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NASA NTRS2020

Radiative Heating from Biomass Burning Aerosol and its Impact on Cloud Structure in the Southeast Atlantic

Marine boundary layer clouds, including the transition from stratocumulus to cumulus, are poorly represented in numerical weather prediction and general circulation models. In many cases, the complex physical relationships between marine boundary cloud morphology and the environmental conditions in which the clouds exist are not well understood. Such uncertainties arise in the presence of biomass burning carbonaceous aerosol, as is the case over the southeast Atlantic Ocean. It is likely that the absorbing and heating properties of these aerosols influence the microphysical composition and macrophysical arrangement of marine stratocumulus and trade cumulus in this region; however, this has yet to be quantified. The deployment of the Atmospheric Radiation Measurement Mobile Facility #1 (AMF1) in support of LASIC (Layered Atlantic Smoke Interactions with Clouds) provided a unique opportunity to collect observations of cloud and aerosol properties during two consecutive biomass burning seasons during July through October of 2016 and 2017 over Ascension Island (7.96 S, 14.35 W). Thermodynamic profiles will be analyzed through the unique combination of sounding data from radiosonde launches and microwave profiling radiometers, giving observations of additional quantities important for cloud development such as CAPE and CIN at a fine temporal resolution. The thermodynamic profiles will be presented in conjunction with detailed observations of the cloud structure over the site from a K-band cloud radar, micropulse lidar, and laser ceilometer. The observed thermodynamic and cloud profiles will be used as input forcing, alongside aerosols from the Modern Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), for the Rapid Radiative Transfer Model (RRTM) to gain information regarding the radiative heating profiles. Idealized experiments using RRTM with and without aerosols will be used to quantify the impact of biomass burning carbonaceous aerosol plumes as they pass over the site. Due to documented discrepancies in the single scatter albedo (SSA) between models and observations, further sensitivity experiments will demonstrate the importance of the optical properties of biomass burning aerosol in accurately representing heating within the column. Finally, the heating rates will be put into context of the cloud structure over the site from the perspective of the mass flux closure from the University of Washington shallow convective scheme.

Collow, Allison↗
NASA NTRS2021

Extreme Lake-Effect Snow from a GPM Microwave Imager Perspective: Observational Analysis and Precipitation Retrieval Evaluation

This study focuses on the ability of the Global Precipitation Measurement (GPM) passive microwave sensors to detect and provide quantitative precipitation estimates (QPE) for extreme lake-effect snowfall events over the United States lower Great Lakes region. GPM Microwave Imager (GMI) high frequency channels can clearly detect intense shallow convective snowfall events. However, GMI Goddard PROfiling (GPROF) QPE retrievals produce inconsistent results when compared against the Multi-Radar/Multi-Sensor (MRMS) ground-based radar reference dataset. While GPROF retrievals adequately capture intense snowfall rates and spatial patterns of one event, GPROF systematically underestimates intense snowfall rates in another event. Furthermore, GPROF produces abundant light snowfall rates that do not conform with MRMS observations. Ad-hoc precipitation rate thresholds are suggested to partially mitigate GPROF’s overproduction of light snowfall rates. The sensitivity and retrieval efficiency of GPROF to key parameters (2-meter temperature, total precipitable water, and background surface type) used to constrain the GPROF a-priori retrieval database are investigated. Results demonstrate that typical lake-effect snow environmental and surface conditions, especially coastal surfaces, are underpopulated in the database and adversely affect GPROF retrievals. For the two presented case studies, using snow cover a-priori database in the locations of originally deemed as coastline improves retrieval. This study suggests that it is particularly important to have more accurate GPROF surface classifications and better representativeness of the a-priori databases to improve intense lake-effect snow detection and retrieval performance.

