Engineering topics

Luke, Edward

Publications and source records attributed to Luke, Edward.

30 records · Page 2

DOE OSTI2019

Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) Field Campaign Report

With their extensive coverage, low clouds greatly impact global climate. Presently, low clouds are poorly represented in global climate models (GCMs), and the response of low clouds to changes in atmospheric greenhouse gases and aerosols remains the major source of uncertainty in climate simulations. The poor representations of low clouds in GCMs are in part due to inadequate observations of their microphysical and macrophysical structures, radiative effects, and the associated aerosol distribution and budget in regions where the aerosol impact is the greatest. The Eastern North Atlantic (ENA) is a region of persistent but diverse subtropical marine boundary layer (MBL) clouds, whose albedo and precipitation are highly susceptible to perturbations in aerosol properties. Boundary-layer aerosol in the ENA region is influenced by a variety of sources, leading to strong variations in cloud condensation nuclei (CCN) concentration and aerosol optical properties. A permanent ENA site was established by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility on Graciosa Island in the Azores, providing invaluable information on MBL aerosol and low clouds. At the same time, the vertical structures and horizontal variabilities of aerosol, trace gases, cloud, drizzle, and atmospheric thermodynamics are critically needed for understanding and quantifying the budget of MBL aerosol, the radiative properties, precipitation efficiency, and lifecycle of MBL clouds, and the cloud response to aerosol perturbations. Much of this data can be obtained only through aircraft-based measurements. In addition, the interconnected aerosol and cloud processes are best investigated by a study involving simultaneous in situ aerosol, cloud, and thermodynamics measurements. Furthermore, in situ measurements are also necessary for validating and improving ground-based retrieval algorithms at the ENA site. The Aerosol and Cloud Experiments in Eastern North Atlantic (ACE-ENA) project was motivated by the need for comprehensive in situ characterizations of boundary-layer structure, and associated vertical distributions and horizontal variabilities of low clouds and aerosol over the Azores. The ARM Aerial Facility (AAF) Gulfstream-1 (G-1) aircraft was deployed during two intensive measurement periods (IOPs). The first deployment took place from June 21 to July 20, 2017, and the second one took place from January 15 to February 18, 2018. Flights were carried out in the Azores, near the ARM ENA site on Graciosa Island. Deployments during both seasons allow for examination of key aerosol and cloud processes under a variety of representative meteorological and cloud conditions. The science themes for the deployments include: (1) Budget of MBL CCN and its seasonal variation; (2) Effects of aerosol on cloud and precipitation; (3) Cloud microphysical and macrophysical structures, and entrainment mixing; (4) Advancing retrievals of turbulence, cloud, and drizzle; and (5) Model evaluation and processes studies.

Eastern North Atlantic, Graciosa Island, aerosols,↗

DOE OSTI2018

Marine boundary layer aerosol in the eastern North Atlantic: seasonal variations and key controlling processes

The response of marine low cloud systems to changes in aerosol concentrationrepresents one of the largest uncertainties in climate simulations. Majorcontributions to this uncertainty are derived from poor understanding of aerosolunder natural conditions and the perturbation by anthropogenic emissions. Theeastern North Atlantic (ENA) is a region of persistent but diverse marineboundary layer (MBL) clouds, whose albedo and precipitation are highlysusceptible to perturbations in aerosol properties. In this study, we examineMBL aerosol properties, trace gas mixing ratios, and meteorologicalparameters measured at the Atmospheric Radiation Measurement Climate ResearchFacility's ENA site on Graciosa Island, Azores, Portugal, during a 3-yearperiod from 2015 to 2017. Measurements impacted by local pollution onGraciosa Island and during occasional intense biomass burning and dust eventsare excluded from this study. Submicron aerosol size distribution typicallyconsists of three modes: Aitken (At, diameter <~100 nm),accumulation (Ac, D p within ~100 to ~300 nm), andlarger accumulation (LA, D p > ~ 300 nm) modes, with averagenumber concentrations (denoted as N At , N Ac , and N LA below) of 330, 114, and 14 cm -3 , respectively. N At , N Ac , and N LA show contrasting seasonalvariations, suggesting different sources and removal processes. N LA is dominated by sea spray aerosol (SSA) and is higher in winter andlower in summer. This is due to the seasonal variations of SSA production,in-cloud coalescence scavenging, and dilution by entrained free troposphere(FT) air. In comparison, SSA typically contributes a relatively minorfraction to N At (10 %) and N Ac (21 %) on an annual basis. Inaddition to SSA, sources of Ac-mode particles include entrainment of FTaerosols and condensation growth of Aitken-mode particles inside the MBL, whilein-cloud coalescence scavenging is the major sink of N Ac . The observedseasonal variation of N Ac , being higher in summer and lower in winter,generally agrees with the steady-state concentration estimated from majorsources and sinks. N At is mainly controlled by entrainment of FTaerosol, coagulation loss, and growth of Aitken-mode particles into theAc-mode size range. Our calculation suggests that besides the directcontribution from entrained FT Ac-mode particles, growth of entrained FTAitken-mode particles in the MBL also represent a substantial source ofcloud condensation nuclei (CCN), with the highest contribution potentiallyreaching 60 % during summer. The growth of Aitken-mode particles to CCN sizeis an expected result of the condensation of sulfuric acid, a product fromdimethyl sulfide oxidation, suggesting that ocean ecosystems may have asubstantial influence on MBL CCN populations in the ENA.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Drivers of Seasonal Variability in Marine Boundary Layer Aerosol Number Concentration Investigated Using a Steady State Approach

Marine boundary layer (MBL) aerosol particles affect the climate through their interaction with MBL clouds. Although both MBL clouds and aerosol particles have pronounced seasonal cycles, the factors controlling seasonal variability of MBL aerosol particle concentration are not well-constrained. In this paper an aerosol budget is constructed representing the effects of wet deposition, free-tropospheric entrainment, primary surface sources, and advection on the MBL accumulation mode aerosol number concentration (N a ). These terms are further parameterized, and by assuming that on seasonal timescales N a is in steady state, the budget equation is rearranged to form a diagnostic equation for N a based on observable variables. Using data primarily collected in the subtropical northeast Pacific during the MAGIC campaign (Marine ARM (Atmospheric Radiation Measurement) GPCI (GCSS Pacific Cross-section Intercomparison) Investigation of Clouds), estimates of both mean summer and winter N a concentrations are made using the simplified steady-state model and seasonal mean observed variables, and are found to match well with the observed N a . To attribute the modeled difference between summer and winter aerosol concentrations to individual observed variables (e.g. precipitation rate, free-tropospheric aerosol number concentration), a local sensitivity analysis is combined with the seasonal difference in observed variables. This analysis shows that despite wintertime precipitation frequency being lower than summer, the higher winter precipitation rate accounted for approximately 60% of the modeled seasonal difference in N a , which emphasizes the importance of marine stratocumulus precipitation in determining MBL aerosol concentrations on longer time scales.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

A case study of microphysical structures and hydrometeor phase in convection using radar Doppler spectra at Darwin, Australia

To understand the microphysical processes that impact diabatic heating and cloud lifetimes in convection, we need to characterize the spatial distribution of supercooled liquid water. To address this observational challenge, vertically pointing active sensors at the Darwin Atmospheric Radiation Measurement (ARM) site are used to classify cloud phase within a deep convective cloud in a shallow to deep convection transitional case. The cloud cannot be fully observed by a lidar due to signal attenuation. Thus we develop an objective method for identifying hydrometeor classes, including mixed-phase conditions, using k-means clustering on parameters that describe the shape of the Doppler spectra from vertically pointing Ka band cloud radar. This approach shows that multiple, overlapping mixed-phase layers exist within the cloud, rather than a single region of supercooled liquid, indicating complexity to how ice growth and diabatic heating occurs in the vertical structure of the cloud.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Understanding Rapid Changes in Phase Partitioning between Cloud Liquid and Ice in Stratiform Mixed-Phase Clouds: An Arctic Case Study

Understanding phase transitions in mixed-phase clouds is of great importance because the hydrometeor phase controls the lifetime and radiative effects of clouds. These cloud radiative effects have a crucial impact on the surface energy budget and thus on the evolution of the ice cover, in high altitudes. For a springtime low-level mixed-phase stratiform cloud case from Barrow, Alaska, a unique combination of instruments and retrieval methods is combined with multiple modeling perspectives to determine key processes that control cloud phase partitioning. The interplay of local cloud-scale versus large-scale processes is considered. Rapid changes in phase partitioning were found to be caused by several main factors. Some major influences were the large-scale advection of different air masses with different aerosol concentrations and humidity content, cloud-scale processes such as a change in the thermodynamical coupling state, and local-scale dynamics influencing the residence time of ice particles. Other factors such as radiative shielding by a cirrus and the influence of the solar cycle were found to only play a minor role for the specific case study (11–12 March 2013). Furthermore, for an even better understanding of cloud phase transitions, observations of key aerosol parameters such as profiles of cloud condensation nucleus and ice nucleus concentration are desirable.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

A path towards uncertainty assignment in an operational cloud-phase algorithm from ARM vertically pointing active sensors

Abstract. Knowledge of cloud phase (liquid, ice, mixed, etc.) is necessary to describe the radiative impact of clouds and their lifetimes, but is a property that is difficult to simulate correctly in climate models. One step towards improving those simulations is to make observations of cloud phase with sufficient accuracy to help constrain model representations of cloud processes. In this study, we outline a methodology using a basic Bayesian classifier to estimate the probabilities of cloud-phase class from Atmospheric Radiation Measurement (ARM) vertically pointing active remote sensors. The advantage of this method over previous ones is that it provides uncertainty information on the phase classification. We also test the value of including higher moments of the cloud radar Doppler spectrum than are traditionally used operationally. Using training data of known phase from the Mixed-Phase Arctic Cloud Experiment (M-PACE) field campaign, we demonstrate a proof of concept for how the method can be used to train an algorithm that identifies ice, liquid, mixed phase, and snow. Over 95 % of data are identified correctly for pure ice and liquid cases used in this study. Mixed-phase and snow cases are more problematic to identify correctly. When lidar data are not available, including additional information from the Doppler spectrum provides substantial improvement to the algorithm. This is a first step towards an operational algorithm and can be expanded to include additional categories such as drizzle with additional training data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

On the unified estimation of turbulence eddy dissipation rate using Doppler cloud radars and lidars: Radar and Lidar Turbulence Estimation

Coincident profiling observations from Doppler lidars and radars are used to estimate the turbulence energy dissipation rate (ε) using three different data sources: (i) Doppler radar velocity (DRV), (ii) Doppler lidar velocity (DLV), and (iii) Doppler radar spectrum width (DRW) measurements. Likewise, the agreement between the derived ε estimates is examined at the cloud base height of stratiform warm clouds. Collocated ε estimates based on power spectra analysis of DRV and DLV measurements show good agreement (correlation coefficient of 0.86 and 0.78 for both cases analyzed here) during both drizzling and nondrizzling conditions. This suggests that unified (below and above cloud base) time-height estimates of ε in cloud-topped boundary layer conditions can be produced. This also suggests that eddy dissipation rate can be estimated throughout the cloud layer without the constraint that clouds need to be nonprecipitating. Eddy dissipation rate estimates based on DRW measurements compare well with the estimates based on Doppler velocity but their performance deteriorates as precipitation size particles are introduced in the radar volume and broaden the DRW values. And, based on this finding, a methodology to estimate the Doppler spectra broadening due to the spread of the drop size distribution is presented. Furthermore, the uncertainties in ε introduced by signal-to-noise conditions, the estimation of the horizontal wind, the selection of the averaging time window, and the presence of precipitation are discussed in detail.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Biological and Environmental Research Exascale Requirements Review. An Office of Science review sponsored jointly by Advanced Scientific Computing Research and Biological and Environmental Research, March 28-31, 2016, Rockville, Maryland

Understanding the fundamentals of genomic systems or the processes governing impactful weather patterns are examples of the types of simulation and modeling performed on the most advanced computing resources in America. High-performance computing and computational science together provide a necessary platform for the mission science conducted by the Biological and Environmental Research (BER) office at the U.S. Department of Energy (DOE). This report reviews BER’s computing needs and their importance for solving some of the toughest problems in BER’s portfolio. BER’s impact on science has been transformative. Mapping the human genome, including the U.S.-supported international Human Genome Project that DOE began in 1987, initiated the era of modern biotechnology and genomics-based systems biology. And since the 1950s, BER has been a core contributor to atmospheric, environmental, and climate science research, beginning with atmospheric circulation studies that were the forerunners of modern Earth system models (ESMs) and by pioneering the implementation of climate codes onto high-performance computers. See http://exascaleage.org/ber/ for more information.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Fingerprints of a riming event on cloud radar Doppler spectra: observations and modeling

In this paper, Radar Doppler spectra measurements are exploited to study a riming event when precipitating ice from a seeder cloud sediment through a supercooled liquid water (SLW) layer. The focus is on the "golden sample" case study for this type of analysis based on observations collected during the deployment of the Atmospheric Radiation Measurement Program's (ARM) mobile facility AMF2 at Hyytiälä, Finland, during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) field campaign. The presented analysis of the height evolution of the radar Doppler spectra is a state-of-the-art retrieval with profiling cloud radars in SLW layers beyond the traditional use of spectral moments. Dynamical effects are considered by following the particle population evolution along slanted tracks that are caused by horizontal advection of the cloud under wind shear conditions. In the SLW layer, the identified liquid peak is used as an air motion tracer to correct the Doppler spectra for vertical air motion and the ice peak is used to study the radar profiles of rimed particles. A 1-D steady-state bin microphysical model is constrained using the SLW and air motion profiles and cloud top radar observations. The observed radar moment profiles of the rimed snow can be simulated reasonably well by the model, but not without making several assumptions about the ice particle concentration and the relative role of deposition and aggregation. In conclusion, this suggests that in situ observations of key ice properties are needed to complement the profiling radar observations before process-oriented studies can effectively evaluate ice microphysical parameterizations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2013

Discrete Surface Evolution and Mesh Deformation for Aircraft Icing Applications

Robust, automated mesh generation for problems with deforming geometries, such as ice accreting on aerodynamic surfaces, remains a challenging problem. Here we describe a technique to deform a discrete surface as it evolves due to the accretion of ice. The surface evolution algorithm is based on a smoothed, face-offsetting approach. We also describe a fast algebraic technique to propagate the computed surface deformations into the surrounding volume mesh while maintaining geometric mesh quality. Preliminary results presented here demonstrate the ecacy of the approach for a sphere with a prescribed accretion rate, a rime ice accretion, and a more complex glaze ice accretion.

ice accretion↗

NASA NTRS2007

Marine Boundary Layer Cloud Properties From AMF Point Reyes Satellite Observations

Cloud Diameter, C(sub D), offers a simple measure of Marine Boundary Layer (MBL) cloud organization. The diurnal cycle of cloud-physical properties and C(sub D) at Pt Reyes are consistent with previous work. The time series of C(sub D) can be used to identify distinct mesoscale organization regimes within the Pt. Reyes observation period.

Jensen, Michael↗

NASA NTRS2002

Computational Systems for Multidisciplinary Applications

In this paper, we briefly describe our efforts to develop complex simulation systems. We focus first on four key infrastructure items: enterprise computational services, simulation synthesis, geometry modeling and mesh generation, and a fluid flow solver for arbitrary meshes. We conclude by presenting three diverse applications developed using these technologies.

Soni, Bharat↗