produced in updraft regions, including lightning occurring in overshooting tops, which is a distinctive signature of severe weather. Global 3D lightning information is also critical for understanding the vertical distribution of NOx production and identifying anomalously electrified storms. Furthermore, the vertical distribution of lightning has implications for how microphysical (e.g., ice-based) and thermodynamical (e.g., latent heat release) processes vary regionally, as well as seasonally – e.g., winter lightning typically occurs at lower altitudes than summer lightning and is often associated with tall, man-made structures. Finally, global-scale 3D lightning observations would directly provide flash type (i.e., CG or IC) information that is very useful in all of the studies mentioned in this paragraph and is fundamental in identifying/documenting deleterious CG-caused impacts (e.g., wildfires, power-outages, crop and property damage, and associated insurance claims). A new, satellite mission concept called CubeSpark is being designed to address these shortcomings and fill this measurement gap by providing novel 3D observations of total lightning activity. CubeSpark will utilize a constellation of low-Earth orbiting small satellites that make radio frequency (RF) and bi-spectral optical measurements of lightning. Two options for combining these measurements to retrieve the 3D location of lightning are considered with corresponding measurement simulators built to understand the level of detail and viability of each approach. Although the level of detail varies for each combined measurement approach, results indicate that a 3D location accuracy of < 1-2 km in each dimension is feasible across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high-latitudes.

lightning↗

NASA NTRS1980

Water-ice and water-updraft relationships near -10 C within populations of Florida cumuli

Evidence is presented for a sequential development of cloud water, rainwater, graupel, and crystalline ice with the aging of the cloud. This evidence is based on in-cloud microphysical data set collected in Florida convective towers that were penetrated close to their tops near -10 C; the very rapid onset of graupel that appears on repeat penetrations of some towers is of particular interest. A separate data set shows a large scatter in the relationship between the maximum value of cloud water and vertical velocity which indicates that measurements of cloud water can be misleading as an indication of growth activity. The sequential pass data showing the evolution of ice and water are consistent with a rime-splintering, secondary ice production hypothesis.

Sax, R. I.↗

NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering significant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

cloud↗

NASA NTRSDate not supplied

Reconstructing Subgrid Cloud Variability Guided by CloudSat/CALIPSO Observations

Predicting realistic cloud subgrid variability remains a challenge for Global Climate Models (GCMs) even though it can play an important role for proper representation of processes pertaining to cloud microphysics, precipitation, and radiation, but also for comparisons with satellite observations which are of much higher resolution than model grids. The diagnostic approach of subgrid cloud variability is commonly handled by subcolumn cloud generators. For a specific GCM, one ideally wants the subgrid variability used for comparisons with satellite observations to be created by the same generator and with the same rules as the one used for model integration. With this in mind, we have embarked in an effort to test and improve cloud subcolumn generators appropriate for GCMs. For this purpose, we use cloud (hydrometeor) products from active observations by the CloudSat radar (CPR) and the CALIPSO lidar (CALIOP). Cloud products from active sensors while suffering signi􀂦cant sampling and coverage drawbacks have the advantage of resolving both horizontal and vertical variability. The main question is: given a profile of cloud condensate mean and variance, can we create a subgrid cloud field that is statistically similar to the observed subgrid cloud field? By “statistically”, we suggest that we do not aspire to reproduce “well” each individual subgrid cloud field of a GCM-scale region, but that our generator performs well for a large ensemble of cases. We simulate radar, passive imager, and radiation flux fields from the observed 2D cloud fields and create one-point statistics; we use the profiles of cloud condensate mean and variance as input to the generator to create subgrid cloud fields; we compare the statistics; we adjust the rules of the generator to create the best possible agreement between the radar, imager and radiation field statistics. In this process, the active observations have actually a dual role: they provide the actual subgrid cloud field which can be reduced to a profile of mean and variance used by the subcolumn generator, but they also provide the rules needed by the generator, such as measures (e.g, decorrelation length) of the vertical overlap of cloud fraction and of the condensate horizontal variability. This presentation will show our progress using Cloudsat and CALIPSO products in this dual fashion.