Lisa Milani↗
NASA NTRS2025

Describing Seasonal Mixtures of Cloud Regimes Via “Regimes of Regimes”

We propose a new type of cloud classification, relevant to monthly or longer time scales, but which inherently still encompasses cloud subgrid variability information at ~100 km scales. Our proposed classification partitions frequencies of occurrence over these scales of previously defined cloud regimes (CRs). We call the resulting distinct cloud entities regimes of regimes (RORs). While the CRs have been previously shown to successfully classify daily mesoscale subgrid variability via distributions of cloud fraction within distinct combinations of cloud top pressure and cloud optical thickness, the RORs essentially represent the prevalent seasonal mixtures of these CRs. RORs thus embody the seasonal cloudiness of a mesoscale region. We show that each ROR can still be associated with more traditional cloud classifications via composites of coincident active (lidar and cloud radar) cloud views. In a first application that gauges the potential utility of RORs, we pair them with CERES EBAF radiative fluxes to gain insight into recent trends of the cloud radiative effect. The ROR corresponding to an environment of shallow convection stands out in this analysis largely because of its declining population. Our study demonstrates the potential of RORs to categorize globally mesoscale cloudiness at monthly/seasonal scales and to serve as proxies of different atmospheric states at these scales.

Nayeong Cho↗
DOE OSTI2020

Sensitivity Study for Forecasting Variables of WRF-Solar Using a Tangent Linear Approach

Integrating solar generation in recent years has highlighted the need for improved accuracy in predicting solar power. Confidence in solar power forecasting can be achieved by designing an ensemble that provides reliable probabilistic information for solar radiation with reduced uncertainty and error. Ideally, ensemble members are created through the optimized perturbation of the initial conditions in numerical weather prediction (NWP) models. Tangent linear models are capable of efficiently investigating the sensitivity of solar radiation to model input parameters because they do not require individual perturbation of each variable. This sensitivity study using tangent linear models provide us the capability to identify the right variables to perturb in an ensemble prediction system. In this study, we developed tangent linear models for WRF-Solar modules that directly impact the computation of solar radiation and the simulation of cloud formation and dissipation including the Fast All-sky Model for Solar Applications (FARMS), the Noah land surface model (LSM), the Thompson microphysics, the Mello-Yamada-Nakanishi-Niino (MYNN) boundary layer parameterization, and the Deng scheme for a shallow-convection parameterization. A sensitivity analysis was conducted under various scenarios based on satellite observations and model simulations from the National Solar Radiation Data Base (NSRDB) and WRF-Solar, respectively. Critical forecasting variables that are highly sensitive to the forecasting of global horizontal irradiance (GHI), direct normal irradiance (DNI), cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes were determined using the relevant WRF-Solar module. This study will be used as a guidance on future research leading to high-quality probabilistic solar forecasting. In this presentation, we discuss the validation of tangent linear approach for WRF-Solar modules and illustrate how the sensitivity results are valuable in the improvement of probabilistic solar prediction.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2015

CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations

We have identified several errors in the calculations that were performed to create Fig. 3 of Del Genio et al. (2012). These errors affect the composite evolution of precipitation and column water vapor versus lag relative to the Madden-Julian oscillation (MJO) peak presented in that figure. The precipitation and column water vapor data for the April and November 2009 MJO events were composited incorrectly because the date of the MJO peak at a given longitude was assigned to the incorrect longitude band. In addition, the precipitation data for all MJO events were first accumulated daily and the daily accumulations averaged at each lag to create the composite, rather than the averaging of instantaneous values that was used for other composite figures in the paper. One poorly sampled day in the west Pacific therefore biases the composite precipitation in that region at several lags after the MJO peak. Finally, a 4-day running mean was mistakenly applied to the precipitation and column water vapor data rather than the intended 5-day running mean. The results of the corrections are that an anomalous west Pacific precipitation maximum510 days after the MJO peak is removed and the maximum in west Pacific precipitation one pentad before the MJO peak is now more evident; there is now a clear maximum in precipitation for the entire warm pool one pentad before the MJO peak; west Pacific column water vapor now varies more strongly as a function of lag relative to the peak; and precipitation, and to a lesser extent column water vapor, in general vary more smoothly with time. The corrections do not affect any other parts of the paper nor do they change the scientific conclusions we reached. The 4-day running mean error also affects Figs. 1 and 2 therein, with almost imperceptible impacts that do not affect any results or necessitate major changes to the text.

