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At least 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Laser Disdrometer Quantities (LDQUANTS) and Video Disdrometer Quantities (VDISQUANTS) Value-Added Products Report

Disdrometers are useful instruments that measure the distribution of raindrop sizes (drop size distribution: DSD) and the associated rainfall rates/accumulation as those raindrops fall to the ground. These DSDs are a quantity of interest to members of the modeler and observational communities. However, use of disdrometer data for model evaluation, radar monitoring, or other activities requires careful quality control and processing for key DSD properties of interest (e.g., the number concentration of drops) to ensure appropriate physical (scattering, fall speed) assumptions. The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Laser Disdrometer Quantities and Video Disdrometer Quantities Value-Added Product (LDQUANTS/VDISQUANTS VAP) uses standard methods from Tokay et al. (e.g., 2013, 2014) to filter drops with unrealistic fall speeds. Further, it estimates several microphysical/geophysical quantities of parameterized DSDs (gamma or exponential assumption type fitting methods) as in previous disdrometer studies and ARM long-term efforts (e.g., Testud et al. 2001, Giangrande et al. 2014, Thompson et al. 2015). Disdrometers are also beneficial for cross-checks with other instrumentation, including rain gauges and radars. To support research interests and related radar monitoring activities, this product calculates radar equivalent quantities, including dual polarization radar quantities (e.g., Z, Differential Reflectivity ZDR, etc.), using T-Matrix scattering and additional wavelength, temperature, and drop shape assumptions (e.g., Thurai et al. 2007). All of these efforts allow disdrometer data sets to become more useful and easily handled by modeling and observational studies, or routine instrumentation checks.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Variability in Ice Nucleating Particles Across Greater Houston Texas

The concentration and cloud-forming potential of a region's ice nucleating particle (INP) population have uncertain impacts on deep convective clouds. Specifically, ice nucleating particles (INPs) may affect various cloud properties related to the formation, lifetime, and precipitation of deep convective clouds. As part of the U.S. Department of Energy's TRacking Aerosol and Convection interaction ExpeRiment (TRACER) campaign, researchers from Texas A&M University deployed three Davis Rotating-drum Universal-size-cut Monitoring (DRUM) samplers throughout Greater Houston, Texas from June through September 2022. Ambient particles, collected at the surface with the DRUM samplers in four aerodynamic diameter size ranges (>3, 3–1.2, 1.2–0.34, and 0.34–0.15 μm), were analyzed in offline cold-stage ice nucleation experiments. The INP population in Greater Houston is complex, varying by site and day, but can be generalized by a weak to moderately efficient mode of INPs at −24°C and an efficient mode at −15°C. Analysis reveals that supermicron particles are largely responsible for ice nucleation warmer than −20°C across the region while submicron particles dominate at temperatures colder than −20°C. Additionally, significant spatial diversity in the INP population was observed, with differences in mean nucleation temperature between sites for nearly every size cut. Although INP concentrations were typically ∼0.08 L −1 at −20°C throughout the campaign, a notable region-wide increase in INP concentration for particles freezing at temperatures warmer than −20°C occurred from mid-August to mid-September. This comprehensive characterization of Greater Houston's INP population, including spatial, temporal, and particle size variations, can help constrain ice microphysics parameterizations in weather and climate models.

Thompson, Seth A. [Texas A & M Univ., College Stat↗
DOE OSTI2020

Azimuthally averaged wind and thermodynamic structures of tropical cyclones in global climate models and their sensitivity to horizontal resolution