clouds↗

NASA NTRS1983

Microphysical properties of the Shuttle exhaust cloud

A data base describing the properties of the exhaust cloud produced by the launch of the STS has been developed based on data from a series of ground and aircraft based measurements made during the launches of STS 2, 3, and 4. Aircraft observations were performed during the STS-3 launch with a NOAA WP-3D Orion hurricane research aircraft which contained instrumentation for cloud condensation nucleus and ice nucleus counting, Aitken particle counting, and pH determination. Ground observations were conducted at 50 different sites, as well as in the direct exhaust from the solid rocket booster flame trench at all three launches. The data is analyzed in order to determine any possible adverse impacts of the exhaust products on human health and/or the environment. Analyses of the exhaust cloud measurements indicate that in the case of the ground cloud where plenty of large water drops are present and considerable scavenging and fallout of aerosol takes place, possible adverse impacts of the remaining aerosols (CCN and IN) on natural precipitation processes which may occur in the launch area hours after the launch are remote. However, it is determined that under certain atmospheric conditions there could be short term adverse effects on visibility.

Keller, V. W.↗

DOE OSTI2025

Marine and continental stratocumulus cloud microphysical properties obtained from routine ARM Cimel sunphotometer observations

This study investigates marine and continental stratocumulus (Sc) cloud properties obtained from an automated implementation of a multispectral photometer retrieval. Photometer methods simultaneously retrieve cloud optical depth (τ) and cloud droplet effective radius (r e ), with estimates for liquid water path (LWP) calculated on the availability of those quantities. These applied methods evaluate retrieved cloud properties for Sc identified during a recent 6 year period over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program sites in Oklahoma, USA (SGP) and in the Azores, Portugal (ENA). Modest agreement in key quantity retrievals is found between the routine photometer products and multisensor collocated profiling references. Cumulative breakdowns contingent on cloud thickness indicate increases in all retrieved quantities in thicker clouds, with larger discrepancies in the relative performance between the retrievals collected in the presence of drizzle. Under continental cloud conditions, the clouds of a similar thickness and r e to those sampled under marine conditions report a factor of 1.5 larger τ and LWP. An r 2 ≅0.65 is found between photometer τ retrievals and shadowband radiometer measurements, with photometer retrievals reporting a high (relative) bias. The τ intercomparisons indicate that variability between retrievals is a factor of three larger than errors reported from individual retrieval input perturbation tests. Photometer r e retrievals suggest a low r 2 (< 0.1) having a standard deviation ≅ 3 µm when compared to ARM baseline multi-sensor radar/radiometer references (accounting for offsets in the cloud droplet number concentration assumptions of the latter). However, photometer LWP calculations remain relatively unbiased in non-drizzling conditions, with errors O (50 g m −2 ) and r 2 ≅0.5 to collocated radiometer and interferometer references. Additional sensitivity tests for island influences on marine Sc properties suggest that while island-influenced winds may promote larger cloud LWP or thickness, the influence could be within retrieval method uncertainty and/or collocated instrument variability.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2001

Ice Nucleation in Deep Convection

The processes controlling production of ice crystals in deep, rapidly ascending convective columns are poorly understood due to the difficulties involved with either modeling or in situ sampling of these violent clouds. A large number of ice crystals are no doubt generated when droplets freeze at about -40 C. However, at higher levels, these crystals are likely depleted due to precipitation and detrainment. As the ice surface area decreases, the relative humidity can increase well above ice saturation, resulting in bursts of ice nucleation. We will present simulations of these processes using a large-eddy simulation model with detailed microphysics. Size bins are included for aerosols, liquid droplets, ice crystals, and mixed-phase (ice/liquid) hydrometers. Microphysical processes simulated include droplet activation, freezing, melting, homogeneous freezing of sulfate aerosols, and heterogeneous ice nucleation. We are focusing on the importance of ice nucleation events in the upper part of the cloud at temperatures below -40 C. We will show that the ultimate evolution of the cloud in this region (and the anvil produced by the convection) is sensitive to these ice nucleation events, and hence to the composition of upper tropospheric aerosols that get entrained into the convective column.