correction↗
DOE OSTI2022

Criticality in the Shallow-to-Deep Transition of Simulated Tropical Marine Convection

Idealized simulations of tropical, marine convection depict shallow, nonprecipitating cumuli located beneath the 0°C level transitioning into cumulonimbi that reach up to 12 km and higher. The timing of the transition was only weakly related to environmental stability, and 13 of the 15 simulations run with 5 different lapse-rate profiles had rain develop at nearly the same time after model start. The key quantity that apparently controlled deep convective formation was vertical acceleration inside cloudy updrafts between cloud base and the 0°C level. Below a critical value of updraft vertical acceleration, little rainfall occurred. Just as the domain-mean updraft acceleration reached the critical value, the first convection quickly grew to past 12 km altitude. Then, as acceleration increased above the critical value, rain rate averaged in the model domain increased quickly over about a 3-h-long period. The specific value of the critical updraft acceleration depended on how updrafts were defined and in what layer the acceleration was averaged; however, regardless of how criticality was defined, a robust relationship between domain-mean updraft vertical acceleration and rain rate occurred. Positive acceleration of updrafts below the 0°C level was present below 2.75 km and was largest in the 500 m above cloud base. However, the maximum difference between updraft and environmental temperatures occurred between 2 and 3 km. The domain-mean Archimedean buoyancy of updrafts relative to some reference state was a poor predictor for domain-mean rain rate. In conclusion, the exact value of the critical updraft acceleration likely depends on numerous other factors that were not investigated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Atmosphere–Ocean Coupled Energy Budgets of Tropical Convective Discharge–Recharge Cycles

An energy budget combining atmospheric moist static energy (MSE) and upper ocean heat content (OHC) is used to examine the processes impacting day-to-day convective variability in the tropical Indian and western Pacific Oceans. Feedbacks arising from atmospheric and oceanic transport processes, surface fluxes, and radiation drive the cyclical amplification and decay of convection around suppressed and enhanced convective equilibrium states, referred to as shallow and deep convective discharge–recharge (D–R) cycles, respectively. The shallow convective D–R cycle is characterized by alternating enhancements of shallow cumulus and stratocumulus, often in the presence of extensive cirrus clouds. The deep convective D–R cycle is characterized by sequential increases in shallow cumulus, congestus, narrow deep precipitation, wide deep precipitation, a mix of detached anvil and altostratus and altocumulus, and once again shallow cumulus cloud types. Transitions from the shallow to deep D–R cycle are favored by a positive “column process” feedback, while discharge of convective instability and OHC by mesoscale convective systems (MCSs) contributes to transitions from the deep to shallow D–R cycle. Variability in the processes impacting MSE is comparable in magnitude to, but considerably more balanced than, variability in the processes impacting OHC. Variations in the quantity of atmosphere–ocean coupled static energy (MSE + OHC) result primarily from atmospheric and oceanic transport processes, but are mainly realized as changes in OHC. MCSs are unique in their ability to rapidly discharge both lower-tropospheric convective instability and OHC.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term single-column model intercomparison of diurnal cycle of precipitation over midlatitude and tropical land

General Circulation Models (GCMs) have for decades exhibited difficulties in modelling the diurnal cycle of precipitation (DCP). This issue can be related to inappropriate representation of the processes controlling sub-diurnal phenomena like convection. In this study, 11 single-column versions of GCMs are used to investigate the interactions between convection and environmental conditions, processes that control nocturnal convections, and the transition from shallow to deep convection on a diurnal time-scale. Long-term simulations are performed over two continental land sites: the Southern Great Plains (SGP) in the USA for 12 summer months from 2004 to 2015 and the Manacapuru site at the central Amazon (MAO) in Brazil for two full years from 2014 to 2015. The analysis is done on two regimes: afternoon convective regime and nocturnal precipitation regime. Most models produce afternoon precipitation too early, likely due to the missing transition of shallow-to-deep convection in these models. At SGP, the unified convection schemes better simulate the onset time of precipitation. At MAO, models produce the heating peak in a much lower level compared with observation, indicating too shallow convection in the models. For nocturnal precipitation, models that produce most of nocturnal precipitation all allow convection to be triggered above the boundary layer. This indicates the importance of model capability to detect elevated convection for simulating nocturnal precipitation. Sensitivity studies indicate that (a) nudging environmental variables towards observations has a minor impact on DCP, (b) unified treatment of shallow and deep convection and the capability to capture mid-level convection can help models better capture DCP, and (c) the interactions of the atmosphere with other components in the climate system (e.g. land) are also important for DCP simulations in coupled models. Finally, these results provide long-term statistical insights on which physical processes are essential in climate models to simulate DCP.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Shallow-Water Model for Convective Self-Aggregation

Randomly distributed convective storms can self-aggregate in the absence of large-scale forcings. Here we present a 1D shallow-water model to study the convective self-aggregation. This model simulates the dynamics of the planetary boundary layer and represents convection as a triggered process. Once triggered, convection lasts for finite time and occupies finite length. Here we show that the model can successfully simulate self-aggregation, and that the results are robust to a wide range of parameter values. In the simulations, convection excites gravity waves. The gravity waves then form a standing wave pattern, separating the domain into convectively active and inactive regions. We analyze the available potential energy (APE) budget and show that convection generates APE, providing energy for self-aggregation. By performing dimensional analysis, we develop a scaling theory for the size of convective aggregation, which is set by the gravity wave speed, damping time scale, and number density of convective storms. This paper provides a simple modeling framework to further study convective self-aggregation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Satellite Tracking of Shallow Cumulus during CAMP2Ex: The Aerosol and Organization Connection

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Shallow clouds come in many forms, from scattered, short-lived cumulus to organized features that include cold pool boundaries and lines reaching O(100 km) scale lasting several hours. In this study, we explore how cloud morphology and environmental aerosol affect shallow cumulus lifecycle properties. Measuring such influences requires a broad, detailed view of these cloud fields as they grow and decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. We segment shallow cumulus on AHI 0.5-km visible reflectance during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. We collect the resulting cloud tracks by regions containing airborne sampling of the cloud environments and by two specific segmentation techniques: one optimized for small, disorganized cumulus and the other for larger, organized clouds using suitable thresholds for reflectance and blurring. We present an analysis of cloud lifecycle properties using our dual segmentation approach for various sampled environments of CAMP2Ex. A total of 7 research flights (RFs) exhibited ideal conditions for generating cloud-track ensembles under similar thermodynamic and kinematic profiles but with varying aerosol load. We consider lifetime, track-achieved metrics, and ensemble-fitted growth rates to evaluate the aerosol effect. Cloud elongation, a factor in cloud morphology, is also considered for any potential influence in observed shifts in growth rates. The results suggest that aerosol affects cloud lifecycles more significantly for clouds with larger areas and independent of the elongation factor.

Cloud Tracking↗
NASA NTRS2017

Realistic 3D Radiative Modeling of Turbulent Structure of Moderate-Mass Stars and Sun

Understanding the turbulent dynamics of the Sun and stars is a critical element for interpreting observed processes and phenomena on different scales and for predicting extreme events such as flares and super flares. High-­‐resolution observations of the Sun and high-­‐fidelity radiative MHD numerical simulations have substantially advanced our understanding of solar and stellar local dynamics and magnetism from the upper convection zone to the atmosphere and corona. However, global modeling of the Sun with such a high degree of realism is currently not affordable due to the extremely high computational cost of resolving the scales in the convection zone. The physics of the deep solar dynamics can be effectively addressed through modeling more massive solar-­‐type stars where the convection zone is shallower and the convective overturning time is much shorter than those on the Sun. We present recent 3D realistic simulation results of moderate-­‐mass stars and discuss links between solar and stellar dynamics, such as the multiscale structure of granulation, convective overshoot, and others. In particular, these simulations have provided better understanding of the dynamics of the tachocline (the overshoot layer at the bottom of the convection zone) and have explained long-­‐ standing results from helioseismology.

Realistic↗
DOE OSTI2026

Convective Biases in the US DOE Global Storm‐Resolving Model: Insights From Regionally Refined Simulations During the CACTI Campaign

Accurately simulating convective processes in complex terrain remains a critical challenge for global storm-resolving models (GSRMs). This study systematically evaluates moist convective biases in the Regionally Refined Mesh configuration of the U.S. Department of Energy Simple Cloud-Resolving E3SM Atmosphere Model (RRM-SCREAM) using comprehensive observations and large-eddy simulations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in the mountainous area of central Argentina. Comparisons of simulations with high-resolution observations and reanalysis data indicate that RRM-SCREAM effectively captures large-scale meteorological patterns, including regional atmospheric gradients and diurnal variability. However, RRM-SCREAM disproportionately produces smaller precipitation clusters referred to as “popcorn convection,” and exaggerated rainfall intensities compared to observations and reference models. Detailed examination of a representative orographic shallow-to-deep convective transition case shows that RRM-SCREAM delays initial shallow convection growth due to lower-tropospheric dryness and sustained convective inhibition, but once triggered, deep convection becomes overly vigorous with excessively strong vertical velocities and elevated cloud ice content, linked to a thermodynamic structure characterized by suppressed low-level moistening and excessive upper-level moisture retention. Our results highlight specific deficiencies in the model representation of convective vertical velocity, cloud microphysical processes, and convective precipitation organization within RRM-SCREAM. Addressing these biases is essential for improving the predictions of convective clouds and precipitation in the global high-resolution atmospheric models.

Su, Tianning [Lawrence Livermore National Laborato↗
NASA NTRS1982

Bifurcation and stability of low-order steady flows in horizontally and vertically forced convection

A nonlinear spectral model of two-dimensional, shallow Boussinesq convection which responds to heating in both the horizontal and vertical directions is examined. The governing partial differential system is converted to an infinite set of ordinary differential equations and truncated to a small set to permit detailed study of the number and types of transitions from one flow configuration to another. The Hadley number and the Rayleigh number are defined as the horizontal and vertical thermal forcing mechanisms, respectively, for inclusion in the nonlinear spectral model, which is composed of three equations. The model is then used to describe steady states, linearly stable solutions, and balancing factors in unstable stratification. The number and the distribution of the steady states are found to be qualitatively independent of the aspect ratio and the Prandtl number.

Yost, D. A.↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Cu Growth Rates on Geostationary Imagery and Linkages to Cloud Organization

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Common tropical cloud features, such as convective rolls and cold pool fronts, form and persist for different periods within environments that support such development. Determining differences in lifecycle amongst these features in varying environments requires viewing their evolution from initiation to decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented on AHI 0.5-km visible reflectance and tracked during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. The resulting cloud tracks were collected according to regions containing airborne sampling of individual clouds at various stages of their lifecycles, yielding ensembles of tracks in separate environments. We present an analysis on lifecycle properties extracted from the cloud-track ensembles and their potential connections to cloud organizations observed throughout CAMP2Ex. Each ensemble is evaluated by calculating cloud-layer growth rates and comparing to spatial parameters, including track-achieved area and cloud-top height. The apparent clustering of growth rates for specific ensembles is then compared against overall cloud organizations, such as isolated congestus and cold pool fronts, that are observed with the airborne data. Finally, we consider how such differences in cloud growth appear in the airborne radar observations of intercepted cloud tracks.

Cloud Tracking↗
NASA NTRS2021

The GF Convection Parameterization: Recent Developments, Extensions, and Applications

Recent developments and options in the GF (Grell and Freitas, 2014, Freitas et al.,2018) convection parameterization are presented. The parameterization has been expanded to atrimodal spectral size to simulate three convection modes: shallow, congestus and deep. Incontrast to usual entrainment/detrainment assumptions, we assume that Beta Functions (BFs),commonly applied to represent Probability Density Functions (PDF’s), can be used tocharacterize the vertical mass flux profiles for the three modes, and use the BFs to deriveentrainment and detrainment rates. We also added a new closure for non-equilibrium convectionthat improved the simulation of the diurnal cycle of convection, with a better representation ofthe transition from shallow to deep convection regimes over land. The transport of chemicalconstituents (including wet deposition) can be treated inside the GF scheme. The tracer transportis handled in flux form and is mass conserving. Finally, the cloud microphysics has beenextended to include the ice phase to simulate the conversion from liquid water to ice in updraftswith resulting additional heat release and the melting from snow to rain.

Saulo R De Freitas↗
DOE OSTI2022

Precipitation–Moisture Coupling Over Tropical Oceans: Sequential Roles of Shallow, Deep, and Mesoscale Convective Systems

We report Precipitation over tropical oceans rapidly increases when the environmental column saturation fraction (CSF) increases past a critical value of ~0.7. Past studies suggested that increased stratiform rainfall greatly contributes to the rapid rainfall enhancement. In this study, the sequential roles of non-deep convection, deep convection, and mesoscale convective system (MCS) in precipitation-moisture interactions are examined using 19 years of satellite observations. When CSF is below ~0.5, non-deep convection dominates total rainfall, and predominantly contributes to moistening of the environment. Between the CSF range of 0.5–0.7, transition to deep convective rainfall begins. Meanwhile, MCS contribution to total rain rapidly increases, and the environment is further moistened. MCS becomes the major rainfall type above the critical CSF value (~0.7), with the rapid increase of total rain mostly explained by the rapid increase in MCS rain area. Rainfall reduction at high CSF values is jointly contributed by MCS and non-deep convection.

58 GEOSCIENCES↗
NASA NTRS2015

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

parameterization↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Maritime Clouds on Geostationary Imagery to Extract Lifecycle Characteristics

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Satellites have provided many statistics on shallow clouds, such as size, structure, and geographical coverage, from static views of recurring cloud fields. But determining why certain cloud features appear and persist for different periods requires a time-evolving view of their behaviors. Geostationary satellites provide a unique opportunity to follow the time evolution of individual convective features, given their enhanced spatial and temporal sampling. A cloud-tracking tool was developed to identify properties of cloud lifecycle from the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2EX) field campaign of 2019. The mission conducted intensive sampling of shallow cumulus in the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented according to thresholds in 0.5-km visible reflectance and with blurring techniques. Despite being limited to daytime hours, the segmentations yielded the best resolution possible for capturing cloud initiation and decay. The tracking procedure is based on a computer vision package that includes Kalman filters for motion prediction, object overlap search, and the Hungarian (or Kuhn-Munkres) matching algorithm for track designation. AHI radiances available within the tracked cloud boundaries are assembled to form individual spectral histories. The resulting catalog provides thousands of cloud histories for domains measuring only a few degrees in latitude and longitude. We present an overview of the cloud-tracking tool, strategies to identify development stages from cloud tracks, and preliminary results that document cumulus lifecycle properties from satellite. The application of AHI 0.5-km reflectance has both strengths and limitations when attempting to track lifecycles of the smallest resolvable clouds. We show that by aggregating cloud tracks from a few case studies of CAMP2EX, we can discern differences in cloud lifetime and development according to ensembles selected from areas of interest. The results demonstrate an ability to quantify lifetimes and assess rates of change in cloud characteristics that are likely controlled by the surrounding environment and meteorology.

Cloud Tracking↗