Characteristics of tropical cyclones (TCs) in global climate models (GCMs) are known to be influenced by details of the model configurations, including horizontal resolution and parameterization schemes. Understanding model-to-model differences in TC characteristics is a prerequisite for reducing uncertainty in future TC activity projections by GCMs. This study performs a process-level examination of TC structures in eight GCM simulations that span a range of horizontal resolutions from 1° to 0.25°. A recently developed set of process-oriented diagnostics is used to examine the azimuthally averaged wind and thermodynamic structures of the GCM-simulated TCs. Results indicate that the inner-core wind structures of simulated TCs are more strongly constrained by the horizontal resolutions of the models than are the thermodynamic structures of those TCs. As expected, the structures of TC circulations become more realistic with smaller horizontal grid spacing, such that the radii of maximum wind (RMW) become smaller, and the maximum vertical velocities occur off the center. However, the RMWs are still too large, especially at higher intensities, and there are rising motions occurring at the storm centers, inconsistently with observations. The distributions of precipitation, moisture, radiative and surface turbulent heat fluxes around TCs are diverse, even across models with similar horizontal resolutions. At the same horizontal resolution, models that produce greater rainfall in the inner-core regions tend to simulate stronger TCs. Further, when TCs are weak, the radial gradient of net column radiative flux convergence is comparable to that of surface turbulent heat fluxes, emphasizing the importance of cloud-radiative feedbacks during the early developmental phases of TCs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Overview of the New Version 3 NASA Micro-Pulse Lidar Network (MPLNET) Automatic Precipitation Detection Algorithm

Precipitation modifies atmospheric column thermodynamics through the process of evaporation and serves as a proxy for latent heat modulation. For this reason, a correct precipitation parameterization (especially for low-intensity precipitation) within global scale models is crucial. In addition to improving our modeling of the hydrological cycle, this will reduce the associated uncertainty of global climate models in correctly forecasting future scenarios, and will enable the application of mitigation strategies. In this manuscript we present a proof of concept algorithm to automatically detect precipitation from lidar measurements obtained from the National Aeronautics and Space Administration Micropulse lidar network (MPLNET). The algorithm, once tested and validated against other remote sensing instruments, will be operationally implemented into the network to deliver a near real time (latency <1.5 h) rain masking variable that will be publicly available on MPLNET website as part of the new Version 3 data products. The methodology, based on an image processing technique, detects only light precipitation events (defined by intensity and duration) such as light rain, drizzle, and virga. During heavy rain events, the lidar signal is completely extinguished after a few meters in the precipitation or it is unusable because of water accumulated on the receiver optics. Results from the algorithm, in addition to filling a gap in light rain, drizzle, and virga detection by radars, are of particular interest for the scientific community as they help to fully characterize the aerosol cycle, from emission to deposition, as precipitation is a crucial meteorological phenomenon accelerating atmospheric aerosol removal through the scavenging effect. Algorithm results will also help the understanding of long term aerosol–cloud interactions, exploiting the multi-year database from several MPLNET permanent observational sites across the globe. The algorithm is also applicable to other lidar and/or ceilometer network infrastructures in the framework of the Global Aerosol Watch (GAW) aerosol lidar observation network (GALION).

Simone Lolli↗
DOE OSTI2024

Mechanical and Thermal Forcing for Upslope Flows and Cumulus Convection over the Sierras de Córdoba

Abstract The upslope flow processes affecting the vertical extent of orographic cumulus convection are examined using observations from the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. Specifically, clear air returns from the U.S. Department of Energy (DOE) second-generation C-band scanning Atmospheric Radiation Measurement (ARM) precipitation radar (CSAPR2) are used to characterize the structure and variability of the ridge-normal (i.e., up/downslope) flow components, which transport mass to the crest of Argentina’s Sierras de Córdoba and contribute to convective initiation. Data are compiled for the entire CACTI period (October–April), including days with clear skies, shallow cumuli, cumulus congestus, and deep convection. To examine shared variability among >70 000 radar scans, we use (i) a principal component analysis (PCA) to isolate modes of variability in the upslope flow and (ii) composite analysis based on convective outcomes, determined from GOES-16 satellite observations. These data are contextualized with observed surface sensible heat fluxes, thermodynamic profiles, and synoptic-scale analysis. Results indicate distinct thermally and mechanically forced upslope flow modes, modulated by diurnal heating and synoptic-scale variations, respectively. In some instances, there is a superposition of thermal and mechanical forcing, yielding either deeper or shallower upslope flow. The composite analyses based on satellite data show that successively deeper convective outcomes are associated with successively deeper upslope flow layers that more readily transport mass to the ridge crest in conjunction with lower lifting condensation levels, facilitating convective initiation. These results help to isolate the forcing mechanisms for orographic convection and thus provide a foundation for parameterizing orographic convective processes in coarse resolution models.