Jensen, Eric↗

NASA NTRS2020

The GPM Ground Validation Program

We present a detailed overview of the structure and activities associated with the NASA-led ground-validation component of the NASA-JAXA Global Precipitation Measurement (GPM) mission. The overarching philosophy and approaches for NASA's GV program are presented with primary focus placed on aspects of direct validation and a summary of physical validation campaigns and results. We describe a spectrum of key instruments, methods, field campaigns and data products developed and used by NASA's GV team to verify GPM level-2 precipitation products in rain and snow. We describe the tools and analysis framework used to confirm that NASA's Level-I science requirements for GPM are met by the GPM Core Observatory. Examples of routine validation activities related to verification of Integrated MultisatellitE Retrievals for GPM (IMERG) products for two different regions of the globe (Korea and the US) are provided, and a brief analysis related to IMERG performance in the extreme rainfall event associated with Hurricane Florence is discussed.

precipitation↗

NASA NTRS2008

Analysis of Proposed 2007-2008 Revisions to the Lightning Launch Commit Criteria for United States Space Launches

Ascending space vehicles are vulnerable to both natural and triggered lightning. Launches under the jurisdiction of the United States are generally subject to a set of rules called the Lightning Launch Commit Criteria (LLCC) (Krider etal., 1999; Krider etal., 2006). The LLCC protect both the vehicle and the public by assuring that the launch does not take place in conditions posing a significant risk of a lightning strike to the ascending vehicle. Such a strike could destroy the vehicle and its payload, thus causing failure of the mission while releasing both toxic materials and debris. To assure safety, the LLCC are conservative and sometimes they may seriously limit the ability of the launch operator to fly as scheduled even when conditions are benign. In order to safely reduce the number of launch scrubs and delays attributable to the LLCC, the Airborne Field Mill (ABFM II) program was undertaken in 2000 - 2001. The effort was directed to collecting detailed high-quality data on the electrical, microphysical, radar and meteorological properties of thunderstorm-associated clouds. Details may be found in Dye et al., 2007. The expectation was that this additional knowledge would provide a better physical basis for the LLCC and allow them to be revised to be less restrictive while remaining at least as safe. That expectation was fulfilled, leading to significant revisions to the LLCC in 2003 and 2005. The 2005 revisions included the application of a new radar-derived quantity called the Volume Averaged Height Integrated Radar Reflectivity (VAHIRR) in the rules governing flight through anvil clouds. VAHIRR is the product of the volume averaged radar reflectivity times the radardetermined cloud thickness. The reflectivity average extends horizontally 5 km west, east, south and north of a point along the flight track and vertically from the 0 C isotherm to the top of the radar cloud. This region is defined as the "Specified Volume". See Dye et al., 2006 and Merceret et al., 2006 for a more thorough description of VAHIRR. The units are dBZ km (not dBZ per kilometer) and the threshold is 10 dBZ km. It is safe to fly through an anvil cloud for which VAHIRR is below this threshold everywhere along the flight track as long as (1) the entire cloud within 5 nmi. (9.26 km) of the flight track is colder than 0 C, (2) the points at which VAHIRR must be evaluated are at least 20 km from any active convective cores and recent lightning, and (3) the radar return is not being attenuated within the Specified Volume around those points.

Dye, James E.↗

NASA NTRS2014

Sport Transition of JPSS VIIRS Imagery for Night-time Applications

The NASA/Short‐term Prediction, Research, and Transition (SPoRT) Program and NOAA/Cooperative Institute for Research in the Atmosphere (CIRA) work within the NOAA/Joint Polar Satellite System (JPSS) Proving Ground to demonstrate the unique capabilities of the VIIRS instrument. Very similar to MODIS, the VIIRS instrument provides many high‐resolution visible and infrared channels in a broad spectrum. In addition, VIIRS is equipped with a low‐light sensor that is able to detect light emissions from the land and atmosphere as well as reflected sunlight by the lunar surface. This band is referred to as the Day‐Night Band due to the sunlight being used at night to see cloud and topographic features just as one would typically see in day‐time visible imagery. NWS forecast offices that collaborate with SPoRT and CIRA have utilized MODIS imagery in operations, but have longed for more frequent passes of polar‐orbiting data. The VIIRS instrument enhances SPoRT collaborations with WFOs by providing another day and night‐time pass, and at times two additional passes due to its large swath width. This means that multi‐spectral, RGB imagery composites are more readily available to prepare users for their use in GOES‐R era and high‐resolution imagery for use in high‐latitudes is more frequently able to supplement standard GOES imagery within the SPoRT Hybrid GEO‐LEO product. The transition of VIIRS also introduces the new Day‐Night Band capability to forecast operations. An Intensive Evaluation Period (IEP) was conducted in Summer 2013 with a group of "Front Range" NWS offices related to VIIRS night‐time imagery. VIIRS single‐channel imagery is able to better analyze the specific location of fire hotspots and other land features, as well as provide a more true measurement of various cloud and aerosol properties than geostationary measurements, especially at night. Viewed within the SPoRT Hybrid imagery, the VIIRS data allows forecasters to better interpret the more frequent, but coarse GOES Imagery. Night‐time Microphysics and Dust RGB Imagery provides cloud analysis of cloud height, thickness, and composition in order for operational applications such as separating fog from low clouds, dust plume detection, and determining precipitating clouds in radar-void/ blocked regions. The Day‐Night Band has a particular benefit to seeing light from cities, fires, or other emissions as well as the reflection of moonlight off of clouds and smoke plumes, given the right lunar phase and angle. Examples from the VIIRS transition and IEP will be presented.

Fuell, Kevin↗

DOE OSTI2025

MOSAiC studies of long-lasting mixed-phase cloud events and analysis of the liquid-phase properties of Arctic clouds

Vertically resolved observations of the temporal evolution of mixed-phase clouds (MPCs) were performed over the central Arctic during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, which lasted from October 2019 to September 2020. The research icebreaker Polarstern , drifting with the pack ice for more than 7 months, mostly at latitudes > 85° N, served as a platform for state-of-the-art remote sensing of aerosols and clouds. The use of the recently introduced dual field-of-view (FOV) polarization lidar technique in combination with the well-established lidar-radar retrieval technique provided, for the first time, a robust instrumental basis to monitor the evolution of the liquid and the ice phase of MPCs and the interplay between the two phases. Two long-lasting Arctic MPC events observed close to the North Pole in mid-winter (December 2019) and late summer (September 2020) are discussed to provide new insight into Arctic MPC evolution processes. In the second part of the article, cloud statistics, covering all seasons of a year, are presented. The focus is on the optical and microphysical properties of the liquid phase. These results are solely derived from the dual-FOV lidar observations. The key findings of the study can be summarized as follows: persistent activation of aerosol particles to form water droplets is of great importance for the longevity of MPCs. The observations confirm that ice formation occurs predominantly via immersion freezing. The field studies suggest that the free tropospheric reservoirs of cloud condensation nuclei (CCN) and of ice-nucleating particles (INPs) were always well filled, i.e., the clouds did not exhaust their supply of activatable and activated particles. The observation of long-lasting MPC events, low ice production rates, and a sufficiently large INP reservoir leads to the recommendation to use a time-dependent immersion freezing parameterization in MPC modeling efforts.

Jimenez, Cristofer [Leibniz Inst. for Tropospheric↗

NASA NTRS2004

Warm Rain Processes Over the Tropical Oceans and Implications on Climate Change

In this talk, we will first show results from TRMM regarding the characteristics of warm rains over the tropical oceans, and the dependence of rate of warm rain production on sea surface temperature. Results lead to the hypothesis that warm rain production efficiency, i.e., autoconversion, may be increased in a warm climate. We use the GEOS-II GCM to test this hypothesis. Our modeling results show that in a climate with increased rate of autoconversion, the total rain amount is increased, with warm rain contributing to a larger portion of the increase. The abundant rainout of warm precipitation at middle to low levels causes a reduction of high cloud cover due to the depletion of water available for ice-phase rain production. As a result, more isolated, but more intense penetrative convection develops. Results also show that increased autoconversion reduces the convective adjustment time scale tends, implying a faster recycling of atmospheric water. Most interestingly, the increased low level heating associated with warm rain leads to more energetic Madden and Julian oscillations in the tropics, with well-defined eastward propagation. While reducing the autoconversion leads to an abundant mix of westward and eastward tropical disturbance on daily to weekly time scales. The causes of the sensitivity of the dynamical regimes to the microphysics parameterization in the GCM will be discussed.

Lau, William K. M.↗

NASA NTRSDate not supplied

Assessment of the Accuracy and Consistency of Cloud Property Retrievals from Passive Radiometers with Varying Spectral Information

Over the past few decades, space-based passive radiometers have been used to study the spatial distribution of clouds and some of their basic properties. Modern radiometers have significantly higher spatial resolution and collect more spectral information (i.e., have more spectral bands) than early instruments, and these advances have allowed researchers to characterize cloud physical and microphysical properties with greater detail. There is significant interest in utilizing as much of the existing satellite record as possible to study global and regional changes in cloud occurrence and distribution as well as the associated changes in reflected shortwave and outgoing longwave fluxes. Cloud property retrieval algorithms such as the NASA Satellite Cloud Optical and Radiative Property System (SatCORPS) have traditionally utilized as much spectral information as possible in order to maximize the accuracy of the retrievals. However, changes to the retrieval algorithm over time in order to take advantage of progressively more spectral information results in inconsistencies in cloud properties which in turn results in inconsistencies with products derived from these properties. It is not possible to implement modern state-of-the-art algorithms to earlier instruments which lack diverse spectral information, but many instruments since the early 2000s generally have approximately similar spectral bands in the visible (~0.65 microns), longwave infrared (~11 microns), and in many cases, the midwave infrared (~3.8 microns) and water vapor absorption (~6.7 microns), portions of the electromagnetic spectrum. Different versions of SatCORPS have been implemented with either the full set of spectral information collected by imagers such as GOES-16 and MODIS or with a reduced set of spectral bands in order to be more consistent with past imagers that lack such diverse spectral information. This study uses independent cloud property retrievals from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) to assess the accuracy of the retrievals (e.g., cloud fraction, thermodynamic phase, altitude) from the different retrieval methods and to demonstrate the advantages and disadvantages of using a reduced set of common spectral bands in order to achieve temporal and spatial consistency across different instruments.

Christopher R. Yost↗

NASA NTRSDate not supplied

Assessing the feasibility of a spaceborne 3D lightning observing concept

The distribution of electrical charge in thunderclouds results from thermodynamic, microphysical, and kinematic processes, which also modulate thunderstorm evolution. It is no surprise that the connection between lightning and these physical processes is so strong that the increase and vertical growth of lightning activity closely follows the vertical growth of the thundercloud, but unraveling these connections is not trivial and requires observations of the three-dimensional (3D) structure of electrical activity in a cloud. Ground-based 3D lightning mapping networks give excellent 3D flash-level detail but are limited to regional coverage. Satellite-based optical lightning mappers give excellent global coverage but are largely limited to 2D summaries of flash rate and radiant intensity, albeit new flash products and stereographic techniques are chipping away this limitation. New observing strategies are needed to expand and diversify the corpus of 3D lightning datasets and motivate studies that unravel connections lightning has with these key physical processes and the surrounding environment. This study examines the feasibility of using a distributed network of orbing satellites with VHF-based lightning detectors to obtain global maps of 3D lightning activity and assess efficacy of this approach for use in a new, small satellite mission concept called CubeSpark. CubeSpark combines new VHF and high-resolution, bispectral optical instruments on a constellation of low-Earth orbiting (LEO) satellites to globally map the 3D electrical structure of thunderstorms and study how it relates to thunderstorm evolution, extreme weather, nitrogen oxide production and distribution, upper atmospheric electrical phenomena, and how 3D flash observations can complement existing satellite-based lightning mappers and improve decision support tools. To locate lightning discharges, CubeSpark seeks to use the VHF time-of-arrival technique, similar to ground-based total lightning mapping networks. The vertical location accuracy of these satellite retrievals will be of poorer quality compared to a ground-based network, which has non-trivial implications for lightning flash reconstruction and lightning-based interpretations of deep convection. We adapt a Lightning Mapping Array (LMA) simulation framework to an orbiting network and use it to address feasibility of 3D lightning detection from space with particular attention to location accuracy of VHF detections of lightning in the vertical. These simulations inform a constellation design study that defines a realistic orbital configuration and depicts the global coverage for CubeSpark. Results indicate that a 3D location accuracy of <1-2 km for each dimension can be achieved across 300-500 km wide swaths, which suggests that CubeSpark can resolve the charge structure of thunderclouds from the tropics to the mid- and high- latitudes.

Lightning↗