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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Understanding ice cloud-precipitation properties of three modes of mesoscale convective systems during PECAN

This study analyzes the precipitation and ice cloud microphysical features of three common modes of linear mesoscale convective systems (MCSs) during the Plains Elevated Convection at Night (PECAN) campaign. Three cases, one for each linear MCS archetype (trailing stratiform (TS), leading stratiform (LS), and parallel stratiform (PS) precipitation), are selected. We focus primarily on analyzing ice cloud microphysical properties and precipitation rates over the classified convective core (CC) and stratiform rain (SR) regions, as well as the two stratiform regions that developed behind (SR1) and ahead (SR2) of the convective line relative to the storm motion. In the three selected cases, the ice water path (IWP) and precipitation rate (PR) have strong correlations in the CC, but not in the SR. In terms of the temporal evolution of the mean IWPs and PRs, both CC and SR IWPs, as well as CC PRs, reach peaks quickly, but take a longer time to dissipate than the increase period. For all three cases, both SR1 and SR2 IWPs are 20-70% of their corresponding CC values in both the LS and PS cases, and up to 95% for the TS case, while all of their PRs are only 7-25% of their CC values. These values suggest that the SR PRs may not only depend on IWPs, but also that the microphysical properties of ice particles such as habit and size distribution may play an important role. Utilizing cloud resolving simulations of these systems may provide better understanding of the physical meanings behind the results in the future.

Cui, Wenjun↗
DOE OSTI2020

Diagnosis of convective organization and cold pools using ARM datasets and evaluation of a unified convection parameterization (UNICON)

Tropical thunderstorms often cluster together. Studies have suggested that the degree to which the tropical thunderstorms are clustered impacts Earth's energy balance and water cycle, as well as extreme precipitation events. However, the processes controlling the spatial distribution of the thunderstorms are poorly understood and are not properly represented in most computer models for weather and climate prediction. Under the goals of better understanding how convection organizes at the mesoscale and advancing the representation of mesoscale convective organization in global climate models, we i) objectively quantified the degrees of convective organization and diagnosed cold pool processes using ARM field campaign observations, ii) examined the organization processes in storm-resolving model simulations, and iii) evaluated the impacts of mesoscale convective organization in global model simulations. The project yielded a firm reference against which the global model representation of mesoscale convective organization and cold pools can be evaluated against and shed new light into the role of parameterized convective organization in the global model simulation of the basic state and variability. Our results revealed two distinct phases of convective clustering during the two-day rain episodes (Cheng et al. 2018) and a new mechanism through which vertical wind shear in the low-troposphere can aid convective organization over tropical oceans (Cheng et al. 2020). It was demonstrated that the interactive representation of cold pools and mesoscale convective organization is key for global models to successfully simulate both the mean state and intraseasonal variability in the tropics (Ahn et al. 2019; 2020).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Urban Impacts on Convective Squall Lines over Chicago in the Warm Season—Part I: Observations of Multi-Scale Convective Evolution

In this study, our aim is to diagnose how two quasi-linear convective systems (QLCS) are organized so one can determine the possible role of the city of Chicago, IL, USA, in modifying convective precipitation systems. In this Part I of a two-part study, we employ large-scale analyses, radiosonde soundings, surface observations, and Doppler radar data to diagnose the precursor atmospheric circulations that organize the evolution of two mesoscale convective systems and compare those circulations to radar and precipitation. Several multi-scale processes are found that organize and modify convection over the Chicago metroplex. Two sequential quasi-linear convective systems (QLCS #1 and #2) were organized that propagated over Chicago, IL, USA, during an eight-hour period on 5–6 July 2018. The first squall line (QLCS #1) built from the southwest to the northeast while strengthening as it propagated over the city, and the second (QLCS #2) propagated southeastwards and weakened as it passed over the city in association with a polar cold front. The weak upper-level divergence associated with a diffluent flow poleward of an expansive ridge built over and strengthened a low-level trough and confluence zone, triggering QLCS #1. Convective downdrafts from QLCS #1 produced a cold pool that interacted with multiple confluent low-level jets surrounding and focused on the metroplex urban heat island, thus advecting the convection poleward over the metroplex. The heaviest precipitation occurred just south-southeast of Midway Airport, Chicago. Subsequently, a polar cold front propagated into the metroplex, which triggered QLCS #2. However, the descending air above it under the polar jet and residual cold pool from QLCS #1 rapidly dissipated the cold frontal convection. This represents a case study where very active convection built over the metroplex and was likely modified by it, as evidenced in numerical simulations to be described in Part II.

Kaplan, Michael L.↗
DOE OSTI2020

A Satellite-Based Estimate of Convective Vertical Velocity and Convective Mass Flux: Global Survey and Comparison with Radar Wind Profiler Observations

Convective vertical velocity (w c ) and convective mass flux (M c ) lie at the heart of GCM cumulus parameterizations, but few observations of these critical parameters are available. In this paper, we develop and evaluate a novel, satellite-based method for estimating profiles of w c and M c . Here, comparisons with collocated ground-based radar wind profiler (RWP) observations show that satellite estimated median w c is slightly greater than the RWP estimates, but they show solid agreement when compared at the 95th percentiles (intense updrafts). RWP-derived and satellite estimated M c are broadly comparable in the lower and middle troposphere, with some differences in the upper troposphere due to differences in convective core sampling. A k-means cluster analysis of multiple years of w c data shows that convective characteristics are distinctly different among extratropical convection, tropical land convection, and tropical oceanic convection. Tropical land convection is significantly more intense and more variable than the oceanic counterpart.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

LOW MACH NUMBER MODELING OF CONVECTION IN HELIUM SHELLS ON SUB-CHANDRASEKHAR WHITE DWARFS. II. BULK PROPERTIES OF SIMPLE MODELS

The dynamics of helium shell convection driven by nuclear burning establish the conditions for runaway in the sub-Chandrasekhar-mass, double-detonation model for SNe Ia, as well as for a variety of other explosive phenomena. We explore these convection dynamics for a range of white dwarf core and helium shell masses in three dimensions using the low Mach number hydrodynamics code MAESTRO. We present calculations of the bulk properties of this evolution, including time-series evolution of global diagnostics, lateral averages of the 3D state, and the global 3D state. We find a variety of outcomes, including quasi-equilibrium, localized runaway, and convective runaway. Our results suggest that the double-detonation progenitor model is promising and that 3D dynamic convection plays a key role.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Unexpected Changes of Aerosol Burdens With Decreased Convection in the Context of Scale-Aware Convection Schemes

Atmospheric aerosols in global climate models (GCMs) can be removed by both large-scale and convective precipitation. As the horizontal resolution of GCMs increases, it is expected that large-scale precipitation increases and convective precipitation decreases if scale-aware convection schemes are well developed. Here, to explore its impact on aerosol burdens, this study develops a novel method and applies it to the National Center for Atmospheric Research Community Atmosphere Model version 5.3 to mimic the behavior of scale-aware convective schemes. Surprisingly, it is found that aerosol burden increases globally as convective precipitation decreases and large-scale precipitation increases, which can be attributed to the reduced light rain. In the light-rain intensity category, the decreased frequency of convective precipitation is not offset by the increased frequency of large-scale precipitation. Therefore, for aerosol simulations in high-resolution GCMs using scale-aware convection schemes, subgrid convection and large-scale condensation should be coordinated to assure light rain stays the same.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Incorporating the Effect of Large‐Scale Vertical Motion on Convection Through Convective Mass Flux Adjustment in E3SMv2

Abstract Recent observational studies suggest that the large‐scale dynamical forcing (vertical motion) plays important roles in deep convection development. In this study we propose a convective mass flux adjustment (MAdj) approach to represent the dynamical effects of large‐scale vertical motion on convection in the Department of Energy's Energy Exascale Earth System Model version 2 (E3SMv2). With MAdj, convection is enhanced (suppressed) when there is large‐scale ascending (descending) motion at the planetary boundary layer top. The coupling of convection with large‐scale circulation significantly improves the simulation of climate variability in E3SMv2 across multiple scales from the diurnal cycle, convectively coupled equatorial waves, to the Madden‐Julian Oscillation (MJO). The standard E3SMv2 tends to simulate overly weak diurnal amplitude of precipitation and overly weak variance of convectively coupled equatorial Kelvin and westward inertio‐gravity (WIG) waves. It also fails to simulate the essential characteristics of the MJO: continuous eastward propagation. With MAdj, the amplitude of diurnal cycle of precipitation is systematically increased and its probability density distribution is much closer to observations. The MAdj can also simulate more realistic eastward propagation of the MJO and much stronger convectively coupled Kelvin and WIG waves. Moreover, the MAdj approach slightly improves the climatology simulations in precipitation, cloud, radiation, circulation, temperature, and moisture fields, with overall root‐mean‐square error (RMSE) of major climatological fields reduced by about 2%. The MAdj approach suppresses excessive grid‐scale precipitation, reducing precipitation wet biases over South China Sea, Philippine Sea, Himalayas, and South Pacific Convergence Zone in western Pacific in summer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Vertically Resolved Convective–Stratiform Echo-Type Identification and Convectivity Retrieval for Vertically Pointing Radars

Using data from the airborne HIAPER Cloud Radar (HCR), a partitioning algorithm (ECCO-V) that provides vertically resolved convectivity and convective versus stratiform radar-echo classification is developed for vertically pointing radars. The algorithm is based on the calculation of reflectivity and radial velocity texture fields that measure the horizontal homogeneity of cloud and precipitation features. The texture fields are translated into convectivity, a numerical measure of the convective or stratiform nature of each data point. The convective–stratiform classification is obtained by thresholding the convectivity field. Subcategories of low, mid-, and high stratiform, shallow, mid-, deep, and elevated convective, and mixed echoes are introduced, which are based on the melting-layer and divergence-level altitudes. As the algorithm provides vertically resolved classifications, it is capable of identifying different types of vertically layered echoes, and convective features that are embedded in stratiform cloud layers. Its robustness was tested on data from four HCR field campaigns that took place in different meteorological and climatological regimes. The algorithm was adapted for use in spaceborne and ground-based radars, proving its versatility, as it is adaptable not only to different radar types and wavelengths, but also different research applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Seasonal variation of shallow-to-deep convection transition and its link to the environmental conditions over the Central Amazon: Shallow-to-Deep Convection Transition

This study aims to characterize the seasonal variation of the shallow-to-deep convection transition and understand how environmental conditions impact the behavior of this transition using data collected from the Observations and Modeling of the Green Ocean Amazon (GOAmazon) field campaign in the Central Amazon (Manaus). The diurnal cycle of the rain/cloud fraction shows that the wet season has more extensive shallow convection before the transition to deep convection with larger fractional coverage and rainfall; deep convection in the transition season is more intense and has higher vertical extension and a stronger updraft. Surface meteorology, atmospheric moisture, instability, and wind shear are contrasted for the shallow/congestus convection (SC) cases and the locally formed shallow-to-deep convection transition (LD) cases. The comparisons suggest that occurrence of the LD is generally promoted under the conditions of high atmospheric moisture and instability but has a weaker dependence on wind shear. The relative importance of these environmental controls also varies in different seasons: The dry and transition seasons require a deeper moist layer from the boundary layer to midtroposphere than the wet season; convective available potential energy (CAPE) is higher during the transition season, but it is a less important factor for shallow-to-deep convection transition than in other seasons; LD only has significantly larger wind shears than SC during the dry season.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving Convection Trigger Functions in Deep Convective Parameterization Schemes Using Machine Learning

Abstract Deficiencies in convection trigger functions, used in deep convection parameterizations in General Circulation Models (GCMs), have critical impacts on climate simulations. A novel convection trigger function is developed using the machine learning (ML) classification model XGBoost. The large‐scale environmental information associated with convective events is obtained from the long‐term constrained variational analysis forcing data from the Atmospheric Radiation Measurement (ARM) program at its Southern Great Plains (SGP) and Manaus (MAO) sites representing, respectively, continental mid‐latitude and tropical convection. The ML trigger is separately trained and evaluated per site, and jointly trained and evaluated at both sites as a unified trigger. The performance of the ML trigger is compared with four convective trigger functions commonly used in GCMs: dilute convective available potential energy (CAPE), undilute CAPE, dilute dynamic CAPE (dCAPE), and undilute dCAPE. The ML trigger substantially outperforms the four CAPE‐based triggers in terms of the F 1 score metric, widely used to estimate the performance of ML methods. The site‐specific ML trigger functions can achieve, respectively, 91% and 93% F 1 scores at SGP and MAO. The unified trigger also has a 91% F 1 score, with virtually no degradation from the site‐specific training, suggesting the potential of a global ML trigger function. The ML trigger alleviates a GCM deficiency regarding the overprediction of convection occurrence, offering a promising improvement to the simulation of the diurnal cycle of precipitation. Furthermore, to overcome the black box issue of the ML methods, insights derived from the ML model are discussed, which may be leveraged to improve traditional CAPE‐based triggers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Effects of organized convection parameterization on the MJO and precipitation in E3SMv1. Part I: Mesoscale heating

Mesoscale organization of convection is typically not represented in global circulation models, and hence its influence on the global circulation is not accounted for. The heating component of a parameterization that represents the dynamical and physical effects of circulations associated with organized convection, referred to as the multiscale coherent structure parameterization (MCSP), is implemented in the Energy Exascale Earth System Model version 1 (E3SMv1). Numerical simulations are conducted to assess its impact on the simulated climate. Besides E3SMv1 simulations, we performed high-resolution (1 km) simulations using the Weather Research and Forecasting (WRF) Model to determine the temperature tendencies induced by mesoscale convective systems embedded in deep convection. We tuned the free parameters of the MCSP based on the WRF simulations. MCSP heating enhances Kevin wave spectra in E3SMv1, improves the representation of the Madden-Julian Oscillation, and impacts on mean precipitation that vary with locations and seasons, including a reduction of biases over the tropical Pacific.

Climate Modeling↗
DOE OSTI2025

Remote Influence of Andean Convection on Amazonian Rainfall and Its Mechanisms

Models from Coupled Model Intercomparison Project Phase 6 produce too much precipitation over the Andes but too little over the Amazon or the Wet Andes-Dry Amazon (WADA) bias pattern. Unlike the conventional view that convection parameterization and land model deficiencies can contribute to Amazonian rainfall biases, we approach this long-standing biased model behavior through the lens of Andean convection. Using Community Earth System Model v1.1 and focusing on the wet season, our mechanism-denial experiments demonstrate that Andean convection notably reduces precipitation over the Amazon during austral summer. The Andean forced Amazonian response operates on weather timescale. Furthermore, the reduction of Amazonian rainfall is detectable within a few hours after initial Andean forcing. The precipitation response is primarily driven by variations in the moisture budget and is moderated by changes in convective available potential energy over the Amazon. Changes in the total advection of moisture over the Amazon are dominated by the vertical advection term and can be attributed to discrepancies in the dynamic omega field. In the experiments, the Andean east flank region is scrutinized where the vertical velocity and moisture fields play an intermediary role for the Andean driven WADA connection. The Andean forcing induces descending anomalies on the Andean east flank. The disturbances of wind and geopotential fields over the Andean east flank propagate eastward via Kelvin waves. Over the Amazon, descending anomalies and advective drying lead to reduction of mid-to-high level cloud, increase of shortwave cloud forcing and surface net radiation, and enhancement of themodynamic stability and rainfall reduction.

58 GEOSCIENCES↗
DOE OSTI2019

A Leray regularized ensemble-proper orthogonal decomposition method for parameterized convection-dominated flows

Abstract Partial differential equations (PDEs) are often dependent on input quantities that are uncertain. To quantify this uncertainty PDEs must be solved over a large ensemble of parameters. Even for a single realization this can be a computationally intensive process. In the case of flows governed by the Navier–Stokes equations, an efficient method has been devised for computing an ensemble of solutions. To further reduce the computational cost of this method, an ensemble-proper orthogonal decomposition (POD) method was recently proposed. The main contribution of this work is the introduction of POD spatial filtering for ensemble-POD methods. The POD spatial filter makes possible the construction of the Leray ensemble-POD model, which is a regularized-reduced order model for the numerical simulation of convection-dominated flows of moderate Reynolds number. The Leray ensemble-POD model employs the POD spatial filter to smooth (regularize) the convection term in the Navier–Stokes equations, and diminishes the numerical inaccuracies produced by the ensemble-POD method in the numerical simulation of convection-dominated flows. Specifically, for the numerical simulation of a convection-dominated two-dimensional flow between two offset cylinders, we show that the Leray ensemble-POD method better reflects the dynamics of the benchmark results than the ensemble-POD scheme. The second contribution of this work is a new numerical discretization of the variable viscosity ensemble algorithm in which the average viscosity is replaced with the maximum viscosity. It is shown that this new numerical discretization is significantly more stable than those in current use. Furthermore, error estimates for the novel Leray ensemble-POD algorithm with this new numerical discretization are also proven.

Mathematics↗
DOE OSTI2019

Deep Convective Organization, Moisture Vertical Structure, and Convective Transition Using Deep-Inflow Mixing

It is an open question whether an integrated measure of buoyancy can yield a strong relation to precipitation across tropical land and ocean, across the seasonal and diurnal cycles, and for varying degrees of convective organization. Building on previous work, entraining plume buoyancy calculations reveal that differences in convective onset as a function of column water vapor (CWV) over land and ocean, as well as seasonally and diurnally over land, are largely due to variability in the contribution of lower-tropospheric humidity to the total column moisture. Over land, the relationship between deep convection and lower-free-tropospheric moisture is robust across all seasons and times of day, whereas the relation to boundary layer moisture is robust for the daytime only. Using S-band radar, these transition statistics are examined separately for mesoscale and smaller-scale convection. The probability of observing mesoscale convective systems sharply increases as a function of lower-free-tropospheric humidity. The consistency of this with buoyancy-based parameterization is examined for several mixing formulations. Mixing corresponding to deep inflow of environmental air into a plume that grows with height, which incorporates nearly equal weighting of boundary layer and free-tropospheric air, yields buoyancies consistent with the observed onset of deep convection across the seasonal and diurnal cycles in the Amazon. Furthermore, it provides relationships that are as strong or stronger for mesoscale-organized convection as for smaller-scale convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Spatiotemporal Characteristics and Large-scale Environments of Mesoscale Convective Systems East of the Rocky Mountains

The spatiotemporal variability and 3-dimensional structures of mesoscale convective systems (MCSs) east of the U.S. Rocky Mountains and their large-scale environments are characterized across all seasons using 13 years of high-resolution radar and satellite observations. Long-lived and intense MCSs account for over 50% of warm season precipitation in the Great Plains and over 40% of cold season precipitation in the southeast. The Great Plains has the strongest MCS seasonal cycle peaking in May-June, while in the southeast, MCSs occur year round. Distinctly different large-scale environments across the seasons have significant impact on the structure of MCSs. Spring and fall MCSs commonly initiate under strong baroclinic forcing and favorable thermodynamic environments. MCS genesis frequently occurs in the Great Plains near sunset, although convection is not always surface triggered. Spring MCS features both large and deep convection, with large stratiform rain area and high volume rainfall. In contrast, summer MCSs often initiate under weak baroclinic forcing, featuring a high-pressure ridge with weak low-level convergence acting on the warm, humid air associated with the low-level jet. MCS genesis concentrates east of the Rocky Mountain Front Range and near the southeast coast in the afternoon. The strongest MCS diurnal cycle amplitude extends from the foothills of the Rocky Mountains to the Great Plains. Summer MCSs have the largest and deepest convective features, the smallest stratiform rain area and the lowest rainfall volume. Lastly, winter MCSs are characterized by the strongest baroclinic forcing and the largest MCS precipitation features over the southeast. Implications of the findings to climate modeling are discussed.

Feng, Zhe↗
NASA NTRS1991

Study of Ardmore, Oklahoma storm clouds. I - Convective storm cloud initiation and development based on the remote sensing gravity-wave-induced convection. II - Satellite infrared remote sensing and numerical simulation

The role of gravity waves is discussed with respect to the vertical velocity of convection. Specific attention is given to wave-induced convection which contributes to the fractions of formation and the development of severe convective storms. Large-amplitude gravity waves and convective instability were investigated in storm clouds above Ardmore, Oklahoma. Rapid-scan satellite imagery and radar summaries provide evidence of water-vapor condensation related to convection which is introduced by gravity waves. Gravity wave periods of 35 minutes are found to initiate weak convection, which can be intensified by gravity waves with periods of 20 minutes. The convective motion reaches a maximum about one hour before funnel clouds develop. Other mechanisms which contribute to convective motion are considered, but gravity waves are the major contributor to the initiation, formation, and development of mesoscale storm clouds. Cloud modeling based on satellite imagery and sounding data showed that by overshooting cloud tops that penetrated the tropopause, storm clouds mature; that these clouds collapse about 9 minutes before the touchdown of tornadoes; and that cloud tops collapse at a high rate about 6 minutes before tornadoes lift off.

Hung, R. J.↗
DOE OSTI2020

Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Evaluating and Improving Scale–Awareness of a Convective Parameterization Closure Using Cloud–Resolving Model Simulations of Convection

This study aims to evaluate a revised closure of the Zhang-McFarlane (ZM) scheme for deep convection and to further improve its scale awareness. Output from two cloud-resolving model (CRM) simulations of both midlatitude organized (MC3E) and tropical unorganized (TWP-ICE) convection are used for the evaluation. By averaging the CRM output over different subdomain sizes from 64 km to 4 km, convection-associated fields are obtained to represent the fields at different horizontal resolutions of global climate models (GCMs). The convection parameterization closure is then tested using these fields. Results show that the cloud base mass flux M b determined from the closure has a relatively good relationship with CRM-simulated convection at coarse resolutions for both MC3E and TWP-ICE, but their correlation degrades at higher resolutions, especially when approaching the gray zone scale under 10 km. The fluctuation of CAPE consumption rate per unit cloud base mass flux for different convective events is found to be an important factor affecting the correlation. When averaged over the base domain, the cloud base mass flux determined by the closure is found to increase with decreasing subdomain size, implying that the closure is not scale-aware. To improve its scale-awareness, a modified closure is designed to alleviate the overprediction of convection at high GCM resolutions. Furthermore, results show that the modified closure has the scale-aware ability to suppress the overprediction problem at high GCM resolutions for both MC3E and TWP-ICE.

54 ENVIRONMENTAL SCIENCES↗