Meteorology & Atmospheric Sciences↗
NASA NTRS2008

Forecasting Lightning Threat using Cloud-Resolving Model Simulations

Two new approaches are proposed and developed for making time and space dependent, quantitative short-term forecasts of lightning threat, and a blend of these approaches is devised that capitalizes on the strengths of each. The new methods are distinctive in that they are based entirely on the ice-phase hydrometeor fields generated by regional cloud-resolving numerical simulations, such as those produced by the WRF model. These methods are justified by established observational evidence linking aspects of the precipitating ice hydrometeor fields to total flash rates. The methods are straightforward and easy to implement, and offer an effective near-term alternative to the incorporation of complex and costly cloud electrification schemes into numerical models. One method is based on upward fluxes of precipitating ice hydrometeors in the mixed phase region at the-15 C level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domain-wide statistics of the peak values of simulated flash rate proxy fields against domain-wide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. Our blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Exploratory tests for selected North Alabama cases show that, because WRF can distinguish the general character of most convective events, our methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because the models tend to have more difficulty in predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models,the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of forecasts become available.

McCaul, Eugene W., Jr.↗
DOE OSTI2022

Impacts of Suppressing Excessive Light Rain on Aerosol Radiative Effects and Health Risks

Global climate models (GCMs) have been used widely to study radiative forcing and health risks of aerosols. A recent study using two GCMs found that light rain plays a dominant role in controlling aerosol loading. However, “too much light rain and too little heavy rain” is a longstanding bias in GCMs. It is unclear how much light rain affects aerosol-cloud-radiation interactions and health risks from air pollution. Here, in this work, we show that, with the correction of the rainfall intensity spectrum in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 by introducing a stochastic deep convection scheme, the reduced frequency of light rain (1–20 mm d -1 ) results in changes of aerosol direct radiative effects (DRE) of up to -0.5 ± 0.03 W/m 2 and aerosol cloud radiative effects (CRE) of up to -0.9 ± 0.03 W/m 2 . The total (CRE + DRE) radiative effects of light rain-mediated aerosol changes exceed the present-day anthropogenic forcing of aerosols relative to preindustrial levels from the Coupled Model Intercomparison Project (CMIP5&6) models. However, the correction of the rainfall intensity spectrum has little effect on anthropogenic aerosol forcing (defined as the radiative perturbation due to changes in aerosol concentrations between the industrial era and preindustrial levels). Due to increased exposure to fine particulates (PM 2.5 ), the estimated global total premature mortality is much higher than previously estimated, by 300,000 ± 60,000 deaths per year, and is more severe in populous regions such as India and China. The findings in this study highlight the need to understand uncertainties in radiative effects and health risks of aerosols due to simulation biases of precipitation in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Collaborative Research: Improved Efficiency and Coupling of the Radiation Code in the ACME Earth System Model (Final Report)

The complexity of radiative transfer, its importance to the exchange of energy in the climate system, and its high computational cost establishes importance of an accurate and efficient radiative transfer parameterization for climate simulation. Previous work by the proposing team at AER led to the development of the radiation code, RRTMG, which has been widely accepted by the global modeling community as a fast and accurate advancement over the previous generation of radiation codes. It has been in use in the NCAR CESM for many years, and it has been implemented in the initial version the DOE E3SM model. However, its computational cost remains high relative to other components in part due to its complexity and to its inefficient use of modern optimization strategies, and this project helped address this limitation for the code’s application in E3SM. Under other funding, the Investigators of this project led an effort to develop a high-performance broadband radiation code, called RTE+RRTMGP, which is a completely restructured code that will take advantage of modern computational capabilities to enhance its performance while retaining the strengths and accuracy of the original code. Designed to perform over a range of computer architectures, RTE+RRTMGP makes extensive use of Fortran 2003 features to improve both its efficiency and its use of memory. RTE+RRTMGP is expected to be adopted in the next generation of RTE+RRTMGP. This project allowed for advancements to the code’s computational capabilities and adding new and enhanced features. This included revising RTE+RRTMGP to run on GPU processors, analysis of and improvements to the code’s timing, modifying the gas optics in RRTMGP to increase the code’s accuracy, extensive validation of computed fluxes, heating rates and forcings, generating a cloud optical property and vertical sampling capabilities for RTE+RRTMGP, implementing a fast and accurate longwave scattering capability, and groundwork for the inclusion of a capability to specify solar variability. Many of the accomplishment in this project necessitated significant collaboration with the E3SM development team. The result of this project was optimization of a key physical component (radiative transfer calculations) of E3SM, directly supporting E3SM’s overarching global modeling objectives. More broadly, this project provided overall advancements in the use of radiative transfer calculations in atmospheric modeling and simulation, particularly for climate.

58 GEOSCIENCES↗
NASA NTRS1995

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗
DOE OSTI2020

Identifying a regional aerosol baseline in the eastern North Atlantic using collocated measurements and a mathematical algorithm to mask high-submicron-number-concentration aerosol events

Abstract. High-time-resolution measurements of in situ aerosol and cloud properties provide the ability to study regional atmospheric processes that occur on timescales of minutes to hours. However, one limitation to this approach is that continuous measurements often include periods when the data collected are not representative of the regional aerosol. Even at remote locations, submicron aerosols are pervasive in the ambient atmosphere with many sources. Therefore, periods dominated by local aerosol should be identified before conducting subsequent analyses to understand aerosol regional processes and aerosol–cloud interactions. Here, we present a novel method to validate the identification of regional baseline aerosol data by applying a mathematical algorithm to the data collected at the U.S. Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) user facility in the eastern North Atlantic (ENA). The ENA central facility (C1) includes an aerosol observing system (AOS) for the measurement of aerosol physical, optical, and chemical properties at time resolutions from seconds to minutes. A second temporary supplementary facility (S1), located ∼0.75 km from C1, was deployed for ∼1 year during the Aerosol and Cloud Experiments (ACE-ENA) campaign in 2017. First, we investigate the local aerosol at both locations. We associate periods of high submicron number concentration (Ntot) in the fine-mode condensation particle counter (CPC) and size distributions from the Ultra-High Sensitivity Aerosol Spectrometer (UHSAS) as a function of wind direction using a meteorology sensor with local sources. Elevated concentrations of Aitken-mode (< 100 nm diameter) particles were observed in correspondence with the wind directions associated with airport operations. At ENA, the Graciosa Airport and its associated activities were found to be the main sources of high-concentration aerosol events at ENA, causing peaks in 1 min Ntot that exceeded 8000 and 10 000 cm−3 at C1, in summer and winter, respectively, and 5000 cm−3 at S1 in summer. Periods with high Ntot not associated with these wind directions were also observed. As a result, the diverse local sources at ENA yielded a poor relationship between Ntot measurements collected at C1 and S1 (R2=0.03 with a slope =0.05±0.001). As a first approach to mask these events, the time periods when the wind direction was associated with the airport operations (west to northwest and southeast to south at C1 and east to south at S1) were applied. The meteorological masks removed 38.9 % of the data at C1 and 43.4 % at S1, and they did not significantly improve the relationship between the two sites (R2=0.18 with a slope =0.06±0.001). Due to the complexity of high-Ntot events observed at ENA, we develop and validate a mathematical ENA Aerosol Mask (ENA-AM) to identify high-Ntot events using 1 min resolution data from the AOS CPC at C1 and S1. After its parameterization and application, ENA-AM generated a high correlation between Ntot in the summer at C1 and S1 (R2=0.87 with a slope =0.84±0.001). We identified the regional baseline at ENA to be 428±228 cm−3 in the summer and 346±223 cm−3 in the winter. Lastly, we compared masked measurements from the AOS with the ARM Aerial Facility (AAF) during flights over C1 in the summer to understand submicron aerosol vertical mixing over C1. The high correlation (R2=0.71 with a slope of 1.04±0.01) observed between C1 and the AAF Ntot collected within an area of 10 km surrounding ENA and at altitudes < 500 m indicated that the submicron aerosol at ENA was well mixed within the first 500 m of the marine boundary layer during the month of July during ACE-ENA. Our novel method for determining a regional aerosol baseline at ENA can be applied to other time periods and at other locations with validation by a secondary site or additional collocated measurements.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Microphysical and Dynamical Effects of Mixed-Phase Hydrometeors in Convective Storms Using a Bin Microphysics Model: Melting

Abstract The dynamics of convective systems are inherently linked to microphysical processes through phase changes that result in warming or cooling. This is especially true of near-surface cooling via evaporation and melting of falling hydrometeors. In most numerical simulations, the melting of frozen hydrometeors (e.g., hail, graupel, snow) is computed within parameterized bulk microphysics schemes, many of which lack the ability to accurately represent mixed-phase hydrometeors (i.e., partially melted ice), which can affect hydrometeor sedimentation, melting, and evaporation of shed drops. To better understand the microphysical and dynamical effects of melting in convective storms, a bin microphysics scheme was used in the Weather Research and Forecasting Model for two idealized cases: a supercell storm and a squall line. Physically based predicted liquid fraction, instantaneous melting, and instantaneous shedding schemes were used to examine the role and importance of melting hydrometeors for these two storm modes. The results suggest that the amount of precipitation is dependent on the representation of melting. Moreover, the dynamic and thermodynamic characteristics of the simulated storms are found to differ substantially between the melting scenarios, resulting in varied storm system evolution; these differences are found to be dependent on the ambient aerosol concentration, although the differences induced by changing the representation of melting generally outweigh those of changing the aerosol loading. The results highlight the large role of melting in convective storm characteristics and suggest that further model improvements are needed in the near future.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2014

The Impact of Microphysics and Planetary Boundary Layer Physics on Model Simulation of U.S. Deep South Summer Convection

Inspection of output from various configurations of high-resolution, explicit convection forecast models such as the Weather Research and Forecasting (WRF) model indicates significant sensitivity to the choices of model physics pararneterizations employed. Some of the largest apparent sensitivities are related to the specifications of the cloud microphysics and planetary boundary layer physics packages. In addition, these sensitivities appear to be especially pronounced for the weakly-sheared, multicell modes of deep convection characteristic of the Deep South of the United States during the boreal summer. Possible ocean-land sensitivities also argue for further examination of the impacts of using unique ocean-land surface initialization datasets provided by the NASA Short-term Prediction Research and Transition (SPoRn Center to select NOAAlNWS weather forecast offices. To obtain better quantitative understanding of these sensitivities and also to determine the utility of the ocean-land initialization data, we have executed matrices of regional WRF forecasts for selected convective events near Mobile, AL (MOB), and Houston, TX (HGX). The matrices consist of identically initialized WRF 24-h forecasts using any of eight microphysics choices and any of three planetary boWldary layer choices. The resulting 24 simulations performed for each event within either the MOB or HGX regions are then compared to identify the sensitivities of various convective storm metrics to the physics choices. Particular emphasis is placed on sensitivities of precipitation timing, intensity, and coverage, as well as amount and coverage oflightuing activity diagnosed from storm kinematics and graupel in the mixed phase layer. The results confirm impressions gleaned from study of the behavior of variously configured WRF runs contained in the ensembles produced each spring at the Center for the Analysis and Prediction of Storms, but with the benefit of more straightforward control of the physics package choices. The design of the experiments thus allows for more direct interpretation of the sensitivities to each possible physics combination. The results should assist forecasters in their efforts to anticipate and correct for possible biases in simulated WRF convection patterns, and help the modeling community refine their model parameterizations.

McCaul, Eugene W., Jr.↗
DOE OSTI2018

The Fifth International Workshop on Ice Nucleation phase 2 (FIN-02): laboratory intercomparison of ice nucleation measurements

Abstract. The second phase of the Fifth International Ice Nucleation Workshop (FIN-02)involved the gathering of a large number of researchers at the KarlsruheInstitute of Technology's Aerosol Interactions and Dynamics of the Atmosphere(AIDA) facility to promote characterization and understanding of icenucleation measurements made by a variety of methods used worldwide.Compared to the previous workshop in 2007, participation was doubled,reflecting a vibrant research area. Experimental methods involved sampling ofaerosol particles by direct processing ice nucleation measuring systems fromthe same volume of air in separate experiments using different ice nucleatingparticle (INP) types, and collections of aerosol particle samples ontofilters or into liquid for sharing amongst measurement techniques thatpost-process these samples. In this manner, any errors introduced bydifferences in generation methods when samples are shared across laboratorieswere mitigated. Furthermore, as much as possible, aerosol particle sizedistribution was controlled so that the size limitations of different methodswere minimized. The results presented here use data from the workshop toassess the comparability of immersion freezing measurement methods activatingINPs in bulk suspensions, methods that activate INPs in condensation and/orimmersion freezing modes as single particles on a substrate, continuous flowdiffusion chambers (CFDCs) directly sampling and processing particles wellabove water saturation to maximize immersion and subsequent freezing ofaerosol particles, and expansion cloud chamber simulations in which liquidcloud droplets were first activated on aerosol particles prior to freezing.The AIDA expansion chamber measurements are expected to be the closestrepresentation to INP activation in atmospheric cloud parcels in thesecomparisons, due to exposing particles freely to adiabatic cooling. The different particle types used as INPs included the minerals illite NX andpotassium feldspar (K-feldspar), two natural soil dusts representative of arable sandy loam(Argentina) and highly erodible sandy dryland (Tunisia) soils, respectively,and a bacterial INP (Snomax ® ). Consideredtogether, the agreement among post-processed immersion freezing measurementsof the numbers and fractions of particles active at different temperaturesfollowing bulk collection of particles into liquid was excellent, withpossible temperature uncertainties inferred to be a key factor in determiningINP uncertainties. Collection onto filters for rinsing versus directly intoliquid in impingers made little difference. For methods that activatedcollected single particles on a substrate at a controlled humidity at orabove water saturation, agreement with immersion freezing methods was good inmost cases, but was biased low in a few others for reasons that have not beenresolved, but could relate to water vapor competition effects. AmongstCFDC-style instruments, various factors requiring (variable) highersupersaturations to achieve equivalent immersion freezing activation dominatethe uncertainty between these measurements, and for comparison with bulkimmersion freezing methods. When operated above water saturation to includeassessment of immersion freezing, CFDC measurements often measured at orabove the upper bound of immersion freezing device measurements, but oftenunderestimated INP concentration in comparison to an immersion freezingmethod that first activates all particles into liquid droplets prior tocooling (the PIMCA-PINC device, or Portable Immersion Mode Cooling chAmber–Portable Ice Nucleation Chamber), and typically slightly underestimated INPnumber concentrations in comparison to cloud parcel expansions in the AIDAchamber; this can be largely mitigated when it is possible to raise therelative humidity to sufficiently high values in the CFDCs, although this isnot always possible operationally. Correspondence of measurements of INPs among direct sampling andpost-processing systems varied depending on the INP type. Agreement was bestfor Snomax ® particles in the temperature regimecolder than −10 ∘ C, where their ice nucleation activity is nearlymaximized and changes very little with temperature. At temperatures warmer than −10 ∘ C, Snomax ® INP measurements (allvia freezing of suspensions) demonstrated discrepancies consistent withprevious reports of the instability of its protein aggregates that appear tomake it less suitable as a calibration INP at these temperatures. ForArgentinian soil dust particles, there was excellent agreement across allmeasurement methods; measures ranged within 1 order of magnitude for INPnumber concentrations, active fractions and calculated active site densitiesover a 25 to 30 ∘ C range and 5 to 8 orders of correspondingmagnitude change in number concentrations. This was also the case for alltemperatures warmer than −25 ∘ C in Tunisian dust experiments. Incontrast, discrepancies in measurements of INP concentrations or active sitedensities that exceeded 2 orders of magnitude across a broad range of temperaturemeasurements found at temperatures warmer than −25 ∘ C in a previous study werereplicated for illite NX. Discrepancies also exceeded 2 orders of magnitude attemperatures of −20 to −25 ∘ C for potassium feldspar (K-feldspar), but these coincidedwith the range of temperatures at which INP concentrations increase rapidly atapproximately an order of magnitude per 2 ∘ C cooling forK-feldspar. These few discrepancies did not outweigh the overall positive outcomes of theworkshop activity, nor the future utility of this data set or future similarefforts for resolving remaining measurement issues. Measurements of the samematerials were repeatable over the time of the workshop and demonstratedstrong consistency with prior studies, as reflected by agreement of databroadly with parameterizations of different specific or general (e.g., soildust) aerosol types. The divergent measurements of the INP activity of illiteNX by direct versus post-processing methods were not repeated for otherparticle types, and the Snomax ® datademonstrated that, at least for a biological INP type, there is no expectedmeasurement bias between bulk collection and direct immediately processedfreezing methods to as warm as −10 ∘ C. Since particle size rangeswere limited for this workshop, it can be expected that for atmosphericpopulations of INPs, measurement discrepancies will appear due to thedifferent capabilities of methods for sampling the full aerosol sizedistribution, or due to limitations on achieving sufficient watersupersaturations to fully capture immersion freezing in direct processinginstruments. Overall, this workshop presents an improved picture of presentcapabilities for measuring INPs than in past workshops, and providesdirection toward addressing remaining measurement issues.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Inter-annual and Long-term Temperature Variations in the Mesopause Region at High Latitudes Generated by the Stratospheric QBO

The Numerical Spectral Model (NSM) simulates the Quasi-biennial Oscillation (QBO) that dominates the zonal circulation of the lower stratosphere at low latitudes. In the model, the QBO is generated with parameterized small-scale gravity waves (GW), which are partially augmented in 3D with planetary waves owing to baroclinic instability. Due to GW filtering, the QBO extends into the upper mesosphere, evident in UARS zonal wind and TIMED temperature measurements. While the QBO zonal winds are confined to equatorial latitudes, even in simulations with latitude-independent wave source, the associated temperature variations extend to high latitudes. The meridional circulation redistributes some of the QBO energy to focus it partially onto the Polar Regions. The resulting QBO temperature variations away from the equator tend to increase at higher altitudes to produce inter-annual variations that can exceed 5 K in the polar mesopause region -- and our 3D model simulations show that the effect is variable from year to year and can produce large differences between the two hemispheres, presumably due to interactions involving the seasonal variations. Modeling studies with the NSM have shown that long-term variations can also be generated by the QBO interacting with the seasonal cycles through OW node-filtering. A 30-month QBO, optimally synchronized by the 6-month Semi-Annual Oscillation (SAO), thus produces a 5-year or semi-decadal (SD) oscillation -- and observational evidence for that has been provided by a recent analysis of stratospheric NCEP data. In a simulation with the 2D version of the NSM, this SD oscillation extends into the upper mesosphere, and we present results to show that the related temperature variations could contribute significantly to the long-term variations of the polar mesopause region. Quasi-decadal variations could furthermore arise from the modeled solar cycle modulations of the QBO and 12-month annual oscillation. Our numerical results are discussed in the context of the observed low summer temperatures reproduced by the model, to demonstrate that the above interannual and long-term variations could contribute significantly to the climatology of Polar Mesospheric Clouds (PMC) investigated by the Aeronomy of Ice in the Mesosphere (AIM) mission.

Mayr, Hans G.↗
DOE OSTI2022

A Decentralized Approach for Modeling Organized Convection Based on Thermal Populations on Microgrids

Abstract In this study, a spectral model for convective transport is coupled to a thermal population model on a two‐dimensional horizontal “microgrid,” covering the typical gridbox size of general circulation models. The goal is to explore new ways of representing impacts of spatial organization in cumulus cloud fields. The thermals are considered the smallest building block of convection, with thermal life cycle and movement represented through binomial functions. Thermals interact through two simple rules, reflecting pulsating growth and environmental deformation. Long‐lived thermal clusters thus form on the microgrid, exhibiting scale growth and spacing that represent simple forms of spatial organization and memory. Size distributions of cluster number are diagnosed from the microgrid through an online clustering algorithm, and provided as input to a spectral multiplume eddy‐diffusivity mass flux scheme. This yields a decentralized transport system, in that the thermal clusters acting as independent but interacting nodes that carry information about spatial structure. The main objectives of this study are (a) to seek proof of concept of this approach, and (b) to gain insight into impacts of spatial organization on convective transport. Single‐column model experiments demonstrate satisfactory skill in reproducing two observed cases of continental shallow convection. Metrics expressing self‐organization and spatial organization match well with large‐eddy simulation results. We find that in this coupled system, spatial organization impacts convective transport primarily through the scale break in the size distribution of cluster number. The rooting of saturated plumes in the subcloud mixed layer plays a key role in this process.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Convection-Permitting Simulations With the E3SM Global Atmosphere Model

This paper describes the first implementation of the Δx = 3.25 km version of the Energy Exascale Earth System Model (E3SM) global atmosphere model and its behavior in a 40-day prescribed-sea-surface-temperature simulation (January 20 through February 28, 2020). This simulation was performed as part of the DYnamics of the Atmospheric general circulation Modeled On Non-hydrostatic Domains (DYAMOND) Phase 2 model intercomparison. Effective resolution is found to be ~ 6x the horizontal dynamics grid resolution despite using a coarser grid for physical parameterizations. Despite this new model being in an immature and untuned state, moving to 3.25 km grid spacing solves several long-standing problems with the E3SM model. In particular, Amazon precipitation is much more realistic, the frequency of light and heavy precipitation is improved, agreement between the simulated and observed diurnal cycle of tropical precipitation is excellent, and the vertical structure of tropical convection and coastal stratocumulus look good. In addition, the new model is able to capture the frequency and structure of important weather events (e.g., tropical cyclones, extratropical cyclones including atmospheric rivers, and cold air outbreaks). Interestingly, this model does not get rid of the erroneous southern branch of the intertropical convergence zone nor the tendency for strongest convection to occur over the Maritime Continent rather than the West Pacific, both of which are classic climate model biases. Several other problems with the simulation are identified, underscoring the fact that this model is a work in progress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Process-Oriented Diagnostics: Principles, Practice, Community Development, and Common Standards

Process-oriented diagnostics (PODs) aim to provide feedback for model developers through model analysis based on physical hypotheses. However, the step from a diagnostic based on relationships among variables, even when hypothesis driven, to specific guidance for revising model formulation or parameterizations can be substantial. The POD may provide more information than a purely performance-based metric, but a gap between POD principles and providing actionable information for specific model revisions can remain. Furthermore, in coordinating diagnostics development, there is a trade-off between freedom for the developer, aiming to capture innovation, and near-term utility to the modeling center. Best practices that allow for the former, while conforming to specifications that aid the latter, are important for community diagnostics development that leads to tangible model improvements. Promising directions to close the gap between principles and practice include the interaction of PODs with perturbed physics experiments and with more quantitative process models as well as the inclusion of personnel from modeling centers in diagnostics development groups for immediate feedback during climate model revisions. Examples are provided, along with best-practice recommendations, based on practical experience from the NOAA Model Diagnostics Task Force (MDTF). Common standards for metrics and diagnostics that have arisen from a collaboration between the MDTF and the Department of Energy’s Coordinated Model Evaluation Capability are advocated as a means of uniting community diagnostics efforts.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluating the Conservation of Energy Variables in Simulations of Deep Moist Convection

Abstract It is often assumed in parcel theory calculations, numerical models, and cumulus parameterizations that moist static energy (MSE) is adiabatically conserved. However, the adiabatic conservation of MSE is only approximate because of the assumption of hydrostatic balance. Two alternative variables are evaluated here: MSE − IB and MSE + KE, wherein IB is the path integral of buoyancy ( B ) and KE is kinetic energy. Both of these variables relax the hydrostatic assumption and are more precisely conserved than MSE. This article quantifies the errors that result from assuming that the aforementioned variables are conserved in large-eddy simulations (LES) of both disorganized and organized deep convection. Results show that both MSE − IB and MSE + KE better predict quantities along trajectories than MSE alone. MSE − IB is better conserved in isolated deep convection, whereas MSE − IB and MSE + KE perform comparably in squall-line simulations. These results are explained by differences between the pressure perturbation behavior of squall lines and isolated convection. Errors in updraft B diagnoses are universally minimized when MSE − IB is assumed to be adiabatically conserved, but only when moisture dependencies of heat capacity and temperature dependency of latent heating are accounted for. When less accurate latent heat and heat capacity formulae were used, MSE − IB yielded poorer B predictions than MSE due to compensating errors. Our results suggest that various applications would benefit from using either MSE − IB or MSE + KE instead of MSE with properly formulated heat capacities and latent heats.

54 ENVIRONMENTAL SCIENCES